Biosensors for Environmental Monitoring

Title : Biosensors for Environmental Monitoring author : Bilitewski, Ursula.; Turner, Anthony P. F. publisher : Taylor & Francis Routledge isbn10 | asin : print isbn13 : 9780203352939 ebook isbn13 : 9780203303856 language : English subject Environmental monitoring, Biosensors, ram--Environnement--Surveillance, ram-Biocapteurs. publication date : 2000 lcc : QH541.15.M64B58 2000eb ddc : 628.5/028/7 subject : Environmental monitoring, Biosensors, ram--Environnement--Surveillance, ram-Biocapteurs.

BIOSENSORS FOR ENVIRONMENTAL MONITORING

BIOSENSORS FOR ENVIRONMENTAL MONITORING Edited by Ursula Bilitewski Gesellschaft für Biotechnologishe Forschung mbH Braunschweig, Germany and Anthony P.F.Turner Cranfield Biotechnology Centre Cranfield University UK

harwood academic publishers Australia • Canada • France • Germany • India • Japan • Luxembourg Malaysia • The Netherlands • Russia • Singapore • Switzerland

This edition published in the Taylor & Francis e-Library, 2004. Copyright © 2000 OPA (Overseas Publishers Association) N.V. Published by license under the Harwood Academic Publishers imprint, part of The Gordon and Breach Publishing Group. All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying and recording, or by any information storage or retrieval system, without permission in writing from the publisher. Printed in Singapore. Amsteldijk 166 1st Floor 1079 LH Amsterdam The Netherlands

British Library Cataloguing in Publication Data A catalogue record for this book is available from the British Library. ISBN 0-203-30385-7 Master e-book ISBN ISBN 0-203-35293-9 (OEB Format) ISBN: 90-5702-449-7 (Print Edition)

CONTENTS Contributors 1. Introduction U.Bilitewski and A.P.F.Turner 2. Technical Principles U.Bilitewski 2.1. Electrodes F.Lisdat and F.W.Scheller 2.1.1. Introduction

ix 1 5 5 5

2.1.2. Potentiometric Transducers

6

2.1.3. Amperometric Transducers

12

2.1.4. Impedance Measurements

20

2.1.5. Concluding Remarks

24

2.2. Optical Sensors G.Gauglitz 2.2.1. Introduction

28

2.2.2. Classification of Optical and Transduction Principles

30

2.2.3. Trends

45

2.3. Flow Injection Analysis U.Bilitewski 2.3.1. Introduction

51

2.3.2. Selected Components of FIA-Manifolds

52

2.3.3. Dispersion

57

2.3.4. Conclusion—Focussing on Biochemical Applications

58

3. Biochemical Principles U.Bilitewski 3.1. Enzyme Assays 3.1.1. Enzyme Substrate Determination A.Warsinke 3.1.2. Enzyme Inhibitors B.Leca, T.Noguer and J.-L.Marty 3.2. Microbial Sensors K.Riedel, G.Kunze, M.Lehmann and A.König

28

51

61 61 61 76 87

3.2.1. Introduction

87

3.2.2. Design and Function

87

3.2.3. Improvement of Selectivity of Microbial Sensors

93

3.2.4. General Considerations of Application

99

Page vi 3.3. Immunoassays B.Hock 3.3.1. Antibody Structure 3.3.2. Polyclonal Antibodies 3.3.3. Monoclonal Antibodies 3.3.4. Recombinant Antibodies 3.3.5. Binding Properties of Antibodies 3.3.6. Immunoassays 3.3.7. Data Processing and Statistics 3.3.8. Cross-Reactivities 3.3.9. Conclusions 3.4. DNA Based Biosensors J.Wang 3.4.1. Introduction 3.4.2. DNA Structure 3.4.3. Sequence Specific Hybridization Biosensors 3.4.4. Detection of Small Analytes Interacting with DNA 3.4.5. Conclusions 4. Water Analysis I.Katakis, M.Campàs and E.Domínguez 4.1. Pesticides U.Bilitewski 4.1.1. Enzymatic Systems T.Noguer, B.Leca and J.-L.Marty 4.1.2. Affinity Sensor Systems G.Gauglitz, J.Piehler and U.Bilitewski 4.2. Biochemical Oxygen Demand (BOD) K.Riedel, M.Lehmann and G.Kunze 4.2.1. Introduction 4.2.2. Structure and Function of the BOD Sensor System 4.2.3. Problems of Practical Use and Comparison of Sensor-BOD and BOD5 4.2.4. Conclusion 4.3. Other Organic Pollutants 4.3.1. Enzymatic Biosensors I.Katakis, M.Campàs and E.Domínguez 4.3.2. Microbial Sensors for Determination of Aromatics and their Halogenated Derivatives

105 105 108 110 112 115 116 120 122 122 124 124 124 126 132 133 137 140 141 150 165 165 165 168 179 182 182 192

K.Riedel, T.Bachmann and R.D.Schmid 4.3.3. Other Types of Sensors for Organic Pollutants I.Katakis, M.Campàs and E.Domínguez 4.3.4. Conclusion I.Katakis, M.Campàs, E.Domínguez and K.Riedel 4.4. Heavy Metals R.E.Williams, P.-J.Holt, N.C.Bruce and C.R.Lowe 4.4.1. Introduction

4.4.2. Current Analytical Methods 4.4.3. Bioassays Using Whole Cells/Organisms 4.4.4. Engineered Microorganisms as Sensors 4.4.5. Sensors Using Biological Molecules 4.4.6. Concluding Comments 4.5. Phosphate A.Warsinke 4.5.1. Introduction 4.5.2. Phosphate as Inhibitor 4.5.3. Phosphate as a Second Substrate 4.6. Nitrate A.Warsinke 4.6.1. Introduction 4.6.2. Enzyme Sensors for Nitrate Determination 5. Analysis of Soil S.Kröger and A.P.F.Turner 5.1. Sampling K.Cammann and W.Kleiböhmer 5.1.1. Introduction 5.1.2. Sampling Strategies 5.1.3. Sampling Protocol 5.1.4. Sampling Depth 5.1.5. Collection of Samples and Sample Transport 5.1.6. Sample Homogenization, Drying, Partition 5.1.7. Sampling Documentation 5.1.8. Summary 5.2. Biosensors for Pesticides and Organic Pollutants in Soil S.Kröger and A.P.F.Turner 5.2.1. Introduction 5.2.2. Detection Methods 5.2.3. Sample Preparation 5.2.4. Pesticides 5.2.5. Organic Pollutants 5.2.6. Biosensors and Organic Solvents 5.2.7. Unconventional Detection Methods

203 211 213 213

216 218 218 219 222 226 226 227 228 235 235 235 239 239 239 241 243 243 245 246 247 247 248 248 250 251 254 265 268 274

5.2.8. Concluding Remarks 6. Gas-Phase Enzyme Electrodes M.J.Dennison and A.P.F.Turner 6.1. Background 6.2. Gas-Phase Biosensors 6.3. Phenol 6.3.1. Sources of Phenol Pollution 6.3.2. Phenols and Air Pollution 6.3.3. Health Effects 6.3.4. Polyphenol Oxidase

6.3.5. Biosensors for Phenol Monitoring 6.3.6. Phenol-Vapour Biosensors 6.4. Formaldehyde 6.4.1. Health Effects of Formaldehyde 6.4.2. Formaldehyde Dehydrogenase 6.4.3. Enzymatic Assays for Formaldehyde 6.4.4. Biosensors for Formaldehyde Vapour 6.5. Ethanol-Vapour Sensing 6.5.1. Biological Elements for Sensing Ethanol 6.5.2. Biosensors for Monitoring Liquid-Phase Ethanol 6.5.3. Biosensors for Monitoring Ethanol Vapour 6.6. Conclusions 7. Chemical Analysis 7.1. Sample Handling and Analysis of Organic Pollutants in Water Matrices S.Lacorte, D.Puig and D.Barceló 7.1.1. Introduction 7.1.2. Strategies for Sample Handling 7.1.3. Chromatographic Techniques 7.1.4. Biological Techniques 7.1.5. Quality Assurance 7.1.6. Conclusions 7.2. Inorganic Compounds 7.2.1. Heavy Metals K.Cammann, W.Buscher, C.B.Breer, H.G.Riepe, B.Rosenkranz and T.Twiehaus 7.2.2. Determination of Nitrate in Waste Water with Chemical Sensors and Modern Separation Techniques K.Cammann, U.Krismann, B.Ross and W.Kleiböhmer 8. Conclusion A.P.F.Turner and U.Bilitewski

277 285 285 286 287 287 287 288 288

290 291 292 293 293 294 294 295 296 297 300 302 309 309 309 311 324 347 351 357 368 368 392

405

Page 1

1. INTRODUCTION URSULA BILITEWSKI and ANTHONY P.F.TURNER The area of Biosensors has been an active field of research for over 30 years. Initially mainly stimulated by the needs of medical analysis to determine well-defined compounds, such as glucose, in complex media, such as whole blood, biosensors have now found wide applications in fields such as bioprocess monitoring, food and environmental analysis. The development and application of biosensor systems is attractive because of specific features of biochemical reactions, which are well-known and utilized in analysis already since several decades, namely as enzyme assays, immunoassays or bioassays. Generally the recognition of an analyte by a suitable biological molecule is rather specific, which means that only a limited number of compounds will be recognised and specific quantification is often possible even in the presence of chemically related compounds. In addition the affinity of the receptor to the analyte and, in the case of a catalytic system, its chemical turnover are so high that a rather sensitive determination is possible. When combined with a transducer, the biochemical reaction is transformed into an electrical signal, allowing its immediate use for documentation and control. Transduction is not limited to optical methods, which are the classical methods of detection in biochemical analytical assays and which may be prone to interference from the sample matrix, but can also be achieved by using electrochemical, thermometric or piezoelectric principles, thus avoiding separation from particles often required in biochemical assays. Because in biosensors enzymes, whole cells, antibodies, receptors or nucleic acids used as receptors are immobilized, they can be re-used and the resulting biosensors can be applied to a number of samples. There is already a huge number of publications in the biosensor field, ranging from books describing the fundamentals of biosensors (e.g. Turner, Karube, Wilson, 1987; Scheller, Schubert, 1989; Hall, 1990; Buerk, 1993; Kress-Rogers, 1997), proceedings of biosensor meetings (e.g. GBF-workshops on biosensors or EC Climate+Environment), scientific journals (e.g. Biosensors and Bioelectronics, Elsevier) and series (e.g. Advances in Biosensors, JAI Press) entirely devoted to biosensortopics to monographs aimed at the description of the state of the art for a specialist field of application, e.g. food analysis (Wagner, Guilbault, 1994) and bioprocess analysis (e.g. Freitag, 1996) and scientific publications in analytical journals (e.g. Analytica Chimica Acta, Electroanalysis, Analytical Chemistry, Analyst) or application-oriented journals (e.g. J. of Biotechnology, J. Food and Agric. Chem.). These numerous publications reflect the flexibility in the design of biosensor systems, which allow to deal with requirements of the different fields of application. As mentioned above biosensor research was stimulated by the needs of medical analysis and has expanded to field such as bioprocess, food and environmental analysis. Each of these fields of application has its own unique requirements with respect to the analytes to be determined, the concentration ranges of analytes, sample matrices and the desired speed and frequency of analysis. Moreover, in each field there exist different regulations, either legal or just by convention, which analytical procedures have to meet. As a consequence, analytical protocols and in particular biosensors

which have been established for one application are often useless in other surroundings. The simplest biosensors are those where the biochemical element is immobilized directly on the transducer and the resulting sensor can be placed directly in the untreated sample giving near immediate results. However, such simple systems are rather rare in practice and limited to some glucose sensors developed for blood analysis. The reason is that the development of such sensors requires fundamental research on the different steps involved in biosensor development and these basic investigations are to be repeated for each biosensor for each application. Among others the parameters to be investigated include: • the biological element to obtain the desired specificity of the sensor; • the immobilization of the biological element to keep it active and stable for a sufficiently long time; • the process of immobilization to facilitate industrial fabrication of the sensor; • the interface between the transducer and the immobilized biological element to achieve reproducible monitoring of the biochemical reaction; • the performance of the transducer, as its specificity and stability should be sufficient not to counteract the specificity and stability of the biochemical element; • the constant accessibility of the biochemical element in its immobilization matrix to the analyte, as constituents of the sample matrix may form an impermeable membrane on top of the sensor with increasing use; • the analytical range of the sensor to meet the requirements of the samples to be investigated. Moreover, not all biosensors can be as simple as glucose sensors based on glucose oxidase. This is particularly relevant for sensors based on bioaffinity interactions, as only some years ago transduction principles were established allowing the determination of the affinity reaction by simple assay formats (see Chap. 2.2.). Usually not-catalyic biochemical reactions require complex assay principles to result in a signal which can be electrically recorded (see Chap. 3.3, 3.4.). In addition, to reduce the research efforts on the sensor itself with respect to adaption to special requirements of samples, manipulations of the samples are tolerated, such as dilution, filtration, extraction and enrichment of analytes. However, strategies were established to achieve automation of these sample pretreatment protocols thus minimizing the manual laboratory work during analysis (see Chap. 2.3.). Thus, the sensors are often integrated in more complex devices and the idea of a biosensor as a device, which is simply placed into the sample and delivers the analytical information, has only been realised, to date, for a few applications. As a consequence of the various achievements and aspects in biosensor research it is impossible to cover all within one book. Therefore, we present here an overview on the current state of the art of the use of Biosensors for Environmental Monitoring, as this area is at present a rather active area of research for example stimulated by national and European research programs.

Among the various fields of application biosensors have attracted special attention in environmental analysis as there is an increasing concern about pollution of the environment with toxic chemicals. Although conventional chemical analytical procedures have also been improved during recent years with respect to sensitivity, reliability, automation, etc. they often require sophisticated, expensive instruments operated by skilled personnel (see Chap. 7.). Biosensor systems promised to allow analysis of samples by simpler and cheaper methods resulting in a more frequent, perhaps even quasi-continuous analysis, thus reducing the risk for hazardous accidents or criminal poisoning of the environment. However, the total analysis of a sample is increasingly less feasible, independent on the method of analysis, as the list of compounds found in environmental samples expands and information about the toxicity of samples is still demanded. Summing parameters have been defined to avoid the necessity of determining each single compound (e.g. total organic carbon, chemical and biochemical oxygen demand) and biological methods are already well-established in environmental analysis, using bacteria or whole animals (daphnia, fish) to evaluate the toxicity of samples. However, there is also increasing ethical concern about the use of animals as indicators of toxicity, and investigations with respect to the utilization of less complex biological elements are a logical consequence. Thus, work was initiated on the applicability of well-defined microbiological strains, isolated enzymes, antibodies and, more recently, isolated receptors and nucleic acids. Based on this a variety of biosensor systems designed for application in environmental analysis can now be found in the literature and some of these (especially the whole-cell systems) have been commercialized. The following chapters describe first technical fundamentals, i.e. the principles of electrochemical and optical transduction (Chap. 2.1, 2.2.), as these are the most wide-spread and important transduction principles, and of principles used for the design of automated analytical instruments (Chap. 2.3.). Due to the diversity of biochemical principles used in biosensor systems for environmental monitoring an explanation of the fundamentals of the different biochemical approaches follows (Chap. 3.). The second part of the book is devoted to examples of biosensor systems from the different environmental compartments, i.e. water (Chap. 4.), soil (Chap. 5.) and air (Chap. 6.); the analyis of water is the most often cited field of application due to its prominence in legislation and the preference for an aqueous phase in biochemical analysis. The analysis of soil and air is of increasing importance and mainly for soil analysis often the same systems as in water analysis are used in combination with sample pretreatment procedures, such as extraction. Thus, some comments on sampling strategies (Chap. 5.1.) and the use of organic solvents are also included as these are of special relevance in soil analysis due to the heterogeneity of soil. Finally, methods of chemical analysis are described (Chap. 7.) to allow a comparative assessment of the possibilities and limitations of chemical and biochemical analytical approaches.

REFERENCES

Buerk, D.G. (1993) Biosensors Theory and Applications. Lancaster, USA: Technomic Publishing Comp. Inc. Freitag, R. (1996) Biosensors in Analytical Biotechnology. London, UK: Academic Press. Hall, E.A.H. (1990) Biosensors. In Biotechnol. Ser., Milton Keynes, UK: Open University Press. Kress-Rogers, E. (1997) Handbook of Biosensors and Electronic Noses, Boca Raton, USA: CRC Press. Scheller, F. and Schmid, R.D. (1992) Biosensors: Fundamentals, Technologies and Applications. GBF-Monographs Vol. 17, Weinheim, Germany: VCH. Scheller, F. and Schubert, F. (1989) Biosensoren. Germany: Birkhäuser-Verlag. Schmid, R.D. and Scheller F. (1989) Biosensors Applications in Medicine, Environmental Protection and Process Control. GBF-Monographs Vol. 13, Weinheim, Germany: VCH. Turner, A.P.P., Karube, I. and Wilson, G. (1987) Biosensors Fundamentals and Applications. Oxford, UK: Oxford Science Publications, Oxford University Press. Wagner, G. and Guilbault, G.G. (1994) Food Biosensor Analysis. New York, USA: Marcel Dekker, Inc.

Page 5

2. TECHNICAL PRINCIPLES URSULA BILITEWSKI Characteristic features of biosensor systems, such as sensitivity, specificity, influence of sample matrix, measuring frequency, are strongly influenced by technical details of the total system. These include the transduction principle, the fabrication technology of the transducer, the degree of automation, etc. Therefore in this chapter the fundamentals of the most wide-spread transduction principles and some aspects leading to automated analytical devices will be mentioned. The first biosensors described were enzyme electrodes being a combination of glucose oxidase with an oxygen or a hydrogen peroxide electrode and still today electrochemical transduction is of major relevance when developing enzyme sensors. That is why the electrochemical fundamentals are described here. In biochemical assays photometry is the major transduction principle, and optical transduction has developed into a major principle also in the field of biosensors. This was mainly due to the availability of optical fibres and decreasing prices for lasers, laserdiodes and optical detectors. Moreover, besides the classical optical principles of fluorescence and absorbance new principles were established based on the evanescent field moving optical detection from volume-based to surface-sensitive measurements. This made them ideally suited as transducers in affinity sensor systems, where they have found major application. Thus, in Chap. 2.2. optical transduction principles are described, focussing however on those being used in affinity sensor systems. As final part (Chap. 2.3.) the principles of flow injection analysis will be described, as they form the basis of most automated biosensor systems. 2.1. ELECTRODES

FRED LISDAT and FRIEDER W.SCHELLER 2.1.1. INTRODUCTION

Considering the number of published papers on biosensors as well as the types of commercialised sensors, electrochemical systems appear to be the most favoured transducers. Electrochemical transduction means that the biological recognition or conversion event is transferred to an electrical signal, which might be a current or a potential. Thus, two types of electrode systems can be distinguished: amperometric and potentiometric. A third group are impedimetric transducers, which detect impedance changes resulting from the analyte interaction with the receptor molecule. In the simplest case these are changes in the conductivity within the medium. Electrochemical methods provide a direct relation between the electrical signal measured and the concentration of charged or uncharged species in solution. In most cases equipment is not sophisticated, but precise and versatile measurements are provided. Furthermore, electrodes are well suited to sensor miniaturisation and by means of semiconductor industry techniques, systems can be mass produced in a defined way.

Analytical information can be transferred from the biomolecule to the transducer by secondary chemical signals (substances produced or consumed by the receptor molecule and detected with an electrochemical system) or by direct electron transfer between the biomolecule and the electrode (Turner et al., 1987; Scheller and Schubert, 1992). The latter approach (direct protein electrochemistry) has gained considerable interest in the literature (e.g. Tarasevich, 1985; Guo and Hill, 1991; Gilmanshin, 1993; Schmidt et al., 1991; Ikeda, 1997) but application for environmental control is rather limited. Therefore, this chapter will concentrate on the first approach. Alternatively to the detection of secondary chemical signals, the direct observation of analyte interaction with a biomolecule is accessible by means of impedance spectroscopy, the basics of which will be described in the last section of this chapter. Application of electrochemical transducers in biosensors for environmental analysis can be seen mainly in two directions: First, enzymes are combined with electrodes to detect phenolic compounds (the phenolic content of a sample is one of the key parameters for the assessment of an environmental situation) or inhibitors of enzymatic activity are determined. Second, for highly toxic substances such as pesticides or herbicides, which have to be determined in very low concentrations (subnanomolar), immunoassays using enzyme or redox labels are used. 2.1.2. POTENTIOMETRIC TRANSDUCERS 2.1.2.1. Fundamentals

Potentiometry is based on the formation of an electrochemical equilibrium at an electrode under the condition of zero current (Kissinger and Heineman, 1984a; Bard and Faulkner, 1980). The equilibrium reaction is characterised by a charge transfer across the phase interface with the same exchange current density for both directions of the electrode reaction. Depending on the type of charge carrier ion electrodes (anions, cations) and redox electrodes (electrons) can be distinguished. In both cases the electrode potential depends in a defined way on the concentration (or better activity) of the substances involved in the electrode reaction. This dependence is given by the Nernst equation: (2.1.1)

where E is the equilibrium potential of the electrode, E0 the standard potential, ai, the activity product of substances taking part in the electrode reaction, vi is the stoichiometric factor of the individual substances according to the reaction equation, n the number of exchanged charges (electrons, ion charge) and R, T and F are Gas constant, temperature and Faraday constant, respectively. The concentration is correlated to the activity by an activity factor taking into account the deviation from the ideal behaviour by interactions of the particles in solution ( ). Constant activity factors can be reached by using supporting electrolytes or buffer systems. Because of the logarithmic potential dependence on concentration, a large concentration range can be covered by potentiometric sensors (several orders of magnitude). The electrode potential is measured versus a reference electrode. This electrode provides a constant potential in different electrolytes with variable composition so that all changes in the

potential measurement are attributed only to processes at the working or sensing electrode (Ives and Janz, 1961; Lisdat et al., 1990; Sawyer et al., 1995). The most frequently used reference systems are calomel and silver/silver chloride electrodes. According to the electrode reactions for both systems, constant chloride concentration has to be ensured in order to provide a reference potential:

This requirement is fulfilled by establishing a constant chloride ion concentration in solution or by separating the reference half cell using a diaphragm from the electrolyte under investigation. It shall be mentioned that the separation of both electrolytes causes a diffusion potential, which results in a potential error if pH and composition are extremely different in both solutions. Ways to minimize the influence of this “liquid junction” on the potential measurement are discussed in the literature (Sawyer et al., 1995; Kortüm, 1962; Bagg, 1990). They are mainly based on the use of “bridging electrolytes” with the same ionic conductivity for an- and cation. For practical measurements, sensing and reference electrode are connected to a digital voltmeter with high input resistance ( ) and the voltage difference is measured. Standard electrode potentials are defined versus the standard hydrogen electrode, but since this electrode is not used for practical measurements the electrode potentials of the most commonly used reference electrodes vs. the standard hydrogen electrode have been collected in Table 2.1. Among potentiometric transducers ion-selective electrodes and the derived gas-sensitive electrodes are used virtually exclusively for analytical applications in biosensors. This is because the lack of selectivity of redox electrodes, which results in Table 2.1. Potential of several reference electrodes vs. the standard hydrogen electrode. electrode system

potential vs. SHE (V)

Ag/AgCl, KCl(sa)

+0.197

Ag/AgCl, KCl(1 mol/l)

+0.236

Hg/Hg2Cl2, KCl(sa)

+0.241

Hg/Hg2Cl2, KCl(1 mol/l)

+0.280

Hg/Hg2SO4, H2SO4(0,5 mol/l)

+0.679

interference of the electrode potential by other electro-active substances. Reduction of electrode dimensions is not a simple task for potentiomeric sensors but with the use of semiconductor devices miniaturised potentiometric sensor elements can be provided (see ISFET section below). The combination of potentiometric transducers with the biocomponent is based on the detection of products of the biocatalytic analyte conversion. The products might be NH3, CO2 or protons. In the latter case actual pH changes caused by the enzyme reaction near the pH electrode are

detected. However, sensitivity is influenced by the buffer capacity of the solution. Combinations of biocatalysis with subsequent chemical reactions allow the introduction of other ion-selective electrodes as transducers in biosensors (e.g. fluoride-sensitive electrodes for enzymes producing H2O2, which subsequently reacts with a fluororganic compound liberating fluoride ions). 2.1.2.2. Ion-selective electrodes (ISE)

These electrodes make use of a solid-state membrane electrolyte showing an exchange equilibrium for the preferred ion and thus establishing a membrane potential across the membrane-solution interface (Morf, 1981; Camman, 1996; Fry, 1991). The most commonly used ISE is the pH glass electrode. It consists of a glass membrane which on one side is in contact with an outer solution and on the other side with an internal filling solution of known pH. In both electrolytes (internal, external) reference electrodes are inserted (Figure 2.1). The ion-conducting glass forms a surface silicic acid/silicate buffer layer which is in equilibrium with hydrogen ions in solution. Thus a membrane potential is formed on both sides of the glass. Because the internal pH is constant, the electrode potential is only dependent on the pH of the outer solution. (2.1.2)

(2.1.3) Due to the high reaction rate of protons, the pH-glass electrode responds fast to concentration changes in solution and, in addition, covers the largest concentration range among ISEs (10−14– 100 mol/l). As an alternative to the pH-glass electrode, metal oxide electrodes can be used for pH determination. These electrodes are based on the combination of a heterogeneous electron transfer reaction with a chemical reaction. Besides antimony oxide, palladium or iridium oxide electrodes can serve as the basic transducer in biosensors. The electrodes are well suited to miniaturisation, however, their potential is influenced by other redox-active substances. Analogous to the pH-glass membrane, other solid membrane electrolytes (such as ion-conducting polymers, solid electrolytes or liquid electrolytes held in a supporting matrix) can be used for ion-selective electrodes (Morf, 1981). Glasses modified in their composition compared to the pH electrodes give access to the determination of several metal ions such as Na+, Li+, Ca2+, Mg2+, Ag+ a.o. With LaF3 single crystals, doped with EuF2 for ionic conductivity, fluoride ions can be detected. Other examples of ion conductors used as sensing material are silver halides (halide detection) and

Figure 2.1. Cross section of a pH-glass electrode incorporating the external reference electrode into the electrode body. NASICON (Na+ detection). A large group of electrodes uses polymer membranes incorporating ionophores—compounds with binding specificity for a certain ion (by complexation). Based on these membranes, ISEs for several an- and cations can be obtained. For biosensor construction —sensitive electrodes are particularly relevant (because of the use of NH3 forming enzymes). 2.1.2.3. Gas-selective electrodes

Two main kinds of these ISEs can be distinguished with only one having importance in the biosensor field. Solid electrolyte cells (Möbius, 1991) using, for example, ZrO2 as ion conductor between two metal electrodes can be applied to gas detection at higher temperatures (e.g. system O2 (ref.), Pt/ZrO2/Pt, O2 for oxygen sensing). For measurements in solution membrane electrodes are used. These electrodes are derived from the pH-glass electrode; the pH-sensitive glass is covered by a thin liquid electrolyte film and a gas permeable membrane. Gases in the test solution can permeate this membrane, change the pH of the electrolyte film and therefore the electrode potential.

For the detection of gas-forming ions such as or (produced by an enzymatic reaction) the pH of the solution is decisive. To convert these weak electrolytes into the non-ionic form which can pass the gas permeable membrane, pH values of > 10 (for NH3) and < 5 (for CO2) have to be aimed at. These values are often far from the optimum condition of the biocomponent, so that compromises have to be found (lowering the sensitivity of the electrode) or the biocatalytic conversion has to be separated from the potentiometric detection. Such an arrangement can be termed a reactor electrode. 2.1.2.4. Ion-sensitive field-effect transistor (ISFET)

For the miniaturisation of potentiometric sensors chemically-sensitive semiconductor devices (CSSD) are particularly suited. In addition to their small size they have the potential for standardised mass fabrication using techniques from the semiconductor industry. The ISFET is the most extensively investigated representative of this group, which has already found commercial application (Janata and Huber, 1979; Bergveld and Sibbald, 1988; Lundström et al., 1991). The structure is derived from the transistor device MOSFET (metal-oxide semiconductor field-effect transistor). In ISFETs, the metal gate of the MOSFET is replaced by the ion-sensitive membrane in contact with the solution and the reference electrode (Figure 2.2). As for all potentiometric sensors an electrochemical potential is established at the solution/ion-sensitive membrane interface. This potential, which is dependent on the concentration of the potentialdetermining ion, affects via the field effect the current flowing in the inversion layer between source and drain. Two modes of operation can be used for the device. In the first version, the drain-source current (IDS) is held constant by compensating changes of the interfacial potential at the sensitive membrane applying an external voltage via the reference electrode (gate voltage VG). For this mode the output of the device is correlated to the concentration via the Nernst equation as usual for potentiometric sensors. In the second mode, the gate voltage is held constant and changes of the drain-source current due to concentration changes are monitored. The semiconductor device provides the advantage of in-situ impedance transduction. The signal coming from the high impedance line between the bulk of the semiconductor and the reference electrode where no current flows, is transferred to the low impedance line between source and drain where current flow is possible in the interfacial inversion layer of the semiconductor. The dependence of the drain-source current from substances in solution as well as from the design of the device is given by the following equation for the unsaturated region where the source-drain current IDS is a function of the applied voltage VDS: (2.1 A)

µ is the electron mobility, COx the capacitance of the gate insulator, W and L represent the width and length of the channel between source and drain (gate region), is the threshold voltage which includes the standard potential of the electro-

Figure 2.2. Schematic view of an ion-sensitive field-effect transistor (ISFET). 1 is the semiconductor bulk (e.g. p-region), 2 and 3 are source and drain (e.g. n-regions), 4 is the insulator layer (typically SiO2), 5 and 6 are the sensitive layer and reference electrode which are in contact with solution, 7 represents the encapsulation of the device, VG and VDS are the gate and drain-source voltage. chemical reaction. VDS and VG represent the voltage applied between source and drain and the gate voltage, respectively, ai is the activity of the electrochemically active substance in solution and Eref is the potential of the reference electrode. Si3N4, Al2O3 or Ta2O5 are the prefered sensitive layers on the gate region of ISFETs for pHdetermination. Fluoride-sensitive ISFETs are obtained by evaporation of LaF3 on top of the gate insulator and metal ion-sensitive devices use chalkogenide glasses (Pb2+, Cu2+, Cd2+ a.o.), silicate layers (Na+ a.o.) or thin polymer membranes with ionophores (K+, Ca2+, Mg2+ a.o.). ISFETs in combination with a biocomponent are referred to as ENFETs (enzyme FETs) or IMFETs (immunochemically sensitive FETs). From the basic MOSFET structure devices can be also derived for gas measurements (Lundström et al., 1991). The gate metal of the field effect transistor serves as the sensing layer and different metals and mixtures are used for different gases to be detected. For example, palladium gas-FETs which are sensitive to hydrogen can be modified by iridium to become a NH3 sensor. Besides the ISFET, there are other semiconductor devices, like diodes and capacitive elements, which can transform the electrochemical potential, according to the device characteristics, to a current, voltage or capacity (Lundström et al., 1991). However, for biosensor construction they are at the moment of minor importance.

2.1.3. AMPEROMETRIC TRANSDUCERS 2.1.3.1. Fundamentals

Amperometry belongs to the group of voltammetric measurements recording an electrode current as a function of applied potential. For amperometric detection, the electrode is held at a potential for electrocatalytic conversion of the redox-active substance in solution and the resulting steadystate current is measured. At the electrode interface heterogeneous electron transfer occurs between the substance and the electrode (oxidation, reduction). The current measured is not only determined by this redox reaction, but with increasing overpotential (deviation from the redox potential of the substance) mass transport phenomena and concentration polarisation become important (Kissinger and Heineman, 1984b; Bockris and Khan, 1993). At a high overpotential, where the electron transfer reaction is accelerated so that the surface concentration of the substance becomes zero (because all particles transported to the electrode are immediately converted), electrode current is limited by diffusion of the substance through the diffusion layer in front of the electrode (Figure 2.3). Using Fick’s first law of diffusion, the current can be described as follows: (2.1.5)

where n, F and D are number of exchanged electrons, Faraday constant and diffusion coefficient of the redox active substance. A is the electrode area, δ denotes the thickness of the diffusion layer and cS the concentration of the substance in the bulk solution. The formula is only valid if the total conductivity is much higher than the conductivity contribution of the species to be detected so that migration effects can

Figure 2.3. Schematic view of the concentration course in front of an amperometric electrode for the case of diffusion limitation (cEl denotes the surface concentration of the electrochemically active substance, cS the bulk concentration in solution and δ the thickness of diffusion layer). be neglected (i.e. in solutions with supporting electrolyte). The proportionality of the current to the concentration gradient in front of the electrode results in a linear current-concentration

relationship under the condition of constant convection (δ=const.). Therefore, diffusion limitation is the case of choice for most applications. In biosensor application this situation is often achieved by use of a membrane in front of the electrode (e.g. for biomolecule immobilisation) and thus membrane thickness may correspond to the diffusion layer thickness avoiding stirring influences on the electrochemical detection. Amperometric measurements are very sensitive; concentrations from the milli-molar concentration range down to the submicromolar level can be determined. If the electrode reaction is well defined fast response of the electrode can be obtained. The high sensitivity in combination with the high response rate are two of the main advantages of amperometric transducers. There are two different electrode configurations that are suitable for practical measurements. Figure 2.4 shows both the two- and three-electrode arrangements. In general, the use of the threeelectrode system is more advantageous because no current flows through the reference electrode and precise measurements at well defined potentials are possible. However, at low current densities two electrode measurement can be used without any significant disturbance. Reference and counter electrode have to be combined and a large electrode surface and low resistance have to be ensured to avoid electrode polarization and serious potential changes, (see, for example, oxygen electrode below). In amperometry the reference electrode is not as critical for the

Figure 2.4. Electrode arrangements for amperometric detection, A—three electrode measurement, B—two electrode measurement (WE working or sensing electrode, RE reference electrode, CE counter electrode).

measurement as in potentiometry, but because it serves as a basis for the definition of the working electrode potential, the reader is referred to section 2.1.2.1. for more details. Due to the different redox potentials of substances present in the sample, the applied potential at the working electrode is of decisive importance for the selectivity in amperometric detection. If the redox potentials of the analyte and interfering substances are very close to each other, the current measured can no longer be correlated to the analyte concentration alone. Different ways can be adopted to solve this interference problem. By use of an electrode material for which the interferant shows high overpotential, the current-analyte concentration calibration can be reestablished (increase the relation between the analyte determined current and interference current). Another possibility is the introduction of protecting or repelling films which allow the analyte to pass the film (or even to enrich within the film) but strictly limit the access of interferants to the electrode surface (e.g. NAFION as anion exchanger can reject acids such as ascorbic or uric acid). For the same purpose, interference removal by means of an enzyme can be effectively used. Interferants are enzymatically converted into substances which are no longer electro-active at the chosen electrode potential and thus do not disturb analyte detection. Another approach avoids the detection of substrates or products of the biocatalytic conversion and uses redox mediators acting as an electron shuttle between the biomolecule and the electrode. The redox potential of such a mediator is low compared to the interferant so that only the mediator contributes to the measured current. On the other hand, the mediator has to show enough redox potential to transfer redox equivalents from or to the biomolecule in solution (see section mediator modified electrodes below). Oxidases are often used as biochemical receptor elements. Their action during analyte conversion can be followed by measuring oxygen or hydrogen peroxide, which is either consumed or produced in the enzymatic catalysis. Basic transducers for their electrochemical detection will be described in more detail in the following sections. 2.1.3.2. Oxygen electrode (Clark cell)

The principal scheme of an oxygen cell (named after its inventor L.C.Clark) is shown in Figure 2.5. The cell consists of a working electrode (noble metal—Pt, Au) which is insulated and then surrounded by a silver electrode operating as reference and counter electrode. Therefore, the silver is covered at the surface by silver chloride. The electrode compartment is separated from the test medium by a gas-permeable membrane and filled with a chloride containing electrolyte. The working electrode is poised at a potential of −0,6V versus the surrounding Ag/AgCl electrode. If oxygen is present in the test medium it can pass the permeable membrane, diffuse through the electrolyte and is then reduced at the noble metal electrode. The following reactions take place at both electrodes of the cell:

It is obvious that during the amperometric detection of oxygen silver is consumed. Therefore, a small working electrode area is advantageous and a sufficient reservoir of

Figure 2.5. Example of a Clark-type oxygen electrode. silver has to be ensured. This applies especially to miniaturised versions of the Clark cell. The main advantage of the oxygen electrode is that it is free from electrochemical interference effects because the gas-permeable membrane rejects all other constituents in the solution which might interfere with the electrochemical oxygen detection at the electrode. The problem of varying oxygen content in different samples to be analysed can be circumvented e.g. by sample dilution with air-saturated buffer or elegantly by mixing the sample solution with a larger volume of air, thus passing the electrode as an aerosol or by introduction of an additional electrode within the oxygen consuming biolayer producing the same amount of oxygen which is consumed during the biocatalytic conversion. 2.1.3.3. H2O2-measurement

Two or three electrode arrangements can be used as detection systems for hydrogen peroxide. In both cases the working electrode is biased at +0.4 −1 V vs. a Ag/AgCl electrode (depending on electrode material and pretreatment) to force H2O2 oxidation:

For the measurement, the electrode is covered with a dialysis membrane to avoid influence from high molecular weight compounds (e.g. electrode fouling by proteins). The main disadvantage of H2O2 detection results from interference by other electrochemically oxidizable species in solution. Besides the described use of repelling films, differential measurements between enzyme-loaded and enzyme-free electrodes are feasible. Despite the principal problem inherent in these measurements, enzyme electrodes based on H2O2 detection have found widespread application being evidence of the high standard in membrane optimisation (design) used for enzyme immobilisation and interference protection. 2.1.3.4. Mediator modified electrodes

Another way to reduce the interference problem is to reduce the potential at the working electrode. The natural electron acceptor (e.g. O2, cytochrome c) of many oxidoreductases can be replaced by redox dyes or other reversible redox systems transferring redox equivalents from the enzyme to the electrode (Figure 2.6). Examples of typical substance classes for these redox mediators are collected in Table 2.2. For practical use redox mediators have not only to be electrochemically reversible but should also have a well defined electrochemical stoichiometry and a high electron transfer rate (to the electrode and to the biomolecule). They

Figure 2.6. Schematic diagram of the mediated electron transfer from the analyte molecule to the electrode (EOX and MOX denotes the oxidised form of enzyme and mediator and Ered, Mred the reduced form).

Table 2.2. Typical classes of compounds used as mediators in amperometric biosensors. anthraquinones benzoamines benzoquinones ferrocene+derivatives hexacyanoferrate (III) indophenols naphtoquinones phenazines Ru, Os complexes viologenes (e.g. methylviologen MV) charge transfer complexes (e.g. tetracyano-p-chinone dimethane TCNQ—tetrathiafulvalene TTF) should show no non-specific interaction with the biomolecule and have to be stable in both redox states—prerequisites limiting the applicability of some redox dyes. The use of mediators brings an additional advantage into the measurement with oxygen-dependent enzymes; the problem of oxygen fluctuations in the solution under investigation can be overcome and even measurements in oxygen-free solution are possible. In order to minimize problems of mediator solubility and stability as well as avoid mediator addition to the solution, the concept of mediator-modified electrodes was developed. The mediator can be adsorbed onto the electrode surface, enclosed together with the enzyme in a conducting polymer on top of the electrode, covalently attached to the electrode surface or mixed into a carbon paste electrode. In all cases communication with the enzyme has to be ensured and leaching out of the mediator has to be avoided. For further discussions see e.g. Bartlett et al. 1991. The principle of mediated electron transfer to the electrode has also importance for the analytical determination of the coenzyme NAD(P)H. This pyridine nucleotide is the coenzyme for more than 300 enzymes providing access to a large number of analytes. However, the electrochemistry of NADH at metal electrodes is not sufficiently reversible resulting in high overpotentials for its oxidation (~1V). Therefore, interference by other redox active substances occurs and in addition, electrode poisoning by products of the two step oxidation process is observed. In contrast, mediated NADH oxidation allows low electrode potentials and leads to well defined electrochemistry. For the mediator modification of electrodes charge-transfer complexes can be effectively used (“organic salt electrodes” [Bartlett, 1990]). 2.1.3.5. Enzyme modified electrodes

Starting from the concept of mediator fixation, the enzyme itself can be covalently immobilised on the electrode leading to enzyme chemically modified electrodes. This

method provides short diffusion distances and thus achieves high mediation efficiency. A more advantageous method is the combined immobilisation of both the mediator and enzyme onto the same detecting electrode. For analyte determination no additives to the solution are required, resulting in a reagentless measuring system. The efficiency of electron transfer can be further improved by “wiring” the enzyme to the electrode. As “wires” mediator-like molecules can be used which are covalently attached to both the electrode and the enzyme molecule and thus, transferring electrons like a “molecular wire” (Heller, 1992). Redox polymers are also suitable for the construction of this kind of enzyme sensors. With these electrodes one comes to the borderline of direct electron transfer between the enzyme and the electrode avoiding any redox shuttle between the partners. Because of the limited application in the environmental field, the interested reader is referred to extensive presentations in the literature (e.g. Tarasevich, 1985; Guo and Hill, 1991; Gilmanshin, 1993; Schmidt et al., 1991; Ikeda, 1997). The surface immobilisation of enzymes can be effectively used for another type of biosensors. The basic idea can be seen in analogy to redox mediation in enzyme sensors. In contrast, however, the analyte itself is here a redox-reversible substance which can be oxidised or reduced by the electrode and subsequently enzymatically re-reduced or re-oxidised to the original form. Therefore, a redox cycle is formed and the amperometric electrode current can be accelerated by several orders of magnitude resulting in an ultrasensitive detection system (see Figure 2.7). Compared with

Figure 2.7. Scheme of a bioelectrocatalytic amplification system. The analyte is electrochemically oxidised and subsequently enzymatically recycled to be again available for electro-oxidation. This analyte shuttling results in an amplification of anodic electrode current giving access to lower concentration ranges compared to the non-amplified electrode reaction. It should be mentioned that in the redox cycle the partners may be arranged vice versa, i.e. combination of enzymatic oxidation and electrochemical reduction.

conventional amperometric electrodes, the concentration range below 10−7 M down to nanomolar or even subnanomolar concentrations is accessible with these bioelectrocatalytic amplification systems (Wollenberger et al., 1997). This is relevant, for example, for the detection of phenolic compounds in environmental analysis. The application of this type of sensors is limited to analytes which show rather reversible redox behaviour at the chosen electrode material and to systems in which the redox intermediates are not poisoning the electrode. 2.1.3.6. (Ultra)-Microelectrodes

The impetus for miniaturisation of electrodes has come particularly from the medical area and is now a general trend in the field of sensors. The reduction in electrode dimension does not simply lead to decreased signals and problems of reliable measurements, but results in a qualitatively new behaviour compared to measurements with “macroscopic” electrodes (Montenegro, 1994; Heinze, 1993; Aoki, 1993). The term “microelectrodes” (or ultramicroelectrodes) is used when electrode dimensions become smaller than the characteristic diffusion layer thickness. In general this applies to planar electrodes with diameters <20 µm. For these electrodes, mass transport in front of the electrode is no longer governed by a planar diffusion field but by a (hemi)spherical field (Figure 2.8). This results in an enhanced mass transport to the electrode and an increased current density compared to macroelectrodes. This increase can reach some orders of magnitude depending on the diameter of the electrode (the smaller the electrode the larger the increase). In addition, the ratio of Faradic and capacitive current is increased and thus the signal: noise ratio is improved. For the steady-state current at a disk electrode under potentiostatic conditions can be written (Heinze, 1993): (2.1.6)

Figure 2.8. Schematic representation of planar diffusion at a macroelectrode (A) and spherical diffusion at an ultramicroelectrode (B). where n is the number of transferred electrons, cS is the concentration of the redox-active substance in solution, D is the diffusion coefficient and d is the disk electrode diameter.

The potential of microelectrodes can be seen not only from the enhanced analytical performance but also from their mass production using techniques of semiconductor industry which increasingly approaches the quality of other sophisticated methods of microelectrode preparation (wire types). This may increase their application in the biosensors field in near future. In addition to measurements at a fixed potential, several potentiodynamic techniques can be used for sensor characterisation. Examples are differential pulse voltammetry (DPV), differential normal pulse voltammetry (DNPV), potential pulse chronoamperometry (CA) a.o. These methods apply a voltage ramp in combination with a potential pulse to the electrode and record the current at elevated points of the potential-time profile. This gives access to the determination of several analytes in a sample with different redox potentials and is particularly valuable in seperating interferant signals. In the biomedical field, they have already found widespread application in neuroscientific investigations. In environmental analysis this development is not so pronounced and for additional information the reader is referred to the literature (Kissinger and Heineman, 1984a; Blaha and Philips, 1996). 2.1.4. IMPEDANCE MEASUREMENTS

Biological recognition or conversion is often accompanied by changes in the impedance of the system. In the simplest case these are changes in conductivity caused by the biocatalytic production of acids. Another example is the determination of changes in the microbial biomass using capacitance measurements. Until now application of this measuring principle for analytical purposes is rather limited. However, the developments in electrode miniaturisation as well as the progress in fast data evaluation give this type of transduction further prospects leading us to a more detailed description of the method. In the field of immunosensing, for example, it allows the construction of label-free immunosensors with a direct detection of the specific binding event. Furthermore, impedance spectroscopy can provide very sensitive measurements with comparable detection limits as optical methods (Berggren and Johansson, 1997; Ameur et al, 1997; Paeschke et al, 1996). The impedance of a system is defined as the quotient of the voltage function applied to the system and the resulting current function which are commonly sinusiodal functions: (2.1.7)

where VM and IM are the amplitudes of alternating voltage and current, f is the frequency, t the time and the phase angle (or shift) between the voltage and current function. Because of this phase shift the impedance appears as a complex quantity. Thus, it can be characterised by the absolute impedance value or modulus |Z| and the phase angle between the voltage and current function and consists of a real and an imaginary part. The vector presentation of the quantity is given in Figure 2.9. Because inductivity plays a minor role in biological systems, impedance can be expressed by capacitive and resistive elements as follows:

(2.1.8) where ZR and ZI are the real and imaginary part of the impedance, j is (−1)1/2, R and C are the resistance and capacitance at the frequency f and w is . In the simple case of a resistor and a capacitor in series, these values are frequency independent; frequency dependence is the proof for a more complex picture of the system including several impedance elements and parallel and series circuits as well. The main goal of impedance measurements (often referred to as impedance spectroscopy) is the creation of an impedance model in the form of an equivalent circuit describing the main physico-chemical properties of the system under investigation. These properties may be surface- as well as bulk-phenomena (Macdonald, 1987; Rubinstein, 1995). The basic impedance elements for the description of biological systems are resistance, capacitance, constant-phase element (CPE) and Warburg impedance. A resistance can represent for example a charge transfer resistance at an electrode (according to a Faradic process) or the bulk resistance of an enzyme membrane. Capacitive elements describe e.g. the double layer capacitance at an electrode or the dielectric properties of an electrode covering material. The constant-phase element (CPE) is a model of a loss capacitor related to inhomogenities of the system under investigation, e.g. fractal porous electrodes or films with a conductivity gradient. The Warburg impedance is an element related to the transport of substances to the reaction layer. It is particularly relevant in the lower frequency range and represents the semi-infinite

Figure 2.9. Vector diagram of the impedance using rectangular coordinates (ZI—imaginary part and ZR—real part of impedance) and polar coordinates (|Z|—modulus or absolute impedance value and —phase angle).

Figure 2.10. Randles equivalent circuit for a simple, one-step electrode reaction including solution resistance (Rs), double layer capacitance of the electrode (Cdl), charge transfer resistance (RCt), which denotes the electron transfer from the electrochemically active substance to the electrode, and diffusion impedance (Warburg impedance—W). diffusion of particles. Figure 2.10 shows an equivalent circuit developed by Randles for the description of a simple one-step electrochemical reaction with diffusional transport to the electrode. In Table 2.3 the impedance definitions of the elements used are shown. For the impedance measurement of a biological material, electrodes have to be introduced into the system. Figure 2.11 gives a schematic representation of an equivalent circuit for such a measuring system. For analytical purposes, different modes of operation are possible, e.g. the impedance of the biological system (ZB) can be determined (as a function of analyte concentration) or simply the change in solution resistance (RS) is evaluated. Alternatively, one electrode might be Table 2.3. Impedance definitions of some elements typically used in model equivalent circiuts. (Rd—diffusion resistance for (correlated to the concentration, the stoichiometry and kinetics of the electrochemical reaction), D—diffusion coefficient, I—diffusion region, ωangular frequency, ) impedance element

impedance definition Z=

resistance

R

capacitance constant phase element (CPE) Warburg impedance (infinite length)

Figure 2.11. Equivalent circuit of an electrochemical cell including a biocomponent and electrolyte solution. The electrodes are described by a parallel circuit of charge transfer resistance and double layer capacitance (ZE1, ZE2). In series to these elements there is the solution resistance (Rs) and the impedance of the biocomponent under investigation (ZB). One electrode might be directly modified by this biocomponent and appears as the sensing electrode in the system. The combined impedance is indicated by ZSE. incorporated into the recognition system and the impedance of this “sensing” electrode (ZSE) is measured (e.g. an antibody-covered metal electrode). For all measurements, the impedance element to be evaluated should determine the overall impedance. This can be achieved by reducing the impedance of the additional elements in the circuit, e.g. electrode impedance (high surface area) or solution resistance (supporting electrolytes) or by selection of an appropriate frequency range of measurement, where the impedance is dominated by the investigated element. If the impedance of other elements is not negligible their values have to be determined carefully. The impedance can be determined in the frequency or time domain. In both measurements a perturbating signal is applied to the system (e.g. ac voltage, voltage jump) and the current response is detected. In the frequency domain, a sinusoidal voltage with small excitation amplitude is applied to the electrochemical cell and the phase and amplitude of the current are detected at different frequencies. Correct data can only be obtained when the impedance determined from the measurement is independent of the applied signal. This is only valid for small ac voltage amplitudes (millivolt) and has to be tested for every cell under investigation. The frequency range covered by commercially available measuring systems extends from about 10−4 Hz to several MHz. In the time domain, a voltage step function is applied to the system and the time dependence of the current response is measured. To obtain the impedance function corresponding to the frequency domain result, Fourier transformation is necessary. Again the voltage step has to be small so that a linear response of the system is observed. Because impedance shows a significant temperature dependence

Table 2.4. Impedance related functions. (

; Ce—capacitance of the empty cell).

Z-impedance

Y-admittance

ε-permitivity

Z

Z

1/Y

1/µε

Y

1/Z

Y

µε

ε

1/µZ

Y/µ

ε

experimental errors can be avoided by temperature control or differential measurement of two electrochemical cells where only one is modified with the biological system. Modern impedance analysers also incorporate data evaluation and fit programs which allow the calculation of transfer functions according to a model equivalent circuit. In validating such a model—describing the essential properties of the biological system—parameter variations such as layer thicknesses, electrode area, as well as analyte and electrolyte concentrations are particularly useful. After validation of the model circuit, in particular for analytical purposes, a reduction in the expenditure of the measurements might be useful. Thus, measurements at evaluated single frequencies may provide sufficient analytical information. Several quantities can be used for the representation of the impedance information obtained within a measurement. Besides impedance plots, these are mostly admittance or permitivity diagrams. Table 2.4 gives the relation of these quantities to each other. For reasons of consistency we will concentrate on impedance plots. In the Bode-plot the logarithm of the absolute impedance as well as the phase angle are plotted versus the logarithm of applied frequency. In this representation, regions of capacitance dominated impedance can be clearly distinguished from regions of resistance dominated one. Because of historical reasons the Nyquist-plots are preferably used in electrochemistry. In this plot the imaginary component of the impedance is plotted versus the real component. Processes with clearly distinguished time constants ( ) can be easily visualised by different semicircles in this diagram. For a better illustration Figure 2.12 shows (with the example of a polyurethane membrane (Lisdat and Moritz, 1994)) both diagrams and the characteristic values which can be determined directly from the plot. 2.1.5. CONCLUDING REMARKS

Signal transduction by means of electrochemical techniques—potentiometry, amperometry, impedance spectroscopy a.o.—is generally based on the use of an “electrode”: a combination of an electron conducting phase with an ion conducting phase aimed at a qualitatively new system. The interface between both phases is of key importance for the analytical application of electrodes. The modulation of the charge transfer at this interface or the charge transport to the interface by chemical and biochemical processes is the basis of the detection event. Using potentiometric measurements a large concentration range is accessible because of the logarithmic concentration-potential dependence. In contrast, the

Figure 2.12. Calculated impedance plots of a polyurethane membrane in 1M NaNO3 solution neglecting the frequency dispersion (values were taken from [30], with a membrane thickness of 2 µm and an area of 1 cm2). Both plots describe the bulk properties of the membrane: RM is the membrane resistance and CM the geometrical capacitance. These quantities are determined by membrane thickness, area, water uptake and electrolyte composition. A—Bode plot, B—Nyquist plot (ωmax is the frequency determined at the maximum of the semicircle). amperometric detection method can provide linear relationship resulting in a smaller concentration range but much higher resolution. Impedance spectroscopy can provide highly sensitive measurements if conditions can be found to minimize additional impedance elements within the circuit. Electrochemical transducers are attractive basic elements for sensor construction. The developments in miniaturization (semiconductor devices, ultramicroelectrodes, interdigitated microstructures a.o.) and their potential for mass fabrication give them clear prospects for intensive application in the biomedical and environmental field.

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activity of the electrochemically active substance in solution electrode area concentration of electrochemically active substance in solution capacity of the gate isolator (ISFET) diffusion layer thickness (in front of an electrode) diffusion coefficient potential of the reference electrode standard potential of an electrochemical reaction frequency activity factor phase angle (or shift) between the voltage and current function Faraday constant ion-selective electrodes ion-selective field effect transistor drain-source current (ISFET) amplitude of alternating current

L (l) µ n

lenght of the channel between source and drain (ISFET) liquid electron mobility (ISFET) number of electrons or charges (in the case of ions) transferred across the phase interface according to the equation of the electrode reaction v stoichiometric factor of a substance according to the equation of the electrode reaction NAD(P)H Nicotinamide adenine dinucleotide (phosphate) NASICON Na3Zr2Si2PO12 R gas constant (s) solid (sa) saturated SHE standard hydrogen electrode t time τ time constant T temperature threshold voltage including the standard potential of the electrochemical reaction (ISFET) VDS voltage applied between source and drain (ISFET) gate voltage (ISFET) VG amplitude of alternating voltage VM ω angular frequency ( ) W width of the channel between source and drain (ISFET) Z impedance |Z| absolute impedance value or modulus

2.2. OPTICAL SENSORS

GÜNTER GAUGLITZ 2.2.1. INTRODUCTION

Electromagnetic radiation supplies a powerful tool for the characterisation of effects occurring in matter and at its interfaces. In recent years such optical transduction has found enlarged interest in biochemical sensing. Accordingly a large number of different principles has been published. For this reason beginning with the optical principles most frequently used, different approaches to transfer them into successful optical transduction principles are summarised and some perspectives are outlined. Next some of the optical transducers proposed most are classified and reviewed. Following the intentions of the book applications to monitor affinity reactions are especially considered. As shown in Figure 2.13, electromagnetic radiation consists of an electric field and a magnetic one. This electromagnetic radiation is characterised by its amplitude, its frequency, its state of polarisation (i.e. the orientation of the vectors of the electric and the magnetic field, respectively), and the phase of the propagating radiation. In vacuum both electric and magnetic field vectors (see Figure 2.13a) are in phase ( ), perpendicular to each other, and perpendicular to the direction of propagation.

Figure 2.13. Electromagnetic radiation, characterised by propagation of the electric and the magnetic alternating fields and its amplitudes, (a) In vacuum both fields are in phase ( ). (b) In matter the two fields propagate with a phase shift. Interaction with matter can have the following effects, which are schematically graphed in Figure 2.14: • The alternating electrical field E induces in matter a dielectric displacement D which acts as a dielectric dipole, being the origin of secondary radiation (Hertz dipole). • In consequence the phase between the two field vectors varies ( accordingly both the wavelength λ of the propagating

, see Figure 2.13b), and

Figure 2.14. Propagation of electromagnetic radiation (λ0, I0) influenced by matter: attenuation ( ), Rayleigh scattering ( ), and change in wavelength by inelastic scattering ( ) or for the emitted radiation ( ).radiation and the velocity of propagation within matter (v) change (the frequency remains constant). Matter is characterised by a refractive index taking c as the velocity of propagation in vacuum. Having passed matter λ reassumes its original value and v becomes c again. Interaction depends on wavelength (dispersion). • The phase shift between the electric and magnet field is extreme in wavelength regions of absorption by matter (anomalous dispersion). In case of absorption the amplitude of propagating radiation (intensity) is reduced ( in Figure 2.14). • The molecular Hertz dipole is the origin of scattering. In dependence on size of the molecules scattering becomes observable (Rayleigh: molecular diameter ). Elastic scattering (Rayleigh) has the same wavelength ( ) as incident radiation and is sent out in a plane perpendicular to the direction of the induced dipoles in the molecule, forming a distribution depending on isotropy or anisotropy of matter. Inelastic scattering (Raman) is accompanied by changes in the wavelength ( ), see Figure 2.14, since part of the “exciting” radiation is transformed to vibrational and/or rotational states. • Furthermore, shifts in the absorption spectrum of matter by any effect cause a change in the amplitude of radiation for a given wavelength or can be spectrally recorded using a white light source. • Absorbing molecules can emit absorbed radiation in the form of fluorescence or phosphorescence, with the intensity of the radiation depending on the concentration of the excited molecules. The intensity of emitted radiation is lower than the absorbed. A wavelength “red” shift is common .

Details are given in physical chemistry or optics textbooks (e.g. Hecht, Zajac, 1974; Born, Wolf, 1989). All these effects can be used in optical transduction. Since the quality of the sensor also depends on the effects monitored either in the sample, at interface, or indirectly, the different possibilities to cause effects by affinity reactions are summarised first. 2.2.2. CLASSIFICATION OF OPTICAL AND TRANSDUCTION PRINCIPLES 2.2.2.1. Classification of effects

Taking the effect of absorption, scattering, reflection, and luminescence (fluorescence, phosphorescence) in the case of sensors applied to affinity reactions, the largest number of applications is related to reflectance as well as fluorescence measurements. This classifies the approaches to either direct optical detection of the immuno reaction, or to the necessity to use labelled components. In principle, the detected effects can be classified according to three approaches: 1. Detection of effects in the analyte: as changes in the refractive index, of the absorption coefficient, of intrinsic fluorescence, or of scattering. 2. Effects detected by observing changes in the matrix: as changes in absorption, colour changes caused by an indicator dye, observation of the affinity reaction between matrix and analyte. Table 2.5. Summary of the effects monitored during sensing via affinity reactions. In the analyte

by a marker

refractive index

in the matrix enrichment or swelling

absorption coefficient

enzyme-labelled systems

intrinsic fluorescence

fluorescence label: intensity, polarisation, colour change of an indicator dye energy transfer

scatter

changes in absorption

affinity reaction between matrix and analyte

3. Effects caused by a marker: as using fluorophore labels and monitoring the intensity, the state of polarisation, or an energy transfer. In the case of direct optical detection of affinity reactions optical transducers respond either to the refractive index change associated with the binding of organic matter to the transducer surface or to changes in a layer formed at the transducer surface. The advantages of direct monitoring of affinity reactions are: (a) less expenditure to develop test schemes and (b) less danger to reduce biological activity of the receptor molecules used.

On the other hand labelled components enhance the sensitivity drastically, thus improving the limits of detection by some orders of magnitude. The different effects are summarised in Table 2.5. According to this classification either effects in the matrix are detected or markers are used in the case of immuno sensing. 2.2.2.2. Optical principles

Besides the classical effects of attenuation and fluorescence modern transducers take advantage of different effects of reflection—especially caused by reflection of radiation at the interfaces of layers. The theory is based on Fresnel’s formula (Hecht, Zajac, 1974) and is well established. As is shown in Figure 2.15, radiation, incident on an interface separating two media of differing refractive indices, either can penetrate or can be reflected at the interface. Passing the interface from a lower to a higher refractive index radiation will be partially reflected (few percent). The rest will be refracted in direction to the optical axis, at an angle depending on the ratio of the refractive indices. Radiation passing the interface in opposite direction will be refracted off the optical axis, thus being totally reflected at an angle of incidence higher than the critical angle (see broken curve in Figure 2.15). Using a layer rather than a single interface, by this total internal reflection, radiation will be guided over considerable distances in this layer, which can be a fibre or a waveguide (see Figure 2.16). It is essential, that even under the condition of total internal reflection the electric field is not zero outside the guiding medium. A socalled evanescent field couples to the electric field guided within the medium, and

Figure 2.15. Reflection at interfaces; (—) reflected and refracted radiation, (······) critical angle for radiation going from higher to lower refractive index, (----) totally reflected radiation. decays exponentially from the interface into the lower refractive index medium. The penetration depth of the evanescent field is in the order of magnitude of the wavelength (see Figure 2.16). This means, part of the radiation field is propagating outside the waveguide in the sample medium. Due to this, the propagation of light guided internally will be affected by the optical

characteristics of the environment of the waveguide. The result is a so-called “effective refractive index” for the guided radiation. Furthermore, the orientation of linearly polarised radiation with respect to the plane of incidence of the waveguide defines the mode of this radiation inside the waveguide. An orientation of the electric field vector perpendicular to the plane of incidence is called a TE-mode (transversal electric, with the magnetic field vector perpendicular to it). The TM-mode (transversal magnetic) is given by an orientation

Figure 2.16. Guided radiation in a waveguide and the decaying evanescent field; (a) attenuated total reflectance, (b) total internal reflection fluorescence (TIRF), c) surface plasmon resonance.

Figure 2.17. Orientation of the electric (E) and magnetic (B) field for the TE-mode in a film waveguide. of the electric field vector parallel to the plane of incidence. The TE- and TM-modes are differently affected propagating in an non-symmetric waveguide. This non-symmetry is caused by the waveguide geometry and by being in contact with analyte on one side and substrate on the other and by the medium close to its interface (different effective refractive indices for the two modes). Thus, both modes show different velocities of propagation. In dependence on changes in the environment of the waveguide they exhibit in addition an increasing phase difference with length of interaction area to the medium next to the waveguide. Figure 2.17 gives the orientation of the field vectors in the TE-mode. Molecules, absorbing at the wavelength of the radiation guided within the waveguide and being immobilised or very close to the interface, attenuate that evanescent field, and by these means radiation guided in the waveguide. This is called “attenuated total reflectance” (ATR) (see Figure 2.16a).

If fluorescent molecules are immobilised at the interface of the waveguide, guided radiation can excite them and fluorescent light is emitted. This fluorescence can be either externally observed or can couple back into the waveguide. It is guided in the waveguide to its end and can be measured there. This “total internal reflection fluorescence” (TIRF) is demonstrated in Figure 2.16b. Even, if molecules immobilised to the interface of the waveguide neither absorb nor fluoresce, changes in the environment of the waveguide can be monitored. E.g. affinity reactions cause changes in the refractive index within this layer close to the waveguide. Thus, the intention of many transduction principles is to read out of the waveguide these effects on the evanescent field at the interface and thus on the propagating radiation. A typical possibility is to coat a metal film on the interface of the waveguide as shown in Figure 2.16c which allows the excitation of socalled surface plasmon waves (Kretschmann, 1971). 2.2.2.3. Transduction principles

At the moment many optical transducers are based on optodes (also called optrodes) using the measurement of either the absorbance (most in a reflective path way) or the fluorescence. The simplest approach is given in Figure 2.18. in which the interaction with the analyte changes the properties of molecules immobilised inside a membrane. This approach is not suitable for monitoring affinity reactions in absorption, since its changes by the reaction will be too small, in general.

Figure 2.18. Optode based on the measurement of absorption in reflection modus. 2.2.2.3.1. Detection of Labelled Components In contrast the use of labelled compounds allows the use of various modifications of optodes as demonstrated schematically in Figure 2.19. This approach is very useful in affinity reactions. Taking labelled molecules, out of various possibilities two specific applications are demonstrated. Binding of an immobilised antibody and of a labelled molecule (e.g. antibody) via an antigen forming a sandwich assay allows increasing fluorescence to be detected (see Figure 2.19a). Another possibility is that the interaction between the labelled molecule and analyte may cause quenching effects (see Figure 2.19b), reducing the fluorescence intensity. Quenching effects not only affect fluorescence intensity but fluorescence life time also. Therefore in the latter case fluorescence life time is influenced by the interaction between the molecules taking place during the affinity reaction.

The most simple approach is to measure the intensity of the fluorescence. However, this causes problems, as many other effects might influence this intensity

Figure 2.19. Optode based on the detection of fluorescence; (a) increase in fluorescence by forming a sandwich assay with marked antibodies and antigens or (b) quenching fluorescence by interaction with antigen; ( ) fluorescent and ( ) non-fluorescent molecules. (Wolfbeis, Boisde, 1992). For this reason the decay times of the fluorescence are preferably measured. Two approaches are common: either the direct measuring of decay times via single photon counting (O’Connor, Phillips, 1984), or the use of phase fluorimetry which is preferable taking into account new developments in electronics (Draxler, Lippitsch, 1996; Szmacinsky, Lakowicz, 1995). In addition, using linearly polarised light to excite fluorophores attached to low molecular weight ligands allows the detection of fluorescence anisotropy. Only fluorophores at an orientation appropriate to the plane of polarisation of the exciting radiation are excited. These labelled molecules will rotate loosing their original orientation (rotational relaxation) with time in dependence on the size of the labelled molecule. The anisotropy of the fluorescence is measured. If fluorescence lifetime and rotational relaxation time are of the same order, depolarisation effects can be measured. This effect is used in the so-called fluorescence polarisation immunoassay (FPIA). Fluorescence anisotropy will increase with binding of the labelled ligand to a receptor (reduction of relaxation rate) (Dandliker, de Saussure, 1970; Jolley, 1996). Whereas this method has found applications in the field of diagnostics and environmental analysis (commercial assays and equipment being available) another method to determine translatorial diffusion coefficients via the fluorescence of labelled molecules is only applied to affinity reactions in research. This is the fluorescence correlation spectroscopy (Eigen, Riegler, 1994). A further approach is the use of the effect of Resonance Energy Transfer (RET) (Wieb van der Meer et al., 1994). Two fluorophores are used as the long-wavelength absorbing dyes Cy5 and Cy5.5 (Amersham Life Science). The fluorescence spectrum of the dye absorbing at the shorter wavelength overlaps with the absorption band of the other dye. The spectra of these two dyes are given in Figure 2.20.

Figure 2.20. Long-wavelength dyes used for energy transfer: (---) absorption of Cy5, (· · · ·) fluorescence of Cy5, (—) absorption of Cy5.5, (– ·· – ·· –) fluorescence of Cy5.5.

Figure 2.21. Close interaction of two suitable fluorophores supplies resonance energy transfer in case of an affinity reaction. Both fluorophores being as close as the Förster distance allow resonance energy transfer (Förster, 1951). This method combines selectivity and sensitivity. It can be also used in homogeneous phase without immobilisation at the solid phase of a transducer. Both the labelled donor antibody and the labelled acceptor-protein (with immobilised analyte conjugate) are added to the analyte solution. The more analyte is present the more the energy transfer between donor and acceptor according to Figure 2.21 is reduced. The analyte blocks the donor antibody, which cannot react with the conjugate any more, and sensitised fluorescence does not happen. RET-based immunoassays have been known for a long time (Ullman et al., 1976). Modern transducers, however, open new fields of application (Brecht et al., 1997).

2.2.2.3.2. Direct optical detection via micro refractometry Two general approaches to apply reflectometric principles to affinity-based sensors using direct optical detection are known. Of these one responds to the refractive index changes associated with the binding of organic matter to the transducer surface. The second refers to optical characteristics changed by the layer formed during binding at the transducer surface. The former approach is considered to be a micro-refractometric effect, the latter approach a reflectrometric effect. The interaction of the guided radiation with its environment is best, if a significant part of the radiation is transported outside the waveguide in the evanescent field. This can be achieved by using small waveguide structures which support only a single mode of propagation. An increase in the refractive index in the environment of the waveguide will reduce the velocity of propagation of the guided wave and as a result reduce its actual wavelength. The term “effective refractive index” had been mentioned referring to this effect. Binding of organic material to the surface of the waveguide device will therefore reduce the velocity of propagation of radiation within the waveguide. To probe this change in propagation velocity a variety of transduction principles have been developed, all of them allowing surface bound affinity interactions to be probed. They can be classified as follows: • grating couplers; • mode couplers; • surface plasmon resonance, and • devices measuring interference or phase differences between the TM- and TE-modes. Grating coupler As demonstrated in Figure 2.22a gratings engraved into the surface of the waveguide can be used to couple radiation in and out of the waveguide. This effect depends on the period of the grating g, the wavelength of the radiation, the angle relative to the plane of the waveguide, and the refractive index of the sample medium close to the grating. Thus, either radiation incident at a certain angle into the waveguide can fulfil the coupling condition or a guided radiation will couple out at the appropriate angle. By these means the propagating wave (dependent on the grating condition affected by the refractive index of the sample medium) within the waveguide is interrogated and indirectly characterises the refractive index of the sample medium. If an affinity reaction takes place right on the grating, the local refractive index will

Figure 2.22. Principles of grating couplers; (a) Input and output coupler according to Lukosz, 1995 (g: grating constant), (b) according to Brandenburg and Gombert, 1993, (c) using a bidiffractive grating (Fattinger et al., 1995), (d) dual chirped gratings according to Kunz, 1993. increase in comparison to water, whereas the wavelength of the radiation as well as its velocity in the waveguide will decrease. As a result the angle of diffraction will be reduced. A schematic set-up is shown in Figure 2.22a. The angle of incidence for optical in-coupling can be changed as well and a combination of input- and output-coupling can be used also (Lukosz, 1995). The set-up has been realised commercially (Artificial Sensing Instruments, Zurich, CH). Varying the angle of incidence both the TE- and TM-mode can be read out, the device being more sensitive. The first arrangement has been modified in various forms. Instead of this mechanical movement between two positions for optimal incidence and outcoupling angles, read out can be done by a linear diode array (Brandenburg, Gombert, 1993), avoiding mechanically moved parts as demonstrated in Figure 2.22b. The possible direct reflection is superimposed by the interesting out-coupling radiation. This will reduce the signal-to-noise ratio. For this reason an interesting approach has been developed, forming a bi-diffractive grating device. A second grating with a different grating constant is engraved on top of the first one and the radiative power is out-coupled at a different direction than the specular reflectance (see Figure 2.22c). The intensity of reflected radiation becomes negligible and the signal-to-noise ratio is increased (Fattinger et al., 1995). A problem of any thin film device is the difficulty to in-couple interrogative radiation. A successful approach is the use of input gratings as well as output gratings. This is demonstrated

in Figure 2.22d. This even allows production techniques leading to very cheap devices (Kunz, 1993). Surface plasmon resonance Usually a Kretschmann-type set-up (Kretschmann, 1971) with a prism is used. A wedge of monochromatic radiation (laser) is incident at the base of the prism coated with a metal film (thickness: 50–100 nm) (Raether, 1977; Liedberg et al, 1983). Instead of monochromatic radiation a collimated beam of polychromatic radiation can be used (Striebel et al., 1994). The impact of the incident radiation excites at a certain angle or wavelength of incidence collective oscillations of the electronic gas at the opposite surface of a metal film, called surface plasmon waves (see Figure 2.23a). These longitudinal electronic density fluctuations are highly attenuated and have a lateral decay length of a few microns in the case of gold. Coupled to them an evanescent field decays into the adjacent sample medium. The resonance angle or wavelength of the incident radiation depends on the optical properties of the prism, the metal film, and especially on the refractive index of the sample medium. At resonance the reflectance is reduced (see Figure 2.23b). The device using monochromatic excitation has been commercialised quite successfully (BiaCore AB, Sweden). Furthermore, light propagating in a waveguide can also excite surface plasmons in a metal film coated on top of the waveguide (see Figure 2.24). However, in this case a low refractive index buffer layer may be required between the metal film and the waveguide in order to meet the coupling conditions (Harris, Wilkinson, 1995). Recently a fully integrated SPR device has been published based on the encapsulation of the required electro-optical components within the optical material through a molding process. This miniature manufacturable transducer was especially developed for low cost biosensor applications in field use (Melendez et al., 1996).

Figure 2.23. Surface plasmon resonance; (a) schematic optical arrangement, (b) reduced reflection at resonance wavelength/angle, (—) and (---) for different refractive indices of sample medium.

Figure 2.24. Surface plasmon resonance based on a waveguide device. Mode coupling Another approach to interrogate the guided radiation is to monitor the phase relation of different modes. This can be achieved taking a set-up called resonant mirror (Cush et al., 1993). Radiation incident at one side of a prism is reflected at the basis. Using 45° polarisation a defined phase between the TM- and TE-modes exists. They couple to the resonant layer causing propagating modes within it (see Figure 2.25). Since both the modes are differently influenced by the effective refractive index according to the evanescent field decaying into the sample, the phase shift between the reflected TM- and TE-modes will vary. The effect is a rotation of the plane of polarisation of the reflected beam with respect to that of the incident one and the interaction length. Mode coupling can also take place between two adjacent waveguides, separated only by low refractive material, via the evanescent fields. This approach is used e.g. in so-called 3×3 couplers which provide in their 3 arms embedded in integrated optical substrate the chance to detect output signals sensitive to phase as given in Figure 2.26.

Figure 2.25. Mode coupling realised in a resonant mirror system.

Figure 2.26. 3×3 coupler to determine the direction of this phase shift between sample and reference arm. The three intensities measured are signals at 120° phase difference. Besides this “passive” phase demodulation an active one is possible. Bringing a modulation device to the output arm and applying a high frequency signal, the overall signal includes the information about the phase shift (Karthe, Müller, 1991). It had been mentioned that within a waveguide TM- and TE-modes propagate at different velocities for a certain refractive index in a medium proximate to the waveguide. Both the modes are coherently excited within a planar waveguide according to Figure 2.27 (Lukosz, Stamm, 1991). Their interaction with the sample depends on the state of polarisation and induces a phase shift in dependence on both the effective refractive indices and on propagation distance. Two principles are used to detect this phase difference (Lukosz et al., 1997; Stamm, Lukosz, 1997): (a) By a polarimetric set-up which measures the state of polarisation of the out-coupled radiation and the amount of orthogonally polarised TM- and TE-modes by application of a beam splitter and two Wollastone-prisms. (b) By lateral fringe shifts calculated from the measured intensity distribution of the interference pattern. This latter method can be extended to a dual-wavelength

Figure 2.27. Integrated optical difference interferometer. operation in which the two modes are excited by two laser lines. Their interference patterns superimpose. By use of a CCD array and Fourier transform analysis their lateral shifts and the corresponding phase shifts can be determined.

Interferometry using integrated optics Mach-Zehnder devices take advantage of interferometry, also (see Figure 2.28a). As shown in the Figure, the most simple case is splitting the input-arm into two symmetric arms, leaving one arm exposed to the analyte, with the other arm serving as reference. The propagation in the sample arm is influenced (Ingenhoff et al., 1993). An interferometric pattern is obtained (as demonstrated in Figure 2.28b) as a superposition of the partial rays after reunification of the two arms. Its signal depends on the change in the refractive index in the sample environment. As mentioned above

Figure 2.28. Interferometric Mach-Zehnder Device (a) with out-coming intensity (b) ( according to the phase shift and the interaction length L. Page 42

)

the change in the signal does not allow the absolute change in refractive index to be determined (increase or decrease of analyte concentration). Therefore these devices can be used in combination with 3×3 couplers to determine the direction of the phase shift (see Figure 2.26). 2.2.2.3.3. Direct optical detection via micro reflectometry The reflectance of radiation at an interface between e.g. air and glass amounts to approximately 4% at perpendicular incidence. This value changes with angle of incidence, wavelength, and ratio of refractive indices of the two media as can be seen in Figure 2.29. This reflectance gives rise to some methods which characterise interfaces and thin layers.

Figure 2.29. Reflectivity of incident radiation to an interface between media of different refractive index in dependence on angle of incidence and state of polarisation. Using polarised light incident to interfaces and layers the amount of information increases, since the reflectivity differs for the two states of polarisation (perpendicular and parallel) with respect to the plane of incidence. Whereas radiation polarised perpendicularly to the plane of incidence demonstrates a continuous increase in reflectance with increasing angle of incidence, the other state of polarisation passes a minimum. This specific angle of polarisation is called Brewster’s angle, also. At this angle only radiation polarised perpendicularly to the optical plane is reflected. Brewster angle reflectometry The characteristics of reflected radiation mentioned above are used in Brewster angle reflectometry and microscopy. Irradiating at angles of incidence close to Brewster’s angle the signal of the reflected radiation will sensitively react to small structural changes at the interface caused by affinity interaction disturbing orientation (Overbeck et al., 1995). Ellipsometry An even more sophisticated method is ellipsometry (Azzam, Bashara, 1988). Polarised radiation is monitored in its interaction with interfaces or layers. By interaction the phase between the two states of polarisation changes as well as the relative amplitudes of the field vectors as symbolised in Figure 2.30. The method allows the separation of the optical constants refractive index n and physical thickness of a layer d using polychromatic radiation. Ellipsometry is an excellent tool for the examination of biomolecular multi-layer systems. Therefore it is especially suitable for the monitoring of affinity reactions as used in biosensors.

Figure 2.30. Schematic representation of the amplitudes and phase of two linearly polarised beams reflected at thin layer. The spectral approach is rather time consuming. Therefore different modifications have been developed using either a CCD camera (Jin et al., 1995) or a miniaturised device based on monolithic technology (Stenkamp et al., 1995). Both approaches simplify the set-up, increase the rate of data acquisition, and extend the capabilities. Reflectometric interference spectroscopy (RIfS) In biomolecular interaction analysis a Fabry-Perot-type interferometer (Hecht, Zajac, 1974) is successfully used (see Figure 2.31). White light is guided by a bifurcated fibre to the biomolecular interaction layer at which affinity reaction takes place. As demonstrated in Figure 2.31b part of it is reflected at the interfaces of this layer. In case the physical thickness of this layer varies by mass uptake, the phase of the superimposed partial beams changes. For just one wavelength the resulting intensity reflected back into the fibre optic varies in dependence on the product refractive index times physical thickness of layer. Considering the spectral superposition a shift of the interference pattern is observed (see Figure 2.31d). This shift is proportional to the change in optical thickness (n·d) and to the bound concentration of ligand to the immobilised receptor in case of affinity reactions (Brecht et al., 1992; Brecht, Gauglitz, 1994).

Figure 2.31. Reflectometric Interference Spectroscopy (RIfS): (a) bifurcated fibre for irradiation of the biomolecular receptor layer, (b) schematic change in thickness of layer by affinity reaction, (c) the deviated superimposed partial beams reflected at the interfaces, and (d) the case of white light interferometry with shifted interference patterns by change in thickness of the layer.

Since interference will result only measurable shifts for optical thickness around 500 nm to a few µm and the biomolecular interaction layers are in the range of a few nm (antibody diameter) an additional layer has to be added which amounts to approximately 500 nm. Its optical properties are chosen such that its refractive index matches that of the biomolecular layer. This principle supplies a rather simple and robust method monitoring environmental analytes (Mouvet et al., 1996; Brecht, Gauglitz, 1997). Optimisation of the receptor layer even allows low molecular weight ligands to be monitored directly (Piehler et al., 1996) as in the case of surface plasmon resonance (Karlsson, Stahlberg, 1995). 2.2.3. TRENDS

Scanning recent literature with respect to optical biosensors, publications are rather dedicated to advanced applications than to new developments of transduction principles. Available methods are optimised, sensitivity is increased, the limit of detection for labelled assays is reduced and the direct optical detection of low molecular weight analytes is approached. Furthermore portables are developed to allow on site control (Golden, 1997). 2.2.3.1. Analytes

Within the last years in environmental analysis new fields of application have been opened to optical biosensors using various types of test formats. Besides the typical water pollutants (Osbild et al., 1995; Rogers, Poziomek, 1996; Marco, Barceló, 1996) new analytes are due to be detected applying optical transduction principles. In recent years interest has concentrated on drugs and explosives (Shriverlake et al., 1997). Both have to be controlled on-line at airports and the later in former military areas. The problem in the case of drugs relates to the low concentrations, therefore requiring time consuming enrichment procedures at the moment. In the field of biochemical pollutants in recent years the detection of microbial contamination of food, industrial waste water and clinical water gains increasing interest (Hobson et al., 1996). Similar potential dangers are realised for endocrine disruptors and estrogenic contaminants (Kavloc et al., 1996; Hock, Seifert, 1997). These compounds are either detected directly by use of antibodies in various types of assays (Hock, Seifert, 1997) or via a biomarker like vitellogenin which proves to be an appropriate tool to determine endocrine effects (Hansen et al., 1997). 2.2.3.2. Miniaturisation

Another trend is the miniaturisation which started with low sized optodes and in the field of integrated optics (Ingenhoff et al., 1993). Developments in telecommunications and semiconductor technology caused lower prices and higher sophisticated equipment. Availability of various processes for micro-structuring low cost electronic components supplies a number of masks useful for the production of integrated optical components. A rather cheap approach are the dual chirped grating devices (Kunz, 1993). More expensive are integrated optical bidirectional couplers (Luff et al., 1996) and Mach-Zehnder devices (Morey, 1997). However, all these developments have large potential in reducing costs by mass production and increasing sensitivity.

Recently ink-jet techniques are discussed as contactless techniques to dispose small sample volumes at closely laterally resolved areas (Blanchard et al., 1996). Droplets are generated by a piezo system pulsed at a voltage of 50–100 V with some kHz repetition rates. The droplet volumes amount to 15–500 pl with 1–2% reproducibility. The piezo accelerates the droplets up to 2 m/s forming areas of 10–100 µm at the receptor surface as demonstrated in Figure 2.32. Such devices are very suitable in nanotiter plate technology (Brecht et al., 1997) in combination with various optical transducers.

Figure 2.32. Microdrop system. At present the fluidic system causes many problems with respect to biomolecular interaction analysis in affinity reactions as used in environmental control. As sample volumes are reduced continuously the volume of the flow cells and of the total fluidic system has to be adapted. For years, micro fluidics, micro pumps, and micro cells have been intended to be used in environmental analysis. However, the systems on the market are rather sensitive to particles in waste water and the micro pumps show some problems in every day work. For this reason hybrid systems avoiding too small flow diameters and sensible micro pumps are considered at the moment (Van den Berg, Bergfeld, 1996) as one of the solutions of the problems. Printed circuit board (PCB) technology allows the concept of very cost effective and simple devices such as that illustrated in Figure 2.33. By computer aided design (CAD) a simple layout

as for circuit boards is designed. Cheap printed-board technology allows cost effective redesign (Schmitt et al., 1996) of the flow cells at small expenditure according to the experience gained during measurements. Changes in geometry, size, and arrangement of the flow channels are easily achieved at low costs.

Figure 2.33. Micro-FIA based on PCB technology, the micro flow cell can be combined with conventional peristaltic pumps or later with micro pumps: (a) schematics and (b) the realisation. 2.2.3.3. Parallelisation

The increasing number of samples in environmental analysis and the requirement of reduced costs per sample and analyte forces developments in the direction of immunoassays with cheap technology for medium to high sample throughput. Labelled systems as mentioned in Section 2.2.2.3.1. provide rather cheap and sensitive approaches. The intention is to measure either a multi-analyte system or many samples (containing just one analyte) at a time. High throughput screening is a matter of choice to analyse many samples at a time. The less the sample and analyte volume and the less preparation and washing steps are necessary the lower the costs are. Therefore homogeneous assays with markers and energy transfer are considered to be preferable (Brecht et al., 1997)—especially in environmental analysis. Modern drug screening requires high throughput devices, also. However, in looking for new lead structures, direct monitoring of the affinity reaction is prefered to avoid long times to optimise assays. Direct optical monitoring allows a high degree of parallelism, since optics allow simple imaging. Any planar transducer could be used in principle monitoring many sites of affinity reaction at the same time. However, methods based on evanescent wave technology lack stability because of the temperature dependence of the refractive index. Reflectometric methods exhibit some advantages in practise. Thus a prototype of parallel optical detection of affinity reactions using reflectometric interference spectroscopy has been developed (Brecht et al., 1996). A microtiter plate is illuminated by a parallel bundle of radiation at one wavelength. According to Section 2.2.2.3.3 the superimposed partially reflected beams result an intensity pattern of e.g. a microtiter plate as given in Figure 2.34.

The necessary apparatus is demonstrated in Figure 2.35. The intensity pattern is stored for one wavelength. After changing the wavelength another pattern is recorded for all the wells in parallel. This approach allows the parallel monitoring of 96 and

Figure 2.34. Intensity image of a the wells of a microtiter plate.

Figure 2.35. High Throughput Screening device for optical imaging of affinity reaction for more than 96 wells in parallel. more wells (up to 1536) at some wavelengths supplying data for interferometric analysis of the binding process. The limit is rather the liquid handling system than the optics. Using sophisticated surface chemistry and regeneration techniques every 15 minutes a new set of samples can be screened. Thus sample numbers of at least a few thousands a day can be examined. These parallelisation techniques are rather limited by the sample volume than the optics. Too small wells do not allow the use of heterogeneous test formats and cause difficulties in pipetting. In the moment picoliter wells are fabricated taking advantage of micro-technology supplying socalled “nano-titer-plates”. Their use in combination with normal fluid handling systems turns out to invoke a large number of problems. Therefore homogeneous phase assays as mentioned in Section 2.2.2.3.1. turn out to be advantageous. Combination of microdrop technology and micro struc-turing with resonance Energy Transfer methods are considered to be useful in high through-put screening approaches in environmental analytics (Brecht et al., 1997).

Commercialisation of some of the optical biosensor principles makes sure that their applications in the field of bioanalytics and environmental analytics will increase. In dependence on the requirements of the applications direct optical detection principles as well as the use of labelled systems and different approaches of fluorescence detection will gain interest. This variety of methods is an advantage environmental analytics certainly will use in the future. REFERENCES

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2.3. FLOW INJECTION ANALYSIS

URSULA BILITEWSKI 2.3.1. INTRODUCTION

Flow Injection Analysis (FIA) was introduced in 1975 by Ruzicka and Hansen as a method of automated liquid handling in chemical analysis. A defined amount of sample is injected in a continuous, non-segmented carrier stream. When the sample zone moves through the tubes of the system in a laminar flow fashion, the original square-wave concentration profile disperses through complex diffusion and convection processes, mixing the sample with the carrier stream (Ruzicka, Hansen, 1988; Valcarcel, Luque de Castro, 1987). This allows chemical reactions to be performed with the sample, as the carrier may contain corresponding reagents. Moreover, any kind of detector equipped with a suitable flow-through cell can be integrated in FIA-systems, e.g. photometers, fluorimeters, pH- or other ion-selective electrodes and amperometric detectors. Thus a variety of investigations can be performed within a FIA-system, ranging from physical characterisation (conductivity, colour), the determination of simple chemical compounds (ions, oxygen) to the determination of analytes via more complex chemical reactions. Basic elements of a FIA-system are a pump, usually a peristaltic pump, for the transportation of the carrier, a detector, and the injector for the sample. However, it was shown that additional elements can be integrated in the basic FIA-set-up, e.g. mixing chambers, catalytic or affinity columns, gas diffusion or dialysis chambers, widening the range of procedures which were automated via FIA to sample pretreatment procedures such as pH-adjustment, dilution or separation from the sample matrix. Due to a constant pumping rate and defined lengths and diameters of tubings there is an exact timing of all processes in the system, allowing even chemical reactions to be run under kinetic conditions without the necessity to wait for equilibrium. Thus, compared to conventional chemical analysis the sampling rate is much faster. The typical shape of a signal obtained from a FIA-instrument is a peak, with the peak height and peak width being influenced by the injected sample volume, the dispersion within the FIAsystem and the turnover of the chemical reaction involved. If all conditions are maintained constant, the peak form usually does not change and the peak height can be taken for signal evaluation. However alternatively, the peak width or peak area can be used. 2.3.2. SELECTED COMPONENTS OF FIA-MANIFOLDS 2.3.2.1. Injectors

Usually a defined volume of the sample is injected in the carrier stream. This was originally achieved by a syringe, and later by injection valves, in which a sample loop of given volume was filled with the sample by a sample pump. Typical injection volumes range from 15 µl to 300 µl, the lower limit given by achievable minimal distances between connectors and the upper limit given by more practical reasons of length of tubing. Injection occurs by turning the sample loop into the flowing line of the carrier, which flushes the loop and as a consequence transports the

sample through the system. These valves are commercially available from several companies, comprising either a single sample loop or two sample loops allowing simultaneous injection of two solutions (e.g. sample+reagent) in two carrier streams which are mixed downstream. This latter approach reduces the required amount of reagent, compared to a system with continuous supply of reagent, or allows the separate storage of two reagents with a reduced stability when stored in a mixture. This is for example of importance, when the amount of active enzyme in the system is to be determined by the injection of enzyme substrates (see Chap. 4.1.2.). However, in some applications modifications of this type of injection are favoured. These are achieved by a replacement of the injection valve by a combination of 4 2/3-way-valves (Stiene, Bilitewski, 1997) (Figure 2.36). The 2 upper valves define a bypass for the carrier stream during the filling of the sample loop, thus allowing con- tinuous washing of the detector cell. The 2 lower valves limit the sample

loop, thus the sample volume is given by the volume of the tubing between these two valves.

Figure 2.36. (a) Filling of the sample loop (b) Injection of the sample.

tinuous washing of the detector cell. The 2 lower valves limit the sample loop, thus the sample volume is given by the volume of the tubing between these two valves. Reaction columns (Chap. 2.3.2.3.) can easily be integrated in the injection valve (Figure 2.36), which simplifies the prolongation of reaction times by a prolongation of the time interval between filling of the sample loop and flushing the content of the sample loop with the carrier. If an affinity column (Chap. 4.1.2.) is integrated into the system, an enrichment of the analyte can be achieved just by an extension of the pumping time of the sample pump, thus increasing the amount of sample pumped through the column. A prerequisite for reproducible results, however, is a reproducible and exact timing of the simultaneous switching of the two valve pairs. This is usually only achieved if the whole system is controlled by an automatic timer or by a computer. The increasing accessibility of computers with corresponding control software allowed the introduction of another injection principle, time-based sampling (Mohns, Künnecke, 1995). This is partly already described above, where the amount of sample used for the analysis is given by the pumping time of the sample through the sample loop with an integrated affinity column. But this principle was modified further, when membrane chambers (Chap. 2.3.2.2; Figure 2.37) were integrated in FIA-systems. The membranes usually separate a sample line from an acceptorcarrier line and diffusion of the analyte through the membrane takes place according to the concentration gradient. The acceptor-carrier line can now form the sample loop of Figure 1. The amount of analyte, which can diffuse from the sample into the acceptor, is given by the time, in which the carrier is pumped through the bypass (2 upper valves) and not through the sample loop (2 lower valves). Prolongation of this interval leeds to an enrichment of the analyte in the acceptor. This principle is mainly applicable if high-molecular weight compounds are to be separated from the sample (Mayer et al., 1996) or if the sample has to be diluted to a certain degree, as only a fraction of the amount of analyte present in the sample diffuses through the membrane.

Figure 2.37. Membrane chamber.

2.3.2.2. Separation of the analyte from a matrix

In classical analytical chemistry there is often a need to separate the analyte from the sample matrix due to the possibility of interference by sample constituents. Examples are turbid samples or coloured samples, both effects will interfere with photometric determinations of analytes. Another reason to require a separation process may be a need for enrichment of the analyte prior to its determination. Examples of suitable separation procedures are liquid/liquid extraction, solid-phase extraction or filtration which have to be performed manually before the sample can be analysed. However, if analysis is possible by automated devices, sample pretreatment becomes the step limiting the number of determinations which can be done in a given period of time. Thus, there is an interest in automation of these procedures and their integration in the whole analytical process. This is a prerequisite, if on-line monitoring of processes, reagent solutions, waterways or effluents is desired, as in these applications the samples are to be taken and analysed automatically without the need for any manual procedure. Therefore a variety of elements were developed allowing the integration of sample pretreatment procedures in FIAdevices (Fang, 1993). Liquid/liquid extraction is one of the classical separation procedures and therefore the first reports on its integration in FIA-devices originate as early as 1978. Usually an organic solvent is mixed with an aqueous phase for example by using a T-shaped mixing chamber, which leads to segments of organic solvent in an aqueous phase or vice versa depending on the ratios of liquids. Extraction takes places through the phase boundaries between the two phases. Its efficiency is improved by using helically coiled tubing as extraction coils, which are made either of hydrophobic materials, such as PTFE, if the analyte is to be transferred from an aqueous solution to an organic solvent, or of hydrophilic materials, such as glass, for the transfer from an organic solution to an aqueous solvent. Efficiency can reach up to 99%. Separation of the two phases is achieved in so-called phase separators, which utilize mainly the differences in density of the two immiscible phases or in affinity and permeability through separation membranes. The first type of separator was a gravitational-phase separator and could be as simple as a T-shaped glass junction, where the mixture of the two phases enters through the horizontal arm, and the two separated phases leave through the two vertical arms in opposite directions. However, nowadays membrane phase separators are preferred, where the separation of the two phases is supported by additional separation membranes allowing the permeation of only one phase. To avoid the use of organic solvents in FIA-systems, which requires the use of special solventresistant materials for the fabrication of chambers, tubing and tube connectors, liquid/liquid extraction is often replaced by solid phase extraction. The classical batch procedure is again exactly transferred to FIA-systems, which means that a column packed with a suitable sorbent is integrated in the sample line followed by elution of the bound compounds. The column design strongly influences the performance of the system. Usually, columns are much smaller than in batch procedures with their volumes ranging from 15 µl to over 400 µl. Similar columns are used in FIA-systems also for catalytic purposes (Chap. 2.3.2.3.). The packing material has to fulfil some requirements besides its ability to bind the analyte:

• the extent of swelling and shrinking should be negligible when solvent conditions are changed; • the mechanical properties should be strong enough to withstand the rather high linear flow rates within a FIA-system; • the kinetic properties of binding and elution of the analyte should be compatible with FIAconditions and occur without damage or inactivation of the sorbent. Ion exchangers and materials, such as glass or polymeric beads, which were modified with suitable affinity reagents, were successfully used in FIA-systems. The first ones are, for example, used for preconcentration of metal ions from water prior to analysis by atomic absorption spectroscopy (AAS). The latter are of importance, for example, in immunoanalytical flow injection systems, where polymeric or glass beads were modified by covalently coupled antibodies which bind the analyte in a typical affinity reaction (Chap. 3.4, 4.1.2.) (Stöcklein et al., 1991). If the analyte differs from the interfering compounds in volatility or molecular weight, separation can be achieved by the integration of membrane chambers. These chambers usually consist of two parts, one being the donor part delivering the analyte, and the other being the acceptor part, both separated by a membrane. They can be constructed e.g. by insertion of a microdialysis fibre as acceptor in conventional tubing through which the original sample is delivered (Palmisano et al., 1996), or by two planar parts, each of which has an open flow channel (Figure 2.37) and openings for tube connectors. The two parts are combined in a sandwich format, i.e. they are separated by a membrane which is the interface between the two flow channels. Depending on the material of the membrane and the design of the chambers only volatile or low-molecular weight compounds can permeate the interface between the two flow channels. For example, if a dialysis membrane is used, high-molecular weight compounds remain in the donor stream whereas low molecular weight compounds can pass through the membrane and reach the acceptor stream (Palmisano et al., 1996; Fang, 1993). If a hydrophobic membrane is used, such as a polypropylene or a teflon membrane, only volatile compounds reach the acceptor stream (gas-diffusion) and all non-volatile compounds are separated (Künnecke, Schmid, 1990a, b; Fang, 1993). This effect is amplified if the chamber is designed such that the donor stream is not in direct contact with the membrane leaving space between the donor and the membrane, which can only be passed by volatile compounds (pervaporation) (Mattos, Luque de Castro, 1994). Applications of these principles are reported for food, environmental and bioprocess analysis (Künnecke, Schmid, 1990a, b; Fang, 1993; Mohns, Künnecke, 1995; Mayer et al., 1996; Papaefstathiou et al., 1997). Usually, the analyte is diluted by these procedures, as a quantitative transfer from the donor stream to the acceptor stream is not aimed at. However, the degree of dilution is dependent on the diffusion time, the length of the flow channels and the temperature and can therefore be adapted to practical requirements. Another element which has gained some attraction in FIA is the development of filtration modules, which are used for the separation of precipitates. The design and material of this component is critical for the performance of the whole device and various approaches are reported in the literature, which have found application not only in the separation of more or less

solid precipitates (Fang, 1993), but also in immunoanalytical systems in the separation of affinity complexes from unbound analyte and tracer (Fernandez-Romero, Luque de Castro). 2.3.2.3. Reaction chambers

The easiest way to perform chemical or biochemical reactions in FIA-systems is the supply of required reagents in a soluble form as additives to the carrier stream (e.g. Mayer et al., 1996) or injected via an injection loop (Kriz, Johansson, 1996). However, this leads to a significant consumption of reagents, which can be avoided, if reagents are entrapped in a reaction chamber. In biochemical analysis this achieved through the immobilization of the biochemical reagent, e.g. the enzyme, antibody or whole cell, on solid supports or behind membranes. Proteins can be immobilized utilizing their physical properties, such as size, charge, hydrophobic domains. Thus, they can be entrapped behind a membrane with small pore sizes so that the protein molecules cannot pass but the enzyme substrates can reach the enzyme. This method is usually applied in combination with electrodes onto which the enzyme is adsorbed (utilization of van der Waals forces and hydrophobic interactions), leading to thin enzyme layers, in which the enzymatic reaction takes place, localized directly on the detector, thus no further dispersion of the sample occurs. More robust enzyme electrodes are obtained, if the enzyme is entrapped in a polymer, which may be covered additionally with a protecting membrane. In these systems only a limited amount of enzyme can be used, as the volume of the enzyme membrane, which forms the volume of the reaction chamber, is limited to avoid increasing diffusion times (Chap. 3.1.). Therefore reaction chambers are designed, which are placed upstream of the detector. The enzymes are immobilized on particles, membranes or on the inner wall of the flow-through reaction channels, thus forming packed-bed reactors or being integrated in suitable chambers with the analyte being transported over the enzyme layer. The amount of enzyme can be varied by the size of the chosen reactor type. As the accessibility of the enzyme for the analyte is most efficient in the packed-bed reactors, these are the preferred design. The particles have to fulfil several requirements, some of which were already mentioned above: • they have to be able to bind the enzyme, which is possible either through ionic forces, if an ion exchanger is used, or through covalent binding, if materials with suitable functional groups are used. The immobilization must be sufficiently stable, even when the composition of the solution changes due to the presence of the sample; • they have to have suitable mechanical properties to be intergrated in a continuous flowing stream; • the analyte and the reaction products should not adsorb on the material. Usually small columns with a volume of some hundred µl are used, and for enzyme immobilization controlled pore glass (cpg), which is activated by silanization, or preactivated polymers (such as Eupergit) are the preferred support materials. Due to the presence of the particles in the column, the dispersion of the analyte in the carrier is increased leading to decreased peak heights and increased peak widths.

For reaction chambers containing not a catalytically active material, such as immobilized enzymes, but an affinity material, such as immobilized antibodies or ion exchangers, a comparable design is used (Chap. 2.3.3, 4.1.2.). Nowadays those reactors can be fabricated using microstructuring technologies (Laurell et al., 1995), with the enzyme (protein) being immobilized on the walls of channels etched in silicon wafers. This allows the fabrication of highly integrated flow-through systems. 2.3.3. DISPERSION

As mentioned already above, the sample is mixed with the carrier due to complex diffusion and convection processes (Valcarcel, Luque de Castro, 1987; Ruzicka, Hansen, 1988; Fang, 1993). These processes occur even when the sample zone moves through the system in a laminar flow, however they are modified when additional components are integrated in the flow-through line, such as T-shaped mixing chambers, membrane chambers or reaction columns. Moreover, diffusion is a time-dependent process, that means that an increase of the residence time of the sample in the FIA-system due to a low flow rate or long tubing leads to an increase of dispersion effects. On the other hand diffusion is also influenced by the concentration gradient between the sample and the carrier, and as a consequence these processes start at the boundaries between the sample plug and the carrier reaching with increasing time the centre of the sample plug. Thus, the efficiency is also dependent on the sample volume, with an increasing sample volume leading to a reduced mixing efficiency at the centre of the sample plug. The dispersion in the FIA-system is quantified via the dispersion coefficient D, which is defined as (2.3.1) with c0 being the original concentration of the analyte in the sample and cmax being the concentration reaching finally the detector. As usually the sample is diluted within the FIA. D can be device, cmax is smaller than c0, and D describes the dilution factor with determined by measuring the absorbance of a dissolved dye, resulting in a signal H0, and dividing H0 by the signal Hmax, which is obtained, when the same dye-solution is used as sample. As mentioned above, it can be modified by changing the sample volume, the flow rate, lengths of tubings and integration of additional components in the FIA-mainfold. Reproducible analytical data, however, are dependent on a constant dispersion of the system, i.e. flow rates, permeabilities through membranes, convection due to passage of packed-bed reactors etc. have to be kept constant in all experiments. 2.3.4. CONCLUSION—FOCUSSING ON BIOCHEMICAL APPLICATIONS

Flow injection analysis has proven to be a versatile tool for the automation of analytical procedures. This includes not only the automation of the analytical chemical reaction itself, e.g. addition of a reagent together with the analyte to result in a coloured product, but also the automation of sample pretreatment procedures. Therefore, FIA-systems are applied where online determination of analytes is required, allowing a much higher sampling frequency than achievable with manual sampling, sample preconditioning and analysis.

The accessibility of analytes by FIA-methods is significantly enhanced by the integration of biochemical reactions in FIA-systems. This is achieved by just adding the enzyme together with required reagents to the carrier stream into which the sample is injected. Due to the dispersion effects the analyte is mixed with the enzyme and the reagents, the enzymatic reaction can take place and resulting products are monitored. However, usually the enzymes are used in an immobilized form, and integrated in the FIA-system either as reactors placed upstream of the detector or as enzyme sensors, i.e. enzyme electrode or opt(r)ode, being the detector for the system. This allows the application of the enzyme for a number of samples, thus reducing the amount of consumed reagents. This approach is mainly applied to the determination of enzyme substrates, where the active site of the enzyme is regenerated automatically due to the low affinity of reaction products to the enzyme (Chap. 3.1.1.). However, mainly in environmental analysis, enzymes are also used for the determination of enzyme inhibitors, which cause a decrease of the enzyme activity (Chap. 3.1.2.). Binding of inhibitors to enzymes may cause an irreversible damage to the enzyme depending on the binding mechanism and the affinity between enzyme and inhibitor. This requires the development of new concepts for the automation of the corresponding assays, as the enzyme can be applied only to single positive samples, the enzyme either has to be regenerated, or has to be replaced automatically. To meet the latter requirement concepts for a reversible integration of enzymes were developed, ranging from reversible immobilization on ion exchangers, to the automated exchange of the whole support together with the enzyme, which is for example possible, when the enzyme is immobilized on magnetic particles which are kept in a reactor by an electromagnet (Günther, Bilitewski, 1995). Similar conditions as in enzyme inhibition assays are found, when immunoassays are to be automated. The binding of an antibody to its antigen usually is irreversible, which requires either continuous supply of antibodies, if they are bound reversibly to a solid support, or the application of additional regeneration reagents, usually buffers with low or high pH (Chap. 4.1.2.). In an alternative approach an affinity column is preloaded with a detectable compound, the replacement of which by the analyte is measured. This allows the application of an affinity column for a number of assays, as long as the column is not exhausted of the detectable compound. However, this format of immunoassays usually is less sensitive than conventional assay formats. In general, the application of FIA-systems is not limited to the examples mentioned above. More concepts for FIA-systems are described in literature, e.g. the application of other biochemical reactions (other binding proteins) or splitting and merging of flow lines to achieve parallel or serial determination of several analytes. However, to mention all the possibilities of FIA-systems is beyond the scope of this chapter, and the reader is referred to the numerous publications on FIA (Fang, 1993; Calatayud, 1996). REFERENCES

Calatayud, J.M. (1996) Flow Injection Analysis of Pharmaceuticals, automation in the laboratory. London, UK: Taylor and Francis, Ltd.

Fang, Z. (1993) Flow Injection Separation and Preconcentration. Weinheim: VCH, Germany. Fernandez-Romero, J.M. and Luque de Castro, M.D. (1996) A flow-injection continuous filtration approach for the automatic determination of monoclonal antibodies. Anal. Chim. Acta, 331, 245–251. Günther, A. and Bilitewski, U. (1995) Characterisation of inhibitors of acetylcholinesterase by an automated amperometric flow-injection system. Anal. Chim. Acta, 300, 117–125. Kriz, D. and Johansson, A. (1996) A preliminary study of a biosensor based on flow injection of the recognition element. Biosens, and Bioelectr., 11, 1259–1265. Künnecke, W. and Schmid, R.D. (1990a) Gas-diffusion dilution flow-injection method for the determination of ethanol in beverages without sample pretreatment. Anal. Chim. Acta, 234, 213– 220. Künnecke, W. and Schmid, R.D. (1990b) Development of a gas diffusion FIA system for on-line monitoring of ethanol. J. Biotechnol., 14, 127–140. Laurell, T., Drott, J. and Rosengren, L. (1995) Silicon wafer integrated enzyme reactors. Biosens, and Bioelectr., 10, 289–299. Mattos, I.L. and Luque de Castro (1994) Study of mass-transfer efficiency in pervaporation processes, Anal. Chim. Acta, 298, 159–165. Mayer, M., Genrich, M., Künnecke, W. and Bilitewski, U. (1996) Automated determination of lactulose in milk using an enzyme reactor and flow analysis with integrated dialysis. Anal. Chim. Acta, 324, 37–45. Mohns, J. and Künnecke, W. (1995) Flow analysis with membrane separation and time based sampling for ethanol determination in beer and wine. Anal. Chim. Acta, 305, 241–247. Papaefstathiou, I., Bilitewski, U. and Luque de Castro, M.D. (1997) Determination of acetaldehyde in liquid, solid and semi-solid food after pervaporation-derivatization, Fres. J. Anal. Chem., 357, 1168–1173. Palmisano, F., Centonze, D., Quinto, M. and Zambonin, P.G. (1996) A microdialysis fibre based sampler for flow injection analysis: determination of L-lactate in biofluids by an electrochemically synthesized bilayer membrane based biosensor. Biosens, and Bioelectr., 11, 419–425. Ruzicka, J. and Hansen, E.H. (1988) Flow Injection Analysis. 2nd edn., Chem. Analysis, 62, New York: John Wiley & Sons.

Stiene, M. and Bilitewski, U. (1997) Electrochemical Detection of African Swine Fever Virus in Pig Serum With a Competitive Separation Flow Injection Analysis-immunoassay. Analyst, 122, 155–159. Stöcklein, W., Jäger, V. and Schmid, R.D. (1991) Monitoring of mouse immunoglobulin G by flow-injection analytical affinity chromatography. Anal. Chim. Acta, 245, 1–6. Valcarcel, M. and Luque de Castro, M.D. (1987) Flow-Injection Analysis principles and applications. Ellis Horwood Ser. in Anal. Chem., Chichester: Ellis Horwood Ltd.

3. BIOCHEMICAL PRINCIPLES URSULA BILITEWSKI In biosensors for environmental analysis very different biochemical elements are used ranging from whole cells to isolated purified enzymes and antibodies and nowadays also receptors and DNA-fragments. These biochemical elements are influenced by constituents of an environmental sample in different ways: Whole cells or isolated enzymes may find substrates in the sample, which will lead to an increase of the catalytic turnover, other samples may contain enzyme inhibitors leading to a decrease of the activity. Antibodies, receptors and DNA usually show no catalytic activity, but form complexes with the analyte. Consequently, their application in analysis leads to completely different assays formats. In the following chapters the fundamentals of the main biochemical reactions relevant for biosensor development are described, with the exception of receptor assays. Though receptors are of increasing importance in environmental screening assays, they are not described here, because the assay formats are very similar to antibody-based assays and the use of receptors is not yet well-established due to their limited availability. 3.1. ENZYME ASSAYS 3.1.1. ENZYME SUBSTRATE DETERMINATION

AXEL WARSINKE 3.1.1.1. Introduction

Most of the successfully developed biosensors are based on the use of enzymes as the biorecognition element. Indeed, enzymes are ideal biomolecules for biosensor application. They are highly specific, the analyte binding region is regenerated due to the catalytic reaction itself and the consumption or production of compounds during the enzymatic reaction can often directly be followed by an appropriate transducer. The potential of enzymes to solve analytical problems has been known for a long time. In 1851 C.F.Schönbein used a ferment (the term enzyme was introduced later) to determine hydrogen peroxide for the first time. At this time the preparations of enzymes were crude because of the lack of appropriate purification methods. This was often accompanied by problems in specificity. Furthermore, the reaction mechanism for a particular enzyme was in almost all cases unknown. Therefore for a long time enzymes have not found application in analyses. After purification methods were developed in the middle of this century, enzymes were available in pure form and sometimes crystallization of an enzyme was successful (1926 crystallization of urease by J.B.Sumner, 1930–36 crystallization of chymotrypsin, trypsin, pepsin by H.Northrop and M.Kunitz). Three dimensional structures (1965 lysozyme by D.Philips) and protein sequences (1963 ribonuclease A by Smyth, Stein and Moore) were solved and reaction mechanisms have been proposed. This was a breakthrough for the development of modern enzymology and opened the window also for application of these compounds in analyses. During this period it became possible to develop some ideas about the general catalytic mechanism of enzymes (Pauling, 1948). Although efforts have been made to

describe the high catalytic efficiency of enzymes, until now the explanations are not sufficient to describe all aspects of enzymatic catalysis in detail. In the next part some general key points will be discussed. 3.1.1.2. Enzyme structure and catalytic properties

In general enzymes are built of a more or less spherical protein matrix with dimensions of 4– 4000 kDa, which often contains cofactors (metal ions or coenzymes) and structural as well as functional components (e.g. H2O, polysaccharides, phosphates). The polar amino acids of the protein matrix are normally found at the outer surface of the protein and communicate with the surrounding solution, whereas the hydrophobic amino acids are found in the core of the protein. The “active site” where the biomolecular recognition and conversion of the target substrate takes place is normally found in a deep cleft or pocket within the hydrophobic part of the enzyme molecule. Besides hydrophobic amino acid side chains, amino acids were found providing carboxyl, amino, phenol, benzene, indol, amido, thiol, guanidine, imidazole, hydroxyl groups which are often directly involved in the catalytic mechanism. The position of each side chain one to another has been optimized during the long period of evolution to evoke optimal conditions for effective catalysis. The pKa values of these side chains in the microenvironment of the active site can differ enormously from the values of the amino acid side chains in free solution. An impression of this is given in the following example. The pKa of β-COOH in aspartic acid was determined to be 3.6 in free solution whereas in proteins pKa’s of 1.5–5.0 can be found. The pKa of the ε-amino group of lysine in free solution is 10.5, whereas in proteins pKa values of 8.5–11 were found. In acetoacetate decarboxylase the pKa of an active site lysine (Lys 115) is about 6.0—that is 4.5pH units less than the value in solution! The reason for this is the spatial proximity to the ε-amino group of another lysine side chain (Lys 116) (Highbarger et al., 1996). Another example of perfect tuning is given by the catalytic triad of serine proteases, where Asp, His, Ser side chains built up a charge relay system and activate thereby the hydroxyl group of Ser for the nucleophilic attack of the amide bond. The fine tuning of the side chains and the conformational change of the polypeptide chains is the key to produce a huge arsenal of groups for general catalytic mechanisms such as substrate binding, transition state stabilization, desolvatisation, generation of entropic traps, acid/base catalysis and covalent catalysis. It is now widely accepted that these key mechanisms are responsible for lowering the free energy of activation of the reaction to be catalysed. In addition, for special reactions (e.g. redox reactions, hydrolysis of very stable bonds) cofactors in the form of metal ions or small organic compounds are used by the enzyme. Thirty percent of all enzymes need metal ions for their catalytic activity. They act as electron donors or acceptors, can mask nucleophiles, can bring the substrate and the protein into the right position for reaction and can bring about exact proximity of the reacting whereas transition metal ions groups. K+, Mg2+, Ca2+ are bound normally with 2+ 2+ 2+ 2+ . (e.g. Cu , Zn , Mn , Fe ) are bound very strongly by coordination with Coenzymes are small organic molecules which are bound to the enzyme very strongly by noncovalent as well as by covalent bounds (e.g. lipoic acid, biotin, FAD+) or they are bound very weakly in the case of cosubstrates (e.g. NAD+). As for the pKa’s discussed the interaction of the side chains of the catalytic site with the cofactor molecule can influence the catalytic behavior enormously (e.g. to activate the carboxyl group in carboxy-biotin or in the case of thiamine pyrophosphate where the substrate undergoes a α-H-elimination, a decarboxylation or a β-Celimination). Depending on the affinity of the protein molecule for the oxidized or for the

reduced form of flavine, for instance, the redox potential can have values from −490 mV to +190mV, respectively. In conclusion we have to note that evolution has developed a huge arsenal of tools which is used to catalyze a specific reaction in a very efficient way. How exactly it is achieved by the enzyme will be a secret for a long time and as Jencks described correctly “Most enzyme-catalyzed reactions are complicated” (Jencks, 1997). Nevertheless, improvements in methods to investigate enzymes in action (e.g. by X-ray methods; Farber, 1995), new resolved structures, site-directed mutagenesis experiments, selection and characterization of new enzymes, and design of artificial enzymes (e.g. catalytic antibodies and mimetica; Kirby, 1996) will give new insights into the secrets of biocatalysis. 3.1.1.3. Kinetic parameters of enzymes

Most enzymes follow Michaelis-Menten kinetics, which can be described by the following equation: (3.1.1)

where E is the concentration of the enzyme, E—S of the enzyme-substrate complex, S of the substrate and P of the product. k1, k2and kcat are the rate constants of the reaction. The binding of the substrate is considered to be reversible, while the formation of the product is irreversible. In this chapter for all enzymes Michaelis-Menten kinetics is assumed. Other types on enzyme kinetics are described in detail in a number of text books (Purich et al., 1995; Kuby, 1990; Segel, 1975). The formation (v) of the product is described by how fast the E—S complex is converted to the product: (3.1.2) Under the assumption that the system works under steady-state conditions the rate of formation of E–ZS and the rate of disappearance is equal. That means: (3.1.3) Under the assumption that the substrate concentration S will not significantly change during the reaction, S is equal to the initial substrate concentration S0. In contrast, E represents not the initial enzyme concentration E0, but the concentration of the free enzyme which is not occupied by the substrate. Therefore: (3.1.4)

The combination of equations 2–4 gives: (3.1.5)

The term is the “Michaelis constant Km”. The Michaelis constant represents the concentration of the substrate that produces half the maximum catalyzed rate. Most enzymes , Km represents the have Km values of about 10−2 to 10−5 M. Under the assumption that dissociation constant ( ) of the enzyme-substrate complex (also called Michaelis complex) and is in that case a value for the affinity of the enzyme for its substrate. Under high substrate concentration, when the enzyme works under maximal velocity, nearly all enzyme molecules are complexed with the substrate, so that . Under high substrate concentration the contribution of Km in relation to S becomes negligible. The equations 3.1.3 and 3.1.5 simplify to: (3.1.6) The maximal overall reaction velocity depends only on the rate constant kcat, which is called “catalytic rate” or “turnover number”, and the concentration of the enzyme. The maximal velocity increases proportionally with the enzyme concentration. Kcat represents the maximum number of substrate molecules that are converted into product per catalytic site per unit time. Most enzymes have kcat values of 1–104 s−1, carbonic anhydrase even has a kcat of 106 s−1. The combination of equation 3.1.6 and 3.1.5 gives the typical Michaelis-Menten-equation: (3.1.7)

where v is the initial velocity of the reaction. It depends on the concentration of the substrate and the kinetic constants Vmax and Km of the enzyme. The Michaelis-Menten diagram is shown in Figure 3.1. At substrate concentrations lower than the Km values the contribution of S in relation to Km becomes smaller. The equation simplifies to: (3.1.8)

Figure 3.1. Reaction rate v plotted against substrate concentration [S] for an enzyme with Km: 100 µM and Vmax: 0.1 µmol/ml*min obeying Michaelis-kinetics. The initial velocity is directly proportional to the substrate concentration, which is shown in the Michaelis-Menten diagram by the straight line. If the concentration of S exceeds widely Km the initial velocity approximates asymptotically Vmax (Figure 3.1). Although kcat and Km are widely characteristics constants for each enzyme and often helpful for the experimental setup with respect to the substrate concentration and the reaction time, for comparison of the proficiencies and specificities of different enzymes other kinetic terms have to be considered. To get an impression of the proficiency of an enzyme the “acceleration rate” should be used rather than kcat values. The “acceleration rate” is defined as the ratio of the catalyzed reaction rate to the uncatalyzed reaction rate (kcat/kuncat). The following example will demonstrate the difference. The enzyme carbonic anhydrase exhibits a kcat of 106 s−1 whereas the enzyme orotidine 5′-phosphate decarboxylase has only a kcat of 39s−1. If we compare only the kcat values it seems clear that the carbonic anhydrase is a more proficient enzyme. Nevertheless, the rate constant for the nonenzymatic decarboxylation of OMP is with extreme small, whereas the nonenzymatic hydratisation of carbon dioxide is, with a rate constant of 0.13 s−1, very fast. If we compare the acceleration rates of both enzymes it becomes clear that the OMP decarboxylase ( ) is a much more proficient enzyme than the carbonic anhydrase ( ) (Radzicka and Wolfenden, 1995). Commonly enzymes have rates of 6 acceleration of 10 –1014. In comparison to chemical catalysts the acceleration rates of enzymes are several orders of magnitude higher. To desribe the specificity of an enzyme for competing substrate, the specificity constants should be used rather than the Km values. The specificity (kcat/Km) constant is the ration of the catalytic rate to the Michaelis constant. The higher the value the more specific is the enzyme for the appropriate substrate. 3.1.1.4. Substrate determination with enzymes in solution

The highly efficient conversion of analytically interesting compounds to products in a very specific manner under moderate conditions, gives enzymes the potential to be an ideal tool in

determination of these compounds. If the physicochemical properties of the substrate differ from the properties of the product the reaction can be followed very easily. In general, two approaches should be considered for substrate determination in solution: 1. endpoint approach and 2. kinetic approach. The end-point approach is based on practically complete conversion of one or more substrates by the enzyme: (3.1.9) (3.1.10) After the reaction has taken place the result can easily be calculated with the aid of known physical constants of the substrate, of a participating coenzyme or of the product formed (e.g. extinction coefficient in the case of light absorbing substance, redox potential of an electrochemically active substance). This approach is very simple and does not need a timerecording spectrophotometer. A typical time curve is shown on Figure 3.2, where the production of NADH was followed with a time-recording spectrophotometer, but it would also be possible to measure the extinction before and 2 min after addition of the enzyme. From the difference of the extinctions (∆E) the concentration of the produced NADH can be calculated by using Lambert-Beer’s law with the molar extinction coefficient of NADH ( ). If the equilibrium is shifted to the reaction products the analyte concentration, substrate S, is equal to the produced NADH concentration and can be

Figure 3.2. Determination of a substrate via NADH production by end-point approach.

Figure 3.3. Influence of various Vmax (A) and Km (B) values to the time necessary for substrate conversion. calculated directly. Problems arise if the equilibrium is shifted to the substrates. In that case a calibration curve has to be used, the cosubstrate has to be added in large excess or a second reaction has to be coupled which traps one product of the reaction. In Figure 3.3 the integrated Michaelis-Menten equation (3.1.11) has been used to demonstrate the influence of Km and Vmax on the reaction time. Because the velocity of an enzymatic reaction is directly proportional to the amount of enzyme E0 (equation 3.1.5) a high concentration of enzyme, represented by Vmax, has to be used to shorten the time of analysis (Figure 3.3a). Furthermore, to reach a nearly complete conversion of the substrate in a reasonable time, the Km value of the enzyme should be as small as possible (Figure 3.3b). This is of special importance to maintain a relatively high velocity for the determination of a low analyte concentration ( ). (3.1.11)

To shorten the time of analysis, to use also unfavourable equilibrium reactions and to use enzymes with high Km values the kinetic approach can be applied. In this case the change of extinction is followed over a given time (Figure 3.4). To maintain a direct proportionality between the velocity (v) and the substrate concentration (S), S should be much smaller than Km. In this case the Michaelis-Menten equation simplifies as described in equation 3.1.8. In other words, for the kinetic determination of a substrate the enzyme should have a higher Michaelis constant ( ) than the substrate concentration (in contrast to the endpoint method). The endpoint and the kinetic method are used in a huge range of modified forms. For instance, if the substrate conversion by an enzyme does not produce any detectable compounds, an enzymatic indication reaction is often coupled to the substrate converting auxiliary enzymatic reaction.

Figure 3.4. Determination of a substrate via NADH production by kinetic approach. 3.1.1.5. Influence of immobilization on the kinetic parameters and substrate concentration

Immobilization of an enzyme normally has a great influence on the physical and chemical properties of an enzyme. The motion and flexibility of the polypeptide chains are restricted, the conformation can be changed as well as the chemical structure and charge. These changes have an influence on the pH- and thermostability, but the immobilization can also have an effect on the kinetic characteristics (e.g. Km value, substrate specificity) of an enzyme. In addition to these direct effects on an enzyme molecule (intrinsic kinetic parameters) the kinetic properties can be changed by distribution and diffusion effects. If these effects can be excluded, the intrinsic kinetic parameters of an immobilized enzyme can be determined as for enzymes in solution (e.g. by Lineweaver-Burk or direct linear-plot diagram). Nevertheless, even if matrix effects can be excluded, the interpretation of the results has to be done very carefully. One example is the determination of the intrinsic catalytic rate ( ). If we determine , it should be possible to calculate . if we know E0. The problem is, that we can have different enzyme populations on the carrier. One population can be totally inactivated, another slightly inactivated and another population can have the same activity as the native enzyme in homogeneous solution. To decide whether we have in our preparation only totally inactivated and fully active enzyme molecules (all-or-none condition) or a mixed population we have to compare the energies of activation for the immobilized and for the free enzyme. If we have the all-or-none condition we will get the same activation energies. If not, we have a mixed population. The value is then an average of all different enzyme populations. Matrix effects can also have a direct influence on the intrinsic kinetic parameters of the enzyme. In contrast to the free enzyme the solvatisation of the immobilized enzyme can be changed and the charge of the carrier surface will influence the interaction of the enzyme with the substrate.

In contrats to the “true” (intrinsic) changes of the kinetic parameters of an enzyme, distribution and diffusion effects can cause apparent changes in the kinetic parameters. This occurs if the matrix surface interacts with substrates, products, protons or intermediates. The concentration of these compounds can be enriched or can be lowered within the immobilisate. In this case, the concentrations will not be the same as in free solution. If someone wants to determine the intrinsic kinetic parameters ( , ) of an immobilized enzyme, all distribution coefficients have to be considered. The interaction of the immobilization matrix with protons can shift the pH value within the matrix up to 2.0pH units in the basic (anionic immobilisate) or the acidic (cationic immobilisate) direction. In the same way the pH profile of the enzyme will also be changed. With increased ionic strength this effect can be reduced. The value of an enzyme is apparently changed, if the immobilisate and the substrate interacts electrostatically. If the charge of the immobilisate and the substrate is different, the substrate will be enriched within the immobilisate and the value is apparently lower. With increased ionic strength this effect can also be reduced. A mathematical description of these two effects is given by Maxwell-Boltzmann distributions: (3.1.12) with charge;

, H+ activity in solution; e, elementary , H+ activity within the immobilisate; , electrostatic potential; k, Boltzmann constant; T, absolute temperature and (3.1.13)

with Simm, substrate concentration within the immobilisate; S0, substrate concentration in solution. If we use Simm instead of S0 within the Michaelis-Menten equation, it gives: (3.1.14)

By division of

the

is changing to an appartent Km value (Kmapp): (3.1.15)

In addition, the same effects as for charge can be observed for hydrophobic interactions of the immobilisate with the substrate. Besides distribution effects the transport of the substrate to the enzyme and the transport of the product to the transducer of a biosensor can be influenced by mass transport effects. If the enzymatic reaction is very fast, the production of the products depends only on the mass transport rate of the substrate to the enzyme. For mass transport we have to differentiate between outer and inner diffusion. Outer diffusion means transport of substrates or other substances to the outer surface of the immobilisate, while inner diffusion means transport within the immobilisate.

In systems with well-stirred solutions the outer diffusion is limited by the film diffusion (Nernst diffusion). In the bulk solution the mass transport is normally very fast by convection, whereas the transport decreases rapidly near the surface. Based on the Nernst concept there is an unstirred thin layer (Nernst diffusion layer) at the surface of the immobilisate with the thickness, where the mass transport is realized by diffusion. The mathematical description is given by the Fick’s first law: (3.1.16) with dn/dt, the flow of material dn across the area in a given time dt; D, the diffusion coefficient of the substrate; F, the particle or membrane area; dc/dx, the concentration gradient. Under the assumption that dc/dx is linear, the diffusion rate is given by: (3.1.17) To have a high diffusion rate the diffusion coefficient should be high, the Nernst diffusion layer (D) thin and the difference between the substrate concentration in the bulk (S0) and the substrate concentration at the surface (Ss) high. If the velocity of a reaction by immobilized enzymes is limited by the film diffusion (v=Vdiffusion) the Michaelis-Menten equation changes to: (3.1.18)

Because the equation considers the situation at the surface of the immobilisate, the and values are apparent values reflecting not the true intrinsic kinetic constant of the enzyme, a fact which is often underestimated. In general, the outer diffusion does not have such a great influence on the performance of an immobilized enzyme (with the exception of implantable sensors) as the inner diffusion. If the substrate concentration is low, the substrate molecules are large, the immobilisate has small pores and the enzyme activity is high, the reaction rate is limited by inner diffusion. Especially in enzyme sensors with membranes or densely immobilized enzyme layers these effects have a great influence on the performance of the biosensor. Under the assumption that the effective diffusion coefficient is (D, the diffusion coefficient of the substrate; P, volume of pores/volume of immobilisate; T, labyrinth factor), distribution effects and outer diffusion effects should have no influence and and the inner diffusion can be described mathematically by the Fick’s second law for a membrane (x=coordinate vertical to the membrane): (3.1.19)

Under stationary conditions

and ( ) the differential equation gives: (3.1.20)

Analytical solutions of this equation are only available for equation 3.1.20 for is given by:

and

The solution of

(3.1.21)

with ; l, layer thickness; x, distance within the enzyme layer from the surface (e.g. transducer), [S](X), substrate concentration at x; [S0], substrate concentration in solution and for product: (3.1.22)

with [P](X), product concentration at x; DPeffective, effective diffusion coefficient for the product. Based on these solutions the concentration profile of the substrate and the product can be modelled for an enzyme layer at a solid phase (e.g. transducer). It is assumed, that the transducer will not consume the product or substrate. In Figure 3.5 the influence of the kinetic constants of the enzyme and the diffusion behaviour of the substrate and the product on the concentration profile within the enzyme layer is modelled. In Figure 3.5a the substrate concentration in the enzyme layer is at each point > 0. That means that not all substrate molecules are consumed by the enzyme within the layer. If we apply this model to an enzyme sensor (solid phase=transducer), the sensor works under kinetic control. Small changes of the enzyme activity will influence the sensor signal. If the concentration of the enzyme in the layer is increased (represented by Vmax in Figure 3.5b) the substrate concentration within the enzyme layer decreases rapidly. All substrate molecules are consumed by the enzyme. The enzyme sensor works then under diffusion control. Small changes of the enzyme activity will not influence the sensor signal. Under these conditions a relatively stable enzyme sensor can be constructed, because decreases in enzyme activity can be tolerated for a period. Another possibility to generate a diffusion controlled sensor is to decrease the diffusion of the substrate (Figure 3.5c). Although the enzyme concentration is the same as in Figure 5a the concentration of the substrate decreases to 0 within the enzyme layer. The sensor works under diffusion control. Both methods to reach diffusion control are often realized in membrane enzyme sensors. That is the reason for the extraordinary stability of this type of biosensor. A useful mathematical term which describes whether the velocity of an immobilized enzyme is kinetic or diffusion limited is given by the enzyme loading factor, fe, which is the quadrate of the Thiele module, lα (equation 3.1.23). As an example, in Figure 3.5a

, but in Figure 3.5b and 3.5c

(3.1.23)

Figure 3.5. (A) Substrate concentration profile within an enzyme layer under kinetic controlled conditions; (B) under diffusion controlled conditions by high enzyme loading; (C) under diffusion controlled conditions by restricted diffusion. If the substrate concentration is very high in comparison to the Km value, the velocity of the reaction approximates Vmax. This means that under these conditions the diffusion has no influence. Whether the inner diffusion of the substrate has or has not influence becomes clear, if the linearisation of the Michaelis-Menten equation (e.g. Lineweaver-Burk-Diagram) does not produce straight lines. Sometimes it is difficult to detect such differences. Another possibility exists if the enzymatic reaction is investigated under different temperatures. At low temperatures the enzymatic reaction controls the reaction rate and the Arrhenius plot will give the true energy of activation. If the temperature increases, the velocity of the enzymatic reaction increases faster than the diffusion rate. Then, diffusion controls partly the velocity of the reaction and the energy of activation decreases apparently. Nevertheless, for such experiments control experiments are very important, because differences in the energy of activation can also be caused by other effects (e.g. conformation changes of the enzyme).

3.1.1.6. Substrate measurement with enzyme sensors

Enzymes can be used in enzyme sensors in various configurations. They can be immobilized to a transducer surface in different manner (e.g. by gel entrapment, membrane fixation, covalent linkage, adsorption). Often more than one enzyme are used in enzyme sensors (multienzyme sensors). For instance, if the product or the substrate are not directly transducable, the analyte converting enzyme is often combined with one or more additional enzymes to produce finally a transducable compound. Therefore the enzyme reactions are connected in linear sequences (Figure 3.6a) or competition reactions (Figure 3.6b). Another possibility to make the enzyme

Figure 3.6. A-E Different types of enzyme sensors (see text).

reaction transducable is to use a mediator or to use the direct communication of the enzyme with the transducer, e.g. by optical methods or by “molecular wires” (Figure 3.6c). Other examples for using more than one enzyme are, to trap an interfering substance by an additional enzyme reaction, shift the measuring range to lower concentrations by substrate recycling (Figure 3.6d) or shift the measuring range to higher concentrations by part elimination of the product. For a kinetically controlled enzyme sensor, if the cosubstrate concentration is not limited, the signal depends linear on the substrate concentration below . For this type of enzyme sensor a very thin enzyme layer can be used. The sensor response (described by I2/DPeffective) is very fast (with amperometric transducer the stationary signal can be reached within 5 s), but also very sensitive to changes in enzyme activity, e.g. by pH, denaturation or inhibition. To increase the sensitivity of the sensor it is necessary to increase by using another enzyme with higher , or by immobilization of a higher amount of enzyme (E0). The sensitivity rises until the sensor becomes diffusion limited. A further increase in enzyme loading will not provide a further increase in sensitivity (Figure 3.7), but due to the additional “enzyme reservoir” the sensor becomes insensitive to changes in enzyme activity. In that way, high stability of the enzyme sensor can be reached. The pH optimum is normally broader as for kinetic controlled sensors. Normally a further increase of enzyme loading is accompanied with a thicker enzyme layer and thereby with a decrease in sensitivity and increase in response time. In practice a compromise is used, where the enzyme loading is high enough to reach diffusion control but low enough to have a fast and sensitive sensor. In general, the linear measuring range of enzyme sensors depends on the transducer and the properties of the enzyme layer. Potentiometric sensors normally have detection limits of 10−4M, whereas the detection limits of amperometric sensors are around 10−7 M. The linear measuring ranges of amperometric enzyme sensors are

Figure 3.7. Influence of the glucose oxidase (GOD) loading in a gelatine layer to the sensor response.

usually 10−6–10−2 M. A reason for a reduced linear range can be the diffusion limitation of a cosubstrate, e.g. oxygen in the case of oxidase based sensors. Nevertheless, for many applications (e.g. amino acid, sugar, fat determination in diluted media) the linear ranges fulfil the requirements. To shift the linear measuring range to higher concentrations (e.g. for measurements in undiluted media like whole blood) additional diffusion barriers (e.g. membranes or polymers) can be used. If the linear range has to be shifted to lower concentrations (e.g. for determination of toxic compounds or hormones) substrate recycling can be used. Two enzymes (Figure 3.6d) as well as one enzyme and a transducer (Figure 3.6e) are normally used for substrate recycling. In an initial reaction the analyte is converted to a product, which is then converted back to the analyte by the second reaction. The consumption or production of a cosubstrate is measured. In that way the detection limit can be shifted to 10−9 M. But you must pay for what you get. The linear range is much smaller than for the nonamplified sensor and if the sensor works with the highest amplification, a decrease in stability is normally observed due to the conversion of a diffusion-controlled sensor into a kinetic-controlled sensor. 3.1.1.7. Conclusions

Enzymes have found widespread application for substrate determination. With the development of better enzymes (with respect to stability, kcat, Km, specificity) by screening or by design of artificial enzymes, the potential for bioanalytical techniques has increased enormously. For bioanalytical application, the kinetic constants of an enzyme as well as the reaction to be catalyzed indicates which experimental setup should be used. For high sensitivity and fast response of a biosensor a high and a thin enzyme layer should be used. To reach a high stability the sensor should work under diffusion control. REFERENCES

Farber, G.K. (1995) Laue crystallography. It’s show time. Curr-Biol., 5(10), 1088–90. Highbarger, L., Gerit, J.A. and Kenyon, G.L. (1996) Mechanism of the reaction catalyzed by acetoacetate decarboxylase. Importance of lysine 116 in determining the pKa of activesite lysine 115. Biochem., 35, 41–46. Jencks, W.P. (1997) From chemistry to biochemistry to catalysis to movement. Annu. Rev. Biochem., 66, 1–18. Kirby, A.J. (1996) Enzyme mechanisms, models and mimics. Angew. Chem. Int. Ed., 35(7), 707–724. Pauling, L. (1948) Nature of forces between large molecules of biological interest. Nature, 161, 707–709. Purich, D.L., Abelson, J.N. and Simon, M.I. (1995) Enzyme kinetics and mechanism. Methods in Enzymology, 249, Pt.D., Academic Press.

Radzicka, A. and Wolfenden, R. (1995) A proficient enzyme. Science, 267, 90–93. Segel, I.H. (1975) Enzyme kinetics: behavior and analysis of rapid equilibrium and steady state enzyme systems. John Wiley & Sons, Inc.

3.1.2. ENZYME INHIBITORS

BÉATRICE LECA, THIERRY NOGUER AND JEAN-LOUIS MARTY 3.1.2.1. Introduction

A large percentage of environmental pollutants are known to act as enzyme inhibitors, resulting in the development of numerous pollutant-detection tests based on the measurement of this property. Environmental pollutants are widely dispersed in waterways, air and soil as a consequence of industrial, agricultural and domestic wastes. Among the large number of enzyme inhibitors spread throughout the environment, pesticides and heavy metals are considered to be particularly hazardous compounds, especially in terms of their effects on human health and ecosystem function. These inhibitors, as well as their corresponding target enzymes are listed in Table 3.1. As one would expect, numerous studies have been devoted to the detection of cholinesterase inhibitors made up of organophosphorus and carbamate insecticides (Durand and Thomas, 1984; Mionetto et al., 1992; Palleschi et al., 1992; Sklàdal and Mascini, 1992; La Rosa et al., 1994; Cremisini et al., 1995; Kumaran and Morita, Table 3.1. Principal Inhibitor Families and their Target Enzymes. Inhibitor

Enzyme

Pesticides: insecticides (organophosphorus and carbamate)

cholinesterase, alkaline phosphatase, acid phosphatase, acylase, lipase, chymotrypsin

herbicides (sulfonylureas, triazines)

tyrosinase, acetolactate synthase, peroxidase

fungicides (dithiocarbamates)

aldehyde dehydrogenase, tyrosinase

Heavy metal salts: beryllium

alkaline phosphatase

cadmium

cholinesterase, G-3-PDH, L-LDH, LAP

chromium

L-LDH, G-6-PDH, cholinesterase, pyruvate kinase, hexokinase

cobalt

urease

copper

L-LDH, urease, GOD, cholinesterase, acid phosphatase

lead

alkaline phosphatase, L-LDH

mercury

urease, L-glycerophosphate oxidase, pyruvate oxidase, LLDH, GOD, invertase, cholinesterase, acid phosphatase

silver

L-LDH, GOD, urease

zinc

L-LDH

G-3-PDH: glycerol- 3 -phosphate dehydrogenase; L-LDH: L-lactate dehydrogenase; LAP: leucine aminopeptidase; G-6-PDH: glucose-6-phosphate dehydrogenase; GOD: glucose oxidase.

1995). Cholinesterase has been shown to be sensitive to a variety of heavy metals (Tran-Minh, 1985; Cokugras and Tezcan, 1993; Sklàdal et al., 1996) which have also been reported to inhibit many oxidases and dehydrogenases (Gayet et al., 1993). Spectrophotometry is currently the most widely used method to detect enzyme inhibitors. Nevertheless, this method often involves the use of enzymes in solution, so that the biocatalyst has to be renewed with each assay, thus increasing the cost of performing such measurements. One of the advantages of the biosensor technique of detection, however, is the use of enzymes in an immobilized state, thus allowing for the continuous use of the same enzyme loading. 3.1.2.2. Inhibition of enzymes in solution

In the first part of this review, we will focus on the inhibition of enzymes in solution. For this purpose, will be taken as our primary reference the theoretical aspects of enzyme inhibition described by Segel (1975). Main (1969) described more specifically the kinetics concerning inhibition of cholinesterase by organophosphorus and carbamate insecticides in solution, while Tran-Minh (1985) presented a kinetic analysis for the inhibition of enzymes in both soluble and immobilized states. Depending on their chemical mode of action, inhibitors can be divided into two groups: reversible or irreversible inhibitors. It must be stressed that substrate is required in all cases for the enzymatic determination of an inhibitor. Usually, the amount of substrate is sufficiently abundant so that the rate of the non-inhibited reaction can be considered unchanged and used as a point of reference. Among the different important parameters influencing the inhibition process, pH must be carefully selected as the interaction of the enzyme with the inhibitor is pHdependent. The main characteristics of the different types of inhibition are summarized in Table 3.2. 3.1.2.2.1. Reversible inhibition

Reversible inhibition is characterized by an equilibrium between the enzyme and the inhibitor, defined by the equilibrium constant Ki (dissociation constant of the enzyme-inhibitor complex, , with [E] and [I] representing respectively the concentrations of enzyme and inhibitor) which reflects the affinity of the enzyme for the inhibitor. The reversibility of inhibition implies that there is no need for incubation of the enzyme with the inhibitor. It is possible to distinguish three main types of inhibition depending on the behaviour of the inhibitor in relation to the active site of the enzyme: competitive, uncompetitive and non-competitive. When inhibition occurs, the expression of the enzymatic reaction rate is modified by a term (1+[I]/Ki) which affects either the maximum velocity Vm (non-competitive inhibition) or the affinity constant Km (competitive inhibition) or both of them (uncompetitive inhibition) (Table 3.2). Considering the classical and more commonly used Lineweaver-Burk plot (1/v=f(1/[S])), each type of inhibition can be determined according to modifications in the slope (Km/Vm), the 1/[S] axis intercept (−1/Km), and/or the 1/v axis intercept (1/Vm). Other linear plots such as Hanes ([S]/v=f ([S]) or Woolf-Hofster (v=f(v/[S])) representations can also be used.

Table 3.2. Principal Characteristics of Reversible and Irreversible Inhibitions. Reversible

Irreversible

dissociation (equilibrium) constant Ki

bimolecular rate constant k;

Inhibitor binding mode

non covalent (ionic, Van der Waals…)

covalent

Change in the inhibitor molecule after dissociation

No

Yes

Reactions Inhibition parameter Equations

(hydrolysis, oxidation…) Need of pre-incubation

No

Yes

Reactivation

rapid by washing out the inhibitor

need of special reactivators

Competitive inhibition (Figure 3.8) This type of inhibition occurs when the inhibitor and the substrate are mutually exclusive; the binding of one species prevents the binding of the other. The simplest and more common feature is encountered when the inhibitor sufficiently resembles the substrate to compete for the same active site of the enzyme. More complex models fit the same type of inhibition, as shown in Figure 3.8. In all of the cases, the degree of inhibition decreases when the substrate concentration increases; inhibition can thus be reversed by using very high concentrations of substrate. The equilibria describing competitive inhibition are given below, showing clearly the mutual exclusion of substrate (S) and inhibitor (I) (with E representing the enzyme, Ks=[E][S]/[ES], the dissociation constant of the complex enzyme-substrate, and k, the rate constant for the breakdown of ES to E and P):

Figure 3.8. Models of Competitive Inhibition according to Segel (1975): a) S and I compete for the same binding site; b) steric hindrance prevents the mutual fixation of I and S; c) I and S share a common binding site; d) I and S binding sites are differents but overlapping; e) the binding of one ligand modifies the conformation of the binding site of the other ligand. Kinetically, competitive inhibition affects the slope of the Lineweaver-Burk plots without modifying the maximal velocity ( ), so that the apparent affinity constant (K′m) of the enzyme for the substrate increases when the concentration of inhibitor increases. The inhibition of urease by thiourea can be cited as an example of competitive inhibition that is of interest in environmental monitoring (Tran-Minh, 1985), with thiourea being a degradation product of dithiocarbamate fungicides. Non-competitive inhibition (Figure 3.9) A non-competitive inhibitor binds to the enzyme independently of the substrate, without modifying the affinity of the enzyme for the substrate. The inhibition in this case is thus independent of the substrate concentration. The main mechanisms of non-competitive inhibition are presented in Figure 3.9. The equilibria describing non-competitive inhibition clearly show that I can bind both to E and ES, leading to inactive EI and ESI complexes:

Figure 3.9. Models of Non-competitive Inhibition according to Segel (1975): a) the binding of I does not prevent the binding of S but induces a conformation change of the catalytic center (C); b) the binding of I prevents sterically the binding of S; c) if I binds first, the catalytic site can not align with the substrate, on the other hand if S binds first, it prevents sterically the binding of I. Even at high substrate concentrations, not all of the enzyme can be driven to the ES form. Consequently, a non-competitive inhibitor acts by decreasing the apparent value of Vm, the apparent Km remaining unchanged. Inhibition of acetylcholinesterase (Tran-Minh, 1985) and L-glycerophosphate oxidase (Gayet et al., 1993) by mercury (Hg2+) constitute two examples of non-competitive inhibition that are of environmental concern.

Uncompetitive inhibition (Figure 3.10) In the case of uncompetitive inhibition, the inhibitor does not bind to the free enzyme but to the ES complex, yielding an inactive ESI complex. This type of inhibition generally occurs only when using monosubstrate systems. Contrary to competitive inhibition, the degree of inhibition increases as the substrate

Figure 3.10. Model of Uncompetitive Inhibition according to Segel (1975). I binds only to the complex ES. concentration increases. The equilibria describing uncompetitive inhibition are provided in the diagram below:

The equilibria show that some ESI complex will always be formed, even at very high substrate concentrations. Uncompetitive inhibition does not modify the slope of the 1/v=f(1/[S]) plots but only increases the value of the intercept on the 1/v axis. This results in a decrease in the apparent values of Vm and Km. Examples of uncompetitive inhibition are the inhibition of urease (Tran-Minh and Beaux, 1979) and acetylcholinesterase (Tran-Minh, 1985; Kambam et al., 1990) by fluoride.

Mixed-type inhibitions These inhibitions are derived from the three types of inhibitions previously described. In all cases, mixed-type inhibitions modify both the Km and the Vm values. A simple mixed system is encountered for alkaline phosphatase inhibition by paraoxon, an organophosphorus insecticide (Ayyagari et al., 1995), where the EI complex has a higher affinity for S than for E ( ) and the ESI complex is inactive:

3.1.2.2.2. Irreversible inhibition Due to the irreversible nature of inhibition, the reaction cannot be expressed in terms of an equilibrium situation, but in terms of initial velocity. The main parameter is thus the bimolecular rate constant ki (Table 3.2). The equation of Aldridge is valid when the concentration of inhibitor is much higher than that of the active sites of the enzyme. Contrary to reversible inhibitors, irreversible inhibitors generally act by covalent binding to the enzyme. When the inhibitor binds to the enzyme, the transient complex EI rapidly evolves towards a new irreversible EI′ complex as a result of chemical modifications. For instance, the binding of organophosphorus insecticides to cholinesterases leads to the phosphorylation of the serine residue at the enzyme catalytic center:

Enzyme activity cannot be restored by lowering the inhibitor concentration, and so the enzyme has to be regenerated and reactivated using special agents. Phosphorylated cholinesterases can be reactivated in this way using a powerful nucleophilic compound such as 2-PAM (2pyridinealdoxime methiodide) or TMB-4 ({1,1′-trimethylenebis-4-(hydroxyimino-methyl)pyridinium bromide}):

Heavy metals ions (Table 3.1) can sometimes be considered as irreversible inhibitors due to the very slow reversibility of inhibition. These compounds act by the binding of the metal salt to protein thiol groups (Webb, 1966). Consequently, the main targets of heavy metals are dehydrogenases and oxidases due to the presence of cysteine residues near the active site:

In some cases, enzymes that have been inhibited by heavy metals can be reactivated using complexing agents such as EDTA or thiols (dithiothreitol) (Gayet et al., 1993). Another difference when compared to reversible inhibition is the need to perform a preliminary incubation between the enzyme and the inhibitor, due to the rather slow rate of the inhibition process. For this reason, the degree of inhibition and the sensitivity of the system are directly related to the incubation time. 3.1.2.3. Inhibition of immobilized enzymes in biosensors

Some new problems arise in the use of immobilized enzymes instead of soluble enzymes to detect inhibitors. First of all, the immobilization of an enzyme generally induces conformational modifications that may affect its activity and its sensitivity towards inhibition. Gayet et al. (1993) reported that the inhibition of L-glycero-phosphate oxidase by mercury salts was reversible and non-competitive in solution, and irreversible after immobilization on either a gelatin film or on the surface of an affinity membrane. Moreover, many reports point out that immobilization induces a decrease in the sensitivity of enzymes towards inhibitors (Tran-Minh, 1985; Campanella et al., 1991; Bernabei et al., 1991; Roda et al., 1994; Cremisini et al., 1995). The theoretical aspects of the use of inhibited enzyme electrodes have been discussed by many authors such as Tran-Minh (1985) and Albery et al. (1990a-c). When using biosensors, the inhibition process is influenced by various new parameters such as microenvironmental effects, diffusion limitations and possible interactions between the substrate and/or the inhibitor and the membrane. This sorption effect can be suppressed by the addition of surfactants, thereby increasing the sensitivity of the biosensor towards organophosphorus pesticides (Evtugyn et al., 1996).

Unlike biosensors devoted to the determination of substrates, the detection of inhibitors requires the use of low enzyme loadings in order to detect very low inhibitor concentrations. Consequently, enzyme electrodes used in such assays must work under kinetic control. This concept is not usual in the design of biosensors for substrate determination where high enzyme loadings are used, so that the responses are governed by diffusional constraints. Generally, the detection of inhibitors proceeds in three steps (Figure 3.11a): — the first step is the determination of the initial response (I1) of the biosensor to a sufficiently high concentration of substrate, — the second step consists of the incubation of the biosensor with the inhibitor for a defined period, — the last step is the determination of the residual response (I2) of the biosensor using the same concentration of substrate as in the first step. The degree of

Figure 3.11. Schematic representation of the two possible methods of determination of inhibitors using a biosensor, a) indirect determination: the responses to substrate are measured before (I1) and after (I2) incubation with the inhibitor during a given time, b) direct determination: the inhibitor is added in the medium once the steady state response (I1 to substrate is reached. inhibition (I %) is then calculated by comparing the responses before and after inhibition according to the relation:

This method has been principally reported by Palleschi et al. (1992) and Marty et al. (1992). The main drawback of the procedure is that it is time consuming because it involves two separate measurements of activity as well as an additional incubation step with the inhibitor. Nevertheless, very low concentrations of inhibitor can be detected using this method. Another approach has been described by Sklàdal and colleagues (Sklàdal, 1991; Sklàdal, 1992; Sklàdal and Mascini, 1992). In a first step, an appropriate concentration of substrate is added in the medium. When a steady-state current is reached, a defined concentration of inhibitor is

injected (Figure 3.11b) inducing a decrease in the intensity of the current as function of time (dI/dt). The relative inhibition (RI) is then determined according to the following relation:

In spite of its relative rapidity, this method suffers from a low sensitivity towards inhibitors. This drawback can be related to the fact that the contact time of the enzyme probe with the inhibitor is too short to bring about a noticeable inhibition in the presence of very low inhibitor concentrations. 3.1.2.4. Conclusion

Many enzymes are inhibited by various substances that are known to have an effect on the environment, such as pesticides or heavy metals (Table 3.1). Enzyme electrodes for the detection of various families of environmental pollutants have been widely reported in literature. Such devices are based on the immobilization of the target enzyme, leading to possible modifications in the inhibition process. Among the various reports, cholinesterases have been widely used in the detection of organophosphorus insecticides. These insecticides correspond to irreversible inhibitors, making it necessary to find a way to reactivate the enzyme after inhibition. This has been successfully achieved by using nucleophilic agents such as 2-PAM (Tran-Minh et al., 1990; Mionetto et al., 1994; Marty et al., 1995). Another important family of toxic compounds is represented by heavy metal salts. These are generally detected using immobilized oxidases or dehydrogenases. The restoration of activity of the immobilized enzyme is generally performed by removal of the metallic ions from the enzyme, by complexation with EDTA or dithiotreitol, or by precipitation using an appropriate counter-ion (Tran-Minh, 1985). It must be stressed that, on occasions, some heavy metals may also act as enzyme activators or cofactors, thereby causing an increased activity in the presence of the pollutant. For instance, carbonic anhydrase binds specifically to its cofactor Zn2+ to form the active holoenzyme. A fiber optic sensor using this enzyme is capable of detecting nanomolar concentrations of zinc (Thompson and Jones, 1993). Contrary to chemical methods of detection, enzyme-based methods appear simple and sensitive. However, such devices often suffer from a lack of specificity as various compounds are likely to inhibit enzyme activity. Nevertheless, this poor specificity could be used to advantage in evaluating a global index of toxicity. REFERENCES

Albery, W.J., Cass, A.E.G. and Shu, Z.X. (1990a) Inhibited enzyme electrodes. Part 1: theorical model. Biosensors and Bioelectronics, 5, 367–378. Albery, W.J., Cass, A.E.G. and Shu, Z.X. (1990b) Inhibited enzyme electrodes. Part 2: the kinetics of the cytochrome oxidase system. Biosensors and Bioelectronics, 5, 379–395.

Albery, W.J., Cass, A.E.G. and Shu, Z.X. (1990c) Inhibited enzyme electrodes. Part 3: A sensor for low levels of H2S and HCN. Biosensors and Bioelectronics, 5, 397–413. Ayyagari, M.S., Kamtekar, S., Pande, R., Marx, K.A., Kumar, J., Tripathy, S.K., Akhara, J. and Kaplan, D.L. (1995) Chemiluminescence-based inhibition kinetics of alkaline phosphatase in the development of a pesticide biosensor. Biotechnol. Prog., 11, 699–703. Bernabei, M., Cremisini, C., Mascini, M. and Palleschi, G. (1991) Determination of organophosphorus and carbamic pesticides with a choline and acetylcholine electrochemical biosensor. Anal. Lett., 24, 1317–1331. Campanella, L., Achilli, M., Sammartino, M.P and Tomassetti, M. (1991) Butyrylcholine enzyme sensor for determining organophosphorus inhibitors. Bioelectrochem. Bioenerg., 26, 237–249. Cokugras, A.N. and Tezcan, E.F. (1993) Inhibition kinetics of brain butyrylcholinesterase by Cd2+ and Zn2+, Ca2+ or Mg2+ reactivates the inhibited enzyme. Int. J. Biochem., 25, 1115–1120. Cremisini, C., Di Sario, S., Mela, J., Pilloton, R. and Palleschi, G. (1995) Evaluation of the use of free and immobilised acetylcholinesterase for paraoxon detection with an amperometric choline oxidase based biosensor. Anal. Chim. Acta, 311, 273–280. Durand, P. and Thomas, D. (1984) Use of immobilized enzyme coupled with an electrochemical sensor for the detection of organophosphates and carbamates pesticides. J. Environ. Pathol. Toxicol. Oncol., 5, 51–57. Evtugyn, G.A., Budnikov, H.C. and Nokolskaya, E.B. (1996) Influence of surface-active compounds on the response and sensitivity of cholinesterase biosensors for inhibitor determination. Analyst, 121, 1911–1915. Gayet, J.-C., Haouz, A., Geloso-Meyer, A. and Burstein, C. (1993) Detection of heavy metals salts with biosensors built with an oxygen electrode coupled to various immobilized oxidases and dehydrogenases. Biosensors and Bioelectronics, 8, 177–183. Kambam, J.R., Parris, W.C.V., Naukam, R.J., Franks, J.J. and Rama Sastry, B.V. (1990) In vitro effects of fluoride and bromide on pseudoacetylcholinesterase and acetylcholinesterase activities. Can. J. Anaesth., 37, 916–919. Kumaran, S. and Morita, M. (1995) Application of a cholinesterase biosensor to screen for organophosphorus pesticides extracted from soil . Talanta, 42, 649–655. La Rosa, C., Pariente, F., Hernandez, L. and Lorenzo, E. (1994) Determination of organophosphorus and carbamic pesticides with an acetylcholinesterase amperometric biosensor using 4-aminophenyl acetate as substrate. Anal. Chim. Acta, 295, 273–282.

Main, A.R. (1969) Kinetics of cholinesterase inhibition by organophosphate and carbamate insecticides. Canadian Medical Association Journal, 100, 161–167. Marty, J.-L., Mionetto, N., Lacorte, S. and Barcelo, D. (1995) Validation of an enzymatic biosensor with various liquid chromatographic techniques for determining organophosphorus pesticides and carbaryl in freeze-dried waters. Anal. Chim. Acta, 311, 265–271. Marty, J.-L., Sode, K. and Karube, I. (1992) Biosensor for detection of organophosphate and carbamate insecticides. Electroanal., 4, 249–252. Mionetto, N., Marty, J.-L. and Karube, I. (1994) Acetylcholinesterase in organic solvents for the detection of pesticides: biosensor application. Biosensors and Bioelectronics, 9, 463–470. Mionetto, N., Rouillon, R. and Marty, J.-L. (1992) Inhibition of acetylcholinesterase by organophosphorus and carbamates compounds. Studies on free and immobilized enzymes. Z.Wasser-Abwasser-Forsch., 25, 171–174. Palleschi, G., Berbabei, M., Cremisini, C. and Mascini, M. (1992) Determination of organophosphorus insecticides with a choline electrochemical biosensor. Sensors and Actuators B, 7, 513–517. Roda, A., Rauch, P., Ferri, E., Girotti, S., Ghini, S., Carrea, G. and Bovara, R. (1994) Chemiluminescent flow sensor for the determination of paraoxon and aldicarb pesticides. Anal. Chim. Acta, 294, 35–42. Segel, I.H. (1975) Simple inhibition systems (Chapter 3). In Enzyme kinetics. Behavior and analysis of rapid equilibrium and steady-state enzyme systems, (eds). pp. 100–159. New York: John Wiley & Sons. Sklàdal, P. (1991) Determination of organophosphate and carbamate pesticides using a cobalt phtalocyanine-modified carbon paste electrode and a cholinesterase enzyme membrane. Anal. Chim. Acta, 252, 11–15. Sklàdal, P. (1992) Detection of organophosphate and carbamate pesticides using disposable biosensors based on chemically modified electrodes and immobilized cholinesterase. Anal. Chim. Acta, 269, 281–287. Sklàdal, P., Fiala, M. and Krejci, J. (1996) Detection of pesticides in the environment using biosensors based on cholinesterases. Intern. J. Environ. Anal. Chem., 65, 139–148. Sklàdal, P. and Mascini, M. (1992) Sensitive detection of pesticides using amperometric sensors based on cobalt phtalocyanine-modified composite electrodes and immobilized cholinesterases. Biosensors and Bioelectronics, 7, 335–343. Thompson, R.B. and Jones, E.R. (1993) Enzyme based fiber optic zinc biosensor. Anal. Chem., 65, 730–734.

Tran-Minh, C. (1985) Immobilized enzyme probes for determining inhibitors. Ion-Selective Electrode Rev., 7, 41–75. Tran-Minh, C. and Beaux, J. (1979). Enzyme electrode for inhibitors determination: ureasefluoride system. Anal. Chem., 51, 91–95. Tran-Minh, C., Pandey, P.C. and Kumaran, S. (1990) Studies on acetylcholine sensor and its analytical application based on the inhibition of cholinesterase. Biosensors and Bioelectronics, 5, 461–471. Webb, J.L. (1966) Enzyme and metabolic inhibitors. II, pp. 635–653. New York: Academic Press.

3.2. MICROBIAL SENSORS

KLAUS RIEDEL, GOTTHARD KUNZE, MATTHIAS LEHMANN and ANDREAS KÖNIG 3.2.1. INTRODUCTION

Microbial sensors consisting of microorganisms in intimate contact with a transducer allow the sensitive determination of a large spectrum of substances and are especially suitable for environmental monitoring because of the following characteristics: • multistep transformations, which are difficult or impossible to achieve with single enzymes or enzyme chains; • ability to recognize a group of substances simultanously, designated as multi-receptor behaviour; • inexhaustible reserve of microorganisms with a wide spectrum of metabolic types; • wide repertoire of specifities; • variability that allows adaptation to the specific conditions; • physiological response to toxic products; • independency from cofactors; • increased stability due to the enzyme environment “optimized by evolution” and well suited for recovery and sense; • inexpensive preparation because enzyme extraction and purification steps are not necessary and the cultivation of microorganisms is simple. Microbial sensors are particularly well suited for environmental control because they are physically robust and stable, easy to handle and cheap to prepare. Especially, the ability to recognize a group of substances is interesting for environmental control. This multireceptor behaviour has been exploited for the determination of complex variables, such as the sum of biodegradable compounds in waste water (BOD), toxicity and mutagenicity (see 4.2.1.). Certainly this multireceptor behaviour causes rather poor selectivity. Therefore, microbial sensors are less suitable for the determination of individual analytes. 3.2.2. DESIGN AND FUNCTION

The design of the microbial biosensor is, in principle, identical to an enzyme sensor. The scheme in Figure 3.12 shows the structure of microbial sensors. The biosensor

Figure 3.12. Schematic design of microbial sensor. consists of immobilized intact cells in intimate contact with a transducer unit, which converts the biochemical signal into an electrical one. 3.2.2.1. Microbial basis

Microbial sensors show important differences to enzyme sensors. Sensing by enzyme sensors is achieved by selective molecular binding of a chemical analyte to the enzyme including the alteration of analyte, whereas the microbial sensor employs physiological responses of living cells as the sensing component. Figure 3.13 demonstrates the flow of the physiological response which includes:

Figure 3.13. Physiological response of microbial sensor.

• substrate uptake through the cell membrane; • intracellular modification or degradation of the substrate by metabolic sequences of the enzyme network; • secretion or separation of metabolic products and by-products; • respiration; • luminescence by photobacteria. This behaviour of microorganisms is related to their physiological state, which is characterized under biosensor conditions by extreme nutrient limitation. Their metabolism is in a stand-by state to guarantee the survival of the cell (Riedel, 1991). The first and critical step of formation of the signal by a microbial sensor is substrate uptake. Solutes can pass into the cells only via specific translocation systems, either by an active transport system or by facilitated diffusion; passive transport events by diffusion are of minor importance. Active transport allows accumulation of substrates up a concentration gradient. This requires carrier proteins with high specificity and it consumes metabolic energy. However, the coupling to the cell energy transducing systems, especially to the respiratory chain is an important aspect of active transport, which is crucial for the formation of the signal from the sensor, for example using glucose, maltose, sucrose and various oligopeptides (Riedel, 1991; Riedel et al., 1989, 1990a). After the uptake of substrate it is degraded specifically by the metabolic sequences of the enzyme networks of the immobilized cells. Under aerobic conditions this is connected with oxygen consumption. Organic acids such as lactate and pyruvate, CO2, ammonium ions and H2S are secreted as by-products. Moreover, the metabolic response to the analytical substrate can cause luminescence by photobacteria. In general, the microbial species chosen for biosensor development must fulfil at least one of the following criteria: • oxygen consumption in the respiratory process for assimilation of substrate; • electrode-active products liberated from reactions of microbial metabolism, e.g. protons, CO2, ammonium ions and H2S; • photoluminescence.

3.2.2.2. Physical basis of the transducer

Transducers are potentiometric or amperometric electrodes, optoelectronic detectors, thermistors, field-effect transistors and piezoelectric crystal systems (Figure 3.12). The selection of a transducer depends on the physiological response such as respiration or photoluminescence as well as on the product formed from the biological layer of the biosensor. A particular advantage of the sensor is the ability to measure the respiratory activity of microorganisms and its alteration caused by the presence of a tested substance. This allows a relatively simple transduction of the analyte response of microorganisms by an oxygen electrode. Therefore, amperometric oxygen electrodes dominate among the transducers used in microbial sensors. However, the application of an optical oxygen electrode was described too (Preininger et al., 1994).

Figure 3.14. Schematic function of microbial sensor with mediators (modified to Kaláb and Skládal, 1994). Metabolic products such as lactate and pyruvate, CO2, ammonium ions and H2S are determined with gas-sensitive, potentiometric electrodes and ion selective electrodes (ISE) (Table 3.5). The direct combination of microorganisms on a gate of a field effect transistor have been developed for the estimation of glucose (Hanazato and Shio, 1983), for alcohol with Acetobacter aceti (Kitagawa et al., 1987) and xylose based on Gluconobacter oxydans cells (Reshetilov et al., 1996). Furthermore, soluble redox mediators, such as phenazine ethosulphate (Turner et al., 1983), ferricyanide (Richardson et al., 1991), or ferricyanide in combination with benzoquinone (Turner et al., 1986) enable the direct measurement of electrons following the metabolic activity of cells. Recently, the use of insoluble mediators was described, such as ferrocene, tetrathiafulvalene and tetracyanoquinodimethane, which were incorporated in carbon paste in connection with Paracoccus denitrificans (Kaláb and Skládal, 1994). The schematic function of this biosensor type is shown in Figure 3.14. These amperometric microbial sensors are not based on oxygen dependency which is advantageous.

Another interesting technique was created by luminescent photobacteria in connected to an optical detector. Such microbial sensors have been described for the determination of metal ions (Guzzo et al., 1992; Holmes et al., 1993) and aromatics (Heitzer et al., 1994). By genetic engineering the lux or light-emitting genes from the photobacteria Vibrio were fused to genetic regulatory or structural genes from Escherichia coli and Serratia marcescens (see 3.2.4.). If microorganisms are combined with a thermistor it is possible to measure the metabolic heat caused by cell reaction to analyte. Such biosensors were described by Mattiasson et al. (1977) as well as Henrysson and Mattiasson (1991, 1993). Further transducers of biosensors are piezoelectric crystals. However, these do not play a role in microbial sensors. 3.2.2.3. Immobilization of microorganisms

The intimate contact between biocatalyst and transducer element by immobilization of the microorganisms is a prerequisite for the constant function of a biosensor. In general, immobilization of the microorganisms for analytical purposes should cause the following effects: • impediment of washout of microorganisms with a increased working stability of the organisms and the biosensor; • reusability of the organisms because of their increased storage stability; • due to the long, predictable, half-life of the activity of the immobilized organisms they become an integrated constituent of the analytical device. Immobilization procedures are limited by the sensitivity of microorganisms. That is why chemical methods, to the best of our knowledge, have been unsuccessful and resulted in decreased biological activity. The preferred immobilization methods are: • entrapment of microorganisms in polymers forming gel membranes such as agar, gelatine, collagen, polyacrylamide, polyvinylalcohol (Riedel et al., 1988a; Matsunaga et al., 1978) and socalled prepolymers (Fukui and Tanaka 1984); • physical methods, like adsorption onto a membrane or sheet of acetylcellulose (Matsunaga et al., 1980), filter paper (Matsunaga et al., 1980; Riedel et al., 1985, 1990b) or nylon (Kulys and Kadziauskiene, 1980) by centrifugation or filtration of a microbial suspension. A very promising approach is the use of socalled prepolymers of ENT (poly(ethyleneglycol)) and ENTP type (poly(propyleneglycol)) or modified polyvinylalcohols for entrapment of microbial cells (Fukui and Tanaka, 1984). This prepolymer method allows defined adjustment of hydrophobicity by alteration of the relation of the hydrophilic ENT and the hydrophobic ENTP. This is important for the determination of polar compounds, such as biphenyl (BeyersdorfRadeck et al., 1992). Moreover, oxygen permeability and substrate diffusion through the immobilized microorganism membrane must be efficient. Although the gel membrane is also influenced by diffusion of substrates, the diffusional resistance is mostly caused by the biomass concentration on the membrane. As shown in Figure 3.15 the signal is strictly related to the cell

loading of the sensor. Mostly a relatively high concentration of biomass and thick membranes are used. Due to the diffusional resistance imposed by the microbial cell membranes the response times for microbial sensors are higher than for enzyme electrodes. Response times comparable in magnitude to enzyme sensors are achieved with very low microbe loadings and suitable immobilization of microorganisms (Riedel et al., 1985, 1988b). The sensitivity of these kinetically controlled sensors is mostly determined by the cell activity, but not by diffusional limitation. 3.2.2.4. Signal formation and measuring principle

Formation of the signal is described for the example of an amperometric sensor based on the respiration of microorganisms. This aerobic process consists of the following steps (Figure 3.16):

Figure 3.15. Influence of cell loading on the signal for glucose (0.15 mmol) (modified to Riedel, 1994).

Figure 3.16. Principle of measurement with microbial sensor (modified to Riedel, 1994). (i) Oxygen diffuses from the air-satured solution through the dialysis membrane, the membrane containing the microorganisms, as well as the teflon membrane and then reduced at the cathode. A small proportion of the oxygen is consumed by the microorganisms. The steady state current represents the oxygen diffusion through the composite membrane and reflects the endogenous respiration of the microorganisms. (ii) If an analyte as assimilable substrate is added to the measuring solution the substrate permeates through the dialysis membrane, subsequently, it is taken up by the microbial cells and then degraded. These processes are caused by an increase of respiration rate resulting in a decrease in the “dissolved” oxygen concentration. The current decreases until a new steadystate is reached. In principle, there are two possibilities for measurement: (i) end-point measurement (steady-state mode), the differences in current I reflect the respiration rate of the substrates Rs, and (ii) kinetic measurement (first derivative of the current-time curve corresponding to the acceleration of respiration A). 3.2.3. IMPROVEMENT OF SELECTIVITY OF MICROBIAL SENSORS

One critical disadvantage of microbial sensors for substrate determination is their low selectivity. Nevertheless biochemical knowledge in connection with gene manipulation enables the alteration of the selectivity and sensitivity of microbial sensors. Approaches for enhancing the selectivity and sensitivity are:

• induction of desired transport and/or metabolic systems; • inhibition or suppression of undesired transport mechanisms and/or metabolic pathways; • construction of species modified by gene manipulation methods; • coupling of enzymes with immobilized microbial cells to form hybrid sensors for elimination of interfering substances or formation of specific products; • combination of various microbial species with supplementary specific metabolic capacities; • exclusion of undesired substrates by dialysis membranes. 3.2.3.1. Influence of selectivity by induction of desired metabolic activity of microorganisms

The induction of desired activity can be achieved by two different methods: • by cultivation of microorganisms with the appropriate substrate; • by incubation of the sensor with the appropriate substrate. The knowledge of the genotype of microorganisms is a prerequisite to influence their sensitivity. The cultivation mode is a widespread procedure and has been used to develop sensors for example for histidine by Pseudomonas sp. (Walters et al., 1980), Table 3.3. Influence of incubation (3h) with inductor (2 mM) on the response of a Bacillus subtilis biosensor to various sugars (Riedel et al., 1990a). Substrate

Increase of biosensorsignal after Incubation [%] Sucrose

Maltose

Lactose

Maltose+ Chloramphenicol

Sucrose

2322

83

168

96

Maltose

83

1905

147

90

Lactose

–

–

2680

–

Glucose

96

118

117

114

Glycerol

82

130

200

63

tyrosine by Aeromonas phenologenes (Di Palantonio and Rechnitz, 1982), maltose by B. subtilis (Riedel et al., 1988b), lactate by Hansenula anomala (Vincke et al., 1985a), ascorbic acid by Enterobacter agglomerant (Vincke et al., 1985b), glutamate (Riedel and Scheller, 1987), and phenols or benzoate by Rhodococcm P1 (Riedel et al., 1991a).

It is also possible to improve the specificity and sensitivity of the microbial sensor to the desired substrate by direct induction. The signal for the induced substrate was increased by a factor of up to 26, as demonstrated for Bacillus subtilis or Trichosporon cutaneum (Table 3.3) (Riedel et al., 1990a). The biosensor can thus be adapted to the desired analytical conditions. Under these conditions the alteration of specificity and sensitivity is highly specific. This was demonstrated for sucrose and maltose by a Bacillus subtilis-containing sensor (Riedel et al., 1990a). Sucrose and maltose gave a low signal in comparison to glucose. The incubation of the sensor with sucrose for 3h caused a drastic increase of sensor response only for this sugar because the response for glucose and maltose was not changed. In each case incubation with the given substrate caused a specific increase of sensitivity for this substance only. Therefore the adequate genotypical potency of the microoganisms is a prerequisite. The achieved activity is constant during incubation. Moreover, the desired uptake systems as well as metabolic pathways were formed by a de novo protein synthesis. This was concluded from the effect of chloramphenicol, because preincubation in the presence of chloramphenicol did not alter the signal (Riedel et al., 1990a). Furthermore, evalution of the Michaelis-Menten kinetics demonstrates that the apparent KM is not influenced by preincubation (Table 3.4), whereas Vmax increases for all substrates tested and achieves similar values (Riedel et al., 1991). It might be assumed that an identical limiting step exists for all substrates tested: the respiration capacity. 3.2.3.2. Influence of selectivity by elimination of undesired activities

The principle of increase of selectivity by elimination of undesired activities have been used repeatedly. Corcoran and Kobos (1983) achieved the selective determination of arginine with an Streptococcus faecium sensor by treatment with sodium azide, which eliminated the reaction of sensor to glutamine and asparagine. A Streptococcus faecium sensor also allows the sensitive determination of pyruvate, because the Table 3.4. Alteration of the Michaelis-Menten apparent KM- and Vmax-values by incubation of a Bacillus subtilis sensor with these substrates (Riedel, 1991). Substrate

app. KM[1/mmol] control

Vmax[nA/mmol]

incubation

control

incubation

Sucrose

1.25

1.25

142

5000

Maltose

2.00

2.00

400

5000

Glycerol

1.25

1.25

1000

5000

interfering reaction of tyrosine decarboxylase is inhibited by thyramine and glycolysis by iodoacetamide (Di Paolantonio and Rechnitz, 1983). Furthermore, the inhibition of undesired metabolic reaction of a B. subtilis biosensor has been used or the determination of glutamic acid (Riedel and Scheller, 1987). In general determination of glutamic acid in the presence of glucose is not possible, because the signal caused by glucose is higher than the signal caused by glutamic acid. The glucose activity can be reduced by inhibition of the glucose uptake system with chloromercuribenzoate (CMB) (Riedel et al., 1988b). CMB is a thiol reagent and irreversibly inhibits the glucose carrier. Additional inhibition of the glucose signal is achieved by reversible inhibition of glycolysis using NaF. An analogous strategy was used by Corcoran and Kobos

(1987) for the elimination of undesired reactions. By treatment of the biosensor consisting of E. coli cells with the enzyme inhibitor 6-diazo-5-oxo-L-norleucin as well as the transport inhibitor gamma-L-glutamylhydrazide, the glutamine response of the cells was strongly reduced. Sometimes the metabolism of the products which should be detected, such as ammonium ions may decrease the sensitivity of the biosensor. By adding isoicotinic acid hydrazide, a competitive inhibitor of transaminases, this process could be selectively eliminated resulting in increased sensitivity (Walters et al., 1980; di Palantonio et al., 1981; Kobos et al., 1979). Inhibitors must be used in relatively low but efficient concentrations achieving partial inhibition, because high concentrations could possibly abolish metabolism. 3.2.3.3. Genetically manipulated species

Microorganisms modified by genetic engineering can be used in biosensor technology in such a manner that they can be utilized for specific tasks in the environmental protection field. For this aim plasmids are constructed containing fusions of regulatory elements with genes encoding products which are easy to detect, for example the lux gene producing a luminescent gene product. Optical biosensors (optrodes) have been developed: • for the determination of benzene a fusion construct is used which contains the TOL plasmid responsible for the degradation of benzene and the gene encoding firefly luciferase which breeds a luminescent E. coli (Ikariyama et al., 1993); • for the determination of naphthalene and salicylate. The bioluminescence reporter bacterium, Pseudomonas fluorescent HK44, carries a transcriptional fusion of the gene nahG derived from the salicylate operon from Pseudomonas fluorescens and the gene casette luxCDABE from Vibrio fischeri (Heitzer et al., 1994); • for the detection of aluminium an E. coli strain is used, which expresses a transcriptional fusion of the genes luxAB of Vibrio harvey (encoding bacterial luciferase) and the genes FliC of E. coli (Guzzo et al., 1992); • for the detection of copper as well as zinc, cadmium, and lead ions with Alcaligenes eutrophus harbouring constructs consisting of the heavy metal resistant gene and the bioluminescence gene (Corbisier et al., 1996). New possibilities are opened by the combination of regulatory genes with structural genes, as demonstrated for example for the determination of Cu2+ with an Saccharomyces cervisiae strain (Lehmann et al., 1997). Plasmids were constructed containing the CUP1 promoter of S. cerevisiae, which is induced by copper ions, fused to the LacZ gene of E. coli. Transformants with these plasmids cannot utilize lactose as a carbon source. The fusion construct is therefore only transcribed and translated in solutions containing Cu2+ ions. When lactose is used as the measuring solution the transformant cells are able to utilize this substance as carbon source only in presence of Cu2+ ions. Therefore changes in oxygen consumption depend on the concentration of Cu2+ ions. These concentrations can be measured by amperometric detection (Figure 3.17).

Figure 3.17. Schematic design of measuring cell and genetically manipulated yeast cell for the detection of Cu2+ ion concentrations. 3.2.3.4. Hybrid sensor

By combination of microorganisms with enzymes it is possible to improve selectivity. Furthermore these combinations enable determinations of polymers, such as starch, proteins and lipids, which cannot be taken up by the microorganisms. For this the microorganisms are combined with hydrolases (Renneberg et al., 1984). Additionally, amperometric hybrid sensors have been developed for the determination of NAD+ on the basis of E. coli and NADase (Riechel and Rechnitz, 1978), urea and creatinine by use a combination of nitrifying bacteria and urease (Kubo et al., 1983) or creatinase (Okada et al, 1982). 3.2.3.5. Combination of various microorganisms

Combination of various species was developed with the aim of achieving a broad substrate spectrum such as for the determination of BOD (see Chap. 4.2.3.2.1.). An other typical example for a biosensor containing a mixed population of species with supplementary specifical metabolic capacity is the biosensor with nitrifiers (König et al., 1997a, b). This sensor, which especially was developed for waste water investigations, contains a mixed culture of Nitrosomonas sp. and Nitrobacter sp. and allows the amperometric determination of ammonia according the following scheme of nitrification:

The oxygen demand by the nitrifying bacteria is therefore a measure for the ammonia concentration in the sample. For this rapid determination method a detection limit for ammonium in the ppb-range was observed. Because this biosensor reacts also to nitrite and urea, it is further suitable for the summary quantitation of nitrifiable N-compounds, the so-called N-BOD (Wagner, 1990; Deai et al., 1991). This parameter can be useful for waste water control. Furthermore, it is possible to estimate compounds, which are inhibitors of nitrification. When starting such investigations the sensor is principally exposed to a surplus of substrate (ammonium or urea). The basic current becomes stable at a low level, because under these conditions the oxygen consumption by the immobilisate increases to the maximum rate, and therefore the oxygen molecules diffuse through the bacterial immobilisate in relatively small amounts. The addition of an inhibitor leads to a rapidly decreased bacterial oxygen consumption. By this time the oxygen diffusion to the probe again takes place normally and becomes noticeable in the increasing currents registered by the Clark electrode until the new steady-state is reached (Figure 3.18). Performing investigations with waste water-relevant inhibitors and nitrification-inhibiting waste waters, for the relation between the inhibitor concentration and the sensor signal a sigmoidal function was found, as usual for toxicological investigations. This is shown in Figure 3.19, when allyl thiourea was used as the nitrification

Figure 3.18. Principle of nitrification inhibition with a microbial sensor containing nitrifiers.

inhibiting agent. A complete concentration series of an inhibitor for quantitation of its inhibitory effect could be recorded within one day, if the inhibitor was a reversible agent. This is a very short time compared with the time required for other tests for measuring the inhibition of nitrification. Finally, the biosensor for nitrifiers also was integrated in a field testing plant for online-monitoring of the sewerage system for nitrification inhibiting effects directly in the waste water stream (König et al., 1997b). 3.2.3.6. Exclusion of undesired substrates by dialysis membranes

An elegant possibility to improve the selectivity of microbial sensors offers the exclusion of undesired substrates by specific membranes. If the microbial sensor was

Figure 3.19. Influence of concentration of allyl thiourea on the signal of a nitrification sensor (König et al., 1997b). covered with a gas-permeable membrane instead of a dialysis membrane, only volatile compounds can penetrate through the membrane and the permeation of nonvolatile components such as carbohydrates, amino acids and ions was hindered. Such microbial sensors were used for the determination of alcohol with Trichosporon brassicae (Karube et al., 1980) and ammonia with nitrifying bacteria (Karube et al., 1981).

3.2.4. GENERAL CONSIDERATIONS OF APPLICATION

Many kinds of microbial biosensor have been developed and described for environmental monitoring. Table 3.5 gives an overview of these biosensors. The determination of complex parameters such as BOD (see 4.2.1.) and toxicity are major application fields of microbial sensors in environmental control because of their multireceptor behaviour. On the other hand is this behaviour a disadvantage for the determination of individual analytes. However, modification of microorganisms by use of genetic engineering as well as biochemical and physiological knowledges should enable an improvement of selectivity and too of sensitivity and stability. Microbial sensors will be of practical relevance in the near future and promise to be of great importance for the sensitive detection of compounds of environmental significance. Table 3.5. Microbial sensors for determination of compounds of environmental relevance (an overview). Analyte

Microorganisms

Transducer

Detection limit [mg/l]

Response time [min]

References

Ammonium ions

Nitrosomonas europaea

amp. Oxygen sensor

0.04

8

Hikuma et al., 1980

Bacillus subtilis

amp. Oxygen sensor

0.2

0.1

Riedel et al., 1990b

Ammonia

nitrifying bacteria

amp. Oxygen sensor

0.09

4

Karube et al., 1981

Nitrate

Azotobacter vinielandii

pot. Ammonium sens.

0.6

7

Kobos et al., 1979

Nitrite

Nitrobacter sp.

amp. Oxygen sensor

2.3

10

Karube et al., 1982

Urea

nitrifying bacteria +urease

amp. Oxygen sensor

125

7

Okada et al., 1982

Proteus vulgaris

pot. Ammonium sens.

0.04

Sulfur dioxide

Thiobacillus thiooxydans

pot. pHelectrode

5

20

Nakamura et al., 1993

Sulfide

Thiobacillus thiooxydans

pot. pHelectrode

1

20

Kurosawa et al., 1994

Sulfite

Thiobacillus thiooxydans

amp. Oxygen sensor

0.3

Ihn et al., 1988

Suzuki et al., 1992

Sulfate

Desulfovibrio desulfuricum

pot. Sulfide sensor

3.8

8–15

Kobos, 1986

Phosphate

Chlorella vulgaris

amp. Oxygen sensor

72

1

Matsunaga et al., 1984

Fe (II)/

Thiobacillus

amp. Oxygen

3

0.5–5

Mandl and

Fe (III)

ferrooxydans

sensor

Macholan, 1990

Cu (II)

E. coli recombinante

Optrode

0.06

Holmes et al., 1993

Hg (II)

E. coli recombinante

Optrode

0.002

Holmes et al., 1993

Al (III)

E. coli recombinante

Optrode

0.001

Guzzo et al., 1992

Phenol

Trichosporon cutaneum

amp. Oxygen sensor

2

0.25

(beigelii)

Neujahr et al., 1979 Riedel et al., 1995

Rhodococus P1

amp. Oxygen sensor

2

0.25

Riedel et al., 1991a

Rhodotorula spec.

amp. Oxygen sensor

1

0.2

Ciucu et al., 1991

Page 101 Analyte

Microorganisms

Chlorophenols

amp. Oxygen 0.3 Trichosporon cutaneum (beigelii) sensor

0.25

Riedel et al., 1995

Rhodococus P1

amp. Oxygen 2 sensor

0.25

Riedel et al., 1993

Rhodococus P1

amp. Oxygen 2.8 sensor

0.25

Riedel et al., 1993

Pseudomonas putida

amp. Oxygen 0.5 sensor

0.25

Riedel et al., 1991b

Chlorobenzoate

Pseudomonas putida

amp. Oxygen 7 sensor

0.25

Riedel et al., 1991b

Biphenyl

Alcaligenes eutrophus

amp. Oxygen >100 sensor

0.25

BeyersdorfRadeck et al., 1991, 1993

PCB

Pseudomonas

amp. Oxygen >100

0.25

Beyersdorf-

Benzoate

Transducer

Detection Response References limit [mg/l] time [min]

putida

sensor

2,4-D

Alcaligenes eutrophus

amp. Oxygen 40 sensor

0.25

BeyersdorfRadeck et al., 1991

Benzene

Pseudomonas putida

amp. Oxygen 5 sensor

2–10

Tan et al., 1994

E. coli recombinante

Optrode

1

Pseudomonas fluorescence

Optrode

1.5

Naphthaline

Radeck et al., 1992, 1993, 1998

8–15

Heitzer et al., 1994

amp. Oxygen 0.1 sensor

2

König et al., 1996

10

Matsunaga et al., 1980

1–2

Okada et al., 1981

Formic acid

Pseudomonas oxalalitus

pot. CO2 sensor

Methane

Methylomonas flagellata

amp. Oxygen 0.4 sensor

Dichloromethane Hyphomicrobium spec.

Ikariyama et al., 1993

Thermistor

5

0.008

Nitrilotriacetic acid

Pseudomonas spec. pot. Ammonium sens.

Cyanide

Pseudomonas fluorescence

Surfactants

not defined bacteria amp. Oxygen 2 sensor

Henrysson et al., 1993

90

5

Kobos and Pyon, 1981

amp. Oxygen 0.1 sensor

2

Lee and Karube, 1995 Nomura et al., 1994

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3.3. IMMUNOASSAYS

BERTOLD HOCK 3.3.1. ANTIBODY STRUCTURE

Antibodies (=immunoglobulins, Ig) are multifunctional binding proteins. They are produced by the immune system of vertebrates and form an essential part of the defense reactions. Antibodies (abs) are responsible for specific recognition of pathogens, toxins and xenobiotics. The huge repertoire of abs covers practically any ligand. High molecular mass ligands function as antigens, low molecular ones as haptens. Any foreign substance, which induces specific ab synthesis after its injection into the body, is an antigen (antibody generator). Antigens are principally macromolecules, e.g. proteins, polysaccharides or nucleic acids. Even synthetic polymers can serve as antigens. The part of an antigen, which binds an ab, is called an antigenic determinant or epitope. An antigen usually displays several different epitopes. The protective function of abs is related to their ability to form specific antigen-ab complexes, which subsequently activate defined effector mechanisms of the immunosystem, followed by neutralisation, destruction and elimination of antigens. The basic structural unit of all abs is the same, independent of their specificity and class. Each basic unit consists of four polypeptide chains, which belong to two different types. Two identical heavy chains (H) and two identical light chains (L) are joined to an immunoglobulin monomer. Figure 3.20 shows the domain structure of an ab of the IgG class, which is usually applied for immunochemical methods. The two symmetrical halves of the molecule are held together by two disulfide bridges between the H chains as well as by noncovalent bonds. Each of the two halves consists of a H and L chain, which again are joined together by a disulfide bridge and by noncovalent interactions. Each chain is subdivided into domains of ca. 110 amino acid residues and displays the same structural motif, the immunoglobulin fold. Each domain contains two highly conserved cystein residues, which form an intradomain disulfide bridge. Abs of the IgG class consist of two domains per L chain and four domains per H chain.

Figure 3.20. Domain structure of the IgG molecule with the flexibilities of the Fab and Fc region. After Clark (1994). •—• Disulfide bridges.

The antigen binding sites are formed by pairs of VL and VH domains. These variable (V) regions display a considerable diversity in a natural ab population whereas the other regions of the chains are relatively constant. H and L chains are therefore divided in two different regions, the variable (V) region, which is responsible for antigen binding, and the constant (C) region, which enables secondary biological functions such as complement binding and macrophage binding. Distinct sequences within the variable regions are characterized by a remarkable diversity, the three hypervariable regions (complementary-determining regions, CDRs), found on each chain and embedded between four frame regions. Immunoglobulin monomers can be digested by proteases into ab fragments. Three fragments are obtained by papain. Two of them are identical Fab fragments (Fragments with antigen binding sites) and consist of the entire L chain and the H chain fragment with the domain .A third fragment does not have an antigen binding site. But it can be crystallized because of its homogeneity in contrast to the Fab fragment. The Fc part has binding sites for the bacterial proteins Protein A and Protein G. This can be used for purifying abs, but also for uniform alignment, e.g. on immunosensor surfaces. Abs can be grouped according to the structure of their H chains into different classes (Table 3.6) and subclasses. In addition, there are two types of L chains, κ (kappa) and λ (lambda), independent from division into classes and subclasses. It is Table 3.6. Properties of the most relevant human immunoglobulins. Property

IgG

IgM

IgA

IgD

IgE

Molecular mass

150,000

900,000

160,000 (and dimer)

185,000

200,000

Number of immunglobulin monomers

1

5

1 (2)

1

1

Heavy chains

γ

µ

α

δ

ε

Light chains

κ and λ

κ and λ

κ and λ

κ and λ

κ and λ

Number of antibody binding sites

2

5

2 (4)

2

2

Average serum concentration 8–16 mg/ml

0.5–2 mg/ml

1.4–4 mg/ml

0–0.4 mg/ml

17–450 ng/ml

Carbohydrate (in %)

12

8

13

12

3

possible to produce abs against already existing abs, e.g. anti-rabbit abs from goat, anti-mouse IgG from rabbit etc. In this case species- or class-specific epitopes serve as antigens. They are usually located on the Fc part. Such anti-abs or anti-Ig are of great importance for the detection and alignment of abs. For more details, the reader is referred to text books of immunology, e.g. Klein (1991); Roitt (1991); Austyn and Wood (1993). 3.3.2. POLYCLONAL ANTIBODIES

Abs are produced and secreted by vertebrate plasma cells, found especially in secondary lymphoid tissues such as spleen, lymph nodes and tonsils. Although each plasma cell produces only a single type of abs of the same affinity and selectivity, vertebrates have a huge genetic repertoire of 108 to 1010 different abs. If an immune response is triggered by the presence of an antigen, the precursors of plasma cells, the B lymphocytes, are activated. Since an enormous amount of different B lymphocytes circulate between blood and lymphatic organs, chances are high for a contacting the antigen. Foreign antigens are recognized by specific membrane-bound receptors on the surface of B lymphocytes. These antigen receptors are related to the subsequently secreted abs with respect to their structure and their specificity. The antigen receptors of a B lymphocyte only recognize a single epitope of an antigen. The activation of a B lymphocyte is a highly complex sequence, involving additional factors as well as T lymphocytes. Optimal immunization schedules are available for strong immune responses with high ab titers (Huber and Hock, 1986). The time periods required for polyclonal antibody (pab) production are normally at least two or three months depending on the immunogenicity of the antigen. An important practical aspect of B cell activation is the impossibility of low molecular weight substances such as pesticides and endocrine substances to trigger ab production. The first step in the signal transduction chain involves cross-linking of membrane-bound receptors by multivalent antigens, aggregation and endocytosis. Since low molecular weight substances do not expose several epitopes, cross-linking by surface receptors can not take place and ab production is prevented. However, this shortcoming of ab production can be circumvented: if low molecular substances are coupled to a suitable antigen, the immunogen, the former ones are recognized by the B lymphocytes as antigenic determinants. Consequently, there are also abs being produced against these determinants during the immune response. Some of these abs may bind to the free low molecular substances, which are then called haptens. Figure 3.21 shows a few possibilities of immunoconjugate synthesis if abs are to be produced against PCP, TCDD, and estradiol. The strategy of hapten derivatization for immunoconjugate synthesis and coupling essentially determines the properties of the produced abs. Before 1975 immunochemical methods were exclusively based on pabs. They are raised by immunizing vertebrates, usually mammals (such as rabbits, sheep or goat) or birds (chicken), and prepared from the blood or the eggs, respectively. Although each B cell and its descendants (a clone of plasma cells) produces only a single type of abs, the injection of an antigen into an

organism triggers the production of different ab species that are directed against different antigenic determinants on the immuno-

Figure 3.21. Immunoconjugate synthesis for antibody production against TCDD, PCP and estradiol. Suitable hapten derivatives are coupled to bovine serum albumin (BSA). conjugate. The expression “polyclonal” points to the fact that these abs are derived from a multitude of plasma cells and therefore represent a heterogeneous mixture of abs. Among this heterogeneous population of abs there are selective ones that may be directed against different antigenic determinants on the antigen. The other abs originate from earlier contacts with other foreign antigens present in the organism. This has to be kept in mind if pabs are used for immunoassay development or immunosensing. It may be more critical for medical applications, e.g. identification and quantification of viruses, than for the environmental field. Antiserum production is relatively simple. Rabbits for instance require usually four to five immunizations, the first three in weekly periods and later, if required, within longer intervals. The first blood drawing can take place approximately six weeks after starting immunization. Up to 30 ml blood can be drawn from the ear vein per session and c. 15ml antiserum can be obtained after blood clotting and centrifugation of the supernatant. Depending on the ab concentration (=titer) the antiserum can be diluted at least 1:10,000 to 1:50,000. Since a microwell plate with 96 cavities requires ca. 30ml ab solution, a single blood drawing is sufficient for coating between 5,000 and 25,000 microwell plates. In spite of these impressive numbers it should not be

overlooked that each antiserum is unique because of its polyclonality and can even change for the same animal if different blood samples are compaired. 3.3.3. MONOCLONAL ANTIBODIES

The efforts to produce abs with uniform properties, e.g. for standardized assays, were only successful when a strategy was found to immortalize B lymphocytes, which can be kept alive at most for 10–14 days, but do not undergo cell divisions. This has been achieved by Köhler and Milstein (1975). They fused B lymphocytes producing abs against red blood cells of sheep with suitable myeloma cells, cancerous cells of the immune system. Selected hybrid cells, the hybridomas, developed abs with uniform affinity and specifities against red blood cells of sheep. In 1984 Georges J.F.Köhler and César Milstein together with Niels K.Jerne received the Nobel prize for medicine for their pioneering work. Table 3.7 summarizes and compares the properties of pabs and mabs. The production of mabs by the hybridoma technology (Figure 3.22) involves five basic steps, immunization of mice or rats (recently also rabbits), fusion of their spleen cells with myeloma cells, HAT selection, screening and cloning. It is followed by mass production of mabs. A suitable immunoconjugate is injected into mice, using an appropriate immunization schedule in order to obtain enough B lymphocytes, which secrete abs directed against the required antigenic determinant. Then the B lymphocytes are taken from the spleen and fused with myeloma cells in the presence of poly-ethyleneglycol (PEG). A mixture of unfused cells, multiple-fused cells and the Table 3.7. Properties of polyclonal and monoclonal antibodies. Properties

Polyclonal Antibodies

Monoclonal Antibodies

supply

limited and variable

unlimited production possible

uniformity

changing properties with different sera and bleedings

constant properties of a given mAb

affinity

mixture of abs with different affinities

uniformly high or low, can be selected by testing

cross-reactivity occurs as a result of different selectivities and low affinity interactions

depends upon the individual ab

classes and subclasses

one defined isotype

typical spectrum

demands on the high purity required for specific antigen antisera

impure antigens or mixtures of antigen can be used, high purity required for screening

Figure 3.22. Production of monoclonal antibodies. See colour plate 1. desired hybridomas is obtained and seeded into the cavities of microtiter plates. The unfused B lymphocytes and the multiple-fused cells die within a short time. As the unfused myeloma cells grow vigorously in contrast to the hybridomas and tend to overgrow the hybridomas, myeloma cell lines are used, which lack the enzyme HGPRT (hypoxanthine-guanine-phosphoribosyltransferase) in the nucleic acid pathway and therefore cannot survive in a culture medium containing aminopterin. Only the hybridoma cells can survive this selection because in the presence of hypoxanthine and thymidine they use a salvage pathway and therefore complement the genetic defect due to the B lymphocyte genome.

The next step involves screening of the growing hybridoma cell colonies for their ability to produce the desired ab. For this purpose a competitive immunoassay (cf. below) is usually applied. This strategy allows the presence of “positive” hybridoma cells to be detected. But alternatives are now available, e.g. optical sensors applying the SPR technique. This more sophisticated approach provides instant information on the affinity and kinetic constants of the abs and therefore simplifies selection of mabs required for specific purposes such as immunochromatography. Subsequently, it is necessary to isolate and multiply (=clone) single positive cells that are still mixed at this stage with other hybridomas (cf. Figure 3.22). Different methods can be used for the cloning, e.g. limiting dilution. After cloning it is necessary to test the clones to see whether they still produce the desired antibody since not all hybridomas are stable. Then the clones are cultivated in a suitable environment. If a stable cell line is available, it can be expanded to larger volumes. For instance, cultures are conveniently grown in roller bottles with 500mL culture medium and mab concentrations up to 50mg/L are obtained. Larger amounts are raised in fermenters. Plants are reported operating in the gram range. 3.3.4. RECOMBINANT ANTIBODIES

Since it is not possible to alter the properties of existing abs, alternatives are required. The necessity of new immunizations should be circumvented, for instance to obtain mabs with altered cross-reactivities. This is achieved at the DNA level by generating and expressing mutant ab genes. This recombinant technology has considerable consequences. It will bridge the gap between artificial peptide receptors and abs. In addition, gene technology offers the option to express ab genes in bacteria, insect cells, yeast or plants. The basic technology for the production of recombinant antibodies (rabs) was developed in the biochemical and medical field in order to produce humanized abs and circumvent allergic reactions during therapy. Today the main emphasis is still laid upon medical applications including HIV and cancer research. In addition there are first applications in the field of environmental (Karu et al., 1994; Kamps-Holtzapple and Stanker, 1996; Kramer and Hock, 1996). Figure 3.23 shows a generalized scheme for the production of rabs. It permits several options, for instance the production of fusion proteins (e.g. enzyme-coupled abs, abs with tags for affinity purification or directed orientation on a sensor surface) or the generation of rab libraries. A proved strategy takes advantage of the natural diversity of the immune system. In this case mRNA is isolated from spleen lymphocytes. cDNA synthesis is followed by the amplification of desired immunoglobulin sequences, e.g. the variable regions of abs, with the aid of the polymerase chain reaction (PCR) with universal primers. After introducing restriction sites at the 3′ and 5′ end, the PCR amplificates are introduced into a suitable vector, followed by transformation of bacterial cells, usually E. coli. Each individual transformed bacterium contains an ab coding DNA sequence, which is multiplied and transferred by cell division to the descendants. They represent a recombinant bacterial clone.

Since B lymphocytes represent a heterogeneous cell population, the entire repertoire of the ab coding DNA sequences is distributed to different clones, which therefore contain a simple gene library.

Figure 3.23. Production of recombinant antibodies and establishment of an H and L chains, which are linked by a synthetic petide linker. Fab: cf. Figure 3.24, in this case, the CH1 and CL domaines are amplified together with the variable regions by means of suitable primers.

Further diversification and refinement of the ab library can be obtained by (1) chain shuffling. The individual H and L chain fragments can be joined by random combination (Marks et al., 1992). The heterodimers can then be expressed as functional rab. (2) Random variation of the variable regions by error-prone PCR followed by selection of suitable rabs. (3) Randomization of CDRs, followed by selection, or (4) a combination of any of these strategies. The potential size of an rab library exceeds far beyond the number of bacterial clones which can usually be handled and screened. They form a huge repertoire for the selection of new ab properties. It is obvious that evolutionary strategies will contribute to simplify the screening problem. An elegant form of expressing and selecting positive clones represents the phage display system for rabs (Barbas et al., 1994; Winter et al., 1994). Single chain fragments of the variable region (scFv), which are stabilized by covalently bound peptide linkers (cf. Figure 3.24), are expressed as fusion proteins with the p III-coat protein of a M13 phage. In this case the phage particle not only displays the expressed rab fragment, but also carries the genetic information. Screening of large libraries can be carried out by panning, magnetic bead separation or immunochromatography in hapten-coated gels. It is obvious that there is a gradual transition from rabs to synthetic binding peptides, which may finally replace abs in analytics. If comparable stabilities, affinities and selectivities can be obtained with synthetic peptides, it appears to be feasable to replace time-consuming ab production in the laboratory of specialists by the much faster selection of recombinant binding proteins from commercially available peptide libraries by application laboratories. Performance of assays will not be affected by the substitution of abs by binding peptides.

Figure 3.24. Architecture of IgG antibodies and their fragments.

3.3.5. BINDING PROPERTIES OF ANTIBODIES

The interaction between an ab and its ligand is based on spacial complementarity but not on covalent bondings. The forces contributing to the binding are (1) electrostatic forces, they are due to the attraction between oppositely charged ionic groups, for example an ionized amino group on a lysine of one protein and an ionized carboxylic group on the other; (2) hydrogen bonding between hydrophilic group such as—OH,—NH2 and—COOH; (3) hydrophobic forces between non-polar, hydrophobic group such as the side-chains of valine, leucine and phenylalanine, which tend to associate in an aqueous environment; (4) Van der Waals forces, which depend upon the interaction between the external electron clouds of molecules. These intermolecular bonds are all weak physical bonds, which require a short distance between ab and antigen (or hapten) to reach sufficient strength of the binding. The primary reaction is predominantly electrostatic bonding and partly Van der Waals bonding, which takes place within seconds to minutes (Jefferis and Deverill, 1991). The primary bond energy may constitute only a small percentage of the total bond energy. However, secondary bonding occurs over longer time periods and may continue to increase for many hours and even several days. As the ab binding site and the ligand are drawn together, hydrogen bonds may be formed. Strengthening of the bonds decreases reversibility of the binding reaction. This should be kept in mind if antigen (or hapten) binding has to be reversed. This situation occurs in tracer displacement assays as well as in immunoaffinity chromatography. In this case, reversal should take place as early as possible. The affinity of the ab bonding is defined by the difference in free energy (∆G) between the ab and its ligand in the free state on the one hand and in the complexed form on the other. The following equations are given for haptens (H) as ligands. (3.3.1) where R=universal gas constant T=absolute temperature K=affinity constant [M−1] of the reaction ab+H=abH The affinity constant is defined as (3.3.2) where k+1=association constant [M−1 s−1] k−1=dissociation constant [s−1]

[abH]=concentration of bound hapten at the equilibrium point [ab]=concentration of free ab binding sites at the equilibrium point [H]=concentration of free hapten at the equilibrium point The high degree of complementarity can provide strong affinities of abs for their ligand. They usually fall into the range between 105 to 1011 M−1 at a mature immune response. For many analyte systems the association constants are found within a range of 10−7 to 10−8 M−1 s−1. Differences in the affinity are mainly related to differences in the dissociation constants. For practical applications the free hapten concentration is of interest where half of the ab sites are bound [H0.5]. In this case (3.3.3) This means that the affinity constant is equal to the reciprocal of the concentration of free hapten at the equilibrium point where half the ab sites are in the bound form. High affinity constants require only low hapten concentrations for half saturation of abs. Abs of this property enable highly sensitive assays. The term avidity applies to antisera and pabs; it describes the tendency of the ab to bind antigens with several epitopes. The avidity is not only influenced by the heterogeneity of abs in a antiserum and the heterogeneity of the epitopes, but also by the fact that two antigen molecules with different epitopes can be simultaneously be bound by an IgG. It should be noted that avidity is less precisely defined as affinity, which characterizes the strength of binding between a monovalent antigen or hapten and a monovalent ab (antigen binding site). The selectivity of an ab towards a defined ligand is usually not an absolute one. It should be considered a rule rather than an exception that an given ab can also recognize similar ligands although with a lower affinity. As the bonding strength is given by the affinity, selectivity of an ab is the relative affinity towards another substance. Relative affinities are usually displayed by the cross-reactivity pattern of an ab. A skilful design of immunoconjugate synthesis can help to avoid unwanted cross-reactivities. On the other hand, ab arrays can be employed to take advantage of abs with different cross reactivities. Chemometrics combined with neuronal networks are more recent approaches in the field of immunosensors for multianalyte analysis. 3.3.6. IMMUNOASSAYS

Since the introduction of immunoassay technology by Berson and Yalow (1959) and in the more general form of saturation analysis, by Ekins (1960), a vast amount of literature has appeared on theoretical aspects of immunoassays and their practical application in medicine and other fields. The reader is referred to extensive reviews for further details, e.g. Chan and Perlstein (1987); Tijssen (1985); Pal (1988); Kemeny and Challacombe (1988); Butler (1991); Van der Laan et al. (1991); Beier and Stanker (1996); Price and Newman (1991). Since the same principles apply to

immunoassays and immunosensors in terms of binding characteristics, the basic aspect and classification principles are summarized below. The most fundamental criterium for classifying immunoassays depends on the measurement of fractional occupancy of ab binding sites (Ekins, 1991) as the occupancy of ab binding sites by the analyte depends on the analyte concentration in the sample. Analyte binding by the ab does not generate a signal, which can be easily measured. Therefore immunoassays and indirect immunosensors (Chap. 4.1.2.) require a tracer as helper reagent, which allows the estimation of ab occupancy by measuring the tracer signal. Figure 3.25 explains the two alternatives: noncompetitive immunoassays and competitive immunoassays. Non-competitive immunoassays measure directly the occupied binding sites. Maximal sensitivity is obtained with an excess of abs. Signal production is usually provided by tracer abs, for instance enzyme-coupled abs. Competitive immunoassays measure unoccupied ab binding sites. Maximal sensitivity is obtained at minimal ab concentrations. Labelled analytes or labelled abs, respectively, can be used as tracers in different formats (cf. below). In spite of the advantages of non-competitive assays such as lower detection limits, higher robustness and at least in some cases faster performance, they cannot be applied for the analysis of dissolved haptens since non-competitive assays require multivalent antigens as analytes, which display more than one epitope.

Figure 3.25. Comparison of non-competitive (a) and competitive immunoassays (b). See colour plate 2.

3.3.6.1. Heterogeneous and homogeneous immunoassays

Heterogeneous immunoassays are characterized by the requirement for separating the free from the solid phase-bound fraction. Either the bound fraction is used for signal generation, as it is the case for solid phase enzyme immunoassays (EIAs), or the unbound fraction as it is practised with radioimmunoassays (RIAs). In contrast, homogeneous immunoassays do not require any phase separation, i.e. the physical separation of free and ab-bound components. Ab-ligand binding as well as its detection by means of a tracer takes place in a homogeneous solution. The detection principle is based on the fact that the ab does not only bind the tracer but also influences the subsequent reaction of the tracer. One of the numerous possibilities is the interference of the ab with the substrate binding of an enzyme tracer. If the analyte concentration is increased, the tracer is displaced from the ab binding sites and is available for the subsequent enzyme reaction with a conversion of a substrate. The omission of a separation step simplifies the assay compared to the heterogeneous approach. However, interferences by matrix effects play a significant role whereas phase separation in heterogeneous assays also removes a significant part of interfering substances. Therefore heterogeneous immunoassays are much more common than homogeneous assays, for instance they are used in practically all commercial immunoassays as well as immunosensors. However, flow injection systems would benefit from the homogeneous approach although even in this case the heterogeneous variant is normally applied (Chap. 4.1.2.). 3.3.6.2. The heterogeneous competitive immunoassay

The most frequently applied format in the immunoassay and immunosensor field is the heterogeneous competitive immunoassay where the amount of bound tracer is related to the analyte concentration in the sample. As the tracer produces the signal, its strength is inversely related to the analyte concentration. Figure 3.26 summarizes the two possibilities approaches for phase separation, binding of the ab to the solid phase (Figure 3.26a) or binding of a coating conjugate with a hapten-derivative to the solid phase (Figure 3.26b). The variant with the immobilized ab uses a labelled analyte as tracer, the variant with the coating conjugate a labelled ab, which has the function of the tracer and simultaneously the reaction partner during the immune reaction. The terminology of these two variants can cause confusion. Variant b with enzyme-labelled abs is designated as Enzyme-Linked Immunosorbent Assay (ELISA) although this term is now often applied to variant a, too. Moreover variant a is sometimes called direct immunoassay and variant b indirect immunoassay. Since these terms can be confused with the same ones applied in the immunosensor field but with different meanings, they should be avoided. Indirect immunosensors are those which require tracers, whereas direct sensors are label-free procedures. In addition, distinctions are made between direct labelling (use of labelled primary abs) and indirect labelling (use of labelled second abs).

Both variant a and b exhibit an inverse relation between signal height and analyte concentrations. The variant with the immobilized coat conjugate (Figure 3.26b)

Figure 3.26. Variants of the competitive immunoassay. See colour plate 3. is frequently used in immunosensor technology because even the application of unlabelled abs provides measurable signals, e.g. by changes of the mass or the refraction index during the immune reaction. An example is direct immunosensing which does not require labelled abs. The mass increase at the sensor surface due to ab binding is sufficient to generate a signal (Chapts. 2.2 and 4.1.2.). The principle used for instance by a SPR sensor relies on the heterogeneous immunoassay although phase separation is not employed. This is described in more detail in Chapter 2.2.2.3.2.). A more simple alternative with unlabelled first abs is indirect labelling, e.g. with labelled second abs. A common practice is the application of peroxidase-labelled anti-mouse abs from rabbit or

goat, which recognize the Fc part of the primary mouse abs. In this case the labelling is independent from the individual ab applied for the immunoassay.

Figure 3.27. Immunosensor based upon the evanescent field principle. Antibodies with free binding sites bind to an immunoconjugate at the sensor surface increasing its thickness. 3.3.7. DATA PROCESSING AND STATISTICS

Although data processing is automated in immunosensors and therefore hidden from the user, it appears to be helpful to get acquainted with the basics in order to deal with problems arising during measurements of samples. As the immune response shows a non-linear relationship to the analyte concentration, curve fitting procedures must be applied. This subject is treated in detail by Rodgers (1984); Dudley et al. (1985); Raggatt (1991). The basic approaches do not differ between immunoassays and immunosensors. A linearization of calibration curves is of advantage for the direct comparison of different calibration curves, for instance for judging cross-reactivities of matrix effects. This is carried out in two steps: (1) curve fitting and (2) linear transformation. Curve fitting is required for computing the curve from which the unknowns will be calculated. The most frequently applied procedure is based on the logit-log model (Rodbard and Cooper, 1970). The logit function is a continuous sigmoidal function with a single point of inflexion. An appropriate compromise between the quality of curve fitting and cost of calculation can be met by the 4-parameter model. It relates the signal y (e.g. the absorption A) to the concentration of the analyte x (3.3.4)

where a, b, c, d=const.

The constants a and d in equation (4) correspond to the upper and lower asymptotes, respectively, of the curve, c to the analyte concentration at the middle of the test and b to the slope of the curve at the middle of the test. Linearization is carried out by transforming equation 3.3.4: (3.3.5)

If log (

) is equated with Y (logit-log transformation), (3.3.6)

is obtained. Equation 3.3.6 represents a straight line with the slope -b and the segment b • log c on the Y axis if Y is plotted against log (x). A simplified model sets a=1 (or 100%) and d=0 and is therefore called the 2-parameter model. Equation (3.3.4) is simplified to (3.3.7) which can be transformed to (3.3.8) Equation 3.3.8 is a straight line if Y is plotted against log (x). The 2-parameter fit is carried out in two steps. First the response (e.g. absorption) is transformed into % B/B0 values, which represent the occupancy of the ab binding sites by the tracer and therefore represent the ratio (3.3.9)

The %B/B0 values lie in between 100 % (=A0, the upper asymptote of the curve) and 0% (=Aexcess, the lower asymptote). They are calculated according to (3.3.10)

Aexcess is the absorption of a sample with an excess of the analyte, A0 the absorption of the control. 50% B/B0 represents the middle of the test. Here half of the ab binding sites are occupied by the tracer. A linearization is obtained after the logit-log transformation

(3.3.11)

by plotting the logit values against the logarithm of the concentration. 3.3.8. CROSS-REACTIVITIES

The affinity of an ab or a mixture of abs is expressed as cross-reactivity. Therefore crossreactivity determines the extent to which an ab or an antiserum reacts with compounds related to the analyte or, even worse, with entirely different compounds. Cross-reactivity can be due to the existence of a heterogeneous ab mixture as it is usually the case with pabs, where individual ab molecules react with different analytes. But even a homogeneous population of ab, such as mab, does not exclude cross-reactivities because it is an intrinsic property of almost all abs, especially those which are directed against haptens, to bind related compounds, usually with different affinities. Cross reactivity is calculated according to the formula (3.3.12) where A=concentration of the analyte at 50 % B/B0 (=logit 0), C=concentration of the cross reacting compound at 50% B/B0. A selective assay does not show significant cross-reactions, whereas a group-selective assay measures a sum parameter. In this case the affinity of all cross-reacting analytes would be the same. However, these two cases are only extremes of a spectrum of assays with different ab affinities. Sensor arrays are expected to deal with different cross-reactivities by using chemometric approaches and neuronal networks for data analysis. 3.3.9. CONCLUSIONS

Antibodies as highly selective binding proteins are used for a great variety of antigens and haptens. At present time immunoassays are the most widely used analytical procedures in the immunochemical field because many test kits are available that fulfill defined quality requirements. Future applications will make extended use of immunochromatography, immunosensors and flow injection immunoanalysis. Therefore it is essential to extend the selectivities of abs to other analytes, especially in the environmental field. Since the classical procedures of ab production are too slow and cumbersome, recombinant techniques are expected to replace eventually the technologies of polyclonal and monoclonal ab production. The most significant breakthrough is expected from evolutionary strategies that are used to select and subsequently modify abs or fragments from ab libraries.

REFERENCES

Austyn, J.M. and Wood, K.J. (1993) Principles of cellular and molecular immunology. Oxford: Oxford University Press. Barbas III, C.F., Hu, D., Dunlop, N., Sawyer, L., Cababa, D., Hendry, R.M., Nara, P.L. and Burton, D.R. (1994) In vitro evolution of a neutralizing human antibody to HIV-1 to enhance affinity and broaden strain cross reactivity. Proc. Natl. Acad. Sci. USA, 91, 3809–3813. Beier, R.C. and Stanker, L.H. (1996) Immunoassays for residue analysis. Food safety. ACS Symposium Series, 621. Berson, S.A. and Yalow, R.S. (1959) Recent studies on insulin-binding antibodies. Ann. N.Y. Acad. Set., 82, 338–344. Butler, J.E. (1991) Immunochemistry of solid-phase immunoassay. Boca Raton, Ann Arbor, Boston, London: CRC Press. Chan, W.D. and Perlstein, M.T. (eds.) (1987) Immunoassay. A practical guide. Orlando (Florida), London: Academic Press, Inc. Clark, M. (1994) Internet (http://www.path.cam.ac.uk/~mrc7/igs/mikeimages.html). Dudley, R.A., Edwards, P., Ekins, R.P., Finney, D.J., McKenzie, I.G.M., Raab, G.M., Rodbard, D. and Rodgers, R.P.C. (1985) Guidelines for immunoassay data processing. Clin. Chem., 31, 1264–1271. Ekins, R. (1991) Immunoassay design and optimisation. In Principles and practice of immunoassays, Price, C.P. and Newman, D.J. (eds.) pp. 96–153, New York, USA: Stockton Press. Ekins, R.P. (1970) Theoretical aspects of saturation analysis. In In vitro procedures with radioisotopes in medicine. International Atomic Energy Agency. Printed by the IAEA, Wien, Austria. Huber, S.J. and Hock, B. (1986) Atrazine in water. In Methods of enzymatic analysis, Bergmeyer, H.U. (ed.) 12, 3rd edn. Weinheim: VCH Verlagsgesellschaft mbH. Jefferis, R. and Deverill, I. (1991) The antigen antibody reaction. In Principles and practice of immunoassay, Price, C.P. and Newman, D.J. (eds.) New York: Stockton Press. Kamps-Holtzapple, C. and Stanker, L.H. (1995) Development of recombinant single-chain variable portion recognizing potato glycoalkaloids. In Immunoassays for residue analysis. Food Safety, 209th ACS Meeting and Exposition, Beier, R.C. and Stanker, L.H. (eds.) pp. 485–499. California: Anaheim.

Karu, A.E., Scholthof, K.-B.G., Zhang, G. and Bell, C.W. (1994) Recombinant antibodies to small analytes and prospects for deriving them from synthetic combinatorial libraries. Food and Agricult. Immunol., 6, 277–286. Kemeny, D.M. and Challacombe, S.J. (1988) ELISA and other solid phase immunoassays. Theoretical and practical aspects. Chichester, New York, Brisbane, Toronto, Singapore: John Wiley & Sons. Klein, J. (1991) Immunologie. Weinheim: VCH Verlagsgesellschaft mbH. Köhler, G. and Milstein, C. (1975) Continuous cultures of fused cells secreting antibody of defined specificity. Nature, 256, 495–497. Kramer, K. and Hock, B. (1996) Recombinant single-chain antibodies against s-triazines. Food and Agricultural Immunology, 2, 97–109. Marks, J.D., Griffiths, A.D., Malmqvist, M., Clackson, T.P., Bye, J.M. and Winter, G. (1992) By-passing immunization: building high affinity human antibodies by chain shuffling. Bio/Technol., 10, 779–783. Price, C.P. and Newman, D.J. (1991) Principles and practice of immunoassays. New York, USA: Stockton Press. Raggatt, P. (1991) Data processing. In Principles and practice of immunoassays, Price, C.P. and Newman, D.J. (eds.) pp. 190–218, New York, USA: Stockton Press. Rodbard, D. and Cooper, J.A. (1970) A model for the prediction of confidence limits in radioimmunoassay and competitive protein binding assays. In In vitro procedures with radioisotopes in medicine. International Atomic Energy Agency, Vienna, 659–673. Rodgers, R.P.C. (1984) Data analysis and quality control of assays: A practical primer. In Clinical Immunoassay: The State of the Art, Butt, W.R. (ed.) New York: Marcel Dekker. Roitt, I. (1991) Essential immunology. 7th edn, London: Blackwell Scientific Publications. Tijssen, P. (1985) Practise and theory of enzyme immunoassays. In Laboratory techniques in biochemistry and molecular biology, Bordon, R.H. and van Knippenberg, P.H. (eds.) 15, p. 549. Amsterdam, New York: Elsevier. Van der Laan, M., Stanker, L.H., Watkins, B.E. and Roberts, D.W. (1991) Immunoassays for trace chemical analysis. Monitoring toxic chemicals in humans, food and the environment. ACS Symposium Series, 451. Winter, G., Griffiths, A.D., Hawkins, R.E. and Hoogenboom, H.R. (1994) Making antibodies by phage display technology. Annual Rev. Immunol., 12, 433–455.

3.4. DNA BASED BIOSENSORS

JOSEPH WANG 3.4.1. INTRODUCTION

The aim of the present chapter is to review new strategies for environmental monitoring based on DNA biosensors. The use of DNA as a selective recognition layer in biosensor design represents a new and exciting area in analytical chemistry. Unlike enzyme or antibodies, nucleic acid recognition layers are very stable, and can be readily synthesized for repeated use. Such recognition layers add new and unique dimensions to our arsenal of environmental biosensors, and should play a major role in future environmental analysis. Various strategies for environmental DNA biosensors will be examined in the following sections, including hybridization detection of nucleic acid from infectious microorganisms, as well as monitoring of small pollutants interacting with the immobilized DNA layer. While the field of DNA biosensors is still in infancy, there is no doubt that such devices will play a major role in future environmental analysis. 3.4.2. DNA STRUCTURE

DNA (deoxyribonucleic acid) is a very long molecule comprising of two very long strands wrapped around each other to form a helix. Each strand is comprised of a large number of monomeric units known as nucleotides (Figure 3.28). An individual nucleotide consists of three parts—a nitrogen-containing heterocyclic base, a sugar and a phosphoric acid residue—all of which are covalently bonded together. The order of the bases specifies the genetic code, while the phosphate and sugar groups have only a structural role. Among the four bases, two (adenine (A) and thymine (T)) are pyrimidines, while the other two (guanine (G) and cytosine)) are purines. The two strands are connected through hydrogen bonding. Only certain pairs of bases form these bonds (Figure 3.29); G always pairs with C (with 3 such bonds) and T always pairs with A (via 2 hydrogen bonds). Such paired DNA strands are said to be complementary. Knowledge of the nucleobase order in one strand is sufficient for defining the primary sequence of the other.

Figure 3.28. DNA structure: the double helix (top) along with the chemical composition of one of the strands (bottom). When DNA is denaturated, the double helix structure is broken down and the two complementary strands separate. Usually heat is needed to break the hydrogen bonds between the bases and disrupt the stacking interactions. Such heat denaturation of DNA is called melting. The binding of two complementary DNA strands together (reassociation of the hydrogen bonding) to reform the double helix is called hybridization. A complete turn of the helix spans ten base pairs, covering a distance

Figure 3.29. The structure of Watson-Crick base pairs. of 3.4 nm. The overall structure creates two distinct helical grooves, a minor one and a major one, which spiral around the surface of the duplex. The grooves create unique microenvironments for the binding of various molecules. The recognition of various pollutants by an immobilized DNA layer often relies on their binding within these grooves or by their intercalation between the base pairs of the double helix. Similar intercalative association has been used also for incorporating a (redox or optical) marker within DNA duplexes in connection with the detection of DNA hybridization. Intercalation is the insertion of a molecule (or its planar part) between two stacked base pairs (Figure 3.30). While it is not affecting the primary or secondary structures of DNA, it induces a partial lengthening (unwinding) of the helix. 3.4.3. SEQUENCE SPECIFIC HYBRIDIZATION BIOSENSORS

Detection of individual DNA sequences provides the basis for detecting a wide variety of microbial and viral pathogens. The basis for such DNA biosensing of specific DNA fragments is base pairing. Namely, such devices rely on the immob-

Figure 3.30. Intercalation association of a small molecule within the DNA. ilization of a single-stranded DNA sequence (the “probe”) on a transducer surface, which upon hybridization to its complementary strand (the “target”) gives rise to an electrical signal (Figure 3.31). The probes are typically short sequences (15–40 mer) that are capable of hybridizing with specific and unique regions of the target

Figure 3.31. Steps in sequence-specific biosensing of DNA hybridization.

Figure 3.32. Top: idealized signal development during the different steps of the hybridization biosensing cycle. Bottom: two assay cycles, in which the regeneration was performed thermally or chemically. (From Abel et al., 1996, with permission.) nucleotide sequence. The inherent specificity of these DNA recognition reactions has been coupled with the high sensitivity of piezoelectric (Okahata, 1992), electrochemical (Mikkelsen, 1996) and optical (Piunno et al., 1995) transducers. Proper surface immobilization is essential to assure high reactivity, accessibility and stability of the surface-bound probe, as well as for minimizing non-specific binding/adsorption events. Several probe immobilization schemes can be employed, depending often on the nature of the physical transducer. These include self-assembly of organized monolayers of thiol functionalized probes, carbodiimide covalent binding to an activated surface, attachment of biotinfunctionalized probes to avidin-coated surfaces, as well as adsorptive accumulation. The performance of such DNA biosensors depends on experimental variables affecting the hybridization event. These include the temperature, salt concentration, presence of accelerating/condensing agents, viscosity, contacting time, base composition (% G+C), and length of probe sequence. Careful control of the hybridization event is thus required. The

stability of duplexes formed between strands with mismatched bases is decreased according to the number and location of the mismatches. Recent studies have demonstrated that significantly enhanced selectivity can be achieved by the use of peptide nucleic acid (PNA) probes (Wang et al., 1996a). PNA is a structural DNA analog, with an uncharged pseudopeptide backbone (instead of the charged phosphate-sugar one). Because of their neutral backbone, PNA probes offer greater affinity in binding to complementary DNA, and improved distinction between closely related sequences. Such mismatch discrimination is of particular importance in the detection of disease-related mutations, in connection to genetic screening and therapy. Attention should be given also to the reusability of the DNA biosensors (i.e. to the regeneration of the surface-bound single-stranded probe after each assay). Both thermal and chemical (urea, sodium hydroxide) regeneration schemes have been shown useful for “removing” the bound target in connection with different DNA biosensor formats. Figure 3.32(bottom) illustrates two assays cycles, in which the regeneration is performed by either thermal or chemical regeneration. The top figure displays the idealized development of the signal during the various steps of the biosensor operation. Depending on the hybridization time, DNA biosensors commonly offer detection limits at the picomolar to nanomolar concentration range. Such levels are not low enough to allow most relevant environmental assays without PCR amplification. Miniaturized, silicon-based PCR units, developed in recent years, may be readily integrated with the new DNA biosensors for facilitating on-site environmental analysis. By further optimizing the probe immobilization, hybridization step, and detection process, DNA biosensors would allow direct detection without the need for a separate amplification step. 3.4.3.1. Electrochemical DNA biosensors

Several recent studies (Millan and Mikkelson, 1993; Wang et al., 1996b) demonstrated the utility of electroactive indicators for detection the hybridization between the surface-confined probe and its target sequence. Such indicator is a small redoxactive DNA intercalating or groove binding substance. Such compound has a much higher affinity for the resulting duplex compared to the single-stranded probe. Accordingly, the concentration of the indicator at the electrode surface increases when hybridization occurs, resulting in increased electrochemical response. For example, Figure 3.33 displays signals for 1 mg/1 of the pathogenic protozoan Cryptosporidium target DNA following different hybridization times (a–f, 1–7 min). Dashed and solid lines are the indicator (Co(phen) ) peaks at the Cryptosporidium-probe coated carbon-paste electrode in the absence and presence of the Cryptosporidium target, respectively. The difference between these peaks thus serves as the hybridization signal. A similar principle has been employed for the detection of DNA fragments from the Escherichia Coli pathogen at disposable carbon strip electrodes (Wang et al., 1997b). As desired for on-site environmental analysis, the operation of these screen-printed devices can

Figure 3.33. Chronopotentiograms for 1 mg/l of the Cryptosporidium DNA target, following different hybridization times(1(a), 2(b), 3(c), 4(d), 5(e) and 7(f) min (From Wang et al., 1997a, with permission). be readily integrated with hand-held analyzers. Both linear-scan or square-wave voltammetric modes (Millan and Mikkelsen, 1993) or constant-current chronopotentiometry (Wang et al., 1996b) can be used to detect the association of the redox indicator with the surface duplex. In addition to carbon paste or strip electrodes, such electrochemical scheme has been carried out in connection to gold and glassy-carbon electrodes. This strategy has been shown useful for the detection of common mutations, associated with diseases such as cancer (Wang et al., 1997c) or cystic fibrosis (Millan et al, 1994). Sequence specific electrochemical biosensors based on other detection strategies have been developed recently. These include electrochemical measurements of the solvent accessibility of nucleobases using electron transfer between DNA and metal complexes (Lumely-Woodyear et al., 1996), and the use of enzyme amplification in connection with an enzyme-intercalant conjugate (Kolakowski et al., 1996) or through proper electrical wiring of the enzyme (Johnston et al., 1995). 3.4.3.2. Optical DNA biosensors

Fiber optic transducers have been used successfully for the detection of DNA hybridization (Piunno et al., 1995; Abel et al., 1996). In a manner analogous to electrochemical hybridization biosensors, such devices commonly rely on the use of fluorescent indicators or labels for detecting the duplex formation. In the first study, the ssDNA probe was immobilized onto a quartz optical fiber activated with a long-chain aliphatic spacer arm. The covalently immobilized oligomers were found to hybridize to complementary ssDNA or ssRNA. The duplex formation at the fiber surface was monitored with the aid of an ethidium-cation fluorescent intercalating agent. The attractive features of this optical sensor include a low detection limit (of 86 ng/ml), reusability (at least 5 cycles) and high storage stability. The device of Abel et al. offered even lower detection limits down to 24 fmol (2×10−13 M) and an efficient chemical regeneration for multiple use (Figure 3.32).

Several hundreds assay cycles were thus performed with the same optical fiber. A biotinylated capture probe was immobilized onto the surface (via avidin), and a fluorescein-labeled complementary strand was used for the evanescent wave fluorescent detection of the hybridization event. The biotin-avidin interaction was used also in connection with a reusable DNA optical biosensor, based on real-rime resonant mirror detection of the duplex formation (Watts et al., 1995). High density DNA chips, described below, also rely on optical transduction of hybridization events. 3.4.3.3. Mass-based DNA biosensors

Mass-sensitive devices, particularly quartz crystal microbalance (QCM), have been used successfully for transducing hybridization events (Okahata et al., 1992). The QCM is a goldplated oscillating quartz crystal device suitable for measuring weight changes on the surface. When placed in an electronic oscillator circuit, an oscillating electrical field is applied to the crystal, resulting in an oscillating mechanical vibration. The fundamental principle of QCMDNA biosensors involves the frequency change (∆f) due to the mass increase on the QCM associated with the duplex formation: (1) where f0 is the resonant basic frequency, ∆m is the weight change on the surface of the crystal, and A is the coated area. Equation 1 is known as the Sauberbrey equation. The decreased resonant frequency upon the increase of mass on the QCM can thus be used for monitoring molecular binding processes. Such piezoelectric transduction mode offers direct in-situ detection of hybridization event, without any (redox or optical) indicator or label, and allows measurements of minutes mass changes (as low 10−12 g). Nonspecific adsorption effects can be addressed using a reference (uncoated) crystal. Additional mass-sensitive transducers, including surface-acoustic wave (SAW) or thickness-shear mode (TSM) devices, have also been used for the detection of hybridization reactions. 3.4.3.4. High-density DNA chips

The discriminative power of nucleic acid hybridization tests can be dramatically enhanced by using more than one oligonucleotide probe. Recent advances in photolitography and combinatorial chemical synthesis have led to the development of high-throughput “DNA chips” (Borman, 1996; Noble, 1995). The high precision and resolution of such thin-film microfabrication technology allows for the generation of high density arrays of immobilized probes (in the range of 105–106 probes per cm2). Using these microfabricated surfaces, multiple sequences can be assayed in a single experiment. Different fragments from the organism, or several microorganisms may thus be determined simultaneously. The multiple hybridization events are commonly detected optically (using fluorescent tags) to produce a readable pattern, based on quantifying the label in each site. The fluorescent intensity data, captured from the scanner, are used with computer files to provide DNA profiling of the test sample. These chips,

pioneered by Affymetrix Inc (Santa Clara, CA), will eventually be incorporated into micromachined analyzers that will integrate the sample handling and amplification step with the detection process. DNA biosensor arrays have been developed also in connection with a bundle of optical fibers, with each fiber carrying a different oligonucleotide probe (Ferguson et al., 1996). Hybridization of fluorescently labeled complementary strands was accomplished by observing the increase in fluorescence that accompanied the binding event. This resulted in a fast (<10min) and sensitive (10 nM) detection of multiple DNA sequences. 3.4.4. DETECTION OF SMALL ANALYTES INTERACTING WITH DNA

Environmental monitoring can benefit from DNA recognition modes other than base-pairing hybridization events. In particular, various interactions of an immobilized double-stranded layer with low molecular weight pollutants can be used for detecting these substances. Since the toxic action of numerous pollutants is related to their interaction with DNA, it is logical to exploit these events for designing new environmental biosensors. Different modes of signal transduction have been used for the detecting of toxic pollutants interacting with the surface-confined nucleic acid layer. These include the detection of analytes based on the displacement of an optical marker from the immobilized dsDNA, electrochemical measurement of electroactive compounds accumulated into the surface-bound DNA, and changes in the intrinsic electrochemical response of the DNA-coated electrode induced by the DNA-pollutant binding event. The intercalative association of aromatic compounds with an immobilized dsDNA layer has been used for designing an evanescent wave optical biosensor for their detection (Pandey and Weetall, 1995). The decreased flow injection response of the ethidium bromide fluorescent marker, associated with its competition and displacement by the target aromatic amine analyte, served as a measure of the pollutant, based on the “intercalative binding strength” (Figure 3.34). The dsDNA was immobilized over the fiber-optic surface using acrylamide-methacrylamidehydrazides prepolymer. Affinity electrochemical biosensors for redox active aromatic compounds have also been developed (Wang et al., 1996c). For example, the “collection” of aromatic amines by the surface-confined dsDNA layer can serve as an effective preconcentration step, in a manner analogous to electrochemical stripping protocols. Chrono-potentiometry has been used for detecting the accumulated aromatic compounds. The enhanced sensitivity thus obtained has been coupled to new dimensions of selectivity provided by the structural requirements for such accumulation. Highly sensitive electrochemical techniques, particularly stripping chronopotentiometry, result in a well-defined anodic signal for DNA, associated with the oxidation of the guanine moiety (Wang et al., 1996d). Ultratrace levels of various nucleic acids have thus been detected (down to 10−16 mol). The ability to use solid electrodes, included screen-printed carbon ones, for

measuring the DNA-guanine signal has opened the door to a new class of solid-state environmental sensors.

Figure 3.34. Typical response of the evanescent fluorobiosensor on injection of 9,10anthraquinone (1, 80 ppm; 2, 18 ppm) at the steady-state response of ethidium bromide (4ppb) in phosphate buffer. (From Pandey and Weetall, 1995; with permission). Changes in the intrinsic guanine signal of DNA modified electrodes (associated with chemical, conformational or structural variations of the immobilized probe), have thus been exploited for environmental monitoring. For example, the decreased guanine signal upon exposure to ultraviolet radiation has been used for detecting radiation-induced DNA damage (Wang et al., 1997d) or trace levels of hydrazine compounds (Wang et al., 1996e). In the latter case, the suppression of the guanine response has been attributed to the formation of electroinactive methylguanine. Nucleic acid modified mercury drop electrodes have also shown very useful for studying the interaction of DNA with damaging agents and detecting minor changes (e.g., strand interruptions) in the DNA double helix (Palecek, 1996); however, such use of mercury electrodes is less suitable for routine on-site environmental analysis. 3.4.5. CONCLUSIONS

DNA biosensors, now in their infancy, are expected to rapidly rise in popularity in the near future. Accordingly, DNA sensor technology is an area that generates a lot of enthusiasm. Such DNA-based devices add new dimension of selectivity—based on nucleic acid recognition—to the arsenal of biosensors proposed for environmental analysis. Various possibilities of using such devices have been discussed in the previous sections, with special attention given to sequencespecific hybridization detection of viral or bacterial pathogens and to the low molecular weight pollutants interacting with the surface-confined DNA. Besides their sensing utility, such nucleicacid coated transducers serve as useful models for studies of pollutant-DNA interactions. Ongoing commercialization efforts should lead to the translation of these and future research efforts into large scale environmental applications.

REFERENCES

Abel, A., Weller, M., Duveneck, G., Ehrat, M. and Widmer, M. (1996) Fiber-Optic Evanescent Wave Biosensor for the Detection of Oligonucleotides. Anal. Chem., 68, 2905–2912. Ferguson, J., Boles, C., Adams, C. and Walt, D.R. (1996) A fiber-optic DNA Biosensor Microarray for the Analysis of Gene Expression. Nature Biotechnology, 14, 1681. Johnston, D., Glasgow, K. and Thorp, H. (1995) Electrochemical Measurments of the Solvent Accessibility of Nucleobases using Electron Transfer between DNA and Metal Complexes. J. Am. Chem. Soc., 117, 893. Kolakowski, B., Battaglini, F., Lee, Y., Klironomous, G. and Mikkelsen, S.R. (1996) Comparison of an Intercalating dye and an Intercalant-enzyme conjugate for DNA Detection in a Microliter-based assay. Anal. Chem., 68, 1197–1200. Lumely-Woodyear, T., Campell, C. and Heller, A. (1996) Direct Enzyme-Amplified Electrical Recognition of 30-Base Model Oligonucleotide. J. Am. Chem. Soc., 118, 5504. Millan, K. and Mikkelsen, S.R. (1993) Sequence-specific Biosensor for DNA based on Electroactive hybridization indicators. Anal. Chem., 65, 2317–2323. Millan, K.M., Saraullo, A. and Mikkelsen, S.R. (1994) Voltammetric DNA biosensor for cystic fibrosis based on a modified carbon paste electrode. Anal. Chem., 66, 2943–2948. Mikkelson, S.R. (1996) Electrochemical biosensors for DNA sequence detection. Electroanalysis, 8, 15–19. Noble, D. (1995) DNA sequencing on a chip. Anal. Chem., 67, 201A–204A. Okahata, Y., Matsunobo, Y., Ijiro, K., Mukae, M., Murakami, A. and Makino, K. (1992) Hybridization of Nucleic acids Immobilized on a Quartz crystal Microbalane. J. Am. Chem. Soc., 114, 8299–8300. Palecek, E. (1996) From Polarography of DNA to Microanalysis with Nucleic acid Modified electrodes. Electroanalysis, 8, 7–14. Pandey, P. and Weetall, H. (1995) Detection of aromatic Compounds based on DNA intercalation using an Evanescent wave biosensor. Anal. Chem., 67, 787–792. Piunno, P., Krull, U., Hudson, R., Dahma, M. and Cohen, H. (1995) Fiber-optic DNA Sensor for Fluorometric nucleic acid determination. Anal. Chem., 67, 2635–2643. Wang, J., Palecek, E., Nielsen, P., Rivas, G., Cai, X., Shiraishi, H., Dontha, N., Luo, D. and Farias, P. (1996a) Peptide nucleic acid probes for Sequence specific DNA Biosensors. J. Am. Chem. Soc., 118, 7667–7670.

Wang, J., Cai, X., Rivas, G. and Shiraishi, H. (1996b) Stripping Potentiometric Transduction of DNA Hybridization Processes. Anal. Chim. Acta, 326, 141–147. Wang, J., Rivas, G., Luo, D., Cai, X., Valera, F. and Dontha, N. (1996c) DNA-modified electrode for the Detection of Aromatic Amines. Anal. Chem., 68, 4365–4369. Wang, J., Cai, X., Jonsson, C. and Balakrishnan, M. (1996d) Adsorptive Stripping Potentiometry od DNA at Electrochemically Pretreated carbon paste electrodes. Electroanalysis, 8, 20–24. Wang, J., Chicharro, M., Rivas, G., Cai, X., Dontha, N., Farias, P. and Shiraishi, H. (1996e) DNA biosensor for the detection of hydrazines. Anal. Chem., 68, 2251–2254. Wang, J., Rivas, G., Parrado, C., Cai, X. and Flair, M. (1997a) Electrochemical Biosensor for detecting DNA sequences from the pathogenic protozoan Cryptosporidium parvum. Talanta, in press. Wang, J., Rivas, G. and Cai, X. (1997b) Screen-printed Electrochemical Hybridization biosensor for the Detection of DNA Sequences from the E.Coli pathogen. Electroanalysis, 9, 395–398. Wang, J., Rivas, G., Cai, X., Chicharro, M., Parrado, C., Dontha, N., Begleiter, A., Mwat, M., Palecek, E. and Nielsen, P. (1997c) Detection of Point Mutation in the p53 Gene using a Peptide Nucleic acid biosensor. Anal. Chim. Acta, in press. Wang, J., Rivas, G., Ozsoz, M., Grant, D., Cai, X. and Parrado, C. (1997d) Microfabricated electrochemical Sensor for the Detection of Radiation-induced DNA damage. Anal. Chem., 69, 1475–1460. Watts, H., Yeung, D. and Parkes, H. (1995) Real-time Detection and Quantitation od DNA Hybridization by an Optical Biosensor . Anal. Chem., 67, 4283–4289.

4. WATER ANALYSIS IOANIS KATAKIS, MÒNICA CAMPÀS and ELENA DOMÍNGUEZ Half of the world’s population is already living in large urban centres. This concentration of human activity creates severe problems in the management of environmental resources, and above all in water management. It is increasingly important to develop new tools and methods that could time-effectively, reliably and inexpensively guarantee public health and help the management of the ecosystem. The use of biosensors to such ends is described in Chapter 4.1 for pesticide monitoring, Chapter 4.2 for BOD measurement, the rest of the organic pollution parameters are dealt with in Chap. 4.3, and in Chapters 4.4–4.6 sensor systems for inorganic pollution are described. It is instructive to review the requirements for environmental analysis in water to define the usefulness of biosensors in such applications. In Table 4.1 the current legislation for water monitoring is summarised. It is obvious from an examination of these data that water analysis as legislated requires the determination of global parameters that indicate the water quality or suitability for human consumption or discharge in the environment. It is not surprising therefore, that the most successful biosensors (and the only commercialised ones) are BOD biosensors that provide a competitive advantage (the time of analysis) when compared with the traditional analytical procedure. Other generic indicators of water quality in general could be correlated with toxicity parameters or with the response of microbial sensors and have been legislated in many countries. However, validation of sensor data with respect to the traditional parameters is always required. But the role of more specific biosensors, such as enzymatic or affinity biosensors, is more difficult to define. In contrast to surface, drinking or ground water, waste water analysis requires the determination of specific organic compounds. A list of these compounds as legislated by the major western countries is given in Table 4.2. Therefore, an obvious area where specific biosensors could find a “niche” market for application, is the analysis of such water samples, especially if this could be made in real time and on-line. This last requirement implies that the biosensor should be highly reliable, meaning the absence of interferences due to matrix effects and a sufficient stability of the sensor. A second possibility for the application of more specific biosensors is the correlation of specifically measurable parameters with generic indicators imposed by legislation. This type of correlation requires very long and costly product development times and always meets with the inertia created when classical techniques have been the analytical standard for many years (see for an example Chap. 4.3.3.1.). In addition, legislative requirements do not justify such investments since they essentially define the environmental analysis market, and this turns out to be fragmented and small. A third area is a highly risky approach from a business point of view: biosensors can provide measurements of parameters that previously could not be determined, in a time scale, at costs and with a simplicity which are not achievable with traditional

Page 138 Table 4.1. Legislated Organic Compounds (other than Pesticides) for Water Monitoring according to its Type. Parameter

Drinking Surface Water Water A1 A2 A3

Method

Biochemical Oxygen >3 −1 Demand (BOD) (mgL O2)

>3

>5

>7

—Determination of the dissolved oxygen before and after incubation of 5 days on the dark

Chemical Oxygen Demand – (COD) (mg L−1 O2)

–

–

30

—Potassium dichromate method

Nitrogen (mg L−1 N)

1

1

2

3

—Mineralization, destination by Kjeldahl method and Molecular Absorption Spectrophotometry

Substances Extractable in Chloroform (µg L−1 dry residue)

100

100 200 500

10** Dissolved or Emulsified Hydrocarbons; Mineral Oil (µg L−1)

—Extraction with purified chloroform, evaporation and dry weight verification

50* 200* 500/ —IR Spectroscopy after extraction 1000* with CCl4 —Gravimetry after extraction with petroleum ether

Phenols (Phenol Index) (µg 0.5** L−1)

1*

1/5* 10/ 100*

—Molecular Absorption Spectrophotometry —4-Aminoantipyrine method —Paranitroaniline method

Surfactants (Reacting with Methylene Blue) (µg L−1)

200**

200 200 500

—Molecular Absorption Spectrophotometry

Polycyclic Aromatic Hydrocarbons (µg L−1)

0.2**

0.2* 0.2* 1*

—UV Fluorescence after TLC —Comparison with a mixture of 6 standard substances with the same concentration

Organochlorinated Compounds (µg L−1)

1

–

–

–

—Gas chromatography after extraction with appropriate solvents and purification

A1: Simple physical treatment and disinfection; A2: Normal physic treatment, chemical treatment and disinfection; A3: Intensive physical and chemical treatments, refining and

desinfection * Mandatory level ** MAC Values Data extracted from Bulletin of the European Communities, No. L 194/33, 07.25.75 and from Boletín Oficial del Estado (Spain), No. 53, 03.02.88 techniques. Such an approach defies the legislative confines or even aspires to redefine them. It is possible that such technological advances will enlarge the existing range of uses confined by legislation. Above all, they point to the possibility of the unravelling of new markets composed of non-expert users that could make the Table 4.2. Major Legislated Limits for Organic Pollutants in Waste Water. Compound

Industrial Sector

Value per month mgL

Chloroform

a) Production of chloromethanes from methanol or a 1 mixture of methanol and methane b) Production of chloromethanes by chloration of methane

1

c) Production of chlorofluorocarbon (CFC)

–

1,2-Dichloroethane (DCE) a) Production of DCE (without transformation or use 1.25 at the same site) b) Production of DCE and transformation or use at the same site, except for e)

2.5

c) Transformation of DCE into substances other than 1 vinyl chloride d) Use of DCE for metal degreasing (out of the industrial sites mentioned in b)

0.1

e) Use of DCE in the production of ion exchangers

0.1

Hexachlorobenzene (HCB) a) Production and transformation of HCB

Hexachlorobutadiene (HCBD) Hexachlorocyclohexane (HCH)

1

b) Production of PCE and CCl4 by perchloration

1.9

c) Production of PCE and/or trichloroethylene by another process

–

a) Production of PCE and CCl4 by perchloration

1.5

b) Production of PCE and CCl4 by another process

–

a) Production of HCH

2

b) Extraction of lindane

2

c) Production of HCH and extraction of lindane

2

d) Other sectors

2

Pentachlorophenol (PCP)

a) Production of PCP-Na by hydrolysis of HCB

1*

Perchloroethylene (PCE)

a) Production of TCE and PCE (procedures TCEPCE)

0.5

b) Production of CCl4 and PCE (procedures CCl4PCE)

1.25

c) Use of PCE for metal degreasing

0.1

d) Production of chlorofluorocarbon

–

a) Production of TCB by dehydrochloration and/or transformation of TCB

1

b) Production and/or transformation of chlorobenzene by chloration of benzene

0.05

a) Production of TCE and PCE

0.5

b) Use of TCE for metal degreasing

0.1

Trichlorobenzene (TCB)

Trichloroethylene (TCE)

Limit values per day will be twice the mentioned concentration The reference method for determination is Gas Chromatography * The reference method for determination is Gas or Liquid Chromatography Data extracted from Boletín Oficial del Estado, No. 2475, 11.23.87, No. 613, 03.13.89, No. 2425, 10.31.89, No. 1244, 05.09.91, No. 1719, 06.28.91 investment in product development worthwhile. Such an outcome of the present activity in biosensor research would be desirable. The difficulties involved in all analytical situations mentioned above explain why the involvement of the private sector in the development of environmental biosensors is generally low. They also point to the directions of most efficient use of resources for the development of commercially important biosensors for environmental analysis that should be based on generic technologies and multianalyte sensors. This explains the fact that at present most of the commercial efforts are centered on microbial sensors and on the development of immunoassays since for the latter exist generally trouble-free methods for the development of antibodies and a well established format (ELISA) to use them (Chap. 3.3.). As a result, many kits have been made commercially available in the last few years that with more or less success have met new analytical challenges and have even started legislation reform processes in some cases. On the other hand, work on enzymatic sensors appears to have centered on the more traditionalist approach of meeting legislative requirements either as disposable sensors or as modular detectors in sample pretreatment flow systems. Having to compete with the well established analytical

methods, these types of biosensors are still in the validation stage. The enzymatic sensors involving the catalytic transformation of the pollutant (Chap. 4.3.1, 4.6.), such as the phenolics sensors based on tyrosinase, are by far the most advanced in this process. The inhibition or enzymatic activity modulation sensors find application mainly in the pesticide (Chap. 4.1.1.), heavy metals (Chap. 4.4.) and phosphate (Chap. 4.5.) monitoring and are treated separately.

4.1. PESTICIDES

URSULA BILITEWSKI More than 300 compounds are used in agriculture for plant protection. They differ in chemical nature and accordingly in their mode of action and application area. Most of the active ingredients are herbicides and among them the organic compounds are the major group. They are organophosphorous compounds (e.g. glyphosat), carbamates, thiocarbamates, urea derivatives (e.g. diuron), triazines (e.g. atrazine) and others. Another important group of pesticides are the insecticides to control animal pests. Again different chemical classes are used: the organophosphorous compounds and carbamates are also active as insecticides, another wellknown group are the chlorinated hydrocarbons (e.g. DDT, aldrin), but also some “natural insecticides” and derived synthetic compounds are known, such as pyrethroides and pyrethrins. Of some groups the biological mode of action is known, for example some herbicides (e.g. atrazine, diuron) block photosynthesis by binding to the photosynthetic reaction centre in plants, and organophosphorous compounds and carbamates are very effective inhibitors of the acetylcholinesterase. However, from a large number of pesticides the site of action is not known, and also toxic effects on animal and men can often not totally be excluded. Due to their different chemical nature these compounds also differ strongly in their natural degradation rate, which may be due to microbial metabolism or chemical turnover, e.g. hydrolysis or photochemical degradation. For example the first generation of insecticides, the chlorinated hydrocarbons, were rather stable, thus remained on the plants and reached water ways and the food chain. To minimize the risk for continuous intoxination in a lot of countries the use of pesticides is regulated and it is aimed at the maintainance of a pesticide-free drinking water. Therefore, upper allowable concentrations were set, for example, in Europe 0.1 µg/L for a single pesticide independent on the toxicity of the compound. This concentration level was defined according to the lower detection limits of standard analytical methods and has stimulated research to improve existing methods and establish new ones. Thus, next to HPLC and GC (see Chap. 7) biochemical methods were established and among them a variety of biosensor systems, aiming at the determination of herbicides, insecticides and fungicides in the relevant concentration range without the necessity of enrichment procedures. They utilize mainly the inhibitory power of pesticides on enzymes (Chap. 3.1.2, 4.1.1.) or the binding of analytes by antibodies (Chap. 3.3, 4.1.2.). 4.1.1. ENZYMATIC SYSTEMS

THIERRY NOGUER, BÉATRICE LECA AND JEAN-LOUIS MARTY 4.1.1.1. Introduction

Biosensors have been found to be simple, cost-effective and easy-to-handle tools that could be extremely useful for environmental monitoring. The detection of pesticides is based, in some cases, on the catalytic transformation of the pesticides by a selected enzyme, i.e. organophosphorus hydrolase for organophosphorus insecticides. Nevertheless, pesticides are toxic compounds that usually act by inhibiting one or several enzyme(s). Therefore, the detection of such compounds is primarily based on the inhibitory properties of the pesticide. Since the

specificity of enzymes for inhibitors is quite wide, the measured response can be related to a family of pesticides rather than to a specific compound. Contrary to immunosensors, enzymebased sensors can be considered as early-warning devices because they are sensitive to a relatively large spectrum of compounds. 4.1.1.2. Organophosphorus and Carbamate pesticides

Organophosphorus and carbamic compounds represent a large percentage of currently used pesticides (insecticides, fungicides, herbicides…). These pesticides have harmful consequences as they act as inhibitors of cholinesterases which are involved in neuronal transmission. It is therefore not surprising to note that cholinesterase-based electrodes form the basis of the detection methods most frequently described in the literature. Acetyl- or butyryl-cholinesterases (AChE, E.C. 3.1.1.7 or BuChE, E.C 3.1.1.8), which are enzymes that catalyze the hydrolysis of acetyl- or butyrylcholine into choline and acetate or butyrate, have been purified and are now commercially available. The development of electrochemical biosensors, based on the potentiometric or amperometric detection of compounds has been evaluated in recent review of this topic by Trojanowicz and Hitchman (1996). The use of cholinesterase as a sensing element does not allow for the selective detection of a particular pesticide, but rather provides an estimation of the total anticholinesterase activity present in a sample. This activity represents the “toxicological index”, which is defined as the quantity of compounds that induce a percentage of cholinesterase inhibition equivalent to that produced by a known amount of a reference pesticide. In this report, paraoxon has been chosen as the reference compound as this pesticide is stable, commercially available, and known to have a strong inhibitory effect on cholinesterases. Each cholinesterase has been characterized by its own affinity for organophosphorus and carbamate pesticides. The activity and stability of cholinesterases, as well as their sensitivity towards a given inhibitor, depend on the type and the source of cholinesterase. Therefore, the selection of a suitable cholinesterase is a key step in the design of a pesticide biosensor. In this paper, we will focus on potentiometric and amperometric biosensors. Potentiometric biosensors have been designed based on the measurement of pH change, electrode potential change or more sophisticated methods such as ISFET (ion-selective fieldeffect transistor) or LAPS (light-addressable potentiometric sensors). The change in pH is induced by the formation of an organic acid during the hydrolysis of the choline ester by an appropriate esterase, with detection based on the use of pH electrodes (Durand and Thomas, 1984; Tran-Minh et al., 1990; El Yamani et al., 1987; El Yamani et al., 1988; Tran-Minh, 1993; Kumaran and Morita, 1995; Budnikov and Evtugyn, 1996).

Among the biosensors based on the change in redox potential, Ghindilis et al. (1996) developed an original approach by coupling BuChE, ChOD and peroxidase. ISFET (Dumschat et al., 1991; Vlasov et al, 1991; Nyamsi Hendji et al., 1993) and LAPS (Rogers et al., 1991; Fernando et al., 1993; Dehlawi et al., 1994) biosensors have also been reported. As can be seen in table 4.3, the highest sensitivity (0.3ppb) was achieved by Tran-Minh et al. (1990) using AChE immobilized on a glass pH electrode by cross-linking with polyacrylamide. With the exception of this work, the detection limits reported are generally close to 3ppb (Table 4.3). The potentiometric methods

are fast and accurate, but they show quite high detection limits. Furthermore, the potentiometric detection of H+ ions lacks sensitivity due to the consumption of protons by the buffer following proton liberation during the enzyme reaction. The amperometric method of detection is generally more sensitive and allows one to obtain a signal that is directly proportional to the analyte concentration. Depending on the cholinesterase substrate, different amperometric approaches have been described using mono- or bi-enzymatic systems based on the detection of thiocholine, O2, H2O2 or 4-aminophenol. With acetyl- or butyryl-choline as the substrate, bienzyme electrodes coupling a cholinesterase with choline oxidase (ChOD) Table 4.3. Potentiometric cholinesterase-based electrodes. Enzyme (origin)

Immobilization mode

Detection limit of References paraoxon (ppb)

BuChE (ns)

cross-linking with BSA and glutaraldehyde

3

El Yamani et al., 1987

BuChE (hs)

immobilization on nylon with HSA and glutaraldehyde

3

El Yamani et al., 1988

AChE (ns)

cross-linking with polyacrylamide

0.3

Tran-Minh et al., 1990

AChE (ee) (biotinylated)

immobilization on biotinylated cellulose nitrate membrane via streptavidin crosslinking (LAPS)

2.8

Rogers et al., 1991; Fernando et al., 1993; Dehlawi et al., 1994

AChE: acetylcholinesterase; BSA: bovine serum albumin; BuChE: butyrylcholinesterase; ee: electric eel; hs: horse serum; HSA: human serum albumin; LAPS: light-addressable potentiometric sensor; ns: not specified. have been reported, with measurement based on the detection of oxygen or hydrogen peroxide, the latter being more sensitive (Table 4.4):

Table 4.4. Bienzymatic electrodes based on an amperometric detection (O2 or H2O2 detection). Enzymes/ Immobilization mode

Potential

Detection limit of paraoxon (ppb)

References

BuChE (hs)+ChOD/ two enzymes in a dialysis membrane

Clark oxygen electrode

300

Campanella et al., 1991

AChE (ns)+ChOD/ covalent linking on nylon with glutaraldehyde

650 mV vs. Ag/AgCl (Pt)

2

Bernabei et al., 1991

AChE (ns) or BuChE (ns)+ ChOD/covalent linking on nylon with glutaraldehyde

650 mV vs. Ag/AgCl (Pt)

2

Palleschi et al., 1992

AChE (ee)+ChOD/ immobilization in PVA-SbQ

650 mV vs. Ag/AgCl (Pt)

0.03

Mionetto et al., 1992

AChE (ee)+ChOD/ immobilization in PVA-SbQ

650 mV vs. Ag/AgCl (Pt)

2.8

Marty et al., 1992

AChE: acetylcholinesterase; BSA: bovine serum albumin; BuChE: butyrylcholinesterase; ChOD: choline oxidase; ee: electric eel; hs: horse serum; ns=not specified; PVA-SbQ: poly(vinylalcohol) bearing styrylpyridinium groups. It is possible to perform a preliminary hydrolysis of the substrate using cholinesterase in solution and then detect choline using a choline biosensor (Palleschi et al., 1992; Bernabei et al., 1993; Cagnini et al., 1995a; Cagnini et al., 1995b). In this way, the lowest measured detection limit was 0.5 ppb paraoxon, as reported by Bernabei et al. (1993). Cremisini et al. (1995) have also made use of a choline probe in which AChE was immobilized separately from ChOD, thus allowing the incubation and measurement steps to be performed independently. In this case, the detection limit was 1.3 ppb of paraoxon. Another approach consists of co-immobilizing the two enzymes at the electrode surface (Bernabei et al., 1991; Wollenberger et al., 1991; Marty et al., 1992; Mionetto et al., 1992) allowing greater sensitivities and higher responses to be obtained. When comparing the results reported in the literature (Table 4.4), the highest sensitivity was obtained by Mionetto et al. (1992) (0.03 ppb paraoxon) using poly(vinyl alcohol) bearing styrylpyridinium groups (PVA-SbQ) as an immobilization matrix. The design of the sensor and the optimization of its performance can be simplified using monoenzymatic systems based on the hydrolysis of acetyl- or butyrylthiocholine by a selected cholinesterase (AChE or BuChE). Using such a principle, detection is based on the oxidation of thiocholine produced on a platinum electrode (Table 4.5):

In this way, the detection potential is lower than that used for the previously described oxidation of hydrogen peroxide (410 mV instead of 650 mV vs. Ag/AgCl on platinum). It is also possible to achieve such a result using electronic mediators such as TCNQ (Martorell et al., 1996) or CoPC (Sklàdal, 1992; Sklàdal and Mascini, 1992). In 1992, Sklàdal reported the detection of 0.08 ppb paraoxon by cross-linking BuChE with glutaraldehyde on a carbon electrode modified with cobalt phthalocyanine (CoPC). Using AChE immobilized in a PVA-SbQ matrix, Marty et

al. (1995) succeeded in reaching a detection limit of 0.03 ppb for paraoxon. Some studies have been successfully validated using chromatographic methods (Marty et al., 1995; Barceló et al., 1995). Monoenzymatic devices using 4-aminophenyl acetate as a substrate have also been reported; in these cases detection was carried out by the oxidation of 4-aminophenol at 0.25 V vs. SCE on a glassy carbon electrode (La Rosa et al., 1994; La Rosa et al., 1995; Pariente et al., 1996). With these electrodes, a detection limit of 1.1 ppb paraoxon is possible. It should be noted that indoxyl acetate has also been used as a substrate by Razumas et al. (1981), with the amperometric detection based on the oxidation of indigo white at 0.3V vs. Ag/AgCl. In this case, butyrylcholinesterase was used in solution which, to our knowledge, is a method that has not been previously reported in a biosensor configuration. Finally, two different cholinesterases can be co-immobilized in the same biorecognition layer (Sklàdal et al., 1994). When compared to sensors using only one specific cholinesterase, such devices permit the detection of a greater number of pesticides, thus enlarging the range of detectable compounds. Table 4.5. Monoenzymatic electrodes based on an amperometric detection (thiocholine oxidation). Enzyme/ immobilization mode

Potential

Detection limit References of paraoxon (ppb)

BuChE (hs)/cross-linking with glutaraldehyde

250mV vs. Ag/AgCl (CoPC modified carbon electrode)

0.08

Sklàdal, 1992

AChE (ee) or BuChE (hs)/cross-linking 300 mV vs. Ag/AgCl with glutaraldehyde (CoPC modified carbon electrode)

1.5

Sklàdal and Mascini, 1992

AChE (ee) or/and BuChE (hs)/crosslinking with BSA and glutaraldehyde

250mV vs. Ag/AgCl (CoPC modified graphite electrode)

2.8

Sklàdal et al., 1994

AChE (ee)/immobilization in epoxygraphite

700 mV vs. Ag/AgCl

28

Martorell et al., 1994

AChE (ee)/immobilization in PVASbQ

410 mV vs. Ag/AgCl 0.03 (Pt)

Marty et al., 1995

AChE (ee or be) or BuChE 300 mV vs. Ag/AgCl (hs)/immobilization on aminated silica (TCNQ modified particles in epoxy-graphite graphite)

27.5

Martorell et al., 1996

AChE (ee)/immobilization in PVASbQ

0.3

Jeanty and Marty, 1997

410 mV vs. SCE (Pt)

AChE: acetylcholinesterase; be: bovine erythocytes; BSA: bovine serum albumin; BuChE: butyrylcholinesterase; CoPC: cobalt phthalocyanine; ee: electric eel; hs: horse serum; PVA-SbQ: poly (vinylalcohol) bearing styrylpyridinium groups; TCNQ: tetracyanoquinodimethane.

One of the main requirements when detecting inhibitors is the need to reactivate the inhibited enzyme in order to allow for continuous monitoring. In the case of irreversible inhibitors of cholinesterases such as organophosphorus insecticides, the reactivation of the enzyme is performed by using a powerful nucleophilic reagent such as 2-PAM (2-pyridinealdoxime methiodide) (Tran-Minh et al., 1990; Mionetto et al., 1994; Marty et al., 1995) or TMB-4 ({1,1′trimethylenebis-4-(hydroxyiminomethyl)-pyridinium bromide}) (Budnikov and Evtugyn, 1996). 4.1.1.3. Other pesticides

In addition to cholinesterase-based biosensors, the detection of pesticides has been carried out using aldehyde dehydrogenase, acetolactate synthase, tyrosinase or peroxidase, with each enzyme being inhibited by a specific family of pesticides. Dithiocarbamate fungicides form the most important class of pesticides for the broad spectrum control of a variety of fungal diseases in crops. They are mainly composed of ethylenebis(dithiocarbamate) (maneb, zineb, mancozeb…) and dimethyldithiocarbamate compounds (ziram, ferbam…). While the target of action of dithiocarbamate fungicides is unknown, these compounds have been detected using biosensors configured to measure the inhibition of aldehyde dehydrogenase (AlDH) or tyrosinase. With respect to aldehyde dehydrogenase, Marty and Noguer (1993) developed an amperometric bienzymic sensor for the detection of ethylenebis(dithiocarbamate) by coupling AlDH with diaphorase, with detection based on hexacyanoferrate (II) oxidation:

The optimization of enzyme loading and incubation time led to a detection limit as low as 1.5ppb maneb (Noguer and Marty, 1997). An alternative form of dithiocarbamate detection is to use tyrosinase as the target enzyme:

Besombes et al. (1995a) used a polypyrrole membrane to detect, among other compounds, diethyldithiocarbamate. Since many dithiocarbamates are hydrophobic compounds, Wang et al. (1993) described a sensor for diethyl-dithiocarbamates to be used in organic media. Another approach, based on reversed micelle systems, was reported by Pérez Pita et al. (1997) in which a detection limit of 22.6ppb ziram was obtained.

Triazine herbicides are photosynthesis inhibitors which are persistent and remain active in the environment for several years, causing continuous water pollution. The detection of these pesticides by sensors has been described by Rawson et al. (1989) using cyanobacteria, and by Rouillon et al. (1995) who used thylakoid membranes. The first enzyme sensor for the detection of these herbicides was that reported by McArdle and Persaud (1993), based on tyrosinase inhibition. Using this principle, McArdle and Persaud (1993) and Besombes et al. (1995a) achieved a detection limit of around 1 ppm atrazine. It must be stressed that tyrosinase has also been used for the detection of a wide range of pesticides and pollutants that can act as substrates or inhibitors (Besombes et al., 1995ab). This lack of specificity may be an advantage if the sensor is used as a warning system for general environmental pollution. Sulfonylurea and imidazolinone herbicides (e.g. sulfometuron methyl, thifensulfuron methyl) are used for the control of broad-leaved weeds and grasses in cereal crops. Based on the fact that these herbicides are powerful inhibitors of acetolactate synthase, Seki et al. (1996) reported the design of an amperometric biosensor the detection of herbicide concentrations as low as 10−6 M, with detection based on the monitoring of oxygenase side-activity of ALS:

4.1.1.4. Conclusion

The detection of environmental pollutants using enzyme-based biosensors has been widely described in literature and appears promising since these devices are simple, fast, portable and they can be used for on-line monitoring. For this purpose, many authors have coupled amperometric biosensors with continuous flow techniques (Wollenberger et al, 1991; La Rosa et al., 1995; Jeanty and Marty, 1997). Such systems could be used as early-warning devices in cases such as water pollution monitoring, for instance. Keeping in mind that pesticides are generally hydrophobic compounds that must be extracted and concentrated using organic solvents, organic phase enzyme electrodes (OPEEs) have been developed. These devices, mainly devoted to substrate determination, have had their use extended towards the determination of pesticide concentrations in organic media. Mionetto et al. (1994) demonstrated the possible use of an acetylcholinesterase-based biosensor for the detection of organophosphorus and carbamate pesticides in organic solvents. Other reports have been devoted to tyrosinase-based sensors used in organic media (Wang et al., 1993; Adeyoju et al., 1994; Adeyoju et al., 1995; Deng and Dong, 1996) or in reversed micellar systems (Reviejo et al., 1995; Stancik et al., 1995). Based on these considerations, biosensors will undoubtedly play an important role in future environmental monitoring. As highlighted by many authors (Evans et al., 1986; Bogue, 1993; Dennison and Turner, 1995; Rogers, 1995), several requirements must be taken into account before such devices can be accepted, used and commercialized. The main problem to be overcome is that linked to the stability of the target enzyme. In view of improving this parameter, investigations now focus on the isolation of enzymes, from natural or genetically engineered thermophilic micro-organisms, that show enhanced stability at high temperatures. The development of artificial enzymes bearing functional moities that mimic natural enzyme activity, named “synzymes”, is also particularly promising.

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4.1.2. AFFINITY SENSOR SYSTEMS

G.GAUGLITZ, J.PIEHLER AND U.BILITEWSKI 4.1.2.1. Introduction

Immunoassays are an attractive approach to environmental analysis providing simple, low-cost but sensitive and rugged detection. However, total assay times of conventional immunoassays based on microtiter plate format are in the range of several hours and these methods are not readily automated. Affinity sensor systems attempt to overcome this drawback. The most straightforward approach is to speed up conventional enzyme immunoassays by using flow systems as described in detail in Chap. 2.3. This has been successfully implemented reaching sensitivities comparable to the corresponding microtiter plate format immunoassay (Krämer et al., 1997b). The development of a variety of novel detection methods led to the concept of the immunoprobe: These techniques allow direct, time-resolved monitoring of the interaction of antibodies with the analyte at a transducer surface. An attractive approach for detecting antibody-analyte interaction is to avoid any labeling of the interacting compounds. A variety of transducers based on optical or acoustical interrogation that allow label-free detection of binding at interfaces have been investigated (Brecht, Gauglitz, 1995b, and Chapter 2.2.). This approach is particularly attractive for implementing immunoprobes and numerous applications with respect to pesticide detection have been reported (Minnuni, Mascini, 1993; Heideman et al., 1993; Bier et al., 1994; Brecht et al, 1995a; Tom-Moy et al, 1995; Horácek, Skládal, 1997; Mouvet et al., 1997; Schipper et al., 1997; Drapp et al., 1997). A combination of the sensitivity of label-based detection and the advantages of a direct assay is possible by using fluorescence labeled antibodies or tracers. Binding at the transducer surface is then detected by selective fluorescence excitation adjacent to the surface by total internal reflection (total internal reflection fluorescence, TIRF). This technique found interest for various analytical problems including environmental analysis (Bier et al., 1992; Zhao et al., 1995; Brecht et al., 1997b). All these methods are based on separation of bound and non-bound species by immobilizing one of the interacting compounds on the surface of a solid support. In addition fluorescence based detection allows rapid detection in homogeneous phase without separation being required. However, this chapter will focus on detection in heterogeneous phase. Some basic principles and requirements valid for all affinity sensor systems will be stated in the first part of this chapter. Later on, the application of different detection methods will be discussed in more detail, followed by a critical conclusion and an outlook to future developments in this field.

Figure 4.1. Typical immunoassay formats used for affinity sensor systems. I: pretreated surface; II: surface after the assay. 4.1.2.2. Assay format, surface modification and sample handling

The performance of affinity sensor systems based on interactions at the solid/liquid interface strongly depends on the assay format, the properties of the surface, and the material transport to the surface. Adjusting these parameters systematically to the detection system is therefore essential. 4.1.2.2.1. Assay formats

Heterogeneous phase immunoassay allows a variety of different test formats. Some typical examples used in affinity sensor systems are depicted in Figure 4.1. Most simple is a binding inhibition assay which is frequently used for immunoprobes. Antibody is incubated with the sample to allow the analyte to bind to the antibody binding sites according to the analyte concentration (law of mass action). The remaining free antibodies are determined by detecting antibody binding to an immobilized analyte derivative. Competitive assays are somewhat more sophisticated as both the analyte and the tracer or the immobilized derivatives simultaneously interact with the antibody. Therefore, the concentrations of the antibody and the tracer or immobilized derivative have to be thoroughly adjusted to reach an optimum performance. However, more parameters are available for tuning the sensitivity and the working range. Displacement assays are attractive for directly monitoring concentrations, but an optimum dissociation rate of tracer is required to get maximum sensitivity and still no “leaching”. 4.1.2.2.2. Immobilization strategies

In almost all sensor systems immobilization of one of the interacting compounds is required. For typical immunoassays in microtiter plate format, immobilization is achieved by adsorption of

proteins or protein conjugates at the surface of the wells and the plate is disposed after the assay. In contrast to this procedure, in automated systems the active surface should be reusable for many times since mounting of new reactors or transducers should be avoided. Either the surface has to be regenerated after the assay by selectively cleaving the analyte-antibody complex or the whole immobilization procedure has to be carried out repeatedly after removing the immobilized compound. Both strategies have been investigated and found applications. For regeneration of the surface by cleaving the analyte-antibody complex, the immobilized compound has to remain on the surface during a regeneration procedure. Typically, harsh conditions such as pH<3, high ionic strength, highly concentrated chaotropic reagents or organic solvents are required to break the bonds between antibodies and haptens. Therefore, covalent attachment to the surface is the method of choice to achieve stable attachment. Furthermore, the immobilized compound itself must be stable under the regeneration conditions. Frequently, proteins such as antibodies will be partly denatured and survive only a few regeneration cycles. Therefore, preferentially the hapten or a hapten-analogue is immobilized and inhibition of antibody-binding is detected (indirect test format) providing following advantages: • suitable analyte derivatives that are readily coupled to the surface are available from immunization (Chap. 3.3.); • the analyte derivatives are usually highly stable as they do not require a protein-component and therefore lead to a long life of the immunoprobe; • the recognizing structure, the antibody, is freshly provided for each assay. However, optimization of the regeneration is required for each analyte-antibody system. Therefore, strategies to reversibly immobilize compounds and remove them after each assay are rather attractive. Readily cleavable affinity systems for site-directed capturing of the compound have been established in affinity chromatography: protein A or G for capturing antibodies, avidin/streptavidin for components conjugated with biotin-derivatives such as iminobiotin, chelator ligands such as nitrilo-triacetic acid (NTA) for capturing His-tagged proteins. The possibilities will be further broadened by increasing application of recombinant antibody production. Typically, the capturing compound is covalently attached to the surface. A further advantage of these methods is gained by the fact, that the compounds are captured orientedly. 4.1.2.2.3. Binding rates The total sequence of an affinity reaction with one partner being immobilized and the other being in solution comprises at least two steps (Eddowes, 1987): 1. The dissolved binding partner, e.g. the antibody in the binding inhibition assay and in the indirect competitive assay, diffuses to the immobilized partner. 2. The binding reaction between both partners occurs.

The slowest reaction determines the overall reaction rate, and thus the analysis frequency. The reaction rates of affinity reactions (step 2) usually follow a second order reaction rate law, which allows an enhancement of the reaction rate through increasing concentrations. Thus, a high surface loading with the immobilized binding partner accelerates the binding reaction. If the dissolved compound is of high molecular weight with a low diffusion coefficient, such as an antibody, its transport to the surface may become the rate limiting step. However, the rate of mass transport is also dependent on the concentration gradient of the diffusing compound. As sample handling in affinity sensor systems is typically done in flow systems shallow flow channels or a wall jet design ensure a fast flow adjacent to the transducer surface by reducing the diffusion layer thickness (Ruzcika, Hansen, 1988). Working under mass transport limitations minor degradation of the immobilized compound does not affect the binding rate and the sensitivity is maintained. 4.1.2.3. Affinity sensor systems based on enzyme tracers

The best established immunoassays for pesticide determination are enzyme-linked immunoassays (EIAs), performed as heterogeneous, competitive assays (Chap. 3.3.). Different assay concepts are described in literature, some of which have found application in commercially available products, such as microtiter plate assays, or assays comprising magnetic particles, tubes or membranes. The function of these support materials is to allow easy separation of bound and unbound components. This is required, as in the final step by the addition of enzyme substrates only enzyme tracer bound to antibodies should be detected, and thus all unbound reagents have to be removed. Usually all steps of the assay involve manual addition of defined volumes of reagents and control of incubation times. In a modified form the performance of the assay is automated using flow injection analysis, which allows automated dosing of reagents and the performance of chemical reactions under kinetic conditions (Chap. 2.3.). Signals are generated after the addition of enzyme substrates. The detection principle can be varied from photometric detection as in conventional ELISAs to fluorimetric or electrochemical detection. It depends mainly on the combination of enzyme used as label and enzyme substrates. From the assay formats described in general in Figure 4.1 mainly the direct and indirect competitive assay formats are realized in sensor systems based on enzyme tracers. Affinity sensor systems with electrochemical detection based on indirect competitive enzyme immunoassays were described by several groups mainly for the determination of 2,4Dichlorophenoxyacetic acid (2,4-D). 2,4-D can readily be immobilized through its carboxylic group, by standard immobilization protocols (Kaláb and Skládal, 1995). However, this indirect competitive format is not limited to 2,4-D, as usually suitable hapten derivatives exist, as they are required also for the preparation of immunoconjugates. Kaláb and Skládal (1995) immobilized 2,4-D on screen-printed electrodes and added the horseradish peroxidase (POD)labelled antibody together with the sample to a reaction chamber mounted on top of the electrode. The amount of bound POD was determined after a washing step by addition of a mixture of hydrogen peroxide and hydroquinone. Hydroquinone was oxidized to benzoquinone,

which was reduced amperometrically at the electrode. This assay was performed manually leading to rather high standard deviations, but it was possible to design a multi-channel device using the same principle (Skládal, Kaláb, 1995). The electrodes were not regenerated, thus they were used only for single experiments. Automation of comparable assays was achieved by using the principles of flow-injection analysis with the hapten being immobilized not directly on the transducer but either on the inner walls of a capillary or on polymeric beads which were filled in a small column. All reagents were pumped automatically to this affinity reactor and the detector was placed downstream. Depending on the enzyme and the substrates electrochemical (Chemnitius et al., 1996) or optical detectors can be used. In most of the enzyme-linked immunosensor systems the antibodies are irreversibly immobilized on solid supports and an enzyme-hap ten-conjugate is used as enzyme tracer and competes directly with free hapten for the antibody binding sites. Suitable immobilization methods are covalent binding of antibodies via bifunctional reagents to activated support materials, such as silanized glass beads (Dietrich, Krämer, 1995; GonzalezMartinez et al., 1997), or polymeric beads or membranes with suitable functional groups, e.g. epoxy-activated beads (Bjarnason et al, 1997; Gascon, 1997; Krämer, Schmid, 1991). Alternatively the very strong binding between biotin and avidin or streptavidin is utilized by coupling the (strept)avidin by one of the above mentioned methods or just by adsorption to a support material followed by addition of the biotinylated antibody (Locascio-Brown et al., 1990; Wittmann, Schmid, 1994; Dietrich, Krämer, 1995). All the immobilization matrices mentioned above cannot serve directly as transducers for the signal generated by addition of enzyme substrates. Thus, they are integrated via small reactors in a flow-through or flow-injection analysis (FIA) system, where the detector is placed downstream of the antibody reactor. A possible setup is shown schematically in Figure 4.2. In this system conventional injection valves were replaced by 2/3-way-valves (see Chap. 2.3.), which allowed incubation times to be defined via pumping times of the reagents. All procedures required in an ELISA were automated by choice of the corresponding reagents and flowing lines. The valves 1 and 2 define whether the carrier or the enzyme substrates were pumped to the detector directly or via the affinity reactor leading to the baseline and to the analyte dependent signal, respectively. In the latter case also the valves 3, 4, and 5 were switched accordingly. The baseline was recorded while the main immunochemical reagents, i.e. the sample and the enzyme tracer, were pumped subsequently only to the affinity column, where incubation times could be prolonged either by extension of the pumping time or by choice of the stop-and-go-mode. To remove unbound reagents the reactor together with connecting tubings was washed with a buffer

Figure 4.2. Schematic diagram of a flow-through device used for automated performance of a competitive enzyme-linked immunoassay (v=valves, P=pumps, D=detector). solution, which may contain additives such as detergents or ethanol to guarantee complete removal of adsorbed compounds. The amount of enzyme tracer bound in the immunosorbent column was determined as almost final step, when the enzyme substrates were transported first to the affinity reactor, and then, after an incubation period, to the detector. Usually enzyme substrates are chosen, which result in colored or fluorescent products, e.g. hydrogen peroxide and hydroxyphenylpropionic acid (HPPA), but this is not a prerequisite, as for other than environmental applications in comparable systems also electrochemical detectors were used (Kanecki et al., 1994). Whereas previous developments required exchange of the immunosorbent material after each assay (Krämer, 1990), nowadays investigations are intensified with respect to regeneration of the antigen-antibody-binding leading to a reusability of the antibodies. Thus, in addition to the reagents used also in conventional ELISA protocols, a regenerating solution, e.g. glycin-HCl buffer pH 2, is required. Regeneration of the binding sites is obtained by washing the reactor with the respective solution for some minutes. After regeneration the system has to be cleaned again by washing with buffer to avoid damage of antibodies or enzyme tracers used in the following assay by residual acidic solutions. In some of the systems this approach seems to work rather promising, as several hundred measuring cycles were reported (Wittmann, Schmid, 1994; Gonzalez-Martinez et al., 1997). However, successful complete regeneration requires either a low affinity between antibodies and analyte/ tracer, which usually is combined with a reduced sensitivity of the assay, or hard conditions applied during regeneration, e.g. very low or very high pH, which may damage the antibody leading to a loss of activity after several regeneration cycles (Dietrich, Krämer, 1995). Thus the stability of antibodies during regeneration has to be tested, if this approach is followed.

As a consequence of the limitations described above using irreversibly immobilized antibodies nowadays immunoanalytical FIA-systems are described based on reversibly immobilized antibodies (Krämer et al., 1997a, b). It is well known in biotechnology from purification protocols for monoclonal antibodies that these proteins bind specifically to binding proteins, such as protein A or protein G, and that they can be eluted from these affinity columns by a shift to low pH-values. The two proteins, protein A and protein G, differ in their specificity for different subclasses of immunoglobulins (Anderson et al., 1997), but the basic principle of IgG binding is the same. As performed in affinity purification of antibodies, an antibody-solution can be pumped through a column containing a material with immobilized protein A or protein G and binding of the antibody occurs. The same approach is followed in a so-called flow-injection immunoaffinity analysis (FIIAA) device, having reduced the size of the column to an analytical column. The set-up can be comparable to the system shown in Figure 4.2. The additionally required antibody solution can be delivered either by integration of another flow channel by an additional 2/3-way valve, or by premixing defined amounts of sample and antibody replacing the sample solution in Figure 4.2. The affinity complex of antibody and analyte is then captured by the protein A/protein G-material. Suitable protein A- or protein G-materials are either commercially available as affinity chromatography materials or they can be prepared by covalent immobilization of protein A/G to glass beads, polymers or membranes. Regeneration of the system leads to a regeneration of the protein A/G-antibody-binding, i.e. the antibodies are removed from the system together with the analyte and the tracer and have to be replaced prior to or together with each measuring cycle. As protein A/G-binding of IgGs is well-known it is not necessary to investigate the influence of various regeneration conditions on the stability of the system. However, antibodies and tracer-solutions have to be used in their final concentrations, i.e. as highly diluted protein solutions. This may lead to problems, if the system is to be applied continuously without service. Then possibilities of stabilization have to be evaluated. In general it can be summarized that in most of the sensor systems based on enzyme tracers all steps of established microtiter plate assays are automated via flow injection immunoanalysis. This often allows the reduction of the assay time down to less than 30min., including even the additional step of regeneration of the antibody binding sites, as incubation times can be reduced as much as allowable to result in reliable data, and it is not necessary to wait until equilibrium is established. Which assay format preferably is chosen is dependent on some properties of analyte and antibody. If the hapten can be immobilized directly through a suitable functional group, such as 2,4-D through its COOH-group, or if a suitable hapten-derivative is available, this approach may be the method of choice, especially if monoclonal antibodies are available, as complete regeneration can be achieved by addition of proteinases, because no protein has to remain active on the support material. On the other hand, for each analyte a new affinity material has to be prepared. If only polyclonal antibodies, or no haptens with suitable functional groups are available, the immobilization of antibodies may be preferred. This can be done by standard procedures, or through the biotin-(strept)avidin-system, the latter one allowing the preparation of a common basis material for different analytes. However, the stability of the antibodies after regeneration has to be investigated.

The method of reversibly immobilized antibodies probably is to be chosen, if a common affinity material is to be used for different antibodies without the need to optimize immobilization and regeneration conditions. Only binding properties of the different antibody-subclasses have to be considered. However, the antibodies are again consumed by each assay and protein solutions of a rather high degree of dilution are used. Example

A FIA-system according to the principle shown in Figure 4.2 and originally developed for atrazine determination with the monoclonal antibody being immobilized reversibly to a commercially available protein A-material was used for diuron-determination also (Krämer et al., 1997b). Only concentrations of the antibody- and the enzymetracer-solution had to be adapted for the new analyte. The atrazine- and the diuron-system showed lower detection limits of 0.02 µg/1 for both analytes, which was well below the in Europe allowable concentration for pesticides of 0.1 µg/1 and was comparable to the sensitivity obtained with corresponding microtiterplate-ELISA. The affinity material protein A could be used for several hundred measurements, with the stabilities of the antibody-, enzymetracer- and enzyme substratesolutions getting major importance. Application to spiked water samples showed only minor matrix effects. 4.1.2.4. Label-free methods

Label-free detection of the analyte-antibody interaction provides elegant possibilities to implement immunoprobes. These detection techniques are sensitive to the change in surface loading occurring upon the binding of molecules. Most of them are based on optical interrogation (Brecht, Gauglitz, 1995b, Chapter 2.2.). Application of various detection principles to implement immunoprobes for pesticide detection has been investigated: grating couplers in different modes of operation (Bier et al., 1994; Piehler et al., 1997); surface plasmon resonance (Minnuni, Mascini, 1993; Mouvet et al., 1997); reflectometric interference spectroscopy (Brecht et al., 1995a; Mouvet et al., 1996); integrated optical Mach-Zehnder interferometer (Drapp et al., 1997; Schipper et al., 1997). Results with several methods were critically reviewed with respect to application in environmental monitoring (Brecht, Gauglitz, 1997a). The most straightforward and elegant approach for label-free detection is to immobilize the antibody at the transducer surface and to directly monitor binding of the analyte. However, this concept has not yet been realized for environmental applications because binding of analytes with a typical molecular mass of 100–500g/mol to the immobilized antibody (150000 g/mol) leads to only minor changes in surface loading. Therefore, usually an analyte derivative is immobilized and the inhibition of antibody binding in the presence of free analyte is detected. Surface modification is particular important for label-free immunoprobes since non-specific protein adsorption cannot be discriminated by this detection technique. Non-specific interaction is typically reduced by shielding of the substrate surface with inert polymers. Most frequently, a dextran based matrix coating is used providing low non-specific binding and high binding capacity. Efficient surface chemistry has been described on gold (Löfas, Johnsson, 1990), on silica (Piehler et al., 1996) and on metal oxides (Buckle et al., 1993; Polzius et al., 1996). An

analyte derivative with high affinity to the antibody (typically the hapten) is covalently attached to the polymer at the surface in high concentration to ensure mass transport limited binding. Repeated use of such surfaces over more than 200 cycles was possible without a significant loss of activity (Brecht et al., 1995a; Mouvet et al., 1997). Assays are typically carried out in a binding inhibition assay format. The antibody (0.2 to 5 µg/ml) is incubated with the sample. After a pre-incubation period of several minutes, the mixture is exposed to the sensor surface by a flow system over a period of 2–10 min. Antibody binding at the surface is monitored with a time resolution of 1 to 10s. Including the subsequent regeneration period of 1–5 min., the typical total assay time is approx. 10–20 min. Monitoring of the interaction allows evaluation of the interaction kinetics. Mass transport limited binding in flow through systems leads to constant binding rates and the binding curve can be readily evaluated by linear regression. Calibration curves are obtained by plotting the slope of the binding curve versus the analyte concentration (Bier and Schmid, 1994). Examples Immunoassays carried out with the same antibody under comparable conditions by using different label-free transducers allow comparison of the performance. Typical

Figure 4.3. Immunoassay determination of simazine by RIfS. A: inhibition of antibody binding at various simazine concentrations. B: calibration curve. binding inhibition curves obtained by a label-free immunoprobe based on reflectometric interference spectroscopy (RIfS) are shown in Figure 4.3. The slopes of the binding curves were determined by linear regression. The calibration curve is shown in Figure 4.3B. The limit of detection was approximately 0.1 µg/1 taking 3 times the standard deviation into account. The same immunoassay was carried out on a slab waveguide SPR device (WSPR, Chap. 2.2.). In this case, surface chemistry was carried out on a gold layer pretreated with mercaptopropionic acid. Typical binding curves and a calibration curve are shown in Figure 4.4. Linear binding due to mass transport limitation is well to observe. The assays were carried out in a laboratory for environmental analysis and the results were validated by using standard instrumentation (Mouvet et al., 1997).

Results for the same immunoassay carried out with different label-free transducers have been compared in a critical review (Brecht, Gauglitz, 1997a). Comparison of the limits of detection in terms of surface coverage and pesticide concentration indicate rather similar performance of these transducers. In all cases, the limit of

Figure 4.4. Simazine immunoassay carried out with a WSPR device. A: binding curve of 0.33 µg/ml anti-simazine Fab; B: calibration curve detection was near to 0.1 ppb which is the upper limit for pesticides in water in Europe. Therefore, improvement of the sensitivity of one order of magnitude is required for reasonable application. However, when investigating real samples with label-free immunoprobes, strong interference of the sample matrix with the binding signal was observed (Mouvet et al., 1996). This is a principal problem due to the non-selectivity of labelfree detection and will limit the application to very defined samples. 4.1.2.5. Fluorescence based immunoprobes

Fluorescence detection by total internal reflection interrogation combines the elegance of the immunoprobe concept with the sensitivity and the low background of label-based detection. Details about this detection principle are discussed in Chapter 2.2. Fluorescence immunosensors for the detection of pesticides are described based on either immobilized antibodies (Brummel et al., 1997; Anis et al., 1993) or on immobilized haptens (Bier et al., 1992; Wortberg et al., 1994). Binding of the partner labelled with a fluorophor is monitored in real-time. Fluorescent dyes frequently used in this field are fluorescein or rhodamins. In recent years, long-wave fluorophors such as Cy5, Cy5.5 or Cy3 have become available. These dyes are very attractive since low-cost light sources can be used and further reduction of the background is achieved. The dyes are coupled to hapten derivatives or proteins via suitable functional groups and bifunctional reagents. In most of the systems reported so far, optical fibers have been used as transducers and have been optimized for these applications (Anderson et al., 1993). Waveguide based fluorescence excitation has been proved to allow highly sensitive detection (Plowman et al., 1996; Abel et al., 1996) and further developments are expected from this field. Fluorescence immunoprobes allow a variety of assay formats which have to be selected with respect to antibody affinity and tracer chemistry. Mixing of all reagents prior to the incubation or

serial incubation on the surface is possible. Immobilizing the hapten at the transducer surface and pre-incubation of antibody with the analyte leads to a binding inhibition assay. If the antibodies were immobilized on the surface, the fluorophore-labelled hapten competes with the analyte present in the sample for the antibody-binding sites. Thus the signal decreases with increasing analyte concentration. Serial incubation allows the analyte to occupy as many antibody binding sites as correlate to its concentration leaving only the unoccupied sites for the tracer. This may be advantageous, if the affinity of the tracer to the antibody is higher than of the analyte. Alternatively, the replacement of the fluorescence-tracer by the analyte can be monitored (Kusterbeck et al., 1990). In this situation the antibody is pre-loaded with the fluorescent tracer leading to a high starting signal. As soon as the sample with the pesticide reaches the transducer surface, the tracer is replaced by the non-fluorescent analyte leading to a decrease in signal. The rate and the final value are related to the concentration of the analyte. However, if the dissociation rate of the tracer from the antibody is too high, leaching of the fluorescent tracer is observed even if only buffer is added (Zhao et al., 1995). On the other hand, if the affinity between antibody and

Figure 4.5. Detection of antibody binding in a binding inhibition assay (A) and calibration curve (B). tracer is too high, the tracer cannot be replaced by the analyte. Thus, application of displacement immunoprobes requires compromises between high affinity antibodies required for low background signals and lower affinity antibodies required for a low limit of detection. Coupling of activated fluorescent dyes (active esters, thioisocyanates) directly to proteins is a well-established procedure. Additionally, immobilized haptens are usually chemically very stable allowing regeneration even with harsh reagents. Immunoprobes based on indirect binding inhibition assays are therefore readily set up. Preparation of low molecular weight fluorophorelabelled haptens is tedious and not yet routinely established. One major problem of haptenfluorophor-conjugates is fluorescence quenching upon binding at the antibody. However, assays with low molecular weight tracers can be carried out very fast due to a better mass transport to the transducer surface and is therefore attractive.

Example A waveguide TIRF set-up was used for implementing a fluorescence based immunoprobe (Brecht et al., 1997b). The assay was carried out in a binding inhibition format. Anti-simazine antibody labeled with Cy5.5 was incubated with simazine in various concentrations. After preincubation, the mixture was exposed to the waveguide for several minutes. Binding of the free antibody was determined by monitoring the bleaching of the fluorescent dye after the incubation (Figure 4.5). The detection limit of 0.1 ppb of this immunoprobe is not yet sufficient for application. However, the reproducibility is better than observed for label-free detection and further improvement by optimization of the assay conditions is expected. 4.1.2.6. Summary, conclusions and future trends

The principles of the affinity sensor systems discussed in this Chapter are also applicable to other affinity reactions, such as receptor-ligand-interactions or binding to lectins, avidins or even nonbiological, artificial receptors. However, they are best-established for immunoreactions, as they are based on the same principles known from well-established heterogeneous phase immunoassays in microtiter plate formats. Automation can be achieved by performing the conventional assays in flow-through systems. These methods are already established and good sensitivities have been achieved. For further miniaturization and simplification, the concept of the immunoprobe is very attractive. Label-free detection proved to be capable to detect analyte concentration in the sub-ppb range. However, interference by the sample matrix when working with real sample is a principal problem for these systems. The lack of selectivity of the detection principle will be limiting for field tests. Applications of these methods are advantageous when labeling of compounds should be avoided. For routine analytics, labeling of antibodies does not significantly increase the costs per assay. Therefore, immunoprobes based on labeled compounds such as TIRF detection are more attractive in this field. This approach combines the sensitivity and the specificity of fluorescence detection with the elegance of direct monitoring of the binding event. Further optimization of waveguide design will supply highly sensitive fluorescence detection. Miniaturized low-cost setups using standard optical components from the telecommunication market will be available. Due to this high potential of fluorescence based detection, further developments are expected in this field. The main challenges for affinity sensor systems for environmental monitoring will be parallelization of several affinity reactions to allow multi-residue detection. For heterogeneous phase detection, spatially resolved surface modification will be an important task for achieving highly parallel detection. An approach using micro-drop delivery systems, smart biochemistry and waveguide-based fluorescence detection for flexible multi-residue analysis is presently investigated within a EC environmental project (Brecht et al., 1997b). Further developments are also expected from fluorescence based homogeneous phase detection. Methods such as fluorescence depolarization (Dandliker, de Saussure, 1970; Matveeva et al.,

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4.2. BIOCHEMICAL OXYGEN DEMAND (BOD)

KLAUS RIEDEL, MATTHIAS LEHMANN and GOTTHARD KUNZE 4.2.1. INTRODUCTION

Many substances contained in waste water are measured as sum parameters, such as the Biochemical Oxygen Demand (BOD). The BOD is an indispensable part of waste water control systems and gives evidence about the organic pollution that is biodegradable. The oxygen demand is determined from a sample of activated sludge over an incubation period of 5 days (BOD5). The major disadvantage of this parameter is the long incubation time of 5 days, which delays the evaluation of the degree of pollution until well after the event. Therefore, the conventional BOD test is not suitable for online process control. A more rapid estimation of BOD is possible by using microbial sensors containing complete cells immobilized on an oxygen electrode. The first report of such a microbial BOD sensor was published by Karube et al. in 1977. Since 1983 a BOD-sensor sytem based on this microbial BOD-sensor has been produced by Nisshin Electric Co. Ltd. (Karube, 1986). Meanwhile, commercially available BOD-sensor systems have been produced by AUCOTEAM GmbH Berlin (Merten and Neumann, 1992), PGW GmbH Dresden (Szweda and Renneberg, 1994), and Dr. Bruno Lange GmbH Berlin (Riedel et al, 1993). 4.2.2. STRUCTURE AND FUNCTION OF THE BOD SENSOR SYSTEM 4.2.2.1. Design of the BOD sensor system

The design of various described BOD biosensors is similar. A general design of BOD sensors is shown in Figure 4.6. The main parts of such a biosensor are the microorganisms as biological recognition system and the oxygen electrode as physical

Figure 4.6. Diagram of microbial BOD-sensor. transducer. These parts are separated by a gas permeable membrane. The cells are immobilized using an outer semipermeable membrane covering the sensor. The dominant transducer in BOD-sensors is the amperometric oxygen electrode. The application of an optical oxygen transducer instead of the normally amperometric oxygen electrode was described by Preininger et al. (1994). Another interesting technique is the use of luminous bacteria Photobacterium phosphoreum (Hyan et al., 1993). The cellular assimilation of organic compounds from the waste water correlates with the intensity of luminescence in this technique. The usage of a biofuel cell type electrode for BOD determination (Karube et al., 1977) is another possibility. The current generated by the biofuel cell is resulted from the oxidation of hydrogen and formate which is produced by Clostridia from organic compounds under anaerobic conditions. The microbial sensor is incorporated into a measuring system. There are two measuring systems: • a stirred measuring chamber system, which is shown in Figure 4.7; • a flow-through system. A prerequisite for precise measurement is a sufficient and constant oxygen content of the buffer and all measuring solutions. This is achieved by stirring the buffer in the measuring chamber or by an air pump in the through-flow system. A very good oxygen supply is achieved by an aerosol technique in which the buffer or buffer sample stream is saturated by air in the relation 1:100 (Riedel et al., 1991).

Figure 4.7. Schematic diagram of a BOD-biosensor system based on a stirred measuring chamber. 4.2.2.2. Function of microbial BOD sensor

BOD determination with microbial sensor is based on direct measurement of the oxygen consumption of the microorganisms on the oxygen electrode. This consumption depends on the organic substrates contained in the sample. The function of microbial BOD sensors is the same as described in section 3.2.2.4. If a waste water sample is added to the measuring system biodegradable substrates are used for respiration by the microbial cells present on the sensor. This causes an immediate decrease of the oxygen concentration. This effect is measured with the oxygen electrode. In general, two kinds of measurements are possible: • end-point measurement (the difference of current I reflects the respiration rate of the substrates) with relatively long measuring times (up to 20 min.); • kinetic measurement (the first derivative of the current-time curve dI/dt), which allows measuring times of about 1 min. The last measuring method acts positively on the measuring frequency and stability of the biosensor, because the accumulation of substrates in the microbial cells remains at a low level and any toxic compounds that may be present in the waste water acts on the sensor for only a short period. The measuring frequency depends on the accumulation of substrates in the microbial cells of the sensor, which depends again on the exposure time of the sample. This is important because the sensor is not ready to carry out another measurement until the microorganisms are nutrient-limited again.

Page 168 A general problem of microbial BOD sensors is the poisoning of microbial cells by potential toxic substances in the waste water. Toxic effects of heavy metals on the activity of microorganisms are well known. Therefore, the influence of Cu2+, Zn2+, Pb2+, Hg2+, and Cd2+ on the signals of the Trichosporon cutaneum containing biosensor were tested. Whereas Cu2+, Zn2+, Pb2+ showed only small effects, the activity of the biosensor was clearly inhibited by Hg2+, and Cd2+ concentrations of 50 mg/ml (Riedel et al., 1990a). In this regard, the use of resistant strains is of interest. Slama et al. (1995) described a heavy metal resistant BOD-sensor using Alcaligenes eutrophus, which harboured plasmids encoding resistance to nickel, copper, cadmium, and zinc. An arsenic resistant BODsensor based on Pseudomonas putida has been developed by Ohki et al. (1990). Another interesting possibility to eliminate toxic effects of heavy metals on the BOD-sensor is achieved by covering the sensor with a poly(4-vinylpyridine)-coated polycarbonate membrane (Li and Tan, 1994). The poly(4-vinylpyridine)-membrane eliminates the heavy metal ions without decrease of sensitivity. 4.2.3. PROBLEMS OF PRACTICAL USE AND COMPARISON OF SENSOR-BOD AND BOD5 4.2.3.1. Distinctions between sensorBOD and BOD5

For practical use a correct evaluation of the application and the limitations of the methods is necessary to decide whether the microbial BOD sensor or the conventional 5-day test is most suitable. Repeatedly it has been described that the sensor BOD-values are not identical to those of the BOD5. Differences between both tests resulted from the different principles. The biosensor uses a single or defined combination of species of microorganism with a fixed metabolic state instead of an undefined population obtained from the activated sludge of the respective waste water plant which is used in the conventional method. Additional differences between the sensor and the 5-day test resulted from the time range. The determination of BOD with a microbial sensor is a quick test for biological activity by a selected microbial species, whereas the BOD5 measures the sum of various biochemical processes in a biosludge during a period of 5 days. These processes include: • adaptation to substrates which is caused by induction of enzymes necessary for degradation; • enzymatic hydrolysis of polymers, e.g. starch, proteins, lipids; • alteration in the composition of biosludge resulting in an increase or decrease in the population of some species. In contrast, polymers cannot be estimated with a BOD-sensor, because the hydrolysis of these polymers is impossible in the short measuring time. However, it is possible to register the metabolic reactions and alterations of microoganisms, which take place during 5 days of incubation by the BOD5, if the microbial sensor as well as the waste water samples are pretreated.

Finally, the microbial BOD sensor needs to be calibrated before it can be used as a biochemical activity test which reveals results comparable to those of the conventional BOD5 value. 4.2.3.2. Improvement of correlation between the sensor BOD and BOD5

A relatively good correlation of sensor BOD and BOD5 can be often achieved by the following procedures: • selection of suitable microorganisms utilizing a broad spectrum of substrates; • induction of metabolic capacities by incubation of biosensor with the desired substances or waste water; • hydrolysis of polymers by enzymatic or acid treatment of waste water. 4.2.3.2.1. Selection of suitable microorganisms

Multi-receptor behaviour which is the ability to recognize a large number of substances, is one prerequisite for the use of microorganisms for the BOD-sensors. Therefore activated sludges of waste water plants were investigated. Biosensors with undefined variety of microbial species in the form of activated sludge, as described by Karube et al. (1977) as well as Strand and Carlson (1984), revealed no reproducible results (Hikuma et al., 1979). Mixing cultures such as activated sludge are not stable. Biosensors using one species of microorganism seem to be more suitable (Table 4.6). However, depending on the substrate spectrum of the microbial species used, the application of one of these species enables the determination only of a proportion of the organic compounds contained in waste water (Table 4.7). An additional problem is the various sensitivities of the microbial species used in the biosensor and the biosludge to pure substances, which is shown by the sensor BOD/BOD5-ratio of Table 4.8. In general, compounds such as lactose, maltose, sucrose and amino acids used for the BOD sensor technique give lower values than those determined by the 5-day test. Conversely, for organic acids and ethanol, the sensor BOD-values are mostly higher than the BOD5-values. The selection of appropriate microorganisms is a possibility to improve the agreement of BOD with BOD5 (Tanaka et al, 1994; Riedel et al., 1998). The recently described biosensor consisting of Arxula adeninivorans cells often showed a higher sensitivity to substrates compared with other microbial BOD sensors, which is demonstrated in Table 4.7. Yeast cells are especially suitable, because they are able to use a wide substrate spectrum combined with a wide measuring range. Another way is the combination of different species of microorganisms using different substrate spectrums. This leads to a biosensor with improved quality. Mixed cultures of closely related strains, such as Bacillus subtilis and B. licheniformis (Tan et al., 1992) as well as Enterobacter spec, and Citrobacter spec. (Galindo et al., 1992) are used. It is also possible to combine nonrelated microbial species as well as species with different or supplementary substrate spectra, which was demonstrated by Riedel et al. (1993) with the bacterium Rhodococcus erythropolis

and the yeast Issatchenkia orientalis. This combination biosensor associates the substrate sensitivity of both species (Table 4.8). Table 4.6. Types and parameters of microbial BOD sensors. Microorganis Transducer ms

Activated sludge

Calibrati Measuri Measurin Precisio Stability on ng range g time n [%] [days] standard (mg/l [min] BOD]

amp. oxygen GGA* electrode

References

5–22

15

7.5

10

Karube et al., 1977

5–22

20

9.0

20

Strand and Carlson, 1984

Arxula amp. oxygen glucose adeninivorans

8–550

1.1

5

30

Riedel et al., 1998

Alcaligenes eutrophus

amp. oxygen glycerol

0.35– 3.66

0.5

4

30

Slama et al., 1995

Bacillus subtilis

amp. oxygen glucose

2–22

0.1–0.2

5

40

Riedel et al., 1988

Bacillus polymyxa

amp. oxygen GGA

1–45

15

6

60

Su et al., 1986

Clostridium butyricum

biofuel cell

50–300

30–40

10

30

Karube et al., 1977

Hansenula anomala

amp. oxygen lactate [mmol]

7

Kulys and Kadzianskie ne, 1980

GGA

0.01–0.4 15–20

GGA

1–45

13–20

6

GGA

<44

30

9

GGA

5–30

15

GGA Photobacteriu optrode (luminescens m phosphoreum e)

5–120

15

Pseudomonas amp. oxygen GGA putida

1–66

8

Pseudomonas amp. oxygen GGA spec.

1–20

15

4

amp. oxygen GGA

1–45

13–20

6

Li and Chu, 1991 30

Ihn et al., 1992 Sohn and Hong, 1993

7

Hyan et al., 1993 7

Ohki et al., 1990

20

Zhang et al., 1986 Li and Chu,

1991 Thermophile amp. oxygen GGA microorg. Torulopsis Candida

amp. oxygen GGA

Trichosporon amp. oxygen GGA cutaneum

1–10

7

10–100

0.2

3–41

18

40

Karube et al, 1989

6

45

Rajasekar et al., 1992

30

Hikuma et al, 1979

Microorganis Transducer ms

Calibrati Measuring range [mg/l on standard BOD]

Measuri Precisio Stabilit References ng time n [%] y [min] [days]

(beigelii)***

glucose

2–100

0.2–0.5

4

40

Riedel et al., 1988

GGA

1–110

5–10

5

30

Preininger et al., 1994

30

Tanaka et al., 1994

22

Tan et al., 1992

optical oxygen sensor unidentified strain 1–1

amp. oxygen waste water**

2–10

amp. oxygen GGA Bacillus subtilis+ B. licheniformis

10–300

4–15

5

Citrobacter amp. oxygen GGA spec. + Enterobacter spec.

6–18

8

< 11

Rhodococcus amp. oxygen glycerol erythropolis + Issatchenkia orientalis***

6–600

0.25–1.1 <5

amp. oxygen GGA Lipomyces kononenkoae + βgalactosidase

4–90

5

Reiss et al., 1993

Tr. cutaneum amp. oxygen glucose (beigelii) + protease + amylase

2–100

3

Riedel et al., 1990b

Tr. cutaneum amp. oxygen starch + amylase

30–200

3.75

* GGA: glucose glutamic acid standard ** artificial waste water (Tanaka et al., 1994)

14

Galindo et al., 1992

40

Riedel et al., 1993, 1996

Heibges et al., 1997

*** commercialed BOD sensors 4.2.3.2.2. Alteration of sensor activity by preincubation The BOD sensor sensitivity can be increased by induction of the metabolic degradation systems of the microorganisms with the respective substrate (Riedel et al., 1990a, 1997—see 3.2.3.1.). For this case the BOD-sensor is incubated with the corresponding waste water for some hours. The achieved activity is constant during the incubation. As shown in Table 4.9, preincubated microbial sensors as well as the conventional BOD method revealed similar results. 4.2.3.2.3. Enzymatic or acid hydrolysis of waste water Microbial sensors are not able to detect polymers, such as proteins, starch or cellulose. That is why the sensor BOD value of waste water is in most cases too small compared Table 4.7. Sensitivity of BOD-sensors consisting of various microorganism species in comparison to the sensorBOD/BOD5 -ratio (substrate solution equivalent 275 mg/l BOD5; calculation of sensorBOD-values with a glucose standard of measuring data according to Riedel and Kunze, 1997). Substrate

SensorBOD/BOD5-ratio Arxula adeninvorans

Issatchenkia orientalis

Rhodococcus erythropolis

Pseudomonas putida

Trichosporon cutaneum*

Glucose

1.00

1.00

1.0

1.0

1.1

Fructose

0.45

0.18

2.08

0.49

0.48–0.86

Galactose

0.80

0.07

0

0.33

Ribose

0.01

0

0

0.06

Xylose

0.41

0.11

0.03

0.23

Sorbitol

0

0

0

0

Sucrose

0.21

0.21

0.05

0.53

0.24–0.47

Lactose

0.07

0

0

0.08

0.01

Maltose

0.20

0.20

0.01

0.20

Glucosamin 0.17

0.16

0.11

0.20

Citric acid

0.03

0.07

0

0

1.0

Acetic acid

3.81

2.04

8.61

0.12

2.4

Ethyl alcohol 4.40

3.37

0.76

2.12

2.23

Glycerol

0.10

0.01

1.57

0.23

1.04

Alanine

1.36

0.47

0.49

1.36

0.75

Glycine

1.72

0.39

0.22

0.45

0.82

Glutamic acid

0.16

0.85

0.59

0.25

1.09

Lysine

0.76

0.11

0.03

0.61

Methionine

0.69

0.34

0.16

0.28

Tryptophan

0.17

0.10

0

0.05

Butyric acid 0.83 Na

0.95

6.87

5.27

Capron acid 3.10 Na

0.99

6.81

1.75

Capryl acid Na

5.01

0.51

6.9

4.36

Caproic acid 3.65 Na

0.92

5.72

3.89

Lauryl acid Na

0.55

0.48

2.85

2.34

Propionic acid Na

0.70

0.40

5.47

0.08

Oil

0.03

0.12

0.15

0.06

Phenol

0

0.07

0.03

0.02

Benzoate

0.02

0.07

0.03

*References: Hikuma et al., 1979; Riedel et al., 1990 to the BOD5 method. Three possibilities have been described to overcome this problem: • pretreatment of waste water with hydrolases or acids; • installation of a column with hydrolases before the BOD sensor; • construction of hybride sensors consisting of microorganisms and hydrolases. Table 4.8. Sensitivity of BOD sensor containing Rhodococcus erythropolis or Issatchenkia orientalis as well as their combination in comparison to BOD as sensorBOD/BOD5-ratio (calibration with glycerol) (calculated according to Riedel et al., 1997). SensorBOD/BOD5-ratio

Substrate Rhodococcus erythropolis

Issatchenkia orientalis

Rh. erythropolis + Is. orientalis

Glycerol

1.00

1.00

1.00

Fructose

4.62

0.32

1.50

Glucose

0.85

0.93

0.52

Sucrose

0.30

0.10

0.09

Maltose

0.09

0.29

0.10

Lactose

0.05

0.02

0.04

Acetic acid

12.74

9.83

10.43

Ethyl alcohol

14.69

0.72

4.19

Glutamic acid

3.50

2.08

3.19

Glycine

0.25

0.96

0.56

Alanine

0.14

0.70

0.27

Table 4.9. Increase of sensor activity by adaption to the appropriate substrate or waste water incubation (Riedel, 1997). Substrate Waste water

BOD sensor

BOD5[mg/l]

Sensor BOD [mg/l]

References

untreated induced Fructose*

Trichosporon cutaneum 0.71

0.44

0.66

Maltose*

0.49–0.76

0.02

0.15

Alanine*

0.55

0.19

0.41

OECD model waste water

18000

10640

13680

Chemical factory

726

470

853

Food factory

8000

4076

8764

n.d.

91

146

Municipal waste water

n.d.

15

46

Industrial waste water

n.d.

14

34

Paper factory

Issatchenkia + Rhodococcus

Riedel et al., 1990a

Riedel et al., 1997

Table 4.10. BOD-values determined after pretreatment of waste water from a paper factory with cellulases and ß-glucosidases (Riedel 1997). Waste water

Sensor BOD [mg/l] untreated

Increase of BOD [%]

enzymatic treatment

Sample 1

10

29

290

Sample 2

12

22

183

Sample 3

44

75

170

Sample 4

26

39

150

Sample 5

5

21

420

The effect of enzymatic treatment of waste water on the sensor BOD was demonstrated by an example in a paper factory (Riedel, 1997). This waste water gave biosensor BOD-values, which were lower than those of the BOD resulting by the 5-day method. The reason for this is that the microbial sensor was not able to detect cellulose. A drastic increase of sensor BOD values of waste water was achieved if it was treated by enzymes or acid (Table 4.10). The high specificity of enzyme limits the application of this method, because enzymes, such as proteases, amylases, cellulases and others, are required for the desired waste water. Therefore, the acid hydrolysis of waste water is preferred for practical use. The polymers in waste water are split into their monomers such as monosaccharides, glycerol and fatty acids by acid hydrolysis for one hour at 100°C (Kasel et al., 1996). The hydrolysis of waste water caused in most cases an increase of BOD (Table 4.11). As a result the concurrence of sensor BOD- and BOD5 is improved (Riedel, 1997). Degradation of polymers in waste water can also be achieved by a hybrid sensor, consisting of microorganisms and hydrolases, such as amylase or proteases (Riedel et al., 1990a) or a column with immobilized amylases (Heibges et al., 1997). This system has been used for BOD determination of starch containing waste water. 4.2.3.3. Calibration and calculation of BOD5

The determination of BOD by a microbial sensor as a biological activity test needs a calibration which enables the comparison with the conventional BOD. For calibration of the BOD-sensor the so-called GGA-standard (glucose and glutamic acid) according to BOD5-standards (JIS K 3602, 1990), glucose or glycerol with determined BOD5 (Riedel et al., 1990a, 1990b; Riedel and Uthemann, 1994) are used. However this so-called GGA-standard for BOD5-calibration is not suitable for microbial sensors, because: • of its instability due to microbial contaminations; • the glutamic acid reaction caused by microorganisms is decreased in the presence of glucose which is due to glucose repression. Table 4.12. BOD-values estimated by microbial sensors and determined by the 5 day method for various waste water samples. Microbial sensor

Trichosporon cutaneum

Reference

Riedel et al., 1990a, Tan et al., 1992 Riedel et al., 1997 Hikuma et al., 1979

Riedel et al., 1998

sensor [mg/l]

sensor

Waste water

BOD5 [mg/l]

domestic waste water

170

ratio*

B. subtilis+ B. licheniformis

sensor

ratio

154

0.91

Rh. erythropolis Arxula +Is. orientalis adeninivorans

sensor

ratio

ratio

domestic waste water

285

334

1.17

domestic waste wate

366

366

1.00

domestic waste water MW6

131

90

0.69

98

0.75

domestic waste water MW8

123

91

0.76

86

0.70

domestic waste water MW11

180

162

0.96

123

0.68

domestic waste water MW13

112

63

0.58

89

0.79

domestic waste water MW14

53

23

0.49

37

0.70

domestic waste water MW17

108

50

0.46

86

0.80

domestic waste water MW18

153

57

0.37

77

0.50

domestic waste water MW21

114

46

0.40

68

0.60

domestic waste water MW22

166

100

0.60

175

1.05

Page 177 Microbial sensor

Trichosporon cutaneum

B. subtilis+ B. licheniformis

Rh. erythropolis Arxula +Is. orientalis adeninivorans

domestic waste water MW23

169

130

0.77

195

1.15

waste water plant effluent MW12

3

6

2.00

2

0.67

waste water plant effluent MW15

1

2

200

1

1.00

waste water plant effluent MW20

0

0

waste water plant effluent MW24

3

2

0 3

1.00

Sewage water SW1 140

104

0.74

Sewage water SW2 0

0

Semi-liquid manure 9936

12900

Food factory waste 152 water IW1

155

Food factory waste 8000 8764 water IW2

1.02 1.10

Food factory waste 151 water IW3 Starch factory waste water IW4

4000 4250

Palm oil mill waste 9840 12400 water IW5

147

0.97

1.06 1.26

Fermentation factory w.w. IW6

15040

15640

1.04

Pharmaceutical factory IW7

2076

1897

0.91

Chemical industry w.w. IW8

726

Industrial waste water IW9

852

0.67

1.17 253

389

1.54

1.30

Figure 4.8. Comparison between BOD values estimated by the sensor and that determined by 5 day method of inflow at sewage treatment plant with 2.5 Mio population equivalent over a period of twelve days (Riedel et al., 1997).

Figure 4.9. Comparison between BOD values estimated by the sensor and that determined by 5 day method of outflow of sewage treatment plant with 200,000 population equivalent over a period of eleven days (Riedel et al., 1997).

Table 4.13. Comparison of BOD values estimated by the conventional 5-day method to those calculated by the sensorBOD and with a correlation factor of the inflow at a sewage treatment plant with 2.5 million population equivalent over several days. Calculation factor: 1.225±0.054 (after Riedel et al., 1997). Days BOD5[mg/l] SensorBOD [mg/l] calculated BOD5[mg/l] Deviation calc. BOD5to BOD5 1

220

250

306

+86

4

190

153

187

−3

5

210

168

206

−4

6

210

161

197

−13

8

275

241

295

+20

12

170

141

174

+4

assimilate, for example from fermentation and food plants. The sensor showed constantly low values compared to those of the BOD5 method for domestic waste water which contained relatively high concentrations of polymers such as proteins, starch and lipids and only low concentrations of easily assimilable compounds. In this case acid hydrolysis of waste water can improve the coincidance of sensor BOD and BOD5. The hydrolysis of waste water has in most cases caused an increase of sensor BOD as shown in Table 4.12 and the concurrence of sensor BOD- and BOD5 was improved (Riedel, 1997). Moreover, the agreement of sensor BOD and BOD5 additionally depends on the substrate spectrum of microorganisms of sensor. The yeast A. adeninivorans is a suitable microbial species for a BOD-sensor because it can use a broad spectrum of substrates. The BOD-values of waste waters determined by this sensor are in relatively good agreement with the results obtained by the BOD5 method (Riedel et al., 1998). Owing to the different measuring principles and different compositions of the waste waters, the sensor BOD values are not identical to the BOD5. According to the profile lines of sensor BOD and BOD5 (Figure 4.8 and 4.9) they are only similar. For this case the BOD5 value can be calculated from sensor BOD values by using a specific conversion factor (Table 4.13). A high content of easily assimilable compounds as well as relatively low concentrations of polymers such as proteins, starch and lipids are prerequisites for the described correlation. 4.2.4. CONCLUSION

Short measuring times as well as high precision of the sensor BOD system offer more opportunities to monitor waste water, and give dischargers and seepage water operators the means to comply with steadily increasing demands to carry out their own checks. However application of the BOD sensor is limited, because there are some restrictions due to legislation. In most countries the BOD5 is the industrial standard. Therefore, the problem of official acceptance of the sensor BOD is their comparatibility to legally-binding BOD5 determined by the conventional method. However, the sensor BOD values are not identical with BOD5 in all cases. The reason for these differences are the different measuring principles as well as compositons of waste waters. The microbial sensor responds mainly to the easily assimilable compounds in waste water. Consequently, the sensor BOD value is lower than that obtained by the BOD5 technique. Therefore, the microbial BOD sensor should be considered as a new parameter in waste water monitoring. It is already accepted as standard in Japan (JIS K 3602, 1990). Otherwise it is necessary to recalculate the sensor BOD-values into BOD5 values. At present the regulations of the German “Länder” concerning the in-house monitoring of waste water states that a simplified or alternative method for determination of the BOD can be used if the values are obtained with methods which reliably fulfil the specified aim of the analysis. Such a calculation of BOD5 values with a correlation factor is possible in many cases. A prerequisite is, that only the quantitative composition, but not the qualitative composition, is altered. It is best to achieve agreement of sensor BOD and BOD5 values by acid hydrolysis of waste water. REFERENCES

Galindo, E., Garcia, J.L., Torres, L.G. and Quintero, R. (1992) Characterization of microbial membranes used for the estimation of biochemical oxygen demand with a biosensor. Biotechnol. Techniques, 6, 399–404.

Heibges, A., Metzger, J.F., Reiss, M. and Harmeier, W. (1997) Erweiterung des Substratspektrums eines mikrobiellen BSB Sensors durch eine Enzymsäule mit immobilisierter alpha-Amylase und Amyloglucosidase. 15. DECHEMA-Jahrestagung der Biotechnologie., Abstract 330–333. Hikuma, M., Suzuki, H., Yasuda, T., Karube, I. and Suzuki, S. (1979) Amperometric estimation of BOD by using living immobilized yeasts. Eur. J. Appl. Microbiol. Biotechn., 8, 289–297. Hyan, C.-K., Tamiya, E., Takeuchi, T. and Karube, I. (1993) A novel BOD sensor based on bacterial luminescence. Biotechnol. Bioeng., 41, 1107–1111. Ihn, G.S., Park, K.H., Pek, U.H. and Moo Jeong, I. (1992) Microbial sensor of biochemical oxygen demand using Hansenula anomala. Bull, korean Chem. Soc., 13, 145–148. JIS K 3602 (1990) Japanese Industrial Standard: Apparatus for the estimation of biochemical oxygen demand (BODS) with microbial sensor. Karube, I., Matsunaga, T., Mitsuda, S. and Suzuki, S. (1977) Microbial electrode BOD sensor. Biotechn. Bioeng., 19, 535–547. Karube, I. (1986) Trends in bioelectronics research. Science Technol. Japan, July/Sept. 32–40. Karube, I., Yokoyama, K., Sode, K. and Tamiya, E. (1989) Microbial BOD sensor utilizing thermophilic bacteria. Anal. Lett., 22, 791–801. Kasel, A., Grabert, E. and Frischwasser, H. (1996) Studies on the measurement of the Biochemical Oxygen Demand (BOD): sensor-BOD in comparison with BOD5 according to DEV H 51. BIOspektrum: PE032. Kulys, J. and Kadziauskiene, K. (1980) Yeast BOD sensor. Biotechn. Bioeng., 22, 221–226. Li, Y.R. and Chu, J. (1991) Study of BOD microbial sensors for waste water treatment control. Appl. Biochem. Biotechnol., 28, 855–863. Li, F. and Tan, T.C. (1994) Monitoring BOD in the presence of heavy metal ions by a poly(4vinylpyridine) coated microbial sensor. Biosensors and Bioelectron., 9, 445–455. Merten, H. and Neumann, B. (1992) BSB-Kurzzeitmessung mit Biosensor. BioTec, 6. Ohki, A., Shinohara, K. and Maeda, S. (1990) Biological Oxygen demand sensor using an arsenic resistant bacterium. Anal. Sci., 6, 905–906. Page 181 Preininger, C., Klimant, I. and Wolfbeis, O.S. (1994) Optical fiber sensor for biological oxygen demand. Anal. Chem., 66, 1841–1846.

Rajasekar, S., Madhav, V.M., Rajasekar, R., Jeyakumar, D. and Rao, G.P. (1992) Biosensor for the estimation of biological oxygen demand based Torulopsis Candida. Bulletin of Electrochem., 8, 196–198. Reiss, M., Tari, A. and Hartmeier, W. (1993) BOD-biosensor basing on an amperometric oxygen demand electrode covered by Lipomyces kononenkoae. Bioengineering, 9, 87. Riedel, K. (1997) Microbial BOD sensors: Problems of practical use and comparison of sensorBOD and BOD5. In Frontiers in biosensorics, Scheller, F.W., Schubert, F. and Fedrowitz, J. (eds.) 2, pp. 99–108, Basel, Boston, Berlin: Birkhäuser Verlag. Riedel, K. and Kunze, G. (1997) Rapid physiological characterization of microorganisms by biosensor techniques. Microbiol. Research, 152, 233–237. Riedel, K., Renneberg, R., Kühn, M. and Scheller, F. (1988) A fast estimation of BOD with microbial sensors. Appl. Microbiol, Biotechn., 28, 316–318. Riedel, K., Lange, K.P., Stein, H.J., Kühn, M., Ott, P. and Scheller, F. (1990a) A microbial sensor for BOD. Water Res., 24, 883–887. Riedel, K., Renneberg, R., Lange, K.P., Ott, P. and Scheller, F. et al. (1990b) Mikrobiologisches Sensorsystem zur Bestimmung des “Biochemischen Sauerstoffbedarfs” (BSB) von komplex zusammengesetzten, höhermolekularen Verbindungen enthaltenen Medien. DD-Patent 275 379 A3. Riedel, K., Neumann, B., Klimes, N., Fahrenbruch, B., Scheller, F., Merten, H., Klinger, E. and Stein, H.-J. (1991) A microbial sensor for BOD. GBF Monographs, 17, 51–54. Riedel, K., Kloos, R. and Uthemann, R. (1993) Minutenschnelle Bestimmung des BSB. LWB Wasser, Boden undLuft, 11/12, 35–38. Riedel, K. and Uthemann, R. (1994) SensorBSB—ein neuer mit Biosensoren gewonnener Summenparameter in der Abwasseranalytik. Wasserwirtsch.—Wassertechn., 2, 35–38. Riedel, K., Uthemann, R., Yang, X. and Renneberg, R. (1997) Determination of BOD with a combination-sensor containing Rhodococcus erythropolis and Issatchenkia orientalis., Biosens. Bioelectron., unpublished. Riedel, K., Lehmann, M., Renneberg, R. and Kunze, G. (1997b) Arxula adeninivorans based sensor for the estimation of BOD. in Anal. Lett., 31, 1–12. Slama, M., Zaborosch, Ch. and Spener, F. (1995) Microbial sensor for rapid estimation of Biochemical Oxygen Demand (BOD) in presence of heavy metal ions. In Heavy metals in the environment, Wilken, R.-D., Förster, U. and Knödel, A. (eds.) 2, pp. 171–174, Edinburgh: CEP Consultants Ltd.

Sohn, M.-J. and Hong, D. (1993) Comprehension of the response time in a microbial BOD sensor (II). Bull. Koraean. Chem. Soc., 14, 666–668. Strand, S.E. and Carlson, D.A. (1984) Rapid BOD measurement for municipal wastewater samples using a biofilm electrode. J. Water Pollut. Control Fed., 56, 464–467. Su, Y.C., Huang, J.H. and Liu, M.L. (1986) A new biosensor for rapid BOD estimation by using immobilized growing cell beads. Proc. Natl. Sci. Counc. B. ROC., 10, 105–112 . Szweda, R. and Renneberg, R. (1994) Rapid BOD measurement with the Medingen BODmodule. Biosensors and Bioelectron. 9, IX–X. Tan, T.C., Li, F., Neoh, K.G. and Lee, Y.K. (1992) Microbial membrane modified dissolved oxygen probe for rapid biochemical oxygen demand measurement. Sensors and Actuators B, 8, 167–172. Tanaka, H., Nakamura, E., Minamiyama, Y. and Toyoda, T. (1994) BOD biosensor for secondary effluent from wastewater treatment plants. Wat. Sci. Tech., 30, 215–227. Zhang, X., Wang, Z. and Jian, H. (1986) Microbial sensor for the BOD estimation. Huanjing Kexue Xuebao, 6, 184–192.

4.3. OTHER ORGANIC POLLUTANTS 4.3.1. ENZYMATIC BIOSENSORS

IOANIS KATAKIS, MÒNICA CAMPÀS and ELENA DOMÍNGUEZ The majority of efforts and publications on enzymatic environmental biosensors has been dedicated to phenolic compound sensors. However, some publications appeared on innovative approaches for correlation with environmental parameters of analytes measured with well studied enzymatic systems and on the use of new biomaterials for the detection of compounds determined with difficulty, in the catalytic or inhibition mode, and these efforts are given special consideration below. 4.3.1.1. Sensors for phenolic compounds

Phenolic compounds are seen from Tables, 4.1 and 4.2 to be important water contaminants. They are included in the priority lists for strict monitoring in almost all industrialised countries. The official method for their determination is colourimetric detection of the reaction product with 4aminoantipyrine after sample pretreatment including distillation and/or chloroform extraction (EPA Methods 1983). The “phenol index” that is determined in this way is used as a measure for the quality of drinking, coastal, and surface water. Since the 1970s there have been efforts to replace or complement the time-consuming and laborious 4-aminoantipyrine method with enzymatic sensors. Most of such biosensors have been based on the enzyme tyrosinase (E.C. 1.14.18.1) and on electrochemical transduction. Mechanistic aspects of the action of this enzyme and the usual transduction schemes were summarised on several occasions recently (Peter and Wollenberger, 1997; Wittmann and Schmid, 1997; Wittmann et al., 1991; Burested et al., 1996; Sánchez-Ferrer et al., 1995). In short, this copper enzyme possesses two activities, mono- and di-phenolase. Due to the predominant presence of the mono phenolase inactive form (met-form) in commercial enzyme preparations, the enzyme is slow to respond and is inefficient as a detector of phenolic compounds. However, in the presence of a diphenol, the catalytic cycle is activated producing quinones and the scheme results in an efficient biorecognition cascade. This activation is achieved more efficiently when combined with electrochemical detection through the reduction of the quinones produced. This general catalytic scheme is summarised in Figure 4.10. The electroreduction has been performed on graphite (Narváez et al., 1996; Ortega et al., 1993), composite (Lutz and Domínguez, 1996; Onnerfjord et al., 1995; Wang et al., 1994a), and carbon paste (Burstdt et al., 1995; Wang and Chen, 1995; Wang et al., 1994b; Skládal, 1991) electrodes, but its poor reversibility and the possible polymerisation of by-products led to sensors with poor stability and high detection limits. More recent efforts claim to improve the reversibility of the electroreduction step by the use of surface modified electrodes (Hedenmo et al., 1997;

Page 183 Table 4.14. Phenolics Sensors Based on Tyrosinase. Electrode Configuration

Analysis Linear Detection Sensitivity Response Stability Mode Range/µM Limit/µM nA Time/s −1 −2 µM cm

GC

FIA

References

–

0.014– 0.058

650– 37000

2

6 h contin. Adeyoju et al., 1996

GC/Polypyrrole SteadyState

–80

0.04

0.1–300

3

–

Cosnier and Innocent, 1992

GC/Polypyrrole SteadyState

0.01–70

0.01

246

30

–

Besombes et al., 1995a

GC/Cellulose Gel

SteadyState

5–100

0.5

87 org. solvents

>60

3 months 4°C 3 h contin.

Deng and Dong, 1995

Composite

FIA

10–100

1

31

–

↓ 10% (20 Wang et h) al., 1994a

Composite

FIA

10–300

1

11

12

14 days

Graphite

SteadyState

0.7–25

0.24

820

12

1 h contin. Kulys and Schmid, 1990

Graphite

FIA

0.01–< 5

3 10−3

490

2

1 month stor.

Ortega et al., 1993

Graphite/Micelle SteadyState

20–140

6

112

20

48 h

Liu F. et al., 1994

CP

–

–200

0.013

1450

120

1 h contin. Skládal, 1991

CP

SteadyState

0.005– 0.05

0.3

–

60

↓ 20 % (2 Wang and weeks) Chen, 1995

CP (Ru dispersed)

FIA

100–600

15

0.8

40

–

CP/dodecane

FIA

1–10

–

226

107

at least 2.5 Wang et h al., 1997a

CP/quinone

FIA

–

0.01

39

60

>5h contin.

mediator > 7 days

Önnerfjord et al., 1995

Wang et al., 1994b

Hedenmo et al., 1997

stor. Screen Printed

−3

SteadyState

0.05–14

0.25 10

Flow through

21–149

0.03 (gas) 300–5000 60–600

250

2–5

Graphite NMP+

disposable Kotte et al., 1995 20 days stor.

mediator Gold Array/

5 days contin.

Dennison et al., 1995

Glycerol gel Chamber GC: glassy carbon CP: carbon paste

Figure 4.10. Proposed enzyme mechanism of Tyrosinase. Kotte et al., 1995; Kulys and Schmid, 1990). Such electrodes lowered substantially the detection limits and improved the operational stability of the biosensors. Other efforts using tyrosinase electrodes have centered on the use of these biosensors for detection of phenolic compounds in organic solvent and gas (Saini et al., 1995; Dennison et al., 1995). The analytical characteristics of the most representative efforts using tyrosinase as the biorecognition element for phenolics detection are included in Table 4.14. The most advanced of these sensors are currently at a preprototype stage developed by the Umweltforschungszentrum Leipzig-Halle/Senslab GmbH in

Germany consisting of a screen-printed electrode incorporating a zeolite impregnated with NMP+ that acts as a catalytic site for the reduction and recycling of the enzymatically produced quinones to catechol. The detection limits of these disposable sensors reached the sub nM level and were used in real samples without any pretreatment. These sensors were validated with the 4-aminoantipyrine method (Kotte et al., 1995) and the results were satisfactory due to the phenolic nature of about 90% of the signal of the phenol index (Narváez et al., 1997). It therefore appears that a product based on this or a similar technology may soon result from the almost twenty years of research efforts on tyrosinase sensors. In the same work it was noted however that the selectivity of tyrosinase for different phenolic compounds is quite distinct from that of the 4-aminoantipyrine method. The majority of the polychlorinated and nitro- and aminophenols are not oxidised by tyrosinase, although at least some of them give moderate to full signals with the 4-aminoantipyrine method. This fact does not necessarily mean that a biosensor based on tyrosinase is doomed to fail as a phenolics sensor. It is possible for example to develop a “biosensor phenol index” that could be used as a satisfying substitute in the thousands of possible phenolics determinations in industrial, regulatory and even household situations, though it may never acquire legislative relevance. However, even the best tyrosinase sensors have detection limits barely sufficient for the low detection limits required for drinking water analysis. An elegant solution to this problem was suggested by Markower et al. (1996) where the quinones produced by the tyrosinase enter an enzymatic amplification cascade mediating a dehydrogenase co-immobilized on the electrode surface in the presence of its cosubstrate. As the specificity of the biosensors for phenolic compounds remained as the major problem, furthermore as the most toxic phenols, the ortho- and polysubstituted phenols, are no substrates of the tyrosinase, other enzymatic systems were sought as biorecognition elements. Biosensors for phenolic compounds based on laccases and peroxidases were reported (Marko-Varga et al., 1995; Yaropolov et al., 1995) and one report by Ruzgas et al. (1995) showed the detection of even chlorophenols with peroxidase. It remains to be seen whether this configuration leads to a biosensor that yields results that correlate better with the 4-aminoantipyrine index. The mechanism of action of laccases is less known than that of tyrosinase, with a wide selectivity for p-diphenols, catechols and aromatic amines (Thurston, 1994). Peroxidases however, would accept almost any reductant as substrate and for this it is conceivable that a broad range of phenols could be detected by those sensors. On the other hand, the broad substrate specificty of the enzyme causes problems in the interpretation of the analytical signal if the sensor is used without a pretreatment step. Kinetic resolution of the response and signal processing may be useful in this respect. 4.3.1.2. Enzyme sensors for other organic compounds

From Table 4.2 and from the ATSDR list of hazardous compounds (see Appendix) (http:\www.epa.gov/) several single compounds of environmental relevance can be targeted for detection by biosensors. Such sensors would correspond to the first “niche” already mentioned above (p. 147). It should be noted that such sensors should meet the most stringent reliability and operability criteria if they are to be used routinely in waste water analysis. Organic acids, aldehydes, polycyclic aromatic hydrocarbons, etc. can be included in the list of such target compounds. In this line, some sensor configurations appeared in recent years in the literature. Although most of these works are limited to a proof of concept level, they are worth mentioning

here since they demonstrate the possibility for the development of enzymatic biosensors for a variety of environmental applications. In some cases, new enzymes (not commercially available) were isolated to transform catalytically the contaminant, a strategy that shows an alternative way to antibodies raised as biorecognition elements (Chap. 4.3.3.). Page 186 Table 4.15. Enzyme Sensors for Specific Compounds in Water. Analyte

Enzyme

Glucose and Lactic acid

Benzoic acid

Stability

Application

References

Glucose Ox 100 glucose and Lactate Ox 0.05 lactate

glucose: stable at least 1 day lactate: ↓ 50% in 1 day

Detection of silage effluent pollution in river water

Stephens et al., 1997

Tyrosinase

10

–

–

Smit and Rechnitz, 1993b

Phenol, Catechol, p- Tyrosinase Cresol, 2Chorophenol

5 (phenol)

1 month stor.

Identification Burestedt and et al., 1995 quantification of spiked river water samples

Phenol, p-Cresol, 4- Tyrosinase Chlorophenol Methoxyphenol

–

–

Identification Wang et and al., 1997a quantification of spiked river water samples

Chlorophenol

0.4

↓ 15%, 7 days

Monitoring of Besombes chlorophenols in et al., water 1995b

Tyrosinase

Detection Limit/µM

↓ 80%, 54 days Hydrogen Peroxide and 2-Butanone Peroxide

Peroxidase

10

–

Measurements Wang et in untreated al., 1996a river and ground water samples

Atrazine, Phenol, Pentachlorophenol, Cadmium and Chromium

23 enzymes

–

–

Identification of Cowell et metal and al., 1995 organic pollutants in potable water

Benzoic acid and Ammonia

Nitrilase

150

7 days at 25°C

Organonitrile Liu et al., determination in 1995 water

Aldehydes

Aldehyde DH 5 – benzaldehyde

–

Pariente et al., 1995

Formaldehyde vapour

Formaldehyde 0.3 DH

7h continuous

–

Hammerle et al., 1996

Formaldehyde and Formic acid

Formaldehyde – DH and Formate DH

–

Formaldehyde Ho, 1987 determination in water and biological samples

Purines

Xanthine Ox

–

–

–

Urea

Urease

1–100

1 month stor.

Analysis of Zhylyak et water pollution al., 1995 by heavy metals

Barbosa et al., 1995

Ox: oxidase DH: dehydrogenase Thus, Liu et al. (1995) demonstrated a benzonitrile biosensor using a Rhodococcus sp. nitrilase for the hydrolysis of the analyte to benzoic acid and ammonia. The benzoic acid was reduced on a glassy carbon microelectrode where the biotinylated nitrilase had been immobilized. Stable responses were obtained and the sensor could detect 0.15mM benzonitrile both in aqueous and organic solvents. Smit and Rechnitz (1993a) were the first to use tyrosinase in its inhibition mode to detect benzoic acid. Although the work was not more than a proof-of-concept effort, it suggested that the judicial use of electroactive diphenols as substrates for tyrosinase could provide a means to differentiate between different inhibitors of the enzyme without the need for signal processing. Besombes et al. (1995b) also used tyrosinase in an inhibition sensor for the measurement of chlorophenols, pesticides and cyanide, achieving µM detection limits in water samples in the presence of various tyrosinase substrates for the baseline current. The enzyme electrode was constructed by electropolymerisation of an amphiphilic pyrrole-tyrosinase sensing layer. A detailed study on the use of combinations of inhibited enzymes for the detection of five contaminants (among those pentachlorophenol and phenol) and signal processing with neural networks (Cowell et al., 1995) showed a way to improve the reliability of inhibition sensors. Wang et al. (1996a) showed that peroxidase-based electrodes can be used for remote sensing applications in natural water simulating conditions for the detection of organic peroxides (2butanone peroxide) at the µM level. An aldehyde sensor based on NADH-producing aldehyde dehydrogenase immobilised on an electrode surface modified with quinoid functionalities for the catalytic recycling of NADH to NAD+ (Pariente et al., 1995) was demonstrated, although the problem of NAD+ -immobilization

was not solved, but such sensor could be conceivable in a FIA environment. A similar enzyme was used by Hammerle et al. (1996) to produce a gas sensor for formaldehyde. The principle of the use of formate dehydrogenase for the detection of formic acid was also shown earlier (Ho, 1987). Finally, the action of xanthine oxidase on purines (Barbose et al., 1995) was studied, demonstrating that an exhaustive study of the action of new and existing enzymes on contaminants could lead to configurations that could be used in environmental applications. The potential of using in an innovative way known and well-developed biosensor technology to provide new environmental pollution indicators that are useful to specific industries when combined with the capacity to provide rapid and reliable measurements was demonstrated by Stephens et al. (1997). In this work the authors showed the opening of possible market niches using glucose and lactate biosensors in silage effluents at different maturation stages of stored silage. In this manner, water management can be rationally designed. The sensors were validated with effluent from silos showing a satisfactory reliability completing an analysis in less than a minute. The most representative efforts to develop enzyme sensors for specific organic compounds in water are summarized in Table 4.15. REFERENCES

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4.3.2. MICROBIAL SENSORS FOR DETERMINATION OF AROMATICS AND THEIR HALOGENATED DERIVATIVES

KLAUS RIEDEL, TILL BACHMANN AND ROLF D.SCHMID 4.3.2.1. Introduction

Aliphatic and aromatic hydrocarbons and their chlorinated derivatives as well as organophosphorus and carbamate insecticides play an important role in industry and agriculture as pesticides, fungicides, herbicides, detergents and pharmaceuticals etc. (see ATSDR-list in Appendix). Due to their possible toxicity and persistence in the biosphere they have a high impact on the environment. Therefore their monitoring is essential for environmental protection and waste control. Conventional analysis by chromatographic methods is expensive and timeconsuming with regard to sample preparation and sample throughput. However, biosensors based on microorganisms, enzymes or antibodies open new possibilities for rapid analysis. Microorganism-based biosensors have been described for following aromatics: phenol, benzoate, naphthalene, dibenzofuran, biphenyl and their chlorinated derivatives. All the microorganisms used for these biosensors, degraded aromatics with oxygen consumption. The utilisation of microorganisms in biosensors requires some microorganisms which have adapted their metabolism to these unnatural compounds or their metabolic enzymes to be are active towards these substances. In general, the aerobic degradation of aromatics shows a high similarity for all microbial species. The aerobic microbial degradation of aromatics is mainly performed by a common mechanism (Figure 4.11) (Dagley, 1987): The initial reactions are the formation of diols by dioxygenases. This diols (catechol) are the key intermediates of aerobic degradation of aromatics. The following step is the cleavage of catechol to muconic acid. Further cleavage and oxidation reactions may lead to complete mineralization. Due to the fact, that the aerobic degradation of the various aromatics leads to general intermediates, microbial biosensors are relatively unspecific. The key metabolite catechol or the adequate diol structure of an aromatic compound causes a very high signal with all microbial sensors. The first step of degradation is the most specific and the formation of adequate enzyme is induceable. This opens the possibility to improve the sensor’s selectivity and sensitivity. The induction of desired enzymes can be obtained by direct cultivation of the microorganisms being used for the sensor with the analyte as sole carbon source. On the other hand the microrganisms on the sensor can be directly induced with an adequate aromatic compound as demonstrated for example with the Rhodococcus-sensor for determination of phenol and benzoate (Riedel et al., 1991) (Table 4.16). The sensor was almost specific to phenol, when cultivated with phenol. The cultivation with benzoate caused a specificity for benzoate only. In case of the Rhodococcus sensor the specificity of the microbial sensor increased after incubation of the sensor itself with the desired substrate. Also the incubation of the sensor containing phenol-cultivated cells with benzoate leads to a drastical increase of signal for this compound. These investigations of the Rhodococcus sensor demonstrate both the advantage and disadvantage of cell- and enzyme-sensors (Table 4.17). Indeed the sensor with enzyme extract of phenol-cultivated cells had a high specificity to Page 193

Figure 4.11. General scheme of aerobic degradation of aromatics by microorganisms. phenol, but a need for a cofactor and very little stability. Furthermore, the aerobic degradation of aromatic compounds is an enzymatic multistage reaction and therefore difficult, if not impossible to achieve with enzyme sensors. Table 4.16. Improvement of specificity and sensitivity of an Rhodococcus containing biosensor by cultivation or incubation with phenol or benzoate (substrate concentration: 20 µmol/l) (Riedel et al., 1991). Analyte

Signal [na/min] Cultivation with phenol

Glucose Phenol Benzoate

Incubation of “benzoate”-cells with

benzoate

phenol

benzoate

0

0

36

0

166

0

206

0

0

427

560

677

Page 194 Table 4.17. Comparison of phenol sensors consisting of Rhodococcus cells or enzymes from Rhodococcus (Riedel et al., 1991). Cell sensor

Enzyme sensor

Measuring range [µmol/l]

2–80

2–10

Detection limit [µmol/l]

2

2

Stability [h]

336

12

Need of cofactors

no

NADPH

Interferences

catechol

m-cresol

o-cresol m-cresol chlorophenols 4.3.2.2. Phenol and non-chlorinated phenolderivates

The use of the following microorganisms in combination with oxygen electrodes has been described for the determination of phenol: Trichosporon cutaneum (recently reclassified as T. beigelii), Candida tropicalis, Rhodococcus, Bacillus subtilis, Pseudomonas sp. and Alcaligenes sp. Table 4.18 gives an overview of the characteristic parameters of Table 4.18. Microbial sensors for phenol detection with oxygen electrodes. Microorganisms Specificity

Detection limit [µmol/l]

Trichosporon cutaneum (beigelii)

phenol

20 (=2 mg/l) 5

0.25

5

Neujahr and Kjellen, 1979

Rhodococcus sp. phenol

2(=0.2mg/l) 5

0.25

14

4 (=0.5 mg/l)

5.5

0.25

21

Riedel et al., 1991, 1993

0.5

n.d.

30

n.d.

Gaisford et al., 1991

0.2

12

Ciucu et al., 1991

chlorophenols Escherichia coli phenol chlorophenols

Standard Response Stability References deviation time [d] [%] [min]

(=0.05 mg/l) pentachlorphenol Rhodotorula sp. phenol

10(=1 mg/l) 2

Pseudomonas putida

phenol nitrophenol 2 (=0.1 pyrocatechol mg/l) mesityl oxide aniline 17(1 mg/l)

Azotobacter sp.

phenol hydroquinone catechol chinhydrone

5

20 (=2 mg/l) n.d.

5

1

Ignatov et al., 1995, Rainina et al., 1996

4

n.d.

Reiss et al., 1995

20 (=2 mg/l)

microbial sensors for phenol determination. However, phenol derivates interfered with phenol signals. Catechol and resorcinol where most likely to cause trouble whereas cresols and chlorophenols had little effect. Moreover, common substrates, such as glucose and amino acids, caused small signals only. A Rhodococcus P1, which has been isolated from the sediment of river Saale, in particular had a very high sensitivity to phenol and benzoate, but scarcely reacted to glucose. Therefore, this species is especially suitable for phenol sensors. Pseudomonas putida GFS-8-containing biosensors enable the determination of aniline in addition to phenol (Rainina et al., 1996). The relative activity with aniline is 71% compared to phenol. Furthermore the use of microbial sensors for determination of 2-ethoxyphenol with a Rhodococcus rhodochorus 116-containing sensor has been described (Beyersdorf-Radeck et al., 1994). This microbial sensor reacted to 2-ethoxyphenol with an higher signal than with glucose. The chemically similar compound 2-methoxyphenol and the degradation product catechol as well as glucose and acetate also led to a detectable signal. However, the glucose signal was smaller than the one for 2-ethoxyphenol. As the detection limits reached with any of the described sensors were higher than the 0.5 µg/1 prescribed as the maximum permissible concentration by the EC Directive for Drinking Water, the practical use of microbial phenol sensors is presently not practicable. The WHO (World Health Organisation) recommends a maximum phenol concentration in water of 1 µg/1. 4.3.2.3. Benzene

An optical biosensor has been developed for the determination of benzene using a genetically modified bacterial strain by Ikariyama et al. (1993). The TOL plasmid, responsible for degradation of benzene, was fused with the gene of firefly luciferase to breed a luminescent E. coli. The detection limit for benzene was 10 ppm (10 mg/l) with an measuring time of 4 min. The specificity of this sensor allowed a complex determination of benzene derivates only. In comparison to this, an amperometric biosensor consisting of Pseudomonas putida ML2 was more suitable with regard to sensitivity and specificity, as shown in Table 4.19 (Tan et al., 1994). 4.3.2.4. Polycyclic aromatic hydrocarbons (PAH)

Microbial PAH sensors have been described for detection of naphthalene, dibenzofurane and biphenyl based on the ability to aerobically degrade PAH. A Pseudomonas sp. HH693containing biosensor showed response to dibenzofurane (Beyersorf-Radeck et al., 1998). This sensor was also highly sensitive to metabolic intermediates like 2,3-dihydroxybenzofurane and

catechol, but also similar compounds, led to even higher signals than dibenzofurane. Microbial sensors using Rhodococcus globerulus (old designation: Corynebacterium MB1) reacted to biphenyl, but the signal was smaller than for catechol, 2,3-dihydroxybiphenyl and phenol (Beyersdorf-Radeck et al., 1991, 1993). Therefore, it was possible to detect biphenyl and dibenzofurane in real samples. The sensitivity and specificity reached with sensors for determination of dibenzofurane and biphenyl has not yet allowed practical applications. Page 196 Table 4.19. Microbial sensors for benzene detection. Microorganism Transducer Detection limit (mg/l) Response time (min)

Recombinant Escherichia coli Optical Sensor (luminescence) (Ikariyama et al., 1993)

Pseuodmonas putida ML2 Amperometric Sensor (oxygen) (Tan et al., 1994) 10 5 5 2–10

Sensitivity (in relation to benzene) [%] Benzene [%]

100 100

Toluene

150 2.4

o-Xylene

52 0.3

p-Xylene

46 0.3

m-Xylene

120 0.3

Ethylbenzene

26 1.3

Ethyltoluene

24 n.d.

Chlorotoluene

73 n.d.

Moreover, the sensitivity of a biosensor containing Sphingomonas sp. or Pseudomonas fluorescent allowed the specific determination of naphthalene (König et al., 1996). Table 4.20 gives an overview of the characteristic parameters of these biosensors. Biosensors using Sphingomonas sp. B1 or Pseudomonas fluorescens WW4 reached a remarkably low detection limit of 10 µg/l naphthalene (König et al., 1996). However this sensitivity was not sufficient for drinking water monitoring. The upper limit for PAH concentrations in drinking water is prescribed to be 0.2 µg/1. Moreover, both biosensors showed relatively large responses to salicylate and acetate. The sensitivity and specificity of an optical biosensor based on a genetically engineered bioluminescent catabolic reporter bacterium was also not sufficient for practical use. This sensor was developed for the determination of naphthalene and salicylate by Heitzer et al. (1994). The bioluminescent bacterium, Pseudomonas fluorescens HK44, carried a transcriptional fusion of the nahG gene of the salicylate operon from Pseudomonas fluorescens and the luxCDABE gene cassette from Vibrio fischeri. The detection limit for salicylate and naphthalene was 0.5 mg/l and 1.55 mg/l respectively.

4.3.2.5. Chloroaromatics

Products derived from chloroaromatics or generally haloaromatic compounds are of great industrial importance. Furthermore, chloroaromatic compounds can also be formed as side products during drinking water preparation via the chlorination step. Due to the assumed high toxicity and persistence of these substances, they are suspected to cause considerable problems in the environment. On account of their toxicity the upper limit of these compounds is prescribed as 0.2 µl/l by the EC Directive for Drinking Water. The extremely restricted ability of animals to degrade haloaromatics causes among other things an enhanced persistence of chlorinated hydrocarbons in the environment. Fortunately, some microbial species are capable of Page 197 Table 4.20. Microbial sensors for detection of naphthalene and salicylate.

Transducer

Sphingomonas sp. B1 (König et al., (1996)*)

Pseudomonas fluorescent WW4*) (König et al., 1996)

Ps. fluorescens HK 44 (genetically engineered) (Heitzer et al, 1994)

amper. oxygen electrode

amper. oxygen electrode

optical sensor

Detection limit [mg/l] Naphthalene

3

3

1.55

1.5

4

0.5

3–5

3–5

8–15

20

20

9

5

5

10

100

100

100

60

25

32

Toluene

n.d.

n.d.

30

Benzoate

35

2

n.d.

Acetate

22

67

n.d.

Pyruvate

17

56

n.d.

Ethanol

15

160

n.d.

Salicylate Response time [min] Stability [d] Standard deviation [%] Sensitivity [%] (in relation to Naphthalene) Naphthalene Salicylate

* Upper limit of linear range. degrading such compounds (Westmeier and Rehm, 1985; Reineke, 1986; Reineke and Knackmus, 1988; Sangadkar et al, 1989; Häggblom, 1990; Neilson, 1990). It is suggested that two types of mechanism are operative. First, microorganisms may have evolved specific enzyme systems for the degradation and dehalogenation of halogenated compounds and second, the

haloaromatics may be metabolized and splitted without dehalogenation by enzymes that have to degrade the base compounds. The crucial point is the removal of halogen substituents from the organic base compound. Two distinct mechanisms for this are known: the halogen is removed from the aromatic ring either (i) at early stage of the degradation pathway with reductive, hydrolytic, or oxygenolytic elimination, or (ii) after ring cleavage from aliphatic intermediates by hydrolysis or hydrogen halide by βelimination spontaneously. This ability is used for the development of microbial chloroaromatic sensors. Table 4.21 gives an overview over these biosensors. In general, the specificity is very poor, Page 198 Table 4.21. Microbial sensors for the determination of chlorinated phenols and benzoates. Analyte

Chlorobenzoates

Microorganisms

Pseudomonas putida 87

Rhodococcus sp. P1 Trichosporon beigelii (cutaneum)

Reference

Riedel et al, 1991

Riedel et al., 1993

Main substrate

344-Monochlorophenol Monochlorobenzoate Monochlorophenol

Detection limit [mg/l]

Chlorophenols

Riedel et al., 1995

50

0.4

0.2

0.25

0.25

0.25

Standard deviation [%]

5.5

5.5

5.5

Stability [d]

n.d.

>21

>21

100

14

0

3Monochlorobenzoate

39

8

42

2Monochlorobenzoate

9

11

0

4Monochlorobenzoate

24

1

0

2,4-Dichlorobenzoate

6

2

n.d.

Phenol

0

100

100

2-Monochlorophenol

n.d.

43

373

3-Monochlorophenol

9

45

875

4-Monochlorophenol

4

53

1167

Response time [min]

Sensitivity [%]* Benzoate

2,3-Dichlorophenol

n.d.

36

538

2,4-Dichlorophenol

4

20

725

2,6-Dichlorophenol

n.d.

15

1077

3,4-Dichlorophenol

n.d.

20

n.d.

2,3,6-Trichlorophenol

n.d.

7

inhibition

2,4,6-Trichlorophenol

n.d.

8

inhibition

2,4,5 Trichlorophenol

n.d.

11

inhibition

2

3

Glucose

* In relation to the basic aromatic compounds benzoate and phenole, resp. caused by the degradation mechanism and the unspecific degradation enzymes. This property of microbial sensors opens the possibility of determination of sum parametrs of the desired halogenated aromatics. The microbial species mainly used for biosensors for the estimation of chlorinated aromatics are Pseudomonas, Rhodococcus, Trichosporon, Ralstonia (old name: Alcaligenes). Pseudomonas putida 87 was successfully used to determine 3-chlorobenzoate (Riedel et al., 1991). This biosensor was especially sensitive to 3-chlorobenzoate, although the signal for this compound was lower than for the non-chlorinated benzoate. The relative response of 3-chlorobenzoate was 39 % of the benzoate signal. The sensitivity against further mono- and dichlorobenzoates as well as chlorophenols was comparatively small. The relative response was under ge 199 10% in comparison to benzoate, with the exception of 4-chlorobenzoate (24%). Because detailed knowledge about the degradation mechanism of chloroaromatics by Pseudomonas exists, one is able to understand this observation. The degradation of 3-chlorobenzoate by Pseudomonas putida 87 starts with an decarboxylation producing 3-chlorophenol, which is transformed into chlorocatechol, which in turn is cleaved to chloromuconic acid and eventually dechlorinated (Grishenko et al., 1983). The determination of chorinated phenols was possible with biosensors containing Rhodococcus sp. P1 or Trichosporon beigelii (cutaneum). The Rhodococcus-sensor allowed an overall determination of mono- and dichlorophenols. The sensitivity for mono- and dichlorinated phenols was on an average 30–40 % of phenol. The chlorobenzoate was not degraded by this sensor. Moreover, an specific and sensitive determination of chlorophenols was possible with a Trichosporon beigelii (cutaneum)-containing sensor (Riedel et al., 1995). This sensor used strain Tr. beigelii E4 which had a high specificity to 4-monochloro-, 3-monochloro-, 2,4- and 2,5-dichlorophenol and showed no reaction to benzoate. All tested tri-, tetra- and pentachlorophenols where toxic for this organism. The signals for the mono- and dichlorinated phenols where markedly higher than for phenol itself. Notwithstanding this high specificity, the attained detection limit of 50 µg/l of chlorophenols means that this sensor is not yet suitable for practical application because the permissable concentration in drinking water is 0.5 µg/l phenols (EC Directive for Drinking Water, German Drinking Water Ordinance).

Microorganisms capable of degrading polychlorinated biphenyls (PCB) have been isolated and used in biosensors to determine these xenobiotics. The following three particularly interesting PCB-degrading species Ralstonia eutrophus H850 (new name of Alcaligenes eutrophus), Rhodococcus globerulus fold designation: Corynebacterium MB1, and Pseudomonas putida LB400 were used in biosensors (Beyersdorf-Radeck et al., 1992, 1993). A problem of measuring of these compounds is their hydrophobicity. Therefore PCB was disolved in dimethylsulfoxide. Table 4.22 shows, that the sensors Table 4.22. Relative specificity of microbial sensors to PCB (Beyersdorf-Radeck et al., 1992) (In relation to 3-PCB). Ralstonias eutrophus H850

Rhodococcus globerulus

Pseudomonas LB400

100

100

100

2,2′-PCB

50

40

50

2,3-PCB

130

100

138

3,3′,4,4′5,5′-PCB

205

35

120

3,3′,4,4′-PCB

115

100

200

PCB Mix

24

130

59

Biphenyl

156

44

308

Dibenzofuran

246

18

85

2,3Dihydroxybiphenyl

1568

304

1162

Catechol

1064

218

517

0

0

600

61

65

61

3-PCB

Phenol Benzoic acid

Figure 4.12. Metabolic route for the degradation of 1, 2-dichloroethane in Xanthobacter autotrophicus (Greer et al., 1989).

Page 201 reacted to PCB, but the sensitivity and specificity was not suifficient for the specific determination of PCB. Furthermore, the use of microbial sensors for the determination of 2,4-dichlorophenoxyacetic acid (2,4-D) has been described (Beyersdorf-Radeck et al., 1991, 1998). This Ralstonia eutrophus JMP134-containing sensor was very sensitive to 2,4-D and 2,4,5-T (2,4,5trichlorophenoxyacetic acid). Catechol, benzoic acid and salicylaldehyde caused higher signals, but no or very little signal was obtained for glucose, fructose, ethanol, acetate, biphenyl and phenol. 4.3.2.6. Haloaliphatic compounds

The ability of some microorganisms to dehalogenate haloaliphatic compounds was used to construct biosensors for the determination of dihalomethanes (Henrysson and Mattiasson, 1991, 1993) as well as ethyl bromide, 1,2-dibromopropane, isobutyl bromide, 1-chlorobutane and 1,3dibromobutane (Hutter et al., 1994, 1996). The most detailed knowledge of the degrative mechanisms for haloaliphatic compounds was derived from studies with Xanthobacter autotrophicus, a Gram-positive coryneform bacterium, which uses a large varity of organic compounds, especially 1,2-dichloroethane (Jansen et al., 1984, 1985, 1987). The degradation pathway of 1,2-dichloroethane involves two constitutive hydrolytic dehalogenating enzymes with a broad substrate specificity: dichloroethane dehalogenase and chloroacetic acid dehalogenase (Figure 4.12). Two possibilities to determine this microbial response to haloaliphatic compounds have been described: the halogene-sensitive electrode, and flowcalorimeter. Hutter et al. (1994) have developed a highly sensitive microbial sensor consisting of Rhodococcus sp. combined with bromide- or chloride-sensitive electrodes for determination of brominated and chorinated aliphatics in the ppb range. The detection limit for 1,3dibrompropane, was 4 µg/l and for 1-chlorobutane 50 µg/l, respectively. Relatively high specificity has been reached with a biosensor containing Hyphomicrobium DM2 with a combination of transducers consisting of a flow-calorimeter followed by a chloride-sensitive electrode (Henrysson and Mattiasson, 1991, 1993). The detection limit for this biosensor was 5 µg/l dichloromethane. Chloroforme and 1,2-dichloroethane caused no response. In contrast, the sensor showed higher sensitivity against dibromomethane. REFERENCES

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Beyersdorf-Radeck, B., Riedel, K., Neumann, B., Scheller, F. and Schmid, R.D. (1993) Entwicklung mikrobieller Sensoren zur Bestimmung von Xenobiotika. In Biochemische Methoden zur Schadstofferfassung im Wasser. pp. 141–154, Weinheim: Verlagsgesel-Ischaft mbH. Beyersdorf-Radeck, B., Karlson, U. and Schmid, R.D. (1994) A microbial sensor for 2ethoxyphenol. Anal. Lett., 27, 285–298. Beyersdorf-Radeck, B., Riedel, K., Karlson, U. Bachmann, T.T. and Schmid, R.D. (1998) Screening of xenobiotic compounds degradating microorganisms using biosensor techniques. Microbiol Res., 153, 239–245. Ciucu, A., Magearu, V., Fleschin, S., Lucaciu, L. and David, F. (1991) Biocatalytical membrane electrode for phenol. Anal. Lett., 24, 567–580. Gaisford, W.C., Richardson, N.J., Haggert, B.G.D. and Rawson, D.M. (1991) Microbial sensors for environmental monitoring. Biochem. Soc. Trans., 19, 15. Dagley, S. (1987) Microbial metabolism of aromatic compounds. In Comprehensive biotechnology, Cooney, C.L. and Humphrey, A.E. (eds.) pp. 483–505. Pergamon Press. Häggblom, M. (1990) Mechanisms of bacterial degradation and transformation of chlorinated monoaromatic compounds. J. Basic Microbiol., 30, 115–141. Heitzer, A., Malchowsky, K., Thonnard, J.E., Bienkowski, P.R., White, D.C. and Sayler, G.S., Optical biosensor for environmental on-line monitoring of naphthaline and salicylate bioavailability with an immobilized bioluminescent catabolic reporter bacterium. Appl. and Environment. Microbiol., 60, 1487–1494. Henrysson, T. and Mattiasson, B. (1991) A dichlorethane sensitive biosensor based on immobilized Hyphomicrobium DM2 cells . In Proc. Symp. Environm. Biotechnol., Verachtert, H. and Verstraete, W.F. (eds.) Oostende, 73–76. Henrysson, T. and Mattiasson, B. (1993) A microbial biosensor for dihalomethanes. Biodegradation, 4, 101–105. Hutter, W., Peter, J., Svoboda, H. and Hampel, W. (1994) Biosensorsystem für halogenierte Kohlenwasserstoffe. (in german) ECOINFORM, 5, 377–387. Hutter, J.P., Stöllnberger, W. and Hampel, W. (1996) Detection of halogenated hydrocarbons by a microbial sensorsystems using a stop-flow-techniques. Biotechnol. Techniques., 10, 183–188. Ignatov, O.V. and Kozel, A.B. (1995) The determination of aromatic compounds by microbial biosensors. In Environmental Biotechnology: Principles and Application, Moo-Young, M. et al. (eds.) pp. 66–74. Kluver Academic Publishers.

Ikariyama, Y, Nishiguchi, S., Kobatake, E., Aizawa, M., Tsuda, M. and Nakazawa, T. (1993) Luminescent biomonitoring of benzene derivates in the environment using recombinant Escherichia coli. Sensors and Actuators B, 13/14, 169–172. Janssen, D.B., Scheper, A. and Witholt, B. (1984) Biodegradation of 2-chloroethanol and 1, 2dichloroethane by pure bacterial cultures. In Innovations in Biotechnology, Houwink, E.H. and van der Meer, R.R. (eds.) pp. 169–178. Amsterdam: Elsevier Science Publishers B.V. Janssen, D.B., Scheper, A., Dijkhuizen, L. and Witholt, B. (1985) Degradation of halogenated aliphatic compounds by Xanthobacter autotrophicus GJ 10. J. Gen. Microbiol., 49, 673–677. Janssen, D.B., Keuning, S. and Witholt, B. (1985) Involvement of a quinoprotein alcohol dehydrogenase and an NAD-dependent aldehyde dehydrogenase in 2-chloroethanol metabolism in Xanthobacter autotrophicus GJ10. J. Gen. Microbiol., 133, 85–92. König, A., Zaborosch, C., Muscat, A., Vorlop, K.D. and Spener, F. (1996) Microbial sensors for naphthaline using Spingomonas sp. B1 or Pseudomonas fluorescens WW4. App. Microbiol. Biotechnol., 45, 844–550. Neilson, A.H. (1990) The biodegradation of haloaromatics. J. Appl. Bacteriol., 69, 445–470. Neujahr, H.Y and Kjellen, K.G. (1979) Bioprobe electrode for phenol. Biotechn. Bioeng., 21, 671–678. Rainina, E.I., Badalian, I.E., Ignatov, O.V., Federov, A.Yu., Simonian, A.L. and Varfolomeyev, S.D. (1996) Cell biosensor for detection of phenol in aqueous solution. Appl. Biochem. Biotechnol., 56, 117–127. Reineke, W. (1986) Construction of bacterial strains with novel degradative capabilities for chloroaromatics. J. Bacic Microbiol., 9, 551–567. Reineke, W. and Knackmus, H.-J. (1988) Microbial degradation of haloaromatics. Ann. Rev. Microbiol., 42, 263–287. Reiss, M., Metzger, J. and Hartmeier, W. (1995) An amperometric microbial sensor based on Azotobacter species for phenolic compounds. Med. Fac. Landbouw. Univ. Gent,, 60/4b, 2227– 2230. Riedel, K., Hensel, J. und Ebert, K. (1991) Biosensoren zur Bestimmung von Phenol und Benzoat auf der Basis von Rhodococcus Zellen und Enzymextrakten (in german). Zbl. Bakt., 146, 425–434. Riedel, K., Naumov, A.V., Boronin, L.A., Golovleva, L.A., Stein, J. and Scheller, F. (1991) Microbial sensors for determination of aromatics and their chloroderivates. Part I: Determination of 3chlorobenzoate using a Pseudomonas containing biosensors. Appl. Microbiol. Biotechnol., 35, 557–562.

Riedel, K., Hensel, J., Rothe, S., Neumann, B. and Scheller, F. (1993) Microbial sensors for determination of aromatics and their chloroderivates. Part II: Determination of chlorinated phenols using a Rhodococcus containing biosensors. Appl. Microbiol. Biotechnol., 38, 556–559. Riedel, K., Beyersdorf-Radeck, B., Neumann, B. and Scheller, F. (1995) Microbial sensors for determination of aromatics and their chloroderivates. Part III: Determination of chlorinated phenols using a biosensors containing Trichossporon beigelii (cutaneum). Appl. Microbiol. Biotechnol., 43, 7–9. Sangodkar, U.M.X., Aldrich, T.L., Hangland, R.A., Johnson, J., Rothmel, R.K., Chapman, P.J. and Chakrabaty, A.M. (1989) Molecular basis of biodegradation of chloroaromatic compounds. Acta Biotechnol., 9, 301–306. Tan, H.-M., Cheong, S.-P. and Tan, T.-C. (1994) An amperometric benzene sensor using whole cell Pseudomonas putida ML2. Biosens. Bioelectron., 9, 1–8. Westmeier, F. and Rehm, H.-J. (1985) Biodegradation of 4-chlorophenol be entrapped Alcaligenes sp. A7–2. Appl. Microbiol. Biotechnol., 22, 301–305.

4.3.3. OTHER TYPES OF SENSORS FOR ORGANIC POLLUTANTS

IOANIS KATAKIS, MÒNICA CAMPÀS and ELENA DOMÍNGUEZ 4.3.3.1. Immunosensors for organic compounds

The reports and activity on immunoassay development for environmental analysis including water analysis have been intense in the past few years. The reason for this growth is that immunoassays are ideal candidates for both the first and third “niche” opening strategies mentioned above. The activity is intensified because of the real need of the market for fast and reliable field analytical methods for difficult-to-detect single or group analytes. This need is created by the existence of increasing numbers of landfills and government decisions around the world for their remediation. The intense activity in this field has been evaluated in various recent works (Wittmann and Schmid, 1997; Marco and Barceló, 1996; Rogers and Poziomek, 1996; Dennison and Turner, 1995) and specific applications were recently reviewed (López-Avila and Hill, 1997; Clement et al., 1997). It should be noted, that although immunoassays based on ELISA and similar systems and on newly developed antibodies and immunoconjugates are abundant, the available immunosensor configurations reported are limited in number. Immunosensors use antibodies as biorecognition elements and the advances in hapten design and monoclonal antibody development, and the possibility of production of recombinant antibodies without the need to use small animals as hosts for raising the antibodies, raises new hopes for short turnover times and affinity modulation of the antibodies (Marco and Barceló, 1996). Although ELISA and immunomagnetic formats are readily developed once the appropriate antibodies have been raised, the development of immunosensors is far from straightforward. However, the existence of these alternatives guarantees a marketable product once a need is detected and this fact encourages private and pubic investment in the field. Several immunoassay methods have now been included in the EPA manuals and have been evaluated for reliability and compared to standard techniques (López-Avila and Hill, 1997). The transducing schemes for immunosensors are electrochemical where most of the detection processes are indirect (using competition affinity reactions of the analyte with labelled haptens) and optical or acoustic where the detection can be direct, without the need and complication of labelling chemistries. However, the acoustic sensors are usually unsuitable for detection in water samples due to water adsorption that interferes with the measurement yielding unreliable results. A major drawback in the development of immunosensors is the limited ability for regeneration of the sensors, resulting in disposable devices with little calibration capacity. The use of low affinity antibodies can overcome this problem if the detection limits are sufficiently low. Most immunosensors have been developed for pesticide detection and the interested reader is referred to chapter 4.1.2 for a detailed account. Below some of the recent efforts in immunosensor development for other organic contaminants in water are summarised including some interesting transduction approaches (ELISA-type approaches including immunomagnetic particles and microtiter plates are in general not considered biosensors, http://www.cranfield.ac.uk/biotech/disdoc.htm). By far the most widely publicised success story is the on-site detection of TNT with a portable fibre-optic evanescent wave immunosensor. The immunosensor is based on a competitive fluorescent assay on the surface of an optical fibre (Shriver-Lake et al., 1995). The device has

been used for mapping of contamination by TNT, and TNB in two US military depots. The results (Shriver-Lake et al., 1997) agreed well with the standard EPA method (reverse phase HPLC) and the advantages of performing on-site the analysis in less than 16 minutes and at a fraction of the standard method’s cost demonstrated the superiority of the biosensor. This immunosensor was regenerable, permitting calibration and increasing the reliability of the measurement. Water samples were directly analysed without any pretreatment. Another work by the same authors (Golden et al., 1997) describes the electronics and construction of the portable device that permits the simultaneous measurement from up to four fibres possibly opening the perspectives for multianalyte immunosensors. The application of the sensor for RDX detection has also been described (Bart et al., 1997). A generic immunocomposite amperometric sensor has been demonstrated at the proof of concept level by Santandreu et al. (1997) with long response times using an IgG. The competition with alkaline phosphatase-labelled anti-IgG was used to detect rabbit IgG with phenyl phosphate as substrate. The high detection potentials and irreversibility of the electrochemical reaction may limit the usefulness and life time of this sensor which is however regenerable when fresh surface of the composite is exposed. Another interesting and innovative approach for electrochemical immunosensors demonstrated in two preliminary studies uses bilayer lipid membranes for the construction of immunosensors. In one study by Nikolelis and Siontorou (1997) the incorporation of the biorecognition molecules in the BLMs resulted in enhanced stability and the electrochemical detection resulted to nM detection limits for various pesticides. In another approach Roberts and Durst (1995) reported on immunomigration sensors based on liposomes for the detection of 2.6 pmol PCBs in less than 23 minutes when inhibition of the immunospecific liposome aggregation is detected. A near-infrared fluorescence detection principle has been applied to allow the detection of nearIR-tagged small molecules with high sensitivity. The principle has been applied for ELISA miniaturisation and for bringing it one step closer to an immunosensor format with the use of miniature and inexpensive laser diodes (Wengatz et al., 1996). Along the same lines (miniaturisation) a microformat imaging ELISA has been demonstrated that can use a video detection system (Dzgoev et al., 1996). Such developments may in the next few years lead to hybrid devices between ELISA and sensors combining the advantages of both formats. A very interesting and innovative approach for the development of multianalyte fibre optic immunosensors has been described by Abuknesha and Brecht (1997), Piehler et al. (1995) where spatially resolved specific multiple auxiliary reagents have been used for the simultaneous determination of industrial pollutants and agrochemicals. This possibility has important commercial repercussions. The interesting amplification scheme for the detection of antigens amperometrically that has been introduced by Gleria et al. (1989) has been used for the detection of dinitrophenol (O’Daly et al., 1992) without however achieving the low detection limits expected for such an amplification scheme. It is possible that the problem is the fact that the immunoassay is based on the displacement of the ferrocene-labelled dinitrophenol by the analyte and its subsequent recycling on the electrode surface with a redox enzyme in the presence of its substrate.

PCB immunodetection in waters attracted most interest in the literature. Zhao et al. (1995) have demonstrated an immunosensor for the detection of 2, 4, 5-trichlorophenoxybutyrate (TCPB) with a 10 ppb detection limit. This is still higher than the 0.1 ppb required by legislation, but the sensor could be used multiple times, it had a 5 minute response time and water samples could be directly injected. Although real samples were not analysed, the device appears to be attractive for further development. It consists of a quartz fibre coated with anti-PCB antibodies that were saturated with fluorescein-labelled TCPB. The displacement of the labelled TCPB by the analyte could be detected in the evanescent field. A method for the synthesis of such fluorescently labelled antigens is described in Charles et al. (1995). Despite the microtiter assay format used for the detection of PCBs (Aroclor® 1260), the long assay time (2 h and 30 min), and the high detection limit (100 ppb) reported by Del Carlo and Mascini (1995), the incorporation of electrochemical transduction in this immunoassay is notable. An elegant and successful approach in electrochemical immunosensors for the detection of PCBs (Aroclor® 1016) in a field-portable instrument has been shown by Sadik and Van Emon (1996) using conducting electroactive polymers as an antibody immobilisation matrix and applying a pulsed waveform (pulse frequency of 120 and 480 ms) between 0.40 and −0.60 V. The oscillating potential allows the reversible transduction of molecular interactions and monitoring in real time with a limit of detection of 10 ppb. This technology may offer wider applications for real-time monitoring of pollutants in ground water (Riviello et al., 1994). Finally, although only used in ELIS A formats in water analysis, the development of some new antibodies against trichloroethylene by Hudak et al. (1995) should be mentioned. This test kit in its ELISA format had a detection limit of 1.5 ppm, still higher than the 0.5–0.1 ppm required by the legislation in waste waters. A PAH-immunoassay has been successfully used and validated with HPLC for the detection of poly cyclic aromatic hydrocarbons in 114 ground water samples fulfilling the maximum admissible values set by the German Drinking Water Act (Knopp et al., 1995). An extensive list of references of the evaluation of commercially available kits for immunoassays can be found in López-Avila and Hill (1997) and Sherry (1992). In general, it could be said that despite the numerous works describing generic immunosensors and ELIS As using new and commercially available kits, there are very few works describing immunosensors for environmental applications. The reason for this lag is probably due to the competitive advantage that ELISA enjoys for routine environmental testing (standard method, multiple samples, reliability) especially in its miniaturised or portable formats. 4.3.3.1.1. New types of sensors Some biosensing or chemical sensing schemes especially applied in environmental analysis are worth mentioning as potential technologically important developments for the future. For example, DNA intercalators can be detected with DNA-Cu(II) complexes electrochemically, and with such a molecular construct immobilised on an electrode surface the intercalating drug quinarcine has been detected (Hasebe et al., 1997). A review of this and other kinds of interactions with DNA and their use for the detection of environmental pollutants by electrochemical means has been recently presented by Wang et al. (1997b). In a specific application the detection of aromatic amines at nM levels has been reported (Wang et al., 1996b)

by stripping voltammetry of the accumulated intercalating species. The sensor was directly applied to river water samples and these detection limits were achieved after 10 minute accumulation of the intercalating species. Mecklenburg et al. (1997) have applied optical detection (fluorescence quenching) in sensors with similar principles to detect known mutagens such as bisbenzidine, and 1, 2, 4-benzetriamine. The assay is based on the reduced fluorescence of intercalated ToPro 3 at 661 nm in the presence of the organic compounds. Protein and genetic engineering can also be used to develop novel biorecognition chemistries. For example Marvin et al. (1997) report on the point mutations of sites that are known to allosterically control the binding of maltose to the maltose binding protein. The modification of such sites with fluorophores results in a co-operative change of fluorescence with the binding of maltose that permitted a sensor for maltose with a 5% accuracy and in a range of concentration spanning five orders of magnitude. In another development, Armengaud and Timmis (1997) reported on the isolation of the gene of a ferredoxin participating in the electron transfer mechanism of dioxin dioxygenase from Sphingomonas sp. Such electron transfer proteins could be used for the construction of enzymatic dioxin sensors. Finally, although there have not been any reports yet on their use for environmental monitoring, attention should be paid to the various flavin monooxygenases that with their broad specificity could be used as generic biorecognition elements in this field once appropriate transduction schemes are described. The same is true for the hydrolysing catalytic antibodies that could be raised against any relevant organic contaminant as antibodies would, but with the additional advantage of no need for regeneration once incorporated in a biosensor. One such case has been reported in the past (Blackburn et al., 1990). With the increasing blurring between chemical and bio sensors, it is expected that mixed techniques (combinatorial synthesis, libraries of catalytic DNAs or RNAs, etc.) will have significant input in new types of sensors for new applications in the near future. REFERENCES

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IOANIS KATAKIS, MÒNICA CAMPÀS, ELENA DOMÍNGUEZ and KLAUS RIEDEL The cleanup efforts of hazardous waste landfills, the need of detection of particularly hazardous compounds (see Appendix), and the increasing environmental awareness of the public are factors that point to the necessity for fast, easy to use, low cost field devices such as biosensors. However, such biosensors should be reliable and with a long shelf life even when they are disposable. These requirements are at least partly met by tyrosinase-based sensors for phenolic compounds and by microbial sensors. Microbial sensors in particular open promising possibilities for the detection of aromatics and their halogenated derivatives. Main advantages are their stability and simple preparation. The low specificity of these biosensors turns out to be an advantage, if the determination of sumparameters is considered. The big variety in biochemical and adaptation capabilities of microorganism species allows the selective determination of specific groups of aromatic compounds. However, in most cases the detection limits obtained with microbial sensors and also with tyrosinase-based sensors, which were the most investigated enzyme-based sensors in the last 15 years, are obviously too high to reach the low concentrations required for drinking water analysis

without sample pretreatment. In the case of microbial sensors future improvements are expected by genetic engineering, such as metabolic design, and by the use of analyte specific reporter systems. Usually a higher sensitivity is obtained by immunoanalytical techniques. In the absence of generic technologies for multianalyte immunosensors and of transduction schemes even for single analyte immunosensors, most of the activities in new single analytes or group-specific immunoassays centered on the development of ELISA-formats. As a result, the high initial R&D costs and the fragmented, small volume market for single analytes prohibited the participation of the private sector in environmental biosensor development. Nevertheless, there is a potential market for fast, low cost instruments, and as described above there exist even for immunosensors a conceptual basis for a number of commercially acceptable biosensors. The question is, how the costs associated with prototype and product development will be covered. The success story of the TNT evanescent wave biosensor possible shows a way, where public funds assume the majority of these costs when a well identified need is detected and addressed. It is however true that up to now the expensive transduction method used in this sensor and other such “biosensors” available in the market (e.g. from Biacore, Fisons instruments, etc., see Chap. 2.2.) has proven the only reliable technology with commercial potential, possible due to the simplicity of the detection procedure (direct assays). The high initial investment for the acquisition of such instruments limits the volume of the potential market. It appears therefore that a low cost alternative is required, and this can be either the direct optical or electrochemical detection. Reliable sensor configurations (especially for affinity sensors) with generic character are needed based on transduction schemes that could also take advantage of the new genetic engineering and combinatorial techniques for the development of recognition chemistries. The main part of efforts to launch such commercially viable alternatives seems to be falling to small start-up companies and Universities and Research Institutes. ATSDR. LIST OF HAZARDOUS COMPOUNDS 1. Acetone 2. Acrolein 3. Acrylonitrile 4. Aldrin/Dieldrin 5. Benzene 6. Benzidine 7. Benzo(A)anthracene 8. Benzo(A)pyrene

9. Benzo(B)fluoranthene 10. Bis(2-chloroethyl)ether 11. Bis(chloromethyl)ether 12. Bromodichloromethane 13. Bromoform/Chlorodibromomethane 14. Bromomethane 15. Butadiene 16. Butanone 17. Carbon Disulfide 18. Carbon Tetrachloride 19. Chlordane 20. Chlorobenzene 21. Chlorodibenzofurans 22. Chloroethane 23. Chloroform 24. Chloronaphthalene 25. Chrysene 26. Creosote 27. Creosote (Coal Tar and Wood), Coal Tar and Coal Tar Pitch 28. Cresols 29. DDT, DDE and DDD 30. Diazinon 31. Dibenz(A,H)anthracene

32. Dibenzofuran 33. Dibromochloropropane 34. Dibromoethane 35. Dichlorobenzene 36. Dichlorobenzidine 37. Dichloroethanes 38. Dichloroethenes 39. Dichlorophenol 40. Dichloropropane 41. Dichloropropene 42. Di(2-ethylhexyl) phthalate 43. Diethyl phthalate 44. Dimethylphenols or Xylenols 45. Di-N-butyl phthalate 46. Di-N-octyl phthalate 47. Dinitrobenzene 48. Dinitrocresols 49. Dinitrophenols 50. Dinitrotoluenes 51. Diphenylhydrazine 52. Disulfoton 53. Endosulfan 54. Endrin/Endrin Aldehyde

55. Ethylbenzene 56. Ethylene Glycol/Propylen Glycol 57. Ethylene Oxide (Oxirane) 58. Fluoranthene 59. Fuel Oil 60. Heptachlor/Heptachlor Epoxide 61. Hexachlorobenzene 62. Hexachlorobutadiene 63. Hexachlorocyclohexanes 64. Hexachloro cyclopentadiene 65. Hexachloroethane 66. Hexanone 67. HMX 68. Hydraulic Fluids 69. Hydrazines 70. Isophorone 71. Jet fuels 72. Methoxychlor 73. Methylenebis(2-chloroaniline) 74. Methylene Chloride 75. Methyl Mercaptan 76. Methyl Parathion 77. Methyl Terc-Butyl Ether

78. Mineral-based Crankcase Oil 79. Mirex and Chlordecone 80. Mustard Gas 81. Naphthalene and Methylnaphthalenes 82. Nitrobenzene 83. Nitrophenols 84. N-Nitrosodi-N-propylamine 85. N-Nitrosodimethylamine 86. N-Nitrosodiphenylamine 87. Otto Fuel II 88. PCBs 89. Pentachlorophenol (PCP) 90. Phenol 91. Polybrominated Biphenyls 92. Polycyclic Aromatic Hydrocarbons 93. Pyridine 94. RDX 95. Stoddard Solvent 96. Styrene 97. Tetrachlorodibenzo-p-dioxin 98. Tetrachloroethane 99. Tetrachloroethylene 100. Tetryl

101. Toluene 102. Toxaphene 103. Trichloroethanes 104. Trichloroethylene 105. Trichlorophenol 106. Trichloropropane 107. Trinitrobenzene 108. Trinitrotoluene 109. Vinyl Acetate 110. Vinyl Chloride 111. White Phosphorus and White Phosphorus Smoke 112. Xylenes

4.4. HEAVY METALS

RICHARD E.WILLIAMS, PETER-JOHN HOLT, NEIL C.BRUCE and CHRISTOPHER R.LOWE 4.4.1. INTRODUCTION

Many metals are naturally abundant and, as such, occur in forms largely inoffensive to the ecosystem. Extraction, processing and use by man often cause metals to be reintroduced to the environment in a manner potentially toxic to both man and that environment. Of these metals, some have received much attention from both environmental and sensor researchers, whereas others have been paid scant regard in the literature. This uneven interest broadly follows the differing toxicities and scales of pollution attributable to the respective elements, with the more toxic, e.g. mercury, and industrially prolific, e.g. copper and zinc, receiving most attention. These heavier metals often form a significant proportion of pollutants at sites where environmental damage has occurred. 4.4.1.1. Elements considered

“Heavy metals” has been used as a label for various, sometimes seemingly arbitrary, groups of the heavier elements. This text is no exception. Densities of the metallic elements range from 0.53 gcm−3 (lithium) to 22.6gcm−3 (osmium), with 50% having densities above 7.5 gcm−3. We have decided to consider metals above a density of 7.0 gcm−3 as “heavy”, thus adding zinc, chromium, tin, indium and manganese to the group. Although radioisotopes and scarce metals, e.g. the Lanthanides and Actinides, fall outside the scope of this text, some attention has been paid to the heavier metalloids selenium (4.79 gcm−3), arsenic (5.72 gcm−3) and tellurium (6.4 gcm−3). A list of “heavy metals” is given in Table 4.23. 4.4.1.2. Toxicity of heavy metals

A feature common to all heavy metals is a strong affinity for sulphur, and their interaction with biological systems is generally through the formation of bonds to thiol groups in proteins. Cysteinyl residues have essential roles in the function of many enzymes, particularly those involved in hydrolytic and redox catalysis, e.g. glutathione reductase. Therefore, metals interacting with the essential thiol groups of proteins can be highly detrimental, or even lethal, to a biological species. It must be noted also that some metals, e.g. copper and zinc, are essential to many organisms at trace levels, but toxic at elevated concentrations. This has significant bearing on the sensitivities and dynamic ranges required of tests for heavy metals. 4.4.1.3. Heavy metals in the environment—speciation and bioavailability

Myriad forms of the heavy metals, with greatly varying solubilities and toxicities, are known. The less soluble compounds can be found both in sediments and adsorbed to suspended particulates, e.g. methylmercurysulphide (Fergusson, 1990; Palinkas et al., 1995).

Organometallics usually exist at low overall levels, have low aqueous solubilities and tend to associate with suspended or precipitated matter (Filella et al., 1995). Since organometallics can be highly toxic, e.g. methylmercury, determination of these compounds can be necessary, despite the low soluble concentrations usually encountered. Solvent extraction of water samples is used to remove organic substances for analysis, which obtains organometallics from both association with solids and the Table 4.23. The heavy metals (Merlan, 1991). Metal and Density (g/cm3)

Main Soluble Metal Ions

Other Relevant forms

Most Toxic Forms

Selenium (4.8)

Se4+, Se6+

H2Se, (CH3)2Se

Elemental

—

AsH3, As3+

(CH3)2Te

Elemental

ZnS, ZnO

Low toxicity

3+

5+

Arsenic (5.7)

As , As

Tellurium (6.4)

Te4+, Te6+

Zinc (7.1)

2+

Zn

6+

3+

Chromium (7.2)

Cr > Cr

—

Cr6+

Tin (7.3)

Sn2+, Sn4+

Tri-organotins

CH3, Et3 derivatives

3+

Indium (7.3)

In

Little known

Little known

Manganese (7.4)

Mn2+

MnCl+, MnO4−

MnO2, Mn3O4

Little known

Little known

Sulphides

Low toxicity

Niobium (8.4) Iron (7.9) Nickel (8.9) Cobalt (8.9)

Nb

5+

3+

2+

Fe > Fe Ni

2+

2+

3+

2+

Co > Co

Elemental, Carbonyls

—

Elemental, carbonyls

Cadmium (8.7)

Cd only

—

Species dependent; Cd2+ low toxicity

Copper (9.0)

Cu2+ > Cu+

Organo complexes

Elemental, Cu2+

Polonium (9.0)

Little known

Little known

Little known

but very few soluble

Very few soluble Low toxicity

Bismuth (9.8)

2+

Ni(H2O6)

3+

5+

Bi , Bi mainly,

Molybdenum (10.2) Complex chemistry, but very Few soluble few soluble forms

Little known, low toxicity?

Silver (10.5)

Ag+

AgS, complexes Low toxicity

Lead (12.0)

Pb2+

Alkyls, carbonyls

Tetraethyl and methyl lead

Technetium (11.5)

Little known

Little known

Little known

+

3+

Thalium(11.9)

T1 > T1

Dialkyls

Tl+, notably Tl2SO4

Palladium (12.0)

Many

Many

Many, but low exposure risk

Ruthenium (12.2)

Many

Many

Many, but low exposure risk

Rhodium (12.4)

Many

Many

Many, but low exposure risk

Hafnium (13.1)

Little known

Little known

Little known

2+

Mercury (13.6)

Hg

Alkyls, phenyls

Methyl mercury

Tantalum (16.6)

Ta5+, but few soluble forms

Few soluble forms

Little known

Tungsten (19–3)

Complex chemistry, but few Few soluble soluble forms forms

Little known

Gold (19.3)

Au+, Au3+ but only soluble as complexes

Soluble as complexes

Low toxicity

Rhenium (21.0)

Probably Rh3+

Little known

Little known

Platinum (21.4)

Many

Many

Many, but low exposure risk

Indium (22.5)

Many

Many

Many, but low exposure risk

Osmium (22.6)

Many

Many

Many, but low exposure risk

aqueous phase (Stoeppler, 1991). Depending on the purpose of the analysis, distinguishing between solid phase, aqueous phase and the total metal component of a sample may be necessary (Antonovich and Bezlutskaya, 1996). Some work has focused on measuring “bioavailable” forms, rather than total metal concentrations (Selifonova et al., 1993; Virta et al., 1995), as a better indicator of sample toxicity. “Bioavailability” is, however, a poorly defined and misleading term. There is no such thing as universal “bioavailability”—interactions between a plethora of organisms and the many forms of heavy metals must be considered on individual sets of circumstances. For example, mercury exists mainly as mercuric ions in water systems (Burg and Greenwood, 1991). Since organisms as diverse as bacteria and man can ingest this water-soluble form, mercuric ions may be considered bioavailable. Whilst it can be a potent anti-bacterial, some bacterial strains convert mercuric ions to elemental mercury, which is excreted without harm to the organism (Hughes and Poole, 1989), and humans only absorb about 7% of ingested inorganic mercury (Clarkson, 1972). So whilst mercuric chloride could be classed as “bioavailable”, it is not necessarily a direct toxic threat. In contrast, methylmercury is only sparingly soluble and thus less available. Methylmercury is lethal to many bacteria, but some bacterial species are resistant to it. Humans, to whom methylmercury is highly toxic, absorb up to 95% of this compound following ingestion (Clarkson, 1972). Being lipid soluble, it also has a high bioconcentration factor, and has proved a serious toxin in the aquatic food chain (Fergusson, 1990; Alloway and Ayres, 1997). So, although less readily “available” than mercuric ions, methylmercury is a much greater toxic threat.

Sensor development for water sample analysis has inevitably focused on dissolved substances, but the purpose behind analysing a given sample type should govern the target analyte and sensor design. 4.4.1.4. Water analysis and the law

Legislation defining the permissible levels of heavy metals in drinking water, environmental waters, industrial and agricultural effluents exists in many countries. Such legislation rarely considers metal speciation, but uses parts per million or billion (ppm or ppb) etc. of total metal to define limits instead. Legal maxima for heavy metal concentrations guide the sensitivities required of methods used for water analysis, including sensors. Levels of mercury permissible by European law incorporated as the UK Water Act 1989 are given as an example (Table 4.24). These permissible levels change with some regularity, nearly always to lower concentrations, and these changes can either follow improved analytical sensitivity or drive analytical research (Wilder, 1995). 4.4.2. CURRENT ANALYTICAL METHODS

Water quality is currently screened in a number of ways, with the United Nations and Economic Commission for Europe (UN/ECE) recommended tests grouped to cover toxicity e.g. Microtox® and Toxkit; mutagenicity/carcinogenicity e.g. Mutatox® and Table 4.24. Examples of mercury levels permitted in British and European water systems. Source of Mercury

Permitted levels

Drinking water standard (Britain and Europe)

1 µg/l total Mercury

Mercury and its compounds discharged into waters, above background, in any 12 month period (Britain and Europe)

200g (expressed as metal)

Manufacture of organic and inorganic mercury compounds (Britain)

0.05 mg/l effluent 0.05 g/kg mercury processed

Manufacture of primary batteries containing mercury (Britain)

0.05 mg/l effluent 0.03 g/kg mercury processed

Mercury recovery plants, non-ferrous metal extraction and refining, plants treating toxic waste containing mercury (Britain)

0.05 mg/l effluent

Manufacture of mercury catalysts used in vinyl chloride production (Britain)

0.05 mg/l effluent 0.7 g/kg mercury processed

Industries using mercury catalysts (not vinyl chloride production) (Britain)

0.05 mg/l effluent

5 g/kg mercury processed Industries using mercury catalysts in vinyl chloride production (Britain)

0.05 mg/l effluent 0.1 g/t vinyl chloride production capacity

SOS Chromotest®; and persistence/biodegradation e.g. Biological Oxygen Demand/ Chemical Oxygen Demand (BOD/COD). None are specific for a single metal. When water samples fail the screening tests, analyses for individual metals may carried out. Tests for specific metals acceptable to both British Standards (BS) and the International Standards Organisation (ISO) are largely atomic absorption spectroscopic (AAS) methods, some with flame, e.g. ISO5961 for cadmium and ISO8288 for cobalt; some flameless, e.g. ISO5666 for mercury. BS 6068 covers such tests extensively. Determinations of certain metal species require fractionation prior to AAS, e.g. organometallics such as the alkylmercuries, tests for which use GC-AAS. Other methods include that for arsenic by a spectrophotometric assay of a silver diethyldithiocarbamate complex (ISO6595). Inductively coupled mass spectrometric methods with pre-concentration and chromatographic fractionation steps have been reported, with sensitivities as low as 100 pg Cr3+ and 200pg Cr4+ (Byrdy et al., 1995). Methods relevant to environmental analysis are reviewed comprehensively in Analytical Chemistry (Clement et al., 1997; Clement et al., 1995). The role of laboratory test methods such as the many subtle variations of AAS is not in doubt. There is, however, a growing need for rapid on site screening tests, which, for example, could enable judgement to be made about which samples require laboratory testing, or could rapidly assess the viability of an industrial waste water stream. The versatility and comparative speed of biological methods developed to date, and an increasing amount of research in environmental sensors, suggest that a biosensors approach may be productive in environmental water testing (Kong et al., 1995). The following text groups heavy metal biosensors according, roughly, to the nature of the biological entity concerned, i.e. whole organisms, whole cells or specific proteins. Metal species relevant to environmental water analysis have been summarised (Table 4.23), but we recommend “Metals and their compounds in the Environment” (Merian, 1991) as providing a comprehensive background to this subject. 4.4.3. BIOASSAYS USING WHOLE CELLS/ORGANISMS

Environmental monitoring using living organisms has ranged from exploiting particular pollution responses observed in ecosystems as early warning signs, to attempting to use specific organisms as indicators, either in the field or the laboratory. Zebra fish (Brachydanio rerio) and the crustacean Daphnia magna, amongst other species, are still widely used in static, semi-static and flow-through cells to test for general water toxicity (ISO7346/1/2/3). Such tests are, however, screening tests only, and are inadequate in themselves for defining water quality. Zebra fish tests presently remain part of the UN/ECE recommendations for water quality monitoring.

Experiments using transgenic strains of the nematode worm Caenorhabditis elegans have coupled control regions from stress-inducible genes to the lacZ reporter gene, yielding a colorimetric assay for stress on the organism. Mercury, lead, copper (II), zinc and cadmium ions all induced lacZ expression. The sensitivity of the assay to cadmium ions was shown to lie in the subtoxic region, at around a hundredth of the LC50. (Candido and Jones, 1996) Commercially available general toxicity assays employing luminescent bacteria, such as the Vibrio fischeri Microtox® system (Azur Environmental Ltd, Wokingham, UK) have been employed in studies of heavy-metal toxicity e.g. Sillanpaa and Oikari, 1996. 4.4.4. ENGINEERED MICROORGANISMS AS SENSORS

A wide variety of genes have been identified where the expression is modulated by the concentration of metal ions. By fusing the promoter region of these genes with a reporter gene whose expression is amenable to assay, it is possible to construct more specific whole-cell biosensors that are extremely sensitive. 4.4.4.1. Promoters as sensing elements

In considering the suitability of metal-inducible promoters for use in biosensors, it is worth noting that the dynamic range of their response can vary greatly. This reflects the relationships between living cells and the various metals—some metals are toxic even in trace amounts, whilst others are micronutrients, which can be toxic in excess. Rouch et al. (1995) demonstrated this in comparing mercury and copper dependent promoters. The mercury dependent PmerTPAD promoter from Tn501 is hypersensitive (Hill coefficient is around 2.6), giving a 10–90 % induction across a four-fold change in Hg2+ concentration, which permits full induction of resistance genes at subtoxic Table 4.25. Examples of whole cell luminescent biosensors for heavy metals. Analyte

Promoter Source

References

2+

Tn21 mer operon

(Virta et at., 1995)

2+

Hg

Serratia marescens

(Tescione and Belfort, 1993)

Hg2+

Tn21 mer operon (with transport system)

(Selifonova et al., 1993)

Hg

Cd2+, Zn2+, Cu2+, Hg2+, Co3+, Synechococcus metallothionein promoter, smt Ni2+

(Erbe et al., 1996)

Cu2+, Tl4+/Tl6+, As3+/As5+, Cd2+

(Collard et al., 1994)

Alcaligenes eutrophus Staphylococcus aureus

levels of mercury. In contrast, the copper sensitive promoter PpcoE is hyposensitive (Hill coefficient is around 0.6), giving a response spread over several orders of magnitude. The former

is more suited to the detection of a threshold level of mercury whilst the latter has more potential for use in a quantitative sensor. Induction of expression in the presence of the target analyte may require the interaction of protein regulatory factors with the promoter, as in the interaction between the MerR protein and the promoter region of the mer operon (Foster, 1987). Induction may be contingent on transport of the metal into the cell, which will be highly dependent on the speciation of the analyte (Foster, 1987; Silver and Misra, 1988; Silver, 1992). It is also worth noting that cell viability is needed for reporter gene expression, so analyte toxicity could restrict the dynamic range of the sensor. 4.4.4.2. Sources of promoters

As the molecular basis for heavy metal tolerance in environmental microorganisms is investigated, a growing number of metal-inducible promoters have been identified. These vary in their selectivity and sensitivity—for example, in the case of mercury, both narrow-spectrum induction by Hg2+ ions, and broad-spectrum induction by a range of organomercurial compounds in addition to Hg2+ ions, has been observed. In an alternative approach to the identification of novel promoters, a luciferase reporter gene was cloned into the Tn5 transposon and randomly inserted into the genome of Escherichia coli. This library of gene fusions was then screened to identify clones exhibiting luminescence dependent on concentration of the target metal ion. From this procedure aluminium, nickel and selenite dependent promoters were identified (Guzzo and DuBow, 1994). Examples of biosensors based on metal-inducible promoters linked with luminescence reporter systems are shown (Table 4.25). 4.4.5. SENSORS USING BIOLOGICAL MOLECULES

Heavy metals have a strong affinity for sulphur, and their effect on biological systems is mainly via interactions with thiol groups in proteins. Cysteinyl residues have essential roles in the function of many enzymes, particularly those involved in hydrolytic and redox catalysis. Inhibition of enzyme activity upon titration of active-site thiols with metal ions has formed the basis of heavy metal determination systems emerging from many groups. The metal-binding sites of many metalloproteins are extremely specific chelators for their respective targets, and monitoring the binding events, rather than any resulting catalysis, may enable the detection of metals with no known participation in enzymatic activity. Such heavy metal binding sites exist in metallothioneins and in various protein elements of bacterial heavy metal resistance mechanisms, despite having no apparent catalytic functions. In particular, a cysteine-rich heavy metal-associated (HMA) protein motif has been described in a range of proteins which specifically bind a number of different metals. With structural information becoming available for some of these (Steele and Opella, 1997), it is possible to envisage rational engineering of specificity and affinity (Hellinga, 1996). 4.4.5.1. Heavy metals as enzyme substrates

Many bacterial heavy metal resistance mechanisms are known, which may involve metal ion reductases or other proteins potentially useful in sensor research (Silver and Misra, 1988;

Cervantes and Silver, 1992; Kaur and Rosen, 1992; Nies, 1992; Silver, 1992; Lloyd et al., 1997). Mercuric reductase, involved in both “narrow” and “broad” range bacterial mercury resistance, is a well studied example. Mercuric reductase couples reduction of Hg2+ to oxidation of a nicotinamide cofactor, suggesting the possibility of a linked enzyme assay (Lowe et al., 1996). 4.4.5.2. Inhibition of enzyme activity

Heavy metals are potent inhibitors of the activity of various enzymes, and systems based on this principle have been developed. At present, however, most such systems exhibit low specificity, although they may be very effective general indicators of heavy metal or toxin presence in water samples (Wittekindt et al., 1996; Cowell et al., 1995). Exploiting enzyme inhibition in a biosensor for a specific metal species represents a considerable challenge. It appears possible to optimise specificity for Hg2+, one of the more toxic metal forms, but the specific assay of other species in complex mixtures, such as those encountered in the field, has yet to be proven. Sensitivities reported for various analytes broadly correlate with their toxicity—ranging from mercury at ng/ml through cadmium, zinc, and lead to copper at µg/ml. These methods have an intrinsic lack of specificity. Attempts to overcome this have investigated the possibility of using arrays of different enzymes to build up inhibition profiles for various inhibitors (Cowell et al., 1995; Danzer and Schwedt, 1996). Use of neural networks to perform profile crossmatching can enable identification of specific inhibitors, but it is questionable how applicable this approach could be to the complex mixtures of metals potentially present in field samples. The presence of species involved in the reaction catalysed by the enzyme may be an additional interference with inhibition-based assays, for example ammonia has given high blank readings with urease assays (Jung et al., 1995). Examples of enzyme inhibition biosensors are given (Table 4.26). Table 4.26. Examples of enzyme inhibition biosensors for heavy metals. Analyte

Enzyme

Transduction

References

Hg2+

urease

surface acoustic wave resonance

(Liu et al., 1995)

Cu2+

urease

ion-sensitive field-effect transistor

(Zuern and Mueller, 1993)

urease

calorimetric

(Mattiasson, 1978)

Hg , Cu , Cd , Co2+, Pb2+, Sr2+

urease

conductimetric

(Zhylyak et al., 1995)

Heavy metals

β-galactosidase

colorimetric, fluorometric

(Ayoub et al., 1995)

Heavy metals

oxidases

O2 electrode

(Gayet et al., 1993)

Hg

horse-radish peroxidase

chemiluminescence

(Shekhovtsova et al., 1996)

Heavy metals

urease

colorimetric

(Wittekindt et al., 1996)

Hg2+

invertase and glucose O2 electrode oxidase

Hg2+, Cu2+ 2+

2+

2+

2+

(Amine et al., 1995)

4.4.5.3. Activation of metalloenzyme function

Although a large number of enzymes require specific metal cofactors for activity, just a very few metals fill the majority of metal cofactor roles. Restoration of enzyme activity obtained in the presence of certain metal ions, which might be exploited in assaying those metal ions has, therefore, a narrow range of potential analytes. In some cases, it will be possible to use the reactivation of enzyme activity on addition of metal cofactor as the recognition process. This principle has been demonstrated in the detection of copper, which reconstituted activity in galactose oxidase and ascorbate oxidase activities, and of zinc, which reconstituted activity in carbonic anhydrase and alkaline phosphatase (Satoh, 1990). 4.4.5.4. Fluorescent probes of metal binding sites in metalloenzymes

In fluorescent probe metal assays, apoenzymes have been used as highly refined chelators of target analytes. Certain competitive inhibitors of carbonic anhydrase function by binding to the active-site zinc, preventing its participation in catalysis. The arylsulphonamide compound dansylamide has been shown to bind to enzyme-bound zinc with concomitant enhancement and blue shift of its fluorescence. Thus dansylamide can be used as a probe sensitive to zinc binding by the apoenzyme. Whilst other metals are bound by the enzyme to a certain extent, they do not interact with the sulphonamide, and a fibre-optic biosensor based on this principle has been demonstrated (Thompson and Jones, 1993; Thompson and Patchan, 1995). Furthermore, by detecting fluorescence energy transfer from a fluorescent tag to the bound metal ion, cobalt and copper binding could be detected (Thompson et al., 1996). For metals ions exhibiting d-d absorbance bands at appropriate wavelengths, this may be an alternative probe of active site occupancy. Tracking zinc concentrations by measuring fluorescence of an artificial antibody has been possible—the zinc binding site from carbonic anhydrase was grafted onto a IgG light-chain backbone—showing the potential utility of simple de-novo engineered proteins in biosensing (Wade et al, 1993; Satoh, 1993; Satoh and Iijima, 1995). 4.4.6. CONCLUDING COMMENTS

The purposes behind analysing water samples vary—i.e. is it the total load of a metal or metals in a given water system that needs to be determined, or is it just the presence above a threshold level of a single metal or single metal species? General water quality or toxicity screening will also target a number of non-metallic analytes. Is the purpose better served by a single, general screening test, or by a range of distinct methods for groups of similar analytes e.g. heavy metals, pesticides, nitrates? The form of a metal may be insoluble and largely inert upon introduction to the environment, but with time may well be altered to more soluble and toxic forms. This poses a significant analytical challenge. Is the measurement a one-off, one of a regular sequence, or even “in-line” and continuous? Is it necessary to take a sensor to the sample, or can the sample be brought to an analytical laboratory? Is the measurement for screening purposes, with any unusual results followed by more extensive laboratory analysis, or will it be relied upon alone? Although analysis tends to focus on the chemical composition of waters exiting a process or facility, it is worth remembering that the need to monitor water quality at point of intake exists, notably in the brewing industry. With a clearly understood purpose, it must then be determined that a biological sensor or system is the best option for the corresponding analytical role. UN/ECE

recommendations include integrating the assessment of water quality and effluent quality strategies, with rapid on-the-spot sample prescreening and thence stepwise testing of analyte groups from “coarse to fine”, to gather as much information as possible. Of the systems reported to date, some are commercially available and some are regularly used for environmental or water quality monitoring purposes e.g. the Microtox-® tests. The potential for effective biosensors in the environmental sphere, and the need for such systems, has been documented (Erbe et al., 1996). Of the systems in use, none is a novel biosensor in the format of e.g. the Medisense Exactech® glucose monitor; rather, they are biological systems that, with suitable instrumentation, are analytically useful. Instances of an established sensor being diverted from its intended role to measure a heavy metal have been recorded, such as mercuric ion detection with a glucose probe (Amine et al., 1995) and non-biological portable sensors for heavy metals are also being developed (Williams and D’silva, 1994). Although metals are difficult propositions for immunologists, immunoassays for some metals, including mercury, have been reported (Blake et al., 1997; Szurdoki et al., 1997). These techniques, however, do not yet appear suitable for true sensor development. Because of the wide variety of heavy metals that are of environmental relevance, technologies that can be applied to wide range of metals, both as general screening tests and in the form of metal-specific sensors, are of the most interest. We wait to see if promising research, such as that into arsenate and mercury detection (Khan et al., 1996; Lowe et al., 1996), and general toxicity screening with enzyme inhibition (Danzer and Schwedt, 1996) actually yield any commercially produced, probe or dip-stick type biosensors for a heavy metal or metals. REFERENCES

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4.5. PHOSPHATE

AXEL WARSINKE 4.5.1. INTRODUCTION

The determination of phosphate is not only important for environmental control, but also for clinical diagnostics. Various diseases are accompanied by higher or lower phosphate concentrations (e.g. chronic renal insufficiency, vitamin-D-intoxication, primary hypoparathyroididmus, raccharitis). For animals and plants inorganic phosphate and the related phosphoric acid esters have an important role in the energy status of the cell, glycolysis, mineral and nucleic acid metabolisms and for the constitution of the cell membrane. To increase the yields in agriculture phosphate rich fertilizers are frequently used. Nevertheless, only about 10 percent of the phosphate contamination in a river is due to the usage of fertilizers. The greatest part (80 %) is contributed by domestic waste water. For analysis three different kinds of phosphates can be distinguished: The soluble o-phosphates, the whole phosphates and the particle bound insoluble phosphates. In spring-water and rainwater the o-phosphate is less abundant whereas near the outflow of waste water it occurs in high concentrations. So, the concentration of o-phosphate can be used as an indicator for waste water entrance. An example is the increased load of a river, the Mosel near Koblenz, which was contaminated with 0.1–0.2 mg/1 (about 1–2 µM) in 1961 whereas in 1975 the river was contaminated with 2 mg/l (about 20 µM). Because phosphate is one of the essential nutrients for eutrophication, high concentrations of phosphates can cause accelerated growth of plankton becoming more and more serious in many parts of the world. To control drinking water, food products and body fluids methods are required for phosphorous analyses in samples from many different origins. The recommended maximum value in drinking water is 1 mg/l (10 µM.). Therefore, analytical methods should not only be highly specific but should also be very sensitive. Furthermore, for widespread application the developed method should be reliable and cost-effective. Bioanalytical methods, especially when the biocomponent is reusable, have the potential to fulfil these requirements. Routinely, inorganic phosphate (Pi) is determined by the molybdenum blue method of Fiske and Subbarow in original (1925) or modified forms (Martland and Robinson, 1926; Saheki et al., 1985). After adding molybdate with subsequent reduction, the resulting phosphor-molybdenumblue complex is determined colorimetrically. Recently, Masini et al. (1995) applied this method to sequential injection for on-line monitoring of phosphate during the production of biomass in aerobic fermentations of Saccharomyces cerevisaei. Other methods like ion-selective electrodes (Glazier and Arnold, 1988; Goediker and Cammann, 1989) or ion chromatography (Singh and Nancollas, 1988) have also been described in the past, but normally exhibit low sensitivities, specificities or are rather laborious. A breakthrough in phosphate determination was achieved by the introduction of biomolecules as highly specific analytical tool. To describe all bioanalytical methods for phosphate deter-

mination would be beyond the scope of this chapter. Therefore mainly biosensors will be described. Biosensors for the determination of phosphate are normally based on mono- or multienzymatic reactions and can be divided in two catagories: (1) where phosphate acts as inhibitor (2) where phosphate acts as a second substrate. 4.5.2. PHOSPHATE AS INHIBITOR

Weetall and Jacobson (1972) have reported a spectrophotometric assay based on an alkaline phosphatase (aP, EC 3.1.3.1) reaction which produces a coloured product and which is inhibited in proportion to the phosphate concentration in the sample. To apply this principle to a biosensor, Guilbault and Nanjo (1975) used aP and glucose oxidase (EC 1.1.3.4) in combination with an oxygen electrode (−600 mV, Pt vs. SCE) (Figure 4.13). Glucose-6-phosphate was converted by aP (Figure 4.13) phosphatase to glucose (ß-Glc) which was converted to gluconolactone under oxygen consumption and hydrogen peroxide production by glucose oxidase. The oxygen decrease was measured. After addition of phosphate an oxygen increase was observed due to the inhibition effect of phosphate to the aP. The detection limit for phosphate was found to be 100 µM and therefore not sensitive enough for assay of low concentrations of phosphate ion in river water. In addition to the inhibitory effect of phosphate, the

Figure 4.13. Scheme of an enzyme sensor for phosphate determination by inhibition of the phosphatase reaction.

inhibitory effect of other anions were investigated. The order of inhibition was found to be as follows: . However, it was argued that in an assay for phosphate in rivers, streams or lakes it is unlikely that any of these ions would be present to interfere. Other ions that exist in water solutions as chloride, nitrate and sulfate which gave serious interferences on non-enzymatic ion-selective electrodes, did not show any effect up to 0.1 M. As indicated in Figure 4.13 amperometric hydrogen peroxide detection would also be possible with this principle. Su and Mascini (1995) used a platinum working electrode modified with a poly(phenol) film for hydrogen peroxide measurements instead of a plain electrode and thereby reduced interferences (e.g. ascorbic acid, uric acid). Nevertheless, as with all biosensors based on measurements of the changes in enzymatic activity (kinetic controlled biosensors), this principle is very susceptible to a huge number of different factors (e.g. stability of the biomolecule, inhibition by unknown components, etc.). After each determination the biosensor has to be calibrated very carefully. With respect to stability, Schubert et al. (1984) have improved this principle by use of a potato (Solanum tuberosum) tissue slice instead of alkaline phosphatase. The potato acid phosphatase (EC 3.1.3.2) was stabilized by the native environment allowing several hundred samples to be determined with high sensitivity. The lower detection limit of this hybrid sensor was 50 µM which was not sufficient for measurements in river water or serum, but acceptable for fertilizers and urine samples. Instead of using glucose-6-phosphate as the substrate of aP other substrates have been applied with the same principle. Razumas et al. (1980) used, for instance, catechol phosphate. The catechol released by the aP reaction was detected amperometrically on a solid electrode (+200 mV). Katsu and Kayamoto (1992) used o-carboxyphenyl phosphate as a substrate of aP. The salicylate produced was detected potentiometrically by a salicylate-sensitive membrane electrode. The lower detection limit was found to be 50 µM. The advantage of using substrates other than glucose-6-phosphate is that the sensor is also applicable for phosphate determinations in samples where glucose is present, e.g. for phosphate determination in serum. 4.5.3. PHOSPHATE AS A SECOND SUBSTRATE

The advantage of determining phosphate as a substrate instead as an inhibitor of an enzymatic reaction is obvious. Because the sensor can operate under diffusion control the sensor will be much more reliable and precise than the phosphate sensors operating under kinetic control as described before. The selectivity should also be higher as phosphate acts directly as a reaction partner of a chemical reaction within the active site of an enzyme. Two approaches are used as the initial phosphate utilizing reaction: (1) the use of a phosphate-dependent pyruvate oxidase (EC 1.2.3.3) or (2) the use of phosphorylases.

Pyruvate oxidase catalyzes the oxidation of pyruvate in the presence of phosphate and oxygen, with the formation of acetylphosphate, carbon dioxide, and hydrogen peroxide (Figure 4.14). Mizutani (1980) used this enzyme for the determination of

Figure 4.14. Scheme of an enzyme sensor for phosphate determination by using pyruvate oxidase. pyruvate by using immobilized pyruvate oxidase and an oxygen electrode. Six years later Ngo used the enzyme pyruvate oxidase for the first time for phosphate determination (1986). After the electrode (YSI-Clark 2510 hydrogen peroxide probe (+700 mV)) was immersed in the stirred substrate solution (sample+pyruvate) the reaction was started by adding the pyruvate oxidase to the solution. After 4min signal registration the cell was washed thoroughly with buffer. The registered hydrogen peroxide concentration was proportional to the phosphate concentration within the sample. A range of 50–500 µM phosphate has been measured by this method with high specificity. Kubo et al. (1991) used the same principle, but with oxygen indication, for the development of a phosphate biosensor by immobilization of the enzyme in PVA-SbQ in front of an oxygen electrode (Figure 4.14). The determination time was 7 min with a linear range of 12– 80 µM phosphate. Although 0.8 mM TPP and 10 µM FAD were added to the buffer, after 7 days use the response decreased to 50% of the initial value. This fast inactivation of pyruvate oxidase was one of the main problems for applying this enzyme to bioanalytical problems. The maximum permissible phosphate concentration of the natural waters in Japan is 0.32 µM. To shift the detection limit to lower concentrations Ikebukuro et al. (1996a; 1996b) used pyruvate oxidase in combination with a subsequent luminol chemiluminescence reaction to detect the hydrogen peroxide produced much more sensitively. The enzyme was immobilized to aminoalkylated controlled pore glass by glutaraldehyde and used in a small column within a FIA system, After injection of phosphate into the column, equilibrated with pyruvate, TPP, FAD and MgCl2, hydrogen peroxide was produced. Thereafter, in a mixing cell luminol and p-iodophenol were added and pumped to a flow cell with immobilized peroxidases where the chemiluminescence reaction took place which was detected by a photomultiplier tube. In comparison to the work of Kubo et al. (1991) the linear response was shifted to 0.37–7.4 µM.

The detection limit was observed to be 0.074 µM. In that case the sensitivity was sufficient for water control. By using a column instead of a membrane the amount of immobilized enzyme was increased. Under optimized storage conditions it was possible to detect 7.4 µphosphate for 2 weeks. Besides the pyruvate oxidase-based assays various enzymatic assays have been developed based on an initial phosphorylase reaction. In clinical diagnostics a highly specific enzymatic method based on an phosphorylase reaction has found widespread application (Gawehn, 1985) and this can also be used for other matrices. In the presence of phosphate glycogen (glucosen) is converted by the enzyme phosphorylase a (EC 2.4.1.1) to glycogen (glucosen−1) and glucose-1phosphate. The enzyme phosphoglucomutase (EC 5.4.2.2) converts the produced glucose-1phosphate to glucose-6-phosphate, which is indicated in the presence of NAD or NADP by a glucose-6-phosphate dehydrogenase (EC 1.1.1.49) reaction. The produced NADH is measured spectrophotometrically and is directly proportional to the phosphate concentration in the sample. Based on the same phosphorylase (phosphorylase a) Wollenberger and Scheller (1993) have developed an interesting principle for a reagentless phosphate sensor (Figure 4.15). Glycogen (glucosen) is coimmobilized with phosphorylase a, phosphatase (i.e. alkaline phosphatase), mutarotase (EC 5.1.3–3) and glucose oxidase within a membrane layer. As shown in Figure 4.15, both hydrogen peroxide production or oxygen consumption can be measured with a hydrogen peroxide sensor (+600 mV; Pt vs Ag/AgCl) or with a Clark-type oxygen sensor (−600 mV; Pt vs Ag/ AgCl), respectively. Because phosphate is released during the phosphatase reaction, substrate recycling is achieved. The measuring range is described to be 50–1000 µM with a detection limit of 10 µM. Nevertheless, for practical use of this sensor further optimizations with respect to the coimmobilization within the membrane are necessary. A principle (de Groot, 1984) which is often used in biosensors is based on the combination of the enzymes nucleoside phosphorylase (EC 2.4.2.1) and xanthine oxidase (EC 1.1.3.22). Watanabe et al. (1988) immobilized nucleoside phosphorylase and xanthine oxidase on a triacetyl cellulose membrane and fixed the membrane on the tip of the Clark-type oxygen electrode (−600 mV, Pt vs Ag/AgCl). This enzyme electrode was incorporated into a FIA system. Tris-HCl buffer (0.1 M, pH 7.0) containing inosine (0.2 mg/ml) was pumped continuously to the sensor by a peristaltic pump at a flow rate of 1.4 ml/min. A 50 µl aliquot of the phosphate sample was injected into the flow channel and the oxygen decrease was recorded. Linearity of the phosphate dependency was obtained from 300–1000 µM. Optimizations have produced more stable and sensitive enzyme sensors (D’Urso and Coulet, 1993) with a linear response of 10–250 µM (Haemmerli et al., 1990) and with a lower detection limit of 1.25 µM (Male and Luong, 1991). In contrast to the measurement of the consumed oxygen, in these works both the detection of the hydrogen peroxide as well as the uric acid produced were used (+700 mV; Pt vs Ag/AgCl). A further type of measurement was realized by Kulys et al. (1992). Instead of the oxidation of the reduced xanthine oxidase by oxygen, the reduced enzyme was oxidized on a 7, 7, 8, 8tetracyanoquinodimethane (TCNQ)-modified graphite electrode. The oxidation of the reduced TCNQ (KTCNQ) lead to an anodic current generated by the biosensor at +100 mV.

Figure 4.15. Scheme of a reagentless enzyme sensor for phosphate determination by using coimmobilized glycogen (glucosen), phosphorylase a and phosphatase for substrate recycling. A further improvement in lowering the detection limit was achieved by Wollenberger et al. (1992). They introduced uricase to this principle to convert the produced uric acid to allantoin accompanied by additional oxygen consumption as well as additional hydrogen peroxide production. The coimmobilization of both oxidases resulted in a 130% enhanced response. The oxygen consumption was measured by a Clark-type electrode. To avoid inactivation of the xanthine oxidase by increased hydrogen peroxide concentrations catalase was introduced. The result was an increase of the working stability to at least 8 days with 300 measurements. A detection limit of 0.5 µM and a linear range of 0.5–100 µM have been described for this configuration. Furthermore, the detection limit was improved by application of substrate recycling. Alkaline phosphatase was introduced to release phosphate from the produced ribose-1phosphate due to the nucleoside phosphorylase reaction

Figure 4.16. Scheme of an enzyme sensor for phosphate determination by using nucleoside phosphorylase and phosphatase for substrate recycling. (Figure 4.16). The result was a 20-fold enhancement in sensitivity. Thus the detection limit of the phosphate electrode was shifted to 25 nM which is quite sufficient for water control. Another principle for phosphate determination with internal substrate recycling using an initial phosphorylase reaction is based on a maltose phosphorylase (EC 2.4.1.8) reaction in combination with a phosphatase, mutarotase and glucose oxidase reaction (Warsinke and Gründig, 1992). As shown in Figure 4.17 the maltose molecule is converted by the maltose phosphorylase reaction into β-glucose-l-phosphate and a-glucose with the consumption of one phosphate molecule. By the phosphatase reaction as well as by the mutarotase reaction two molecules β-glucose are produced which are detected within the glucose oxidase reaction by hydrogen peroxide or oxygen measurement. In this way two molecules β-glucose are produced per molecule phosphate. Due to the phosphatase reaction phosphate is liberated from β-glucose-1-phosphate and can be consumed again by the phosphorylase reaction. This internal

Figure 4.17. Scheme of an enzyme sensor for phosphate determination by using maltose phosphorylase and phosphatase for substrate recycling. substrate recycling led to an amplification factor of at least 15. No intermediates other than βglucose are produced during the overall reaction. After optimization a linear range of 0.1–1 µM with a detection limit of 10 nM was obtained, which is the lowest detection limit ever observed for a phosphate biosensor (Conrath et al., 1995). However, because the final product is glucose determined by the glucose oxidase reaction, the sensor is not suitable for serum measurements. The principle should be applicable for environmental control. REFERENCES

Conrath, N., Gründig, B., Hüwel, St. and Cammann, K. (1995) A novel enzyme sensor for the determination of inorganic phosphate. Anal. Chim. Acta, 309, 47–52. DeGroot (1984) Method for the enzymatic determination of inorganic phosphate and Ist application, European Patent EP, 147867.

D’Urso, E.M. and Coulet, R.P. (1993) Effect of enzyme ratio and enzyme loading on the performance of a bienzymatic electrochemical phosphate biosensor. Anal. Chim. Acta, 281, 535– 542. Fiske, C.H. and Subbarow, Y. (1925) The colorimetric determination of phosphorous. J. Biol. Chem., 66, 375–400. Gawehn, K. (1985) Inorganic phosphate. In Methods of enzymatic analysis, Bergmeyer, H.U. (ed.) 7, pp. 552–558. Weinheim: VCH. Glazier, S.A. and Arnold, A. (1989) Phosphate-selective polymer membrane electrode. Anal. Lett., 22, 1075. Goediker, W. and Cammann, K. (1989) Properties of a phosphate sensitive solid state electrode based on cerium-IV-hydrogenphosphate mixed with PVC. Anal. Lett., 22, 1237. Guilbault, G.G. and Nanjo, M. (1975) A Phosphate-selective Electrode based on Immobilized Alakaline Phosphatase and Glucose Oxidase. Anal. Chim. Acta, 78, 69–80. Haemmerli, S.D., Suleimann, A.A. and Guilbault, G.G. (1990) Amperometric Determination of Phosphate by Use of a Nucleoside Phosphorylase-Xanthin Oxidase Enzyme Sensor Based on a dark-Type Hydrogen Peroxide or Oxygen Electrode. Anal. Biochem., 191, 106–109. Ikebukuro, K., Nishida, R., Yamamoto, H., Arikawa, Y., Nakamura, H., Suzuki, M., Kubo, I., Takeuchi, T. and Karube, I. (1996a) A novel biosensor system for the determination of phosphate. J. Biotech., 48, 67–72. Ikebukuro, K., Wakamura, H., Karube, I., Kubo, I., Inagawa, M., Sugawara, T., Arikawa, Y, Suzuki, M. and Takeuchi, T. (1996b) Phosphate sensing system using pyruvate oxidase and chemiluminescence detection. Biosens, and Bioelectr., 10/11, 959–965. Katsu, T. and Kayamoto, T. (1992) Potentiometric determination of inorganic phosphate using a salicylate-sensitive membrane electrode and an alkaline phosphatase enzyme. Anal. Chim. Acta, 265, 1–4. Kubo, I., Inagawa, M., Sugawara, T., Arikawa, Y and Karube, I. (1991) Phosphate sensor composed from immobilized pyruvate oxidase and an oxygen electrode. Anal. Lett., 24, 1711– 1727. Kulys, J., Higgins, I.J. and Bannister, J.V. (1992) Amperometric determination of phosphate ions by biosensor. Biosens, and Bioelectr., 7, 187–191. Male, K.B. and Luong, J.H.T. (1991) An FIA biosensor system for the determination of phosphate. Biosens, and Bioelectr., 6, 581–587.

Martland and Robinson (1926) CVI. Possible significance of hexose-phosphoric esters in ossification. Part VI. Phosphoric esters in blood-plasma. Biochem. J., 20, 847–855. Masini, J.C., Baxter, P.J., Detwiller, K.R. and Christian, G.D. (1995) online spectrophotometric determination of phosphate in bioprocesses by sequential injection. Analyst, 120, 1583–1587. Mizutani, F., Karube, I., Matsumoto, K., Suzuki, S. and Tsuda, K. (1980) Determination of glutamate pyruvate transaminase and pyruvate with an amperometric pyruvate oxidase sensor. Anal. Chim. Acta, 118, 65–71. Ngo, T.T. (1996) Single-Enzyme-Based Amperometric Assay for Phosphate Ion. Appl. Biochem. Biotechnol., 13, 127–131. Razumas, V.J., Kulys, J.J. and Malinauskas, A.A. (1980) Acceleration of the electrode process by biocatalysis. 3. Amperometric analytical systems based on alkaline phosphatase. Liet. TSR Mokslu Akad. Darb Sehr. B, 5, 19–26. Saheki, S., Takeda, A. and Shimazu, T. (1985) Assay of Inorganic Phosphate in the Mild pHrange, Suitable for Measurement of Glykogen Phosphorylase Activity. Anal. Biochem., 148, 277–281. Schubert, F., Renneberg, R., Scheller, F.W. and Kirstein, L. (1984) Plant Tissue Hybrid Electrode for Determination of Phosphate and Fluoride. Anal. Chem., 56, 1677–1682. Singh, R.P. and Nancollas, G.H. (1988) Determination of phosphate, sulfate and oxalate in urine by ion chromatography. J. Chromatogr. Bio. med. Appl., 77, 373–376. Su, Y. and Mascini, M. (1995) AP-GOD biosensor based on a modified poly(phenol)film electrode and its application in the determination of low-levels of phosphate. Anal. Lett., 28(8), 1359–1378. Warsinke, A. and Gründig, B. (1992) Verfahren zum empfindlichen enzymatischen Nachweis von anorganischem Phosphat, German Patent, DE 4227569. Watanabe, E., Endo, H. and Toyama, K. (1988) Determination of Phosphate Ions with an Enzyme Sensor System. Biosensors, 3, 297–306. Weetall, H.H. and Jacobson, M.A. (1972) Studies on phosphate inhibition and quantitation using immobilized bacterial alkaline phosphatase. In Ferment. Technol. Today, Terui, G. (ed.) Proc. IV., 361. Wollenberger, U., Schubert, F. and Scheller, F.W. (1992) Biosensor for Sensitive Phosphate Detection. Sensors and Actuators B, 7, 412–415. Wollenberger, U. and Scheller, F.W. (1993) Enzyme activation for activator and enzyme activity measurement. Biosens, and Bioelectr., 8, 291–297.

4.6. NITRATE

AXEL WARSINKE 4.6.1. INTRODUCTION

As in the case of phosphate, nitrate is a well-known contaminant of ground- and stream water. Nitrate can also contribute to algae blooms and eutrophication and can lead to serious environmental problems. It is generally accepted that nitrate itself is not toxic. However, the reduction of nitrate to the hazardous nitrite, which can form carcinogenic N-nitroso compounds and which can cause methemoglobinemia, occurs in the presence of microorganisms which are present in the saliva within the mouth. Therefore the determination of nitrate and nitrite concentrations is of great interest especially for the supervision of drinking water. The routine methods are photometric (DIN 38405 D9/D10) which require a careful pretreatment of the samples. Other methods are based on ion-selective chromatography (Fritz et al., 1982) and electrochemical methods such as polarographic, voltammetric, and potentiometric determination (Davenport and Johnson, 1973; Hussein and Guilbault, 1974; de Beer and Sweerts, 1989). Although biosensors or bioprobes based on microorganisms have been described for nitrate determination in the past (Larsen et al., 1996; Schramm et al., 1996; Prest et al., 1997), in this part only enzyme sensors will be considered. 4.6.2. ENZYME SENSORS FOR NITRATE DETERMINATION

Hussein and Guilbault (1974) have shown that a potentiometric ammonia electrode can be used for the determination of nitrate and nitrite reductases from Escherichia coli during the cultivation process. The different reductases responsible for nitrate respiration and assimilation can be summarized as: 1. Dissimilatory nitrate reductase (EC 1.9.6.1)

H-donor=formate, succinate, lactate 2. Assimilatory nitrate reductase (EC 1.6.6.2)

H-donor=NADH, NADPH 3. Nitrite reductase (EC 1.6.6.4)

H-donor=NADH, NADPH, flavin (FMN-reduced), viologen

Kiang et al. (1978) used the nitrite reductase from spinach leaves for the determination of nitrite and in combination with the dissimilatory nitrate reductase from E. coli K12 for the determination of nitrate. Thereby the enzymes were used in immobilized form (glutaraldehyde immobilization to glass beads) in a flow system. For column 1 only nitrite reductase was used, whereas in column 2 nitrate reductase and nitrite reductase in a 1:1 ratio were used. As electron donor the reduced form of methyl viologen (MVH) was used, obtained through the chemical reduction of its oxidized form by dithionite. Finally, the ammonia produced due to the nitrite reductase reaction was determined by an air-gap electrode (Ruzicka and Hansen, 1974). Although it was possible to determine nitrate and nitrite with this concept, the method was only reasonable good for the determination of concentration greater than 500 µM (about 3 ppm). Since the U.S. Public Health Service has announced that allowable limits for nitrate and nitrite in potable water are 10 and 0.06 ppm, respectively, the method was not sensitive enough for potable water control. Based on the principle described before Willner et al. (1990) have immobilized the enzyme nitrate reductase in a polyacrylamide gel functionalized by MVH. It was shown that after chemically or photochemically generation of the viologen radical cation MV+ the enzyme can reduce nitrate to nitrite. The same was shown with poly(thiophene viologen)—modified electrodes (Willner et al., 1992). Nevertheless, the reduction of the viologen group could not be obtained by the electrode itself. Because no catalytic cathodic current was observed, the principle could not be utilized for the development of an amperometric enzyme sensor. In 1994 the first amperometric enzyme sensors for nitrate and nitrite were developed by Strehlitz et al. and by Cosnier et al. Strehlitz et al. tested a huge number of artificial electron donors as mediators for nitrite and nitrate reductases which were reduced at different potentials on a graphite electrode. With benzyl viologen as mediator (polarization voltage of the graphite electrode: −800 mV) and nitrate reductase the nitrate response was linear from 2–300 µM, whereas with l-methoxy-NMP+ (polarization voltage of the graphite electrode: −200 mV) and nitrite reductase the nitrite response was linear from 3–45 µM. An improvement in detection limit for nitrite was achieved by using a phenosafranin-modified graphite electrode (applied potential for reduction:—600 mV) and poly(carbamoyl sulfonate) (PCS) hydrogel immobilized tetraheme cytochrome c nitrite reductase. The linear response was up to 250 µM nitrite with a detection limit of 1 µM (Strehlitz et al., 1996). By using electropolymerization of a nitrate reductase-amphiphilic pyrrole viologen mixture on a polypyrrole-viologen precoated carbon disk electrode an amperometric nitrate electrode (applied potential for reduction: −700 mV) has been produced with a lower detection limit of 0.4 µM (Cosnier et al., 1994).

Recently, an interesting optical biosensor for nitrate has been described by using sol-gel immobilized nitrate reductase (Aylott et al., 1997). The procedure is as follows: In a first step the periplasmic nitrate reductase is reduced by sodium dithionite. By adding nitrate to the sensor the enzyme is reoxidized due to the conversion of nitrate to nitrite. The oxidation of the enzyme is accompanied with a decrease in absorbance at 550nm which is used as transducable signal. In contrast to other enzyme sensors, the transducable signal is not obtained by the determination of the cosubstrate or product concentration, but by the determination of changes of the physicochemical properties of the enzyme due to the enzymatic reaction itself. A linear response to nitrate was observed over the range 0–1.5 µM with a detection limit of 0.125 µM which is better than the other sensors described. By using sol-gel entrapment the activity of the enzyme was not affected even after a storage period of up to six months. REFERENCES

Aylott, J.W., Richardson, D.J. and Russell, D.A. (1997) Optical biosensing of nitrate ions using a sol-gel immobilized nitrate reductase. Analyst, 122, 77–80. Cosnier, S., Innocent, C. and Jouanneau, Y. (1994) Amperometric Detection of Nitrate via a Nitrate Reductase Immobilized and Electrically Wired at the Electrode Surface. Anal. Chem., 66, 3198–3201. Davenport, R.J. and Johnson, D.C. (1973) Determination of nitrate and nitrite by forced-flow liquid chromatography with electrochemical detection. Anal. Chem., 46, 1971–1978. DeBeer, D. and Sweerts, J.-P.R.A. (1989) Measurement of nitrate gradients with an ionselective microelectrode. Anal. Chim. Acta, 219, 351–359. Fritz, J.S., Gjerde, D.T. and Pohlandt, C. (1982) Ion Chromatography, Hüthig Heidelberg. Hussein, W.R. and Guilbault, G.G. (1974) Nitrate and ammonium ion-selective electrodes as sensors. I. In bacterial growth curves for isolation of nitrate and nitrite reductases from Escherichia coli. Anal. Chim. Acta, 72, 381–390. Kiang, C.H., Kuan, S.S. and Guilbault, G.G. (1978) Enzymatic Determination of Nitrate: Electrochemical Detection after Reduction with Nitrate Reductase and Nitrite Reductase. Anal. Chem., 50, 1319–1322. Larsen, L.H., Revsbech, N.P. and Binnerup, S.J. (1996) A Microsensor for Nitrate Based on Immobilized Denitrifying Bacteria. Appl. Environ. Microbiol., 62, 1248–1251. Prest, A.G., Winson, M.K., Hammond, J.R.M. and Stewart, G.S.A.B. (1997) The construction and application of a lux-based nitrate sensor. Lett. Appl. Microbiol., 24, 355–360. Ruzicka, J. and Hansen, E.H. (1974) A new potentiometric gas sensor—The air gap electrode. Anal. Chim. Acta, 69, 129–141.

Schramm, A., Larsen, L.H., Revsbach, N.P., Ramsing, N.B., Amann, R. and Schleifer, K.H. (1996) Structure and Function of a Nitrifying Biofilm as Determined by In Situ Hybridization and the Use of Microelectrodes. Appl. Environ. Microbiol., 62, 4641–47. Strehlitz, B., Gründig, B., Vorlop, K.D., Bartholmes, P., Kotte, H., Stottmeister, U. (1994) Artificial electron-donors for nitrate and nitrite reductases usable as mediators in amperometric biosensors. Fres. J. Anal. Chem., 349, 676–678. Strehlitz, B., Gründig, B., Schumacher, W., Kroneck, P.M.H., Vorlop, K.D. and Kotte, H. (1996) Nitrite Sensor Based on a Highly Sensitive Nitrite Reductase Mediator-Coupled Amperometric Detection. Anal. Chem., 68, 807–816. Willner, I., Riklin, A. and Lapidot, N. (1990) Electron-Transfer Communication between Redox Polymer Matrix and an Immobilized Enzyme: Activity of Nitrate Reductase in a ViologenAcrylamide Copolymer. J. Am. Chem. Soc., 112, 6438–6439. Willner, I., Katz, E. and Lapidot, N. (1992) Bioelectrocatlysed reduction of nitrate utilizing polythiophene bipyrdinium enzyme electrodes. Bioelectrchem. Bioenerg., 29, 29–45.

5. ANALYSIS OF SOIL SILKE KRÖGER and ANTHONY P.F.TURNER Soil analysis is complex and challenging because soil is a natural product, alive with microorganisms and even small animals, constantly changing in consistency and composition. Metabolic processes as well as the influence of rain, sunshine and wind guarantee that soil samples do not only differ from place to place, but also samples from identical collection points change with time. A number of physical and chemical parameters, e.g. particle size, organic matter content, pH and water content, are commonly measured to allow a general characterisation of the soil type, but every soil sample will to some extent remain a unique mixture. When dealing with soil samples, the analyst has to be aware of the difficulties inherent in this matrix. Due to the heterogeneous nature of the matrix already the sampling, as the first step of the whole procedure is of importance and can influence the analytical result (Chap. 5.1.). The need to analyse soil samples for a range of pollutants has grown considerably with increasing environmental awareness by the public. Since conventional analysis such as HPLC or GC-MS requires specialist laboratories, highly trained personal, and is time consuming and therefore expensive, alternative analytical methods are being sought. Biosensors have demonstrated their advantages as analytical tools in the medical sector, for example in decentralised monitoring of blood glucose, and the idea of transferring the concept to soil analysis is very attractive. Thus, an overview will be given on biosensors for certain organic compounds (Chap. 5.2.). 5.1. SAMPLING

KARL CAMMANN and WOLFGANG KLEIBÖHMER 5.1.1. INTRODUCTION

Analytical investigations are performed for various reasons, such as in product quality control and with incoming raw products, with legal proceedings and in forensic medicine or in the field of food control and environmental monitoring. One of the most important steps in all these analytical investigations is sampling. After having decided on the problem to be solved by the onstanding investigation and having elaborated an appropriate analytical procedure every analysis starts with the sampling step. The importance of a correct sampling procedure cannot be emphasized enough as it is the decisive step in the whole analytical process to gain a true and reliable result. If the sample to be analysed is not a representative part of the subject of investigation the result of even the most elaborated and sophisticated analytical procedures is worthless. The reliability of an analytical result could depend on the analytical method applied but it always depends on an expert sampling procedure

carefully carried out. Samples either received inappropriately or characterized insufficiently should not be analysed as the results lead to wrong conclusions. It should be noted that errors are summed up according to the equation

The size of the error arising from incorrect sampling compared with the errors from incorrect sample preparation and incorrect measurements are shown in Figure 5.1. It can easily be seen that—due to low variances in the analytical measuring technique—the main sources for errors result from inappropriate and incorrect sampling and sample preparation. So an emphasis should lie on an improvement of these steps before analytical methods are further developed. It should be mentioned that a possible field blank should be taken into account thus regarding a possible contamination from the environment of the sample by dust and other micro particles not being part of the sample. Especially in trace analytical work it is good practice to take field blanks in containers cleaned in the same way as the sample containers in order to check those for impurities or carried over analytes. Taking a field blank consists of opening the container for the same time in the same environment and under similar conditions as the sample container. If stability enhancing solvents or reagents are used during the sampling procedure the same amount is also filled into the field blank containers. By this any interfering input of non-sample material (e.g. contaminated air with aerosols or blossom dust) can be corrected for. The ideal field blank consists of a sample containing all the matrix attributes of the sample under consideration but without the analyte of interest. In

Figure 5.1. Sources of errors in analysis (according to[6]).

the laboratory the field blank can be transferred into the typical reagent blank necessary in every case of trace analysis by treating it like the samples. Very often the standard deviation of these blanks determines the actual detection limit. 5.1.2. SAMPLING STRATEGIES

Sampling strategies and sampling technologies to receive representative samples are fixed in numerous instructions, orders and rules (Markert, 1994; Mason, 1993; Keith, 1991; Petersen and Calvin; Smyth 1996; VDLUFA, 1991). For environmental analysis some of these shall be elucidated in view of soil sampling. Analogous considerations for a strategic measurement planning can be made in other fields of instrumental analysis (material science, food quality control, forensic chemistry, clinical chemistry etc.). In contrast to air and water the solid soil consists of several components forming a heterogenious mixture and therefore demands special measures when samples are taken. Usually harmful substances are spread inhomogeneously in the soil of polluted areas according to type or concentration. Also the vicinity of polluted areas can be differently contaminated by mobilized pollutants. Spreading of substances is dependent on — the chemical properties of the pollutants; — the physico-chemical environment; — characteristics of the soil. In spite of these inhomogeneities samples must be representative for the entirety in view of the characteristics to be analysed. According to the homogeneity of the entirety various numbers of samples have to be taken on various places of the area to be investigated. At the start of every sampling protocol there is the question of which conclusions should be drawn from the final results. That means that the analysis strategy is directly dependent from the aim of the investigation and the desired information. The definition of the analytical aim of the investigation should be ruled by common sense. Too many analyses are performed with a shortage of a basic analytical knowledge. Of course the complexity of the information wanted and the historical knowledge of the sampling area determine the complexity of sampling and analysis. This will be shown with the following three examples. 5.1.2.1. Determination of mean values

For a determination of mean values various single or random samples are united to a mixed sample, and the desired parameters are then determined. This is of some importance in agriculture if the contents of heavy metals and plant nutrients available in soil (ammonia, nitrate, phosphate etc.) should be determined. These values are important to determine the pollutant endurance capacity of the soil for ground water protection reasons prior to a possible deposition

of sewage slurry on the area in question. In Figure 5.2 a possible distribution of the single samples is depicted.

Figure 5.2. Map of the sampling target. Per hectare a mixture is made from 20 single samples of an overall weight of 700 grams. The direction of sampling should be diagonally to the ploughing direction. To exclude a possible pollution from neighbouring fields or roads an edge of 10–15 m should be left free from sampling. 5.1.2.2. Determination of maximum values

For the determination of maximum values the single samples are not united but analysed separately. These maximum values are of interest in view of a critical exposure by skin contact or inhalation of vapours from a contaminated soil e.g. from a playground. In this case the demands are very high as from the sampling strategy it must be possible to localize and to judge the main source of contamination (e.g. in view of playing children).

5.1.2.3. Determination of distribution patterns

A careful and extensive sampling strategy is necessary if a hypothesis of emmission shall be verified according to the distribution and the concentration profile of the pollutant. An example for this is the examination of soil in industrial areas in view of a possible pollution by cadmium or by fluorine in the case of a near-by aluminium plant which can reach considerable high values especially during course of time. Cadmium can be introduced into the soil either from the atmosphere as part of the dust or from certain cadmium containing solid fertilizers, from sewage slurry deposited on the area or from industrial waste. The aim of these investigations could be judging the relative contribution of each source to the overall contamination. 5.1.3. SAMPLING PROTOCOL

The next step of establishing a sampling protocol is gaining knowledge of all sources and data available to evaluate the history of the area in question. These sources can be: — plans and maps; — photographs and drawings; — aerial photographs; — files and records, chronicals, registers; — official documents, approvals and permissions and; — statements and evidence of contemporary witnesses. Samplings schemes have been developed to assist fixing the various points of sampling in order to assure a correct determination of mean values or maximum values. By using additional information sources the final sampling grid is then established in view of the analytical information desired. Figure 5.3 shows how the choice of sample grid and the informations avaliable determine the distribution of samples. These sample grids must not be regarded as totally fixed but can be adopted to the local situation and to the aim of the investigation. The grids shown in Figure 5.4 are the commonly used one. Furthermore there are statistic-based grids available probably with a higher hit probability but also at higher costs for establishing the sample points. Normally the regular “bottle-rack” grid will be applied which can be complemented by additional sampling points when needed. Polar (Figure 5.5) grids are suited for point sources of contamination e.g. a tank leakage or for recording former industrial plant locations with only a few facilities. Additional sampling lines can be laid into that grid. The radius size is dependent from the estimated size of the contamination source.

5.1.4. SAMPLING DEPTH

The sampling depth is mainly determined by the environmental considerations taking into account the following influences and spreading mechanisms:

Figure 5.3. Selecting and adapting a fixed soil sampling plan according to previous information and to objectives (1). — direct intake (orally) by playing children; — intake by plant roots; — solution by precipitation water and material transport by ground water and surface water; — evaporation into ground near layers and into the air; — wash-out and blow-out into neighbouring sites (Table 5.1). These values are approximate values only, locally a change of sampling depths may be necessary according to the structure of soil layers.

Figure 5.4. Examples for various fixed grid plans Importance of representative sampling and divisions to follow (according to (1)) A: rectangular grid; B: random grid; C: bottle rack grid.

Figure 5.5. Example for a polar grid. Table 5.1. Dependence of sampling depth from environmental considerations. Environmental consideration

Sampling depth

soil surface—air

0–10 cm

soil—surface water (wash-out)

0–10 cm

soil—human uptake (oral incorporation)

0–35 cm

soil—plant

0–100 cm

soil—ground water

0–

5.1.5. COLLECTION OF SAMPLES AND SAMPLE TRANSPORT

After having fixed the sampling points and depths the appropriate sampling equipment must be chosen. Inappropriate devices can lead to large errors with respect to the analytical results especially when the contaminants of interest are present at low concentrations. The actual composition of a soil sample can change during sampling and transport for various reasons. The main points to take into account are the following:

— abrasion of sampling devices (in the ppb-range a short contact can falsify the analysis result); — analyte adsorption with sampling devices and transport containers; — analyte contamination by unsufficiently cleaned tools; — gaseous pollutants with a tendency to pass into the atmosphere; — photolytic and microbial decomposition of the analyte; — oxidation of the analyte by oxygen from air. These influences cannot be excluded in any case but an optimal sampling strategy must cover measures to minimize those influences. Apart from these basic selection criteria the selection of sampling tools is determined by the sampling depth and the characteristics of the soil. For taking samples near the surface scoops can be used, for sampling at shallow depths hand drills or push tubes can be used especially in soft soils for a depth of 20–30 cm. 5.1.6. SAMPLE HOMOGENIZATION, DRYING, PARTITION

Prior to further analytical processing in the laboratory the samples have to be devided into representative parts. Ideally the entire sample material ought to be analysed to gain the optimum information. This is practically impossible and thus, after several dividing operations, a minor part of the entire material is analysed. Figure 5.6 shows this mass decline. The final determination is made with a volume that represent much less than 1 % of the original soil sample only, in the chosen example only 5 mg or 1 µl taken from the soil sample are analysed finally.

Figure 5.6. Relation between total sample mass and the final analysed mass. Most analytical methods demand a multi-step sample preparation. In the case of solid samples mechanical steps such as drying and breaking prior to analytical steps such as digestions, or extractions an analyte containing solution can be prepared ready for analysis. An exception from this procedure is necessary only, if preparation steps lead to non-tolerable changes of the sample state or of the analyte concentration. This is valid e.g. for the determination of volatile compounds in soil. In this case the sample to be examined must be

transferred immediately into a gas-tight container suitable for the analysis steps to follow. A sample mix cannot be obtained in such cases. It is then necessary to dry the sample as on one hand most concentration values are referred to the dry mass and on the other hand for many analytical steps to follow it is essential to have dry material. An extraction of soil samples using unpolar eluents such as cyclohexane, toluene or hexane can only be performed with dry samples as otherwise a complete weting could not be possible. Various physical methods can be applied for drying samples: Drying at elevated temperature — infrared — drying oven — micro wave oven Drying at lower temperature — freeze-dried Drying by chemical water absorption — grinding with Na2SO4 None of these methods produces optimal results, for each analytical method a suitable drying method has to be selected, and the loss of analyte during drying has to be determined. Digestions and extraction methods are the more effective the smaller the sample grain size is. Therefore solid samples have to be broken up prior to analytical procedures. Analytical grinders made of porcelain or agate mortar are used for that purpose. A contamination of the sample by abrasion should be taken into account. 5.1.7. SAMPLING DOCUMENTATION

All data concerning the tools, devices, and containers used during sampling including their materials, concerning the weather conditions including the temperature, and soil-specific data concerning character of soil, colour, sensorial observations should be carefully recorded. 5.1.8. SUMMARY

In critical situations (high damage potential in case of false results) experts from the analytical laboratory should have an input into the sampling procedure since they have the background expertise and are aware of the limitations of the storage conditions and possible affect on the

sample by the sampling process, the used sampling tools, and the storage containers. It should be noted that in trace and speciation analysis extra experience is needed and for each analyte the optimum storage and transport conditions need to be considered individually based on a sound knowledge on the many specific problems possible. For environmental multi-analyte trace analysis it is good practice to take more than one sample in parallel and store them under different optimal conditions according to the specific analytes (pH, exclusion of light or oxygen, refrigeration) For organic trace analytes special care has to be devoted to prevent any microbiological activity from metabolising the analyte. Last but not least, when possible and appropriate, certain primary sample material to allow a second confirmatory analysis. REFERENCES

Keith, L.H. (1991) Environmental sampling and analysis: a practical guide. Lewis, Chelsa. Markert, B. (ed.) (1994) Environmental Sampling for Trace Analysis. Weinheim: VCH Verlagsgesellschaft. Mason, B.J. (1983) Preparation of soil sampling protocol: Techniques and strategy. EPA-600/4– 83–020, U.S. EPA, Las Vegas: Environmental Monitoring Systems Laboratory. Petersen, F.-G. and Calvin, L.-D., Sampling. In Methods of soil analysis, Klute, A. (ed.) Part 1, Madison: American Society of Agronomy Inc, Soil Society of America. Smyth, W.F. (1996) Analytical Chemistry of Complex Matrices. New York: Wiley. VDLUFA (1991) Die Untersuchung von Boden. Methodenbuch VDLUFA, Darmstadt VDLUFA-Verlag.

5.2. BIOSENSORS FOR PESTICIDES AND ORGANIC POLLUTANTS IN SOIL

SILKE KRÖGER and ANTHONY P.F.TURNER 5.2.1. INTRODUCTION

The previous chapter (5.1.) has illustrated the importance of the sampling procedure. Once a representative soil sample is collected, the next step is the extraction of the analyte of interest from the bulk, since most analytical methods rely on the analyte being in the liquid phase. Extraction methods are manifold and have to be carefully selected to suit the particular application. A second extraction procedure can simultaneously achieve the elimination of interferences and, if necessary, pre-concentration. Depending on the solubility of the analyte the extraction solvent can be aqueous, but is more commonly organic or a mixture of both. Figure 5.7 summarises the steps involved in soil analysis and standard methods can be found for example in US EPA publications, the “blue book” (HMSO) or are defined by the AOAC International. Biosensors can be integrated into the analytical procedure either after the initial extraction step or after the purification/pre-concentration, depending on the nature of the device, its robustness and the desired detection range. In this chapter, different methods will be introduced in combination with their analytical applications. The aim of this chapter is to review the potential of biosensors for the analysis of pesticides and organic pollutants in soil, describing existing approaches and highlighting areas which may be interesting for future developments. Even though the above mentioned considerations complicate the analytical procedure when compared to the more convenient matrix water, researchers developing biosensors and analysts wishing

Figure 5.7. Flow scheme for conventional soil analysis and biosensor measurements (the method examples given are not comprehensive).

to employ them should not be deterred. The difficulties are identical for all other methods of analysis, physical as well as chemical, and it is conceivable that for many applications biosensors will prove a valuable alternative or addition to the standard laboratory methods. Some recent reviews highlight the potential of biosensors for environmental analysis (Dennison and Turner, 1995; Gizeli and Lowe, 1996; McDonald, 1994; Rogers, 1995).

5.2.2. DETECTION METHODS

An overview of biochemical principles and transducers has been given in chapters 1 and 2 of this book. Broadly, the multifarious combinations of receptors and transducers can be divided into three main classes: metabolic sensors, inhibition sensors and affinity sensors, depending on the type of interaction between the analyte and the biological component. For the analysis of pesticides and organic pollutants, the later two are more important. 5.2.2.1. Metabolic sensors

Metabolic sensors commonly rely on the availability of an organism or enzyme capable of utilising the analyte as a substrate. This is not impossible for pesticides, but unusual, since pesticides by definition are designed to inhibit rather than be broken down. Of course microorganisms have a unique ability to adapt to metabolise almost any compound found in their environment and various strains have been isolated capable of degrading xenobiotics (see Microbial sensors, Chapter 3.2. etc.). Most biosensors for pesticides and organic pollutants such as PAH and PCB described in the literature, however, rely on the inhibition of a biological component (see also Chapter 3.1.2.) or the development of an immunoreagent for a specific compound or class of compounds (see also Chapter 4.1.2.). These two groups of devices are different in their recognition element, but can be combined with similar physical transducers. 5.2.2.2. Inhibition sensors

Inhibition sensors are generic in their detection mode, since for example an enzyme is usually not specifically inhibited only by one compound but rather by one or more groups of chemicals. The advantage of this non-selective approach is its ability to act as an early warning system. It can be especially useful to detect a broad range of analytes simultaneously. The fact that the chosen biological component acts as an indicator for the potential toxicity of the sample lends this approach its significance. The biological compounds employed range from tissue slices through whole cells to isolated enzymes. 5.2.2.3. Affinity sensors

Affinity sensors are based on a receptor molecule specifically recognising and binding an analyte. The receptor can be for example a plant lectin, a membrane receptor protein or, most commonly, an antibody. Biosensors using the antibody/antigen interaction for their analyte recognition are generally named immunosensors. In recent years immunoassays, particularly enzyme linked immuno-sorbent assays (ELISAs), have gained widespread recognition in environmental analysis (Aga and Thurman, 1997) and proven to be useful tools for pesticide detection (Kaufmann and Clower, 1991; Morgan et al., 1996; Watts and Hegarty, 1995). Their acceptance has increased markedly and the US Environmental Protection Agency (US EPA) has modified their standard methods for the evaluation of solid waste to include immunoassays for the detection of pesticides in soil (Telliard, 1996; US EPA SW846, 1995). Based on this change in attitude and legal frame work, the transfer of immunoassays to immunosensors appears desirable and promising.

Immunosensors are generally chosen for their high specificity. Polyclonal antibodies are usually less specific and yield more generic detection methods, while monoclonal antibodies can be raised and selected for remarkable affinity and specificity. Since most pesticides and organic pollutants are haptens, meaning they are too small to elicit immunoreactions, they have to be linked to a carrier. Great care has to be taken during the antibody production since the haptencarrier design crucially influences sensitivity and selectivity of the envisaged assay. An interesting description of antibody production and immunosensor development for environmental analysis was given by Marco et al. (1995 I.+II.) and antibody production specifically for pesticide analysis was reviewed by Hock et al. (1995). A more recent addition towards the design of the recognition element in immunoassays is the possibility of generating recombinant antibodies. Again the technique has so far mainly been applied in the medical field, but as Kramer and Hock (1995) indicate, it holds a lot of promise for environmental analysis. Even further away from the traditional methods of generating the recognition element is the relatively novel techniques of obtaining antibody mimics by molecular imprinting, rational design or combinatorial chemistry. Despite the fact that applying these techniques strictly means leaving the area of biosensors and entering bio-mimetic or chemosensors, it could be an important tool in the development of environmental sensors, in particular for analytes in soil extracts and will be discussed briefly in section 5.2.7. Depending on the envisaged application, the format for environmental biosensors can range from small, hand-held devices for decentralised measurements to sophisticated, automated flowinjection instrumentation combined with complex data handling systems or sensor arrays for multi-analyte detection. 5.2.3. SAMPLE PREPARATION

For a very large number of analytes that are of interest in soil analysis, biosensor or immunoassay based methods exist. It is therefore interesting to consider their adaptation to the more complex matrices. The main considerations to be made before transferring a method e.g. from water to soil analysis are: • How will the analyte be made accessible, i.e. extracted? • What concentration range is to be expected? • Which other interfering molecules could be present in the extract? These key-issues will be dealt with in the following, setting a frame in which the performance of biosensor devices can be evaluated with regard to the requirements of soil analysis. 5.2.3.1. Extraction

Depending on the nature of the analyte, the extraction often utilises organic solvents rather than water, particularly since a number of commonly used pesticides and many organic pollutants display very low water-solubility. Most biosensors have been developed for the aqueous phase,

leaving the soil analyst with the options of a) extracting with water, b) evaporating the solvent prior to re-suspending the analyte in water, c) diluting the extract until the organic solvent does not interfere with the measurement or d) adapting the sensor to the organic phase. All these approaches have been used and have their specific advantages and drawbacks: (a) Extracting with water is very convenient, avoids the problem of having to deal with an organic solvent during the analysis and also afterwards when disposing of the waste. Interesting in this context is the method of hot water percolation (HWP) (Füleky and Czinkota, 1993), based on the coffee percolator principle, representing a rapid and easy soil extraction method. Soilwater samples can also be prepared using a lysimeter, allowing some control over the extraction process to be exerted. Unfortunately the recovery rates for many quite polar pesticides are very low, but it can be argued that the extent to which the analyte is extracted using this method provides some information about its bioavailability. (b) Evaporating the organic solvent between extraction and measurement gives high recovery rates, allows pre-concentration of the sample and avoids disturbance of the assay by the solvent, but is time consuming and often requires specialist equipment (rotary evaporator). Furthermore the introduction of additional handling steps always increases sources of errors. (c) Diluting the extract, until the overall solvent concentration is low and therefore tolerated by the assay, is relatively easy, but introduces inaccuracies (dilution error) and decreases the overall assay sensitivity. (d) The last possibility—adaptation of biosensor measurements to the organic phase—is a relatively new concept, founded on the discovery that biological materials are capable of maintaining their activity in a range of organic solvents. The area of biosensor measurements in non-aqueous environment will be discussed in a separate section (5.2.6). 5.2.3.2. Concentration range

The concentration of an analyte in soil samples is very hard to predict. Pesticide levels in soil are generally of interest for two different reasons: undesired contamination of land (through e.g. accidents or spray-drift) or because of agricultural use. Knowledge about the concentrations of pesticides in farmland-soil is important for a number of reasons, including maintaining a controlled level of pesticide throughout the growing season (dosage) or checking that a herbicide used previously for the control of weeds is not present anymore at the time of sowing a sensitive crop. With regard to organic pollutants, soil samples are usually analysed when a contamination is suspected. If this contamination dates back to, for example, previous industrial use of the investigated site, the expected concentration will depend on the time span between the last use and the analysis, on the mobility of the analyte in soil and on the nature of the soil, as this influences binding of the analyte and microbial breakdown. Contaminations that occur as a consequence of an accident, i.e. spillages, will have very high concentrations in the immediate vicinity, but lower concentrations in the surroundings might have to be analysed to determine the size of the contaminated site. Generally the relevant detection range is considerably higher when dealing with soil samples than is to be expected in water analysis.

5.2.3.3. Interferences

The third aspect, interferences co-eluted from soil samples, is quite complex. As discussed in the introduction, the composition of soil is very variable, leading to a large number of possible interferents, the exact nature of which is difficult to predict. One group of compounds virtually omnipresent in soil samples, although a greater or lesser extent depending on the soil type, are humic substances, the major fraction of soil organic matter. For a comprehensive understanding of the subject the reader is referred to the corresponding literature such as “Humus chemistry” by F.J.Stevenson (1994) and herein especially the chapter on organic matter reactions involving pesticides in soil. Humic substances have been classified into three fractions according to their water solubility: humin is the fraction not soluble in water, humic acid is insoluble under acidic conditions (pH<2) but becomes water-soluble at higher pH-values, and fulvic acid is water soluble at all pH conditions. Humic substances in soil are mixtures of these three fractions, heterogeneous, yellow to black and their chemical composition is poorly understood, since they do not originate from a uniform source. Figure 5.8 depicts a hypothetical structure containing a statistic distribution of the main building blocks of humic substances, i.e. aromatic ring systems, with carboxyl-and hydroxyl- and sugar side groups, linked via c-c, ester-, ether- and imine-bonds. The degree of condensation of the monomers varies and the colour of the structure darkens with increasing number of conjugated double bonds (Gisi, 1990). How much these substances will interfere with biosensor measurements, depends on the nature of the analyte, the extraction method chosen and the detection mode. It is important to be aware of possible reactions occurring between the humic substances and for example an aromatic analyte. Bonding of the analyte can occur, aggravating its extraction, or false positive results can be obtained if e.g. the utilised antibodies in an immunosensor display cross-reactivities with parts of the extracted organic matter. Interesting trends in conventional environmental analysis are the use of supercritical fluid extraction (Chester et al., 1994; Rochette et al., 1993; Snyder et al., 1992; Stearman et al., 1996) and developments in the area of solid phase extraction (Aga and Thurman, 1993; Chirnside and Ritter, 1993; Picó et al., 1994; Puig and Barceló, 1995) as a means of sample purification and pre-concentration. Either

Figure 5.8. Hypothetical structure of humic acid (after Stevenson, 1994). method can be combined with biosensor measurements to overcome some of the difficulties that can be encountered in soil analysis. 5.2.4. PESTICIDES

In the past the development of numerous pesticides has facilitated intense farming, allowing high yields to be gained from otherwise non-viable large monocultures. Herbicides, fungicides, bactericides, insecticides and other pesticides have found application both in professional land management and private households. Unfortunately excessive use has led to high level contamination of soil, transfer to ground- and river water, accumulation in the food chain and disturbances of natural ecosystems. It is beyond the scope of this chapter to fully examine the importance of pesticides, their history, economic importance, biochemistry, toxicology, ecology and use. For more detail the reader is referred to literature such as “The biochemistry and uses of pesticides” (Hassall, 1990), “The UK Pesticide Guide” (BCPC, 1996) and the series of publications by the World Health Organisation on Environmental Health Criteria, which include books on a number of pesticides. Reviews covering the literature on pesticide analysis from 1990 to 1994 have been given by Sherma (1993, 1995) and cover a wide variety of sample matrices. A large number of publications has described biosensor devices for the analysis of pesticides in drinking water (see chapter 4.1.) and many of the derived measurement principles could be or have been transferred to soil analysis. In water analysis the main emphasis is on low detection limits, since the expected level of contamination is in the sub-ppb level and very few matrix effects have to be accounted for. The detection limit for which most assays are developed is below 0.1 ppb, since this is the maximum legal tolerance level for individual pesticides in drinking water in Europe. When developing an analytical method for ground or river water the scientist has to be more aware of possible interference, but still aims for very low detection limits. This emphasis changes considerably when transferring to soil analysis.

When developing a biosensor for the analysis of pesticides in soil, different factors determine the benefit/usefulness of a device. As eluded to in the previous sections, the important questions are: How much sample preparation is necessary? Can the device be used in the field (size, portability, robustness)? Is it suitable for use by non-technical personal, such as farm-workers? Is the analysis quick? Is it economical to use the device for decentralised analysis, or is it only viable in a laboratory? Matrix effects are considerable, as discussed in section 3, and the concentrations encountered can be much higher than in water samples. The legal frame for contamination levels of soil is less stringent than for water. For many pesticides the legislator does not specify maximum contamination levels in soil, but limits the amount of the commercial product containing the respective chemical that can be applied per surface area and year (see “The UK Pesticide Guide” by the BCPC, 1996, or manufactures instructions). This fact makes it more difficult for the researcher to define a relevant concentration range for his detection method. Selectivity, simplicity and robustness become much more important characteristics in sensor development than sensitivity. An interesting example for the logic underpinning soil analysis is given in the U.S. EPA method 4015 (SW 486) for screening of 2,4-D by immunoassay. The agency herein discusses and recommends two commercially available immunoassay test kits (EnviroGard™ 2,4-D in soil and 2,4-D RaPID™, now both ENSYS Europe Ltd.) for sample pre-screening, and the main emphasis is on reliability with regard to correctly detecting negative/positive samples for a set tolerance concentration (e.g. 0.2 ppm or 10 ppm). Below a number of approaches will be discussed, illustrating the relevance of the different biosensor groups for pesticide analysis in soil samples. 5.2.4.1. Metabolic sensors for pesticides

The micro-organism Alcaligenes eutrophus JMP 134 is known to degrade the herbicide 2,4dichlorophenoxyacetic acid (2,4-D) and has been applied in a microbial sensor for the determination of aromatics and their chloroderivatives in buffer solution (Beyersdorf-Radeck et al., 1991), but since the sensor measures the increase in oxygen uptake upon turnover of the substrate, a large amount of non-specific metabolic activity might be expected when analysing soil extracts. Never the less Fradette et al. (1994) used microcalorimetry to monitor biodegradation of 2,4-D in sterilised soil by Pseudomonas cepacia and found a good correlation between the heat generated by microbial activity and the initial 2,4-D concentration. It is therefore conceivable that, by using microorganisms with suitable substrate specificity, whole cell metabolic biosensors for pesticide analysis in soil can be realised. 5.2.4.2. Inhibition sensors for pesticides

As mentioned above inhibition sensors can employ biological elements of different complexity. Plant tissue slices, single cell organisms, isolated enzymes and combinations of these biocatalysts have been applied for pesticide detection. Comparing the performance of thin layers of potato tissue (Solanum tuberosum) containing high amounts of acid phosphatase to the isolated enzyme, Mazzai et al. (1996) developed two

amperometric biosensors for carbamate and organophosphorous pesticides. In their device the researchers co-immobilised glucose oxidase and used glucose-6-phosphate (G6P) as substrate. The acid phosphatase catalysed the turn-over of G6P to glucose and inorganic phosphate. The glucose was metabolised by glucose oxidase in the presence of oxygen to gluconolactone and hydrogen peroxide, of which the later gave rise to a current signal at a commercial platinum electrode. Inhibition of the acid phosphatase by the pesticides malathion, methyl parathion, paraoxon or aldicarb led to a decrease in the observed current response. The authors concluded that both biosensors possessed comparable analytical parameters such as the lower detection limit (low ppb range in aqueous solution), but the plant tissue based device exhibited a longer shelf life and better reliability. A whole cell biosensor has been employed for on-line screening of herbicide pollution of surface waters. This sensor was a mediator assisted amperometric device, using a flow through cell, and a range of cyanobacteria and algae were tested for their response to inhibitors of the photosynthetic electron transport system. Using the cyanobacterium Synechococcus with ferricyanide as mediator detection levels of less than 200 ppb with a response time of less than 10 minutes were achieved for dichlorophenylmethylurea (DCMU), chlortoluron, linuron and ioxynit (Rawson and Wilmer, 1987; Rawson et al., 1989), all of which are urea herbicides inhibiting photosynthesis. Employing the same cyanobacterium, the lipophilic mediator diaminodurene (DAD) and amperometric detection, a biosensor for atrazine and diuron in water has been developed (Martens and Hall, 1994; Preuss and Hall, 1995). The detection limits of this sensor were in the low ppb range and by studying the rate constants (affinities) of the inhibitors in light and dark cycles, the system can differentiate between herbicide classes according to their site of interaction with the photosystem. Both systems described above used entire single cell organisms rather than isolated organelles (e.g. thylakoids) or membranes, since the complexity of preparation and poor stability of such cell components makes them in practice less suitable as biocatalysts in sensors. The increased stability and ease of immobilisation offered by whole cells in biosensor application has been noted previously as advantageous (Karube, 1987). Despite their applicability for herbicide sensing, whole cell sensors have, to the best of our knowledge, not yet been adapted for soil analysis, but a review of their achievements, problems and prospects has been compiled by Korpan and El’skaya (1995). An enzyme inhibited by a range of herbicides is acetolactate synthase II (ALS). ALS is a key enzyme in the biosynthesis of the branched chain aminoacids valine, leucine and isoleucine. In addition to the acetolactate activity the enzyme catalyses an oxygenase reaction. Sulfonylurea and imidazoline herbicides inhibit both the acetolactate activity and prevent the oxygen consumption. Sulfonylurea herbicides are mainly soil-acting against seedling weeds at early stages of their development and are applied in exceptionally low doses (less than 100g/ha) (Hassall, 1990). This presents a particular challenge when analysing soil. Seki et al. (1996) discuss two different ways of detecting these herbicides utilising the inhibition of the two functions of ALS. They propose the development of a biosensor measuring the oxygenase reaction of ALS immobilised in close proximity to an oxygen electrode and compare the inhibition effects obtained to the conventional colourimetric assay for acetolactate activity. In either case inhibitor concentrations in the µM range could be detected and the authors conclude

that the oxygen electrode-based ALS sensor would be a suitable method for the detection of herbicide in the environment, subject to improvements in the stability of the enzyme and the sensitivity of the sensor. Its applicability for the analysis of soil samples remains to be tested. By far the most common biocatalysts in the development of pesticide biosensors based on inhibition studies are cholinesterases. Acetylcholinesterase (AChE) is an enzyme involved in the signal transduction in the central and peripheral nervous system. Organophosphorus and carbamate pesticides inhibit cholinesterase and are therefore powerful insecticides, but at the same time exhibit high toxicity for other animals and humans. Their mode of action is different: organophosphorous pesticides are non-competitive irreversible inhibitors forming a highly stable complex with the enzyme while carbamate pesticides are competitive, reversible inhibitors resulting in a comparably lower toxicity of these compounds (W.H.O., 1986). The list of publications describing biosensors utilising cholinesterase for the detection of these groups of pesticides in water is almost as comprehensive as the number of different physical transducers allow, including amperometric, potentiometric, calorimetric and chemiluminescent sensors. A review of electrochemical biosensors for pesticide detection using esterase inhibition has recently been written by Trojanowicz and Hitchman (1996). In the following only AChE biosensors that have been applied for soil analysis or possess features relevant in this context will be discussed. An amperometric butyrylcholinesterase sensor for organophosphorus pesticides in soil extracts has been described by Campanella et al. (1992). A commercial hydrogen peroxide electrode (Radelkis, Hungary) was modified with a Biodyne nylon membrane on which butyrylcholinesterase and choline oxidase were co-immobilised. Butyrylcholine was added as a substrate, converted to choline and butyric acid. The choline was oxidised to betaine by choline oxidase, consuming oxygen and producing hydrogen peroxide. The electrode was equilibrated in 15 ml of a buffer/substrate solution until a steady state current was obtained (ca. 2 min), at which point pesticide addition led to a reduction in enzyme activity and corresponding current output. The authors reported the optimum working parameters, performed calibrations for a number of different organophosphates and evaluated possible interferences, such as metals and other compounds. Soil extracts were obtained by placing 145 g of soil in a beaker, containing 500ml of either distilled water or an ethanol/water mixture (40:60), and stirring for 1 h at room temperature. Afterwards the suspension was centrifuged and the supernatant directly analysed. Standards of malathion were added (2.5ppm, 5 ppm and 6ppm) and were detected with the biosensor with high accuracy (RSD below 4 %, n=4). The authors did not specify their spiking methodology, or any characteristics of their soil samples. They concluded that ethanol did not interfere with their measurements and did not observe any adverse matrix effects from the extracted soil samples. The advantages of this simple enzyme electrode for environmental monitoring were considered to be speed, easy handling and a relatively long life-time (ca. 10 days). Another publication reporting the application of a biosensor for the measurement of soil extracts described a potentiometric device based on the inhibition of

Figure 5.9. Cholinesterase biosensor for organophosphorous pesticides (after Kumaran and Morita, 1995). A: biosensor; B: experimental system set-up; C: Sensor response and data evaluation. butyrylcholinesterase by organophosphorous pesticides (Kumaran and Morita, 1995). The authors suggested an extraction method for the pesticides from spiked soil samples based on solvent extraction. Anhydrous sodium sulphate and a dichloromethane/acetone mixture were added to the soil, the sample was sonicated followed by manual shaking and filtration. The solvent from the filtrate and additional washings was evaporated at 35°C under nitrogen and the dry residue was re-suspended in a small volume of acetonitrile. The solution was toped up with HEPES buffer, yielding a working solution for the biosensor containing only 1 % acetonitrile. A pH electrode was covered with the enzyme immobilised on a casein blocked transfer membrane and utilised to establish a standard enzyme activity in buffer solution 7 minutes after substrate addition (1.2 mM butyrylcholine). A schematic representation of the set-up is given in Figure 5.9. For the analysis of the soil extract, an aliquot of the buffer/acetonitrile solution obtained was further diluted 1:1 with buffer and pre-incubated with the enzyme-electrode. After ten minutes substrate was added and the decrease in sensor response compared to the pesticide-free standard was inversely proportional to the pesticide concentration in the sample. The detection limit for diazinon was 10 nM and for fenitrothion 3 µM and soil contamination levels of 10–500ppb diazinon and 10–320 ppm fenitrothion could be measured. While the enzyme-membranes can be prepared easily and stored dry for long periods (>3 years) and their response is very reproducible (RSD<5%, n=7), the recovery rate of the pesticides with the extraction method described varied from 44.8 % for heptenophos to 136.2% for diazinon (RSD<14%), which was attributed to low concentrations and possible interactions of the pesticides with the organic matter and clay present in soil. The authors did not observe any adverse effects of the residual solvent or humic

substances co-eluted from soil on the enzyme activity and concluded that the achieved detection limits with an overall assay time of less than one hour including sample preparation were satisfactory. Similarly utilising electrochemical quantification of enzyme inhibition, Palchetti et al. (1997) developed an amperometric biosensor for carbofuran. Choline oxidase was adsorbed to screenprinted carbon working electrodes containing 0.5 % ruthenium. The measurement employed a two enzyme reaction sequence: acetylcholine was converted to acetate and choline by acethylcholinesterase in solution; the immobilised choline oxidase then oxidised the choline to produce hydrogen peroxide which was detected at the electrode surface. The work focused on the application of the sensor to the analysis of pesticides in fruit and a number of different organic solvents were evaluated with regard to their suitability for analyte extraction. It was found that the assay tolerated 1 % acetonitrile in borate buffer and the signal reduction upon inhibition of the enzyme was calibrated in terms of “carbofuran-equivalents”. Despite not being tested for soil analysis, this sensor does possess some of the features important for field measurements. The screen-printed electrodes can easily be mass-produced, are cheap and disposable; this is one way of circumventing problems with stability or electrode fouling when dealing with complex matrices. Furthermore amperometric devices built using screen-printing technology have been used extensively in decentralised monitoring of blood glucose and their potential in instrumentation for field use, like pre-screening of contaminated sites, is evident. Optical sensors have also been applied in this context. Roda et al. (1994) described a chemiluminescent flow sensor for the detection of paraoxon (organophoshate) and aldicarb (carbamate) pesticides based on AChE inhibition (see Figure 5.10). To evaluate the influence different matrices have on the measured luminescence, the results in buffer were compared to range of different homogenates of fruits, vegetables and soil. The samples were prepared by homogenising 2 g of solid matrix and mixing with 10ml buffer. Known amounts of pesticide were spiked into the liquid homogenate and incubated for 1 hour at room temperature. Afterwards the sample was filtered, the residue washed twice with buffer and the combined filtrate re-filtered with 0.2 µm membrane filters. Good recovery rates for the pesticides were obtained, although for soil analysis it has to be considered, that the pesticides are likely to bind more strongly to the matrix when incubated with a dry soil sample for a length of time, than when using this spiking procedure. Two different flow system set-ups were used for the signal generation: the first incorporating only one column with co-immobilised choline oxidase and peroxidase (Figure 5.10A), and the second manifold using an additional column with immobilised acethylcolinesterase upstream from the choline oxidase/peroxidase column (Figure 5.10B). The sample was injected into a buffer stream containing luminol. Acetylcholine was metabolised either by free AChE added to the filtered sample and pre-incubated for 1 hour or by the immobilised AChE in the first column. The resulting free choline was metabolised by choline oxidase to give betaine and hydrogen peroxide. Luminol reacted with the peroxide and, catalysed by peroxidase,

Figure 5.10. Chemiluminescent flow sensor for paraoxon and aldicarb (after Roda et al., 1994). A: free acetylcholinesterase in solution; B: acetylcholinesterase immobilised in column. the production of aminophthalate, nitrogen and water as well as light emission resulted. The inhibition of the light emission could be correlated to the pesticide concentration, with the former configuration (free AChE) being more sensitive. The obtained matrix extracts influenced the response apparently by quenching the light emission and not by enzyme inhibition. To overcome this drawback, the authors compared inhibition values to blanks consisting of unspiked extracts of the same nature as the sample and were thus able measure paraoxon at 10 ppb and 100 ppb spiking level in a number of sample matrices yielding results in good agreement with a standard colourimetric assay. The device could be used with a throughput (after preincubation steps) of 2– 4 min per sample and had a lifetime of about two weeks. A possible problem in environmental monitoring could be the lack of availability of identical, uncontaminated blank samples. 5.2.4.3. Immunosensors for pesticides

Since it is not possible to analyse for one specific compound with an inhibition sensor, and because in complex matrices the recognition element of a biosensor has to be highly selective in order to differentiate between the analyte of interest and matrix effects, immunosensors have most recently been at the centre of attention. The advantages of immunological methods have been eluded to in earlier chapters. For soil analysis, a certain degree of care has to be exercised with regard to cross-reactivities. The reader is reminded of the ill-defined and complex nature of humic substances that are present in most soil extracts. Comparing the hypothetical structure of humic acid depicted in Figure 5.8 to the chemical structure of some pesticides like triazines or phenoxyacetic acid derivatives, the reason for concern is apparent. Never the less some very interesting immunosensors for the analysis of pesticides or their residues in soil have been developed and are discussed below.

5.2.4.3.1. Electrochemical immunosensors The potential of combining the selectivity of immunological analysis with the sensitivity of electrochemical detection has long been recognised (Heineman and Halsall, 1985) and a commercial immunosensor based on electrochemical detection intended for the analysis of pesticides and toxic organic analytes in water, food and soil has been described by Fare et al. (1994). The scientific background to this instrument had been described earlier and its advantages over conventional ELISA systems in field measurements discussed (Sandberg et al., 1992). SmartSense™ produced by the Ohmicron Corporation was a portable immunoassay system using a platinum electrode coated with a conducting polymer as transducer. The highprecision gravure coating process of the electrodes with the polymer was optimised for batch production of thousands of cartridges with good reproducibility. Glucose oxidase was used as the enzyme label conjugated to atrazine in a competition assay with immobilised antibodies. The signal was created in a coupled reaction that produced triiodide which subsequently was quantified by impedance measurements. The system was designed to be robust and user friendly: a three-well system in disposable cartridges was used to run the sample in parallel with two standards, the data analysis was performed by an integral electronic analyser and the overall assay time was below 15 minutes. The authors reported good performance of the instrument as a semi-quantitative screening device for the presence of atrazine in water from different sources, like lakes, streams etc. Data for the analysis of soil was not presented and no extraction protocol was suggested. Noteworthy is the concept of running calibration standards in parallel with the assay, which is another important way to allow for interferences in complex matrices. It is notable, however, that despite early promise SmartSense is not currently commercially available. Another electrochemical immunosensor based on liposome migration will be discussed below together with its optical equivalent. 5.2.4.3.2. Optical immunosensors Designing a test system for extra-lab measurements was the emphasis of work undertaken by Durst and co-workers (Durst et al., 1993; Reeves et al., 1995). The single use device consisted of an immunomigration strip of plastic-backed, porous nitro-cellulose, along which the sample solution was drawn trough different compartments by capillary forces (Figure 5.11). The herbicide alachlor was used as a model analyte in this competitive immunoassay and the signal resulted from the release of a dye from liposome particles used as antigen-labels. Antibodies were immobilised along the migration route forming a capture zone and unbound liposomes migrated to the indicator zone. This

Figure 5.11. Liposome based immunomigration strip (after Durst et al., 1993). immunosensor strip has the advantage of being independent of further instrumentation, since the readout can be performed visually: the colour intensity in the indicator zone is directly proportional to the analyte concentration. The set-up could be used with electrochemical markers inside the liposomes as well or in combination with a refractometer/ photometer if greater accuracy, precision and sensitivity is desired. The assay time was approximately 8min., and the possibility of having parallel test strips for calibration/verification was mentioned. The transfer of this type of assay to soil analysis appears desirable because of the possibility of avoiding further instrumentation and the more intuitive correlation between response and analyte concentration: signal increase with increasing amount of contamination, both of which are features facilitating use by relatively untrained personnel. Of course a number of potential problems would have to be addressed, like blocking of the nitro-cellulose by soil particles or disruption of the liposomes, particularly if organic solvents were present. When transferring the concept to the development of a liposome based amperometric immunosensor as well as an optical enzyme assay with reflectometric read out, Schmid et al. (1997) encountered more difficulties than anticipated. The amperometric sensor was constructed using disposable electrodes screen printed onto ceramic substrate and it proved difficult to obtain appropriate liopsome migration. Despite the difficulties, a prototype liposome-migration immunosensor and several formats of immunostrips suitable for the measurements of s-triazine pesticides in ground water and soil extracts were developed. According to the authors, further improvements are necessary to satisfy all practical needs. Applying waveguide surface plasmon resonance (WSPR) to the determination of simazine in spiked natural surface- and ground-water samples, Mouvet et al. (1997) found a good correlation with HPLC results for samples pre-treated only by filtration (0.45 µm). The advantage of WSPR is that it is a direct measurement system detecting the binding event between the immunocompounds with no need for a labelled competitor. The sensor set-up included the use of aminodextran on a gold surface and a triazine derivative coupled to the amino groups of the dextran. Fab fragments were pre-incubated with the sample so that the free analyte occupied a proportion of the binding sites. This solution was then injected into a FIA system Page 263 past the sensor surface where the free Fab fragments bound to the immobilised atrazinederivative, resulting in a signal inversely proportional to the free analyte concentration. The assay time was approximately 30min., and the sensor could be regenerated by acidic disruption

of the antigen-antibody complex. Cross-reactivities with e.g. atrazine rendered the system more suitable for screening groups of pesticides than for the detection of a single molecule. The pesticides were introduced to the system as highly diluted stock solutions resulting in solvent concentrations of below 0.24 % methanol in the system. The assay did not produce false negative results, but considerable non-specific matrix effects were observed. Specifically the strong unspecific polyanion-polycation binding of organic compounds to the sensor surface prevented the analysis of a soil-water sample (sampled with a lysimetric plate) and other samples with a high organic load. The same general problem was observed when using aminodextran as the sensor surface in reflectometric interference spectroscopy (RIFS) (Mouvet et al., 1996). The technology was likewise found suitable as a method for monitoring pesticides in natural water samples, but since the presence of humic acid caused strong interferences, it is doubtful that either could be transferred easily to soil analysis, without modifying the sensor surface significantly. An overview of optical transducer principles and surface analytical techniques was given by Brecht and Gauglitz (1995). Interferometric analysis methods are presented and discussed herein. Two different immunological techniques using fluorimetry for the detection of dealkylated degradation products of atrazine have been described (Wittmann and Schmid, 1994; Wittmann, 1996). The work included the development of a FIIA (flow injection immuno assay) system as well as a dip-stick format and tested a large range of different sample matrices from natural river water through liquid food and fruit juices to soil extracts. The analytical results with spiked samples were verified by GC analysis and a good correlation and reproducibility was found. For the dipstick production goat anti rabbit IgG was immobilised on nylon membranes (Biodyne B) and used to capture the specific polyclonal rabbit antibodies. The membrane was than attached to PVC backing strips. In the FIIA (see Figure 5.12) porous microglass beads with activated surfaces served as solid support and the antibody immobilisation was performed via the avidin/biotin system. A competition assay between free and horseradish peroxidase labelled antigen resulted in the formation of a coloured product which was quantified using a RQflex reflectometer. The total assay time for the dip-stick assay was reported to be ca. 25 min., with a measurement range for deethylatrazine from 0.1–10 ppb and for the flow system 15 min. including a regenerative washing step, the measurement range being 0.01–10 ppb. The soil extract procedure consisted of an elaborate solvent extraction (first shaking with acetone/water overnight, adding NaCl and dichloromethane and shaking for an additional hour, drying the solvent with anhydrous Na2SO4, evaporating the organic phase under reduced pressure and drying the last part under nitrogen) which concluded with the re-suspension of the dried extract in distilled water ready for analysis. Even though this method was relatively time-consuming, it was still less cumbersome than the preparation necessary for GC analysis, which requires two additional extraction/purification steps. After the described sample preparation protocol no adverse matrix effects were reported for the analysis of soil extracts. The suitability of the dip-stick sensor for field analysis was emphasised, but

Figure 5.12. Flow injection immunoassay (FIIA) for dealkylated degradation products of atrazine based on fluorimetry (after Wittmann and Schmid, 1994). to be practical would have to be combined with a shorter, less complicated extraction procedure, after which the effect of interferences would have to be re-evaluated. Another set of pesticide biosensors was described using fibre-optic techniques (Anis et al., 1993; Eldefrawi et al., 1995; Wong et al., 1993). Here the principle of evanescent fluorosensors was used to study acetylcholinesterase inhibitors and to develop immunosensors. An immunosensor for the class of imidazolinone compounds (e.g. imazethapyr herbicide) was developed using sheep polyclonal antibodies physically adsorbed onto quartz fibres, which were inserted into a flow-cell (depicted in Figure 5.13) (Anis et al., 1993). The analyte detection took place either by displacing a previously bound fluorescein-linked imazethapyr analoge or by reducing the amplitude and/or rate of fluorescence uptake by the fibre upon association (competitive assay), with the displacement assay being the more sensitive (0.001 µM vs. 0.1 µM). The authors prepared soil extracts by water extraction, centrifugation, neutralisation of the clear supernatant with buffer and filtration (0.45 µm). No adverse matrix effects were observed using this method; this was partly attributed to the relatively short contact times between sample and immobilised antibody in flow-through mode, allowing only compounds with high affinity constants to bind. The advantages of this system are the reusability of the fibres after intermittent buffer washes and the possibility for automation allowing the handling of large sample volumes. Eldefrawi et al. (1995) compared the different measurement techniques (acethylcholinesterase inhibition, immunoassay formats) performed with fibre-optic sensors, and stated that by using a portable fluorometer fiber-optic techniques could be adaptable to field work.

Figure 5.13. Flow cell used in the construction of an evanescent fibre-optic fluorosensor (after Wong et al., 1993). 5.2.5. ORGANIC POLLUTANTS

The term organic pollutants is commonly used to describe a large number of different compounds of organic origin found in the environment due to human activity. This includes for example PCBs, PAHs, dioxanes, explosives like TNT and mineral oil hydrocarbons. While the total organic load is a pollution parameter in water analysis quantified as Biochemical Oxygen Demand (BOD), the detection of organic pollutants in soil refers mainly to harmful (xenobiotic) substances. The aspects relevant to the development and application of biosensors for the detection of organic pollutants are little different from the considerations discussed above for

pesticide analysis. The sources of contamination are more varied and the reason for analysis is mainly protection of the environment and specifically humans from contact, often coupled to decisions about the necessity of containment or remediation measures. Well known sites of organic pollutants in soil are areas previously used for industrial activity, like gaswork sites or oil refineries, or occasionally sites of accidents involving vehicles used to transport large quantities of these compounds. In general the problems of low water solubilities, extraction difficulties and potential matrix interferences are very similar to pesticide analysis. One possible additional problem found when analysing for organic pollutants rather than pesticides is the possibility of large quantities of enclosed contaminants in solid particles (e.g. coal clinkers). These are not easily extracted and not bioavailable but still contribute to the results obtained with conventional analysis. This is not necessarily an argument against biosensor analysis, especially when the aim of the measurement is to assess the potential danger a contaminated site poses to human health and the environment, where the biosensor measurement can provide a good indicator. Many immunoassays have been developed to detect the compounds listed above in soil samples and a number of biosensors for organic pollutants have been realised for water analysis. To date the transfer of these principles to sensors for organic pollutants in soil has been very limited. It is expected, that adaptation of immunoassays and of the sensor-technology described in chapter 4.2.2. (xenobiotic analysis in water), as well as the development of systems analogous to those explored for pesticide detection will generate a rapid increase in the number of biosensors for organic pollution in soil in the near future. Advances in the area of biosensors for organic phase measurements (section 6) are likewise a promising source for future soil-biosensor developments. Below some examples for existing technology are given and the reader should extrapolate from related sections to assess the difficulties as well as the advantages of using these methods. As for pesticides, whole cell biosensors have been constructed using micro-organisms with the ability to metabolise organic pollutants. Examples include an amperometric microbial sensor for the determination of aromatics and their chloroderivatives (Riedel et al., 1995) using Trichosporon beigelli and a calorimetric sensor for aromatic compounds such as salicylate metabolised by a Pseudomonas cepacia strain (Thavarungkul et al., 1991). Neither device was adapted to soil measurements, but calorimetric devices—such as the enzyme thermistor—have proven their applicability for environmental monitoring in other cases. Their generic measurement principle, ability to tolerate turbid samples and compatibility with organic solvent measurements (see section 6) as well as the recent advances in miniaturisation of calorimetric sensors, make them potentially useful for soil analysis. For more details on calorimetric biosensors for environmental monitoring see Kröger and Danielsson (1997). Interesting use of a genetically engineered bioluminescent bacterium (Pseudomonas fluorescent HK44) for the construction of an optical flow injection based bio-

Figure 5.14. Set-up for an on-line monitoring system using a whole-cell biosensor for the detection of naphthalene and salicylate by an immobilised bioluminescent catabolic reporter bacterium (after Heitzer et al., 1994). V2=two way valve, V3=three-way valve. sensor for the bioavailability of naphthalene and salicylate has been reported by Heitzer et al. (1994). The device makes use of the fact, that a large number of catabolic plasmids encoding for the breakdown of organic pollutants have been described (Sayler et al., 1990) and can be used to construct transcriptional fusions with the lux gene cassette. The lux genes encode bacterial luciferase as well as a multienzyme fatty acid reductase complex and in combination form the base for bacterial bioluminescence. The consequence of the fusion between the encoding genes is the possibility to specifically induce bioluminescence when the bacterium equipped with the modified plasmid metabolises the relevant organic pollutant(s). The coupling of both activities introduces the element of selectivity usually lacking in whole cell metabolic biosensors, as was demonstrated by the small signal obtained with other easily metabolised carbon sources (i.e. possible interferences). The reporter bacterium was immobilised in an alginate matrix in close proximity to a liquid light guide and exposed to a constant flow of maintenance medium containing all the components necessary to sustain activity. The set-up for the flow system is shown in Figure 5.14. Aqueous samples containing either naphthalene or its breakdown product salicylate were introduced via valves into the maintenance stream (keeping the overall flow rate constant at 5 ml/min) and the subsequent increase in luminescence could be correlated to the analyte concentration. To determine the mentioned pollutants in a real soil sample from a manufacturedgas plant (sieved sandy loam soil < 3.5mm, naphthalene concentration ca. 320 ppm), 136 g of the soil were packed into a column, which was closed with a 20 µm pore size stainless steel plate to prevent soil loss. The column was inserted into the liquid handling system, sterile water was pumped through and the aqueous leachate obtained was combined with the maintenance stream to carry the extracted pollutants to the biosensor tip. An increase in bioluminescence was recorded that corresponded well to the naphthalene concentration measured in the column output (0.5 ppm), indicating that the device was useful in establishing the presence and bioavailability of organic pollutants for which catabolic pathways are characterised sufficiently on a genetic level. The observation that toluene saturated water (ca. 500 mg/l toluene) as liquid sample did

not result in a significant bioluminescent signal and the biosensor remained fully functional after the exposure not only indicated the specificity of the system, but suggested that it could be adapted to organic phase extraction of pollutants from soil, particularly for analytes less water soluble than naphthalene. A review of fibre-optical fuoroimmmunosensors for environmental analysis and in particular the detection of PAHs and aflatoxin has been written by Vo-Dinh et al. (1992). The authors gave consideration to the forces giving rise to antibody recognition, discussed poly-versus monoclonal antibodies and immobilisation methods, affinity-avidity considerations and gave examples of, for example, a measurement system for the carcinogen benzo(a)pyrene. Polychlorinated biphenyls (PCBs) have been extensively used for example as lubricants, fire retardants and immersion oils and have been identified by the U.S. EPA as priory pollutants to be targeted by remediation. Their fast and convenient detection in water samples by a liposomebased immunomigration sensor analogous to the devices described for pesticide sensing in section 4.4 has been investigated by Roberts and Durst (1995). An amperometric immunoassay for PCBs with immobilised PCB-gelatine conjugate, a limited amount of free PCB-antibody and detection via a horseradish peroxidase labelled secondary antibody in flow-injection analysis, was suggested by Del Carlo and Mascini (1996). Zhao et al. (1995) suggested a fibre optic immunosensor for PCBs with fluorescine conjugated 2,4,5-trichlorophenoxybutyrate competing with the analytes for binding to polyclonal antibodies at the optic fibre. Since this group of pollutants is so widespread in a multitude of media, the adaptation of such measurements to soil analysis would be highly desirable. The same applies for the detection of phenol and chlorinated phenolic compounds, which has been realised in water analysis for example by using a polyphenol oxidase enzyme electrode (Besombes et al., 1995). Addressing the specific needs of instrumentation developed for field us, Williams and D’Silva (1994) introduced a prototype for a hand-held battery powered electroanalytical instrument for environmental monitoring. The technique used was anodic linear-scan stripping voltametry and the instrument was applied to heavy metals rather than organic pollutants. Wang and Chen (1995) discussed the application of a remote electrochemical biosensor for field-monitoring of phenolic compounds. The submersible probe described consisted of a tyrosinase containing carbon paste electrode connected via a ca. 20m long shielded cable. Challenges associated with the adaptation of an enzyme electrode to remote sensing, as well as variables relevant to field operation were investigated. Either instrument could be combined with other applications for field use.

5.2.6. BIOSENSORS AND ORGANIC SOLVENTS

The fact that biological molecules such as enzymes can retain their activity in organic media has been know for many years (Dastoli et al., 1966), but only in the past ten years has its full potential, for catalysis of poorly soluble substrates, biotechnological work in unusual environments and bio-analytical methods such as biosensors been recognised. A large number of original papers and reviews (Braco, 1995; Dordick, 1989; Freeman, 1986; Halling, 1987; Klibanov, 1986; Klibanov, 1990; Stöcklein and Scheller, 1995; Zaks and Klibanov, 1988; Zaks and Russell, 1988) have been published concerning biocatalysis in pure or mixed organic phases and theories have been formulated to establish a causal link between solvent characteristic and the performance of the biocatalyst (Laane et al., 1987; Kise et al., 1990; Griebenow and Klibanov, 1996). 5.2.6.1. Enzymes in organic solvents

Generally speaking, proteins such as enzymes are poorly soluble in organic solvents, and therefore different approaches have been pursued when studying organic phase enzyme activity: suspension of the enzyme, enclosure in reverse micelles, modification with e.g. polyethylene glycol (PEG) (Takahashi et al., 1984) or surfactants (Jene et al., 1997) to make the enzyme soluble or simplify immobilisation, as commonly used in biosensors. A consequence of the applicability of enzymes in organic solvents and the sometimes very interesting characteristics displayed by these enzymes was the development of a whole group of new biosensors: organic-phase biosensors and in particular organic-phase enzyme electrodes (OPEs) (review by Saini et al., 1991) and biosensors for organic solvent-based flow analysis, as reviewed by Wang (1993). These biosensors utilise a number of different enzymes or even complete tissue (Wang et al., 1992) in a whole range of solvents, ranging from anhydrous highly polar solvents to mixtures of water-miscible solvents and buffer. Organic-phase enzyme biosensors have been constructed using the same measurement principles as in the aqueous phase: metabolic and inhibition studies, and the potential relevance of this group of sensors to soil analysis is apparent from the soil-sample preparation outlined above (Figure 5.7). Unfortunately it appears that no organic-phase enzyme-biosensors has actually been applied for soil analysis to date, and it is therefore only possible to speculate on their usefulness in the field. Below some potentially relevant organicphase biosensors will be discussed and Table 5.2. gives examples of enzyme/solvent combinations described in the literature that might be of use in the future when developing sensors for soil analysis. An enzyme frequently used for the detection of phenols is tyrosinase and this reaction formed the basis for the first organic-phase enzyme electrode described by Hall et al. (1988) for the detection of p-cresol in chloroform. It has also been combined with a Clark-type oxygen electrode and applied to measure phenol concentrations in buffer saturated chloroform (Schubert et al., 1992) and n-hexane (Campanella et al., 1993). Immobilisation of the enzyme on a graphite disk electrode resulted in a sensor for phenols in olive oil (Wang et al., 1992). The activity and stability of tyrosinase in aqueous and nearly non-aqueous environments (micelles) have been compared (Yang and Robb, 1993) and it was found more stable in chloroform than in aqueous buffer. Consequently a flow sensor for phenol in chloroform and acetonitrile has been developed

(Wang and Lin, 1993) and the effect of further polar organic solvents on the activity of the enzyme entrapped in a poly(ester-sulphonic acid) polymer was investigated (Iwuoha et al., 1995). Horseradish Table 5.2. Examples of sucessfully applied enzyme/solvent combinations potentially relevant for soil-biosensor development. Enzyme

Solvent

acetylcholineesterase

acetonitrile, benzene, butanol, butyl acetate, CCl4, Mionetto et al., 1994 chloroform, cyclohexane, decane, DMSO, docecane, ethanol, ethyl ether, heptane, hexadecane, hexane, nonane, octane, propanol, tetrachloroethane, tetradecane, toluene, tridecane, undecane

alcohol acetonitrile, butylacetate, butylether, chloroform dehyrdogenase

References

Deetz and Rozzel, 1988

acetonitrile, butylacetate, methylene chloride

Guinn et al., 1991

butylacetate

Hall and Turner, 1994

hexane

Kawakami et al., 1992

acetonitrile

Wang et al., 1994

acetonitrile, butylacetate, methylene chloride, diisopropyl ether, tetrahydrofuran

Zaks and Klibanov, 1988

alcohol oxidase butylacetate, ethyl acetate, diethyl ether, octanol

Zaks and Klibanov, 1988

cholesterol oxidase

amylalcohol, benzene, butanol, butanone, butylacetate, chloroform, dichloroethane, hexane, morpholine, pyridine, tetrahydrofuran, toluene

Kazandijan et al., 1986

chloroform: hexane, cyclohexane

Hall and Turner, 1991

glucose oxidase ethanol acetonitrile, butanol

Flygare and Danielsson, 1988 Iwuoha and Smyth, 1994 Iwuoha et al., 1995

horseradish peroxidase

acetone, acetonitrile, chlorobenzene, chloroform, dioxane, ethyl acetate, methylene chloride, methanol, tetrahydrofuran, toluene

Dong and Guo, 1994

amylalcohol, benzene, butanone, butylacetate, chloroform, dichloroethane, hexane, morpholine, pyridine, tetrahydrofuran, toluene

Kazandijan et al., 1986

toluene, toluene:diethylesther

Flygare and Danielsson, 1988

chloroform

Mannino et al., 1994

ethanol

Reslov et al., 1987

benzene, chlorobenzene, chloroform, dioxane, octanol, propanol, toluene

Schubert et al., 1991 & 1992

benzene

Takahashi et al., 1984

acetonitrile, ethanol

Wang et al., 1991

acetonitrile, chloroform

Wang and Lin, 1993

toluene

Zaks and Klibanov, 1988

Page 271 laccase

butanol, ethanol, propanol

Wang et al., 1993

lipase

chloroform, cyclohexane

Flygare and Danielsson, 1988

polyphenol oxidase

chloroform

Hill et al., 1988

chloroform

Estrada et al., 1991

amylalcohol, butanol, hexyl acetate, methyl acetate, octanol

Zaks and Klibanov, 1988

hexane

Campanella et al., 1992

chloroform:

Campanella et al., 1993

chlorobenzene, chloroform, dichlorobenzene

Deng and Dong, 1996

acetonitrile, acetone, tetrahydrofurane

Iwuoha et al., 1995

chloroform

Schubert et al., 1992

hexane

Stancik et al., 1995

acetonitrile, ethanol

Wang et al., 1991

acetonitrile, chloroform

Wang and Lin, 1993

chloroform, hexane, isooctane

Yang and Robb, 1993

tyrosinase

peroxidase was used in a mediated amperometric biosensor for the detection of hydrogen peroxide (Schubert et al., 1991) and the measurement of organic peroxides (Wang and Lin, 1993). Using the same enzymes for inhibition studies, an amperometric FIA-biosensor for thiourea, benzoic acid, diethyldithiocarbamate, hydroxylammonium sulphate and mercaptoethanol in acetonitrile was developed (Wang et al., 1993). Based again on a Clarkoxygen electrode, tyrosinase inhibition was used to detect thiourea derivatives in hexane due to a decreased in its response to phenol (Stancik et al., 1995). Extending the concept of an amperometric biosensor for tyrosinase inhibitors to measurements in pure chloroform, chlorobenzene and 1,2-dichlorobenzene, Deng and Dong (1996) detected benzoic acid, thiourea and 2-mercaptoethanol.

Acetylcholinesterase (AChE), the most commonly used enzyme for inhibition based pesticide biosensors, was studied for biosensor applications in organic solvents (Mionetto et al., 1994). The authors characterised the performance of the free as well as the immobilised enzyme and described a correlation between AChE activity and physico-chemical parameters enabling them to predict the effect of a solvent on the enzyme activity. As previously stated by Laane et al. (1987) the hydrophobicity of the solvent plays an important role. It is assumed that enzyme inhibition by solvents is mainly a result of disturbance of the enzymes hydration shell, a layer of water bound to the enzyme surface and crucial to its activity. From their experiments with free AChE, Mionetto et al. (1994) conclude that solvents can be divided into three groups: 1. water-immiscible, very hydrophobic (no interaction between enzyme and surrounding essential hydration shell); 2. not completely water-miscible, less hydrophobic (can remove hydration shell, but small amounts of water present in the bulk solution can prevent inhibition); 3. water-miscible, hydrophilic solvents (mainly alcohols, strip essential water from enzyme when applied pure). In solvents out of group 1 and 2 the authors observed significant AChE activity, while group 3 solvents proved destructive. Interestingly, immobilisation of the enzyme was found to protected the enzyme, allowing a wider range of solvents (group 3) to be used. These findings were applied in the construction of an electrochemical biosensor for organophosphorus and carbamate insecticides in a large range of different organic solvents. Another reason, why the performance of enzymes in organic solvents is of interest, is their application as labels in immunoassay. Not only enzymes, but antibodies too have been found to remain active in environments other than aqueous buffers (Russell et al., 1989). When reviewing enzymes potentially relevant for the development of biosensors for soil analysis, some enzymes commonly used as labels in immunoassays should be taken into account as well. Typical examples include horseradish peroxidase and glucose oxidase. Both have been mentioned in Table 5.2, and horseradish peroxidase has not only been used in combination with co-adsorbed hexacyanoferrate (II) as a mediator (Schubert et al., 1991) and ultramicroelectrodes for measurements in non-polar solvents (Wang et al., 1991), but chemically modified with 2,4-bis (O-methoxy-polyethylene glycol)-6-chloro-s-triazine to be soluble and active in benzene as well (Takahashi et al., 1984). 5.2.6.2. Antibodies in organic solvents

Compared to the number of publications describing the activity of enzymes in organic solvents, little is known about the performance of antibodies. The first publication describing the action of antibodies in anhydrous organic solvents (Russell et al., 1989) investigated anti-4-aminobiphenyl antibodies immobilised on glassbeads in dioxane, acetonitrile, propanol, butanol and pentanol using a competitive assay with radioactively labelled antigen. The authors showed that the antibodies remain not only active but highly selective in all the solvents tested. Comparing the respective dissociation constants, a correlation was found between the hydrophobicity of the

solvent and its interference with the interaction. Contrary to the correlation described above for some enzymes, the antibody-antigen affinity increased with decreasing solvent hydrophobicity. This phenomenon can be understood when analysing the factors contributing to antibody-antigen binding: for a hydrophobic antigen such as 4-aminobiphenyl non-polar interactions contribute considerably and thus the interaction is weakened by non-polar solvents. The binding of triazines herbicides (atrazine) to two different immobilised polyclonal antibodies in anhydrous nonpolar organic solvents was investigated by Stöcklein et al. (1990). The antibodies were immobilised on immunodyne membranes and used in a competitive assay format. For one of the tested polyclonals the c50% (concentration of analyte needed to outcompete the labelled conjugate) increased with increasing hydrophobicity of the tested solvents (lowest in buffer, highest in n-hexane), as predicted by Russell et al. (1989, see above). Interestingly the second antibody did not display the same pattern. The authors conclude the antigen-antibody binding is not only influenced by solvent polarity, but significantly by the solubility of the analyte in the respective solvent. Not only antibody-antigen interactions, but the ability of some antibodies to catalyse reactions (“catalytic antibodies” or “abzymes”) has been studied in organic solvents. Studying the behaviour of an antibody catalysing stereo-selectively the hydrolysis of an alkyl ester in different aqueous-organic biphasic solvent systems, Ashley and Janda (1992) concluded that higher activity of their system was observed in more polar solvents (log ρ of 4 or above) and determined the amount of water that had to be present in octanol to preserve activity (for optimum activity ca. 15 %). More examples of investigations concerning the influence of organic solvents on antibodies include a paper on the testosterone-antitestosterone interaction at various solvent-water ratios of different solvents (Giraudi and Baggiani, 1993), the selection of monoclonal antibodies to okadaic acid that retain their binding activity in 90–100% methanol (Matsuura et al., 1993), investigations concerning the binding mechanism of an antiestradiol antibody in dilute solutions of organic solvents (De Lauzon et al., 1994) and a study investigating the effects of watermiscible organic solvents on semi-continuos immunochemical detection of coumarin derivatives (Stöcklein et al., 1995). The application of enzymes and antibodies in organic solvents has been reviewed by Stöcklein and Scheller (1995), who emphasise the possibility to analyse hydrophobic analytes such as pesticides directly after organic-phase extraction from soil, food or water samples. Protecting the antibodies by enclosure in reverse miscelles with aqueous centres, Francis and Craston (1994) proposed an immunoassay for parathion without its prior removal from solution in hexane. Free antigen in hexane competed for antibody binding sites with the antigen-coated surface of a micro-titer plate. The sensitivity of the assay was decreased when compared to the aqueous phase ELIS A, but the authors suggested means of circumventing this problem and stated that the concept is simple and therefore could easily be applied to other hexane-soluble analytes. A number of environmental immunoassay and immunosensors have been proven to tolerate small amounts of water-miscible organic solvents (usually ca. 1%, see above) and for example

Goh et al. (1990) described the influence of methanol and acetonitrile have on their enzyme immunoassay for atrazine soil residue analysis. Up to 3 % acetonitrile or up to 10 % methanol were tolerated, the latter yielding the better lower detection level. Encouraged by the above findings of enzyme as well as antibody activities in water-miscible organic solvents, Kröger et al. (1997) developed an electrochemical immunoassay for the herbicide 2,4-D capable of working directly in methanol/buffer extracts of soil samples. The device was based on a solvent resistant screen-printed three electrode system (Kröger and Turner, 1997), utilised monoclonal antibodies screened for their ability to bind the antigen in the presence of methanol and was intended for field use. A simple extraction method for the analyte from soil consisting of alternating shaking and sonication of a soil/solvent slurry followed by filtration was used. The competitive immunoassay was performed with either glucose oxidase as an enzyme label combined with a catalytic working electrode surface (lowering the potential for the detection of hydrogen peroxide oxidation to +300 mV

Figure 5.15. Assay procedure for the detection of 2, 4-D in soil by an amperometric immunosensor (after Kröger et al., 1997). vs. Ag/AgCl), or with horseradish peroxidase and potassium ferricyanide as soluble mediator and a plain carbon electrode. The preferred format was antigen immobilisation at the electrode surface, which was achieved by a number of different methods, and competition of free antigen from the sample with immobilised antigen at the surface. The enzyme-conjugated antibodies were added to a sample aliquot and the competition assay took place in a solution droplet on top of the circular working electrode. From the time of obtaining the soil sample, the extract preparation, competition assay and amperometric measurement of bound antibody-enzyme conjugate took overall ca. one hour; simplicity was the priority in the procedure development rather than sensitivity. A general description of the complete assay procedure is given in Figure

5.15. The detection limits achieved were in the low ppm range, which is adequate for soil analysis (see also US EPA SW846) and could be improved if necessary for other samples. 5.2.7. UNCONVENTIONAL DETECTION METHODS—MOLECULAR IMPRINTING, COMBINATORIAL CHEMISTRY AND RATIONAL LIGAND DESIGN

As indicated above (chapter 5.2.2.), some consideration will be given to a detection method, which is not strictly speaking biosensing: the fabrication of analyte-recognition sites by molecular imprinting. Molecular imprinting is a technique for synthesising artifical binding sites or receptors for a molecule of interest (the “template”) in a highly cross-linked macroporous polymer. It involves assembling socalled functional monomers around the template, then “freezing” them into position by polymerising in the presence of a large amount of cross-linker. The functional monomers are molecules which have both a functional group capable of interacting with some part of the template molecule, by e.g. H-bonding or ion-pair formation, and a polymerisable functional group—usually an acrylate. After the polymerisation the template can be extracted by washing. This leaves binding sites which are complementary in both shape and functionality, to the original template. The technique has recently been reviewed , both generally (Steinke et al., 1995; Wulff, 1995; Mosbach and Ramström, 1996) and with respect to analytical applications (Mayes and Mosbach, 1997). A general model of the steps involved in the imprinting process is given in Figure 5.16. The recognition sites obtained in this manner can possess binding affinities approaching those demonstrated by antibody-antigen systems and have been dubbed “antibody mimics” (Vlatakis et al., 1993). These “mimics” display some clear advantages over real antibodies: they do not rely on animal experiments and the resulting polymers are intrinsically stable and robust, which makes them ideal recognition elements for sensors. Their use in immunoassay-like techniques has been discussed by Andersson et al. (1995) and they have been introduced as recognition elements in conductometric chemical sensors (Kriz et al., 1996). A number of publications have dealt with the development of imprints against molecules of interest in environmental monitoring, such as the pesticides atrazine (Muldoon and Stanker, 1995; Piletsky et al, 1995; Siemann et al., 1996) and 2,4-D (Haupt and Mosbach, 1997), and their application in detection of pollutants. While molecular imprints have been largely applied for the detection of analytes in organic solvents, considerable effort has been made to adapt them to aqueous environments. As discussed above, soil analysis very often necessitates the analysis of organic-phase extracts of the sample matrix and what has long been regarded as a factor limiting the application of molecular imprints, could prove to be of considerable advantage in this field. Combing the developments made, and discussed in the previous sectors, for the adaptation of biosensors to soil analysis with this new group of affinity receptors, holds considerable potential for the future analysis of pesticides and organic pollutants in soil samples, although a number of technical issues remain to be addressed if molecular imprints are to be successfully incorporated into chemical sensors. The second area of rapidly increasing interest is the design of artificial ligands by rational synthesis (molecular modelling) and/or combinatorial chemistry. Small peptides or otherwise derived molecules can mimic some of the features essential to specific binding. These methods

allow binding receptors to be produced for analytes which were previously difficult to detect. Furthermore their less complex nature, compared to natural ligands such as antibodies, renders them potentially more stable and thus suitable for harsh environments, such as soil extracts. An additional advantage is their potential to be easily mass produced and therefore less expensive than conventional affinity ligands. To date, examples for successfully designed and produced artificial ligands include protein A mimics (Dowd et al., 1997) and interesting concepts were discussed in a session on combinatorial libraries on the 12th International Symposium on Affinity Interactions in Kalmar, Sweden (1997). A new EC

Figure 5.16. Schematic diagram of the stages of the molecular imprinting process for atrazine. programme (“Envirosense”) is dedicated to the development of artificial ligands for pesticide metabolites and some of the work undertaken was presented on the Fifth European Workshop on Biosensors for Environmental Monitoring and Stability of Biosensors in Freising, (Bestetti et al., 1997). It will be interesting to see the impact, these new methods will have on the future design of sensor for soil analysis.

5.2.8. CONCLUDING REMARKS

Many factors influence the selection of an appropriate measurement method for a given analytical problem: cost, speed, simplicity, sensitivity, reliability, specificity, robustness, applicability in the field, to name but a few. The choice will almost always be a compromise and depending on the prevailing priorities, the respective requirements will be fulfilled by a different device. It is therefore of utmost importance to know what devices are or could be available, which concepts have been developed, and to appreciate the advantages and drawbacks of individual methods, to make a valid decision. The intention of this chapter was to give an overview of aspects relevant to soil analysis. Meaningful analytical results can only be obtained with sufficient background knowledge about the soil matrix and sample preparation procedures. Overall some very promising results have been achieved for the analysis of pesticides and organic pollutants with biosensors and it is expected that the range of techniques applied to soil measurements will increase significantly in the coming years. Soil analysis in this context can be regarded as an advance on water analysis and as sensor systems become more established, robustness and reproducibility will be improved to be adequate for more challenging environments. Much attention has to be paid to the elimination or accurate quantification of interferences and advances in conventional analytical methods should be monitored and utilised in the development of assay procedures. Applied with the appropriate care and consideration, biosensors and related techniques have a lot to offer to soil analysis, particularly in the areas of decentralised monitoring and sample pre-screening. Finally biosensors should be viewed as a valuable addition to conventional analytical techniques, not necessarily as an alternative. ACKNOWLEDGEMENTS

Dr. A.G.Mayes is gratefully acknowledged for help in preparing the section on molecular imprinting and for providing Figure 5.16. REFERENCES

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6. GAS-PHASE ENZYME ELECTRODES MANUS J.DENNISON and ANTHONY P.P.TURNER 6.1. BACKGROUND

This chapter focuses on the possibilities for developing biological sensors for directly monitoring gaseous analytes. It is principally concerned with research on enzyme biosensors for the monitoring of phenol, ethanol and formaldehyde. These three analytes were selected to illustrate a number of issues. The enzyme which catalyses the oxidation of phenol (polyphenol oxidase) is relatively well characterised, widely commercially available, stable over a period of months (when stored at −20°C) and relatively inexpensive, which makes it ideal for research. In addition, there exists a clear need in the market place for a phenol vapour sensor, phenol being one of the most widely used chemicals in industry (Gilbert, 1994). Detection of ethanol vapours is important for industrial applications and legal reasons. Alcohol oxidase and alcohol dehydrogenase, however, are neither stable nor cheap. They would present problems for a commercial alcohol biosensor, and progress in stabilising the enzymes is certainly needed. Formaldehyde is a very important gas, as it is associated with serious health problems. Legislation introduced into Germany stipulates that all new homes have to be measured for formaldehyde levels (Anon, 1994). This formaldehyde arises from materials used in modern building construction as formaldehyde is an important component of modern glues and resin. Formaldehyde dehydrogenase which oxidises formaldehyde is neither cheap nor stable, but the demonstration of a biosensor for measurement of formaldehyde vapour is an important advance. Current health and safety legislation necessitates the need for monitoring of potentially toxic gases/vapours and it is in this area that cheap, reliable, accurate biosensors could come to the fore. One of the main advantages of using enzyme based systems is their high degree of specificity; precise concentrations of analytes can be detected with little or no cross-interference. These advantages of specificity and sensitivity at ambient temperatures combined with real time results give biosensors a distinct advantage over current gas detection methods. However, the instability of many biological systems remains a serious disadvantage for biosensors and would have to be overcome for successful commercialisation. Gas-phase biosensors are unsuitable for use at high temperatures, because of enzyme inactivation, or at very low temperatures, because of the temperature sensitivity of biological systems. These high and low temperature areas will probably remain the domain of chemical sensors. Gas-phase biosensors, however, could function admirably in the areas of health and safety monitoring and clinical sensing. Non-invasive monitoring of clinically significant gases and vapours in the breath, such as O2, CO2, halothane, acetone, ethanol and certain drugs is also particularly appealing. The field of gas sensing using biosensors has of yet been relatively unexplored, but it presents many new opportunities. 6.2. GAS-PHASE BIOSENSORS

Although biosensors have made a large impact in clinical sensing in the field of blood glucose measurement (Turner, 1997) and have been demonstrated for environmental monitoring (e.g.

phenol) in aqueous and non-aqueous liquids (Dennison and Turner, 1995), they have made little impact on the field of gas or vapour sensing (Saini and Turner, 1995). Early gas-phase biosensors were essentially bioreactors containing the sensing element (usually, bacteria or enzymes) immobilised in an aqueous phase, into which was pumped the gas in question. The gas then dissolved in the aqueous phase where it was detected by the sensing element. Biosensors based on this principle include the earliest reported gas-phase biosensor (Karube et al., 1982). This biosensor was based on a methane-oxidising bacterium, Methylomonas flagellata, in buffer. When methane was pumped into this buffer, the bacteria metabolised the methane reducing aqueous levels of O2. Changes in O2 concentration were detected by a Clark oxygen electrode. A similar biosensor was also constructed for nitrogen dioxide (Karube et al., 1987). The gas phase is usually a much drier environment than the aqueous phase and water from the biosensor will evaporate to the gas phase. This loss of water will eventually affect biological activity negatively and will also alter the concentrations of the substrates and products. Hence, biosensor response, stability and lifetime will be affected by the concentration of water in the air. Using a bioreactor, where the biosensor operates in aqueous solution and measures dissolved gases, overcomes this problem by avoiding direct interfacing with the gas phase. Other examples of whole cell gas sensors include work by Li et al. (1994) who immobilised Penicillium decumbens on an oxygen electrode to detect trimethylamine gas in solution, and Suzuki et al. (1991) who immobilised S-17 autrophic bacteria in a calcium alginate gel on a miniature Clark-type electrode to detect CO2 in solution. Turner et al. (1984) constructed a biosensor for carbon monoxide measurement in solution using carbon monoxide: acceptor oxidoreductase from Pseudomans thermo-carboxydourans. Oxidation of CO by the enzyme was concurrent with the reduction of a mediator, which was detected amperometrically. Further gas-phase enzyme electrodes include a potentiometric biosensor for CO2 (Tierney and Kim, 1993) based on the enzyme carbonic anhydrase dissolved in a commercial hydrogel. This biosensor was able to measure CO2 over the range 1 % to 10% (v/v). Tierney reported that stability and response were strongly dependent on the relative humidity of the test gas. A gas-phase biosensor for ethanol (Mitsubayashi et al., 1994) based on immobilised alcohol oxidase with an oxygen electrode could measure ethanol in the gas phase from 0.358ppm to 1242 ppm. A circulating system of buffer was necessary to prevent dehydration of the enzyme. Spectral changes on HCN binding haemoglobin were used as a basis for a gas-phase HCN biosensor by Moss et al. (1994). Spectral changes were found to correlate to the concentration of HCN over the range 10 ppb to 10 ppm. Air humidity was found to have a significant effect on response, but the authors found they could compensate for it by measurement at a third wavelength. 6.3. PHENOL

Phenol exists as an off-white crystal that readily sublimes (melting point 42°C). It has a characteristic odour—pungent and aromatic—and is easily detected by the human nose. Phenol is one of the most important and widely utilised industrial chemicals (Gilbert, 1994), being used

in the production of pesticides, dyes, disinfectants, antioxidants, pharmaceuticals, oil additives, polyurethanes, phenol-formaldehyde resins, plasticizers, surfactants and explosives. 6.3.1. SOURCES OF PHENOL POLLUTION

Substantial emissions of volatile organic carbons (VOCs), including phenols are due to natural gas, crude petroleum (Faith and Atkisson,1972) and coal liquefaction processes (Dauble et al., 1983). Specific sources involve all places where these materials or their simple products are handled. Coal liquefaction processes developed in the early eighties to provide alternative sources of liquid fuel produce coal liquids with approximately 14% (w/v) phenols (Weiner et al., 1980). However the water soluble fraction of these coal liquids contain nearly 98% phenols (Dauble et al., 1983). Phenolic contamination also arises from industries manufacturing plastics, dyes and especially the wood pulp industry (Neilson et al., 1991). The use of bleaching agents in the wood pulp industry produces chlorophenols. Phenols also arise from the paint and varnish manufacturing industries. Phenol is used in the manufacture of phenol-formaldehyde plastics. These polymers are used extensively for the encapsulation of integrated circuits and have been shown to break down to yield phenol and formaldehyde among other products (Grezeskowiak et al., 1988). The fact that phenolics along with other volatile organic compounds (VOCs) occur in treated wood (Mayer, 1993), varnishes, adhesives and plastics has implicated them in sick-building syndrome. Many studies have shown higher levels of VOCs in indoor air, leading to the suggestion that sick-building syndrome is due to certain VOCs. Domestic disinfectants and non-ionic surfactants (of the nonylphenyl ethoxylate variety) and pharmaceutical products also contribute to the presence of phenols in the environment (Symons, 1990). Agricultural sources of phenols mainly arise from the breakdown of herbicides and pesticides containing the phenolic skeleton. Additionally, there are those phenolic compounds which find uses directly as pesticides, e.g. 2 phenylphenol, used as a fungicide on citrus fruits and pentachlorophenol (PCP) which has previously been used as a pesticide for termites and as a general herbicide, although a EU directive has now restricted its use (Mayer, 1993). 6.3.2. PHENOLS AND AIR POLLUTION

A recent study of air pollution in an industrialised Soviet city, Shchekino, revealed levels of up to 0.5mg/m3 (1.3ppm) phenol vapour in the city air (Drugov and Murav’eva, 1991). In America, Shah and Singh (1988) monitored organic compounds in the atmosphere. Particularly abundant was phenol with median daily concentrations of between 0.0l6 mg/m3 and 0.0313mg/m3 (4ppb and 8ppb). Ciccioli et al. (1992) measured VOCs over the Italian peninsula and measured concentrations of 0.0006mg/m3 (0.2ppb) and 0.0049mg/m3 (1.3ppb) phenol in Rome and Milan respectively. Suburban and rural concentrations of phenol were extremely low, indicating that the highest concentrations of phenol vapour were found in cities and heavily industrialised areas. Phenol vapours also occur in the manufacturing areas of industries using phenol. It is in these locations that workers are exposed to phenolic vapours. A study in a factory manufacturing carpet underlay (a phenol-formaldehyde resin) recorded levels of 4.3mg/m3 (1.1 ppm) on the forming line (Cleghorn and Fellini, 1992). While in a foundry and metal-working plant, workers

were exposed to levels of approximately 0.2 mg/m3 (0.05 ppm). Most of the phenolic vapours were due to the use of phenol-formaldehyde resins (Drugov and Murav’eva, 1991). 6.3.3. HEALTH EFFECTS

Many studies on the effects of exposure to high levels of phenols have been carried out, but there remains a paucity of information concerning the effects of long term exposure to low levels of phenol. Phenol is easily absorbed, regardless of the type of exposure. In humans, phenol solutions and vapour are mostly absorbed through the skin, rapidly concentrating in the liver, central nervous system, the lungs and the blood. The LD50 for phenol in mice, rats, rabbits and dogs ranged from 300–600 mg/Kg bodyweight, whereas the inhalatory LD50 in rats was greater than 900 mg/m3 over an eight hour exposure period (Brown et al., 1975). Toxic effects at sublethal dose levels include tremors, convulsion followed by a low and non-regular pulse and a decline in body temperature. The time weighted average (TWA) limit for phenol vapour exposure is 5 ppm (19–5 mg/m3) over an eight hour period (Sigma-Aldrich, 1988). Exposure to phenol vapour at concentrations greater than the TWA limit, has been shown to have detrimental effects on the organs exposed and on the liver, kidney and blood. The effect of long term exposure to low levels of phenols, which is a more plausible scenario, taking into account recent studies on phenol pollution, is as yet unclear. Naturally occurring organic phenols present in plants are known to have oestrogenic properties (Van Oettingen, 1949; Stob, 1983). A phenol present in certain plastics, p-nonyl-phenol, has been shown to have oestrogenic properties (Soto et al., 1991), as have alkylphenols (Colborn, 1993). PCBs are also believed to have oestrogenic properties. Phenolic compounds have been linked with induction of hermaphroditism in male roach fish; they are also being considered as being responsible, or partly responsible for the decline in western male fertility over the last 50 years (Dispatches, 1994). 6.3.4. POLYPHENOL OXIDASE

The widely observed browning of mushrooms, potatoes and many other plant products is the result of enzymatic oxidation of certain phenolic compounds by poly-

Figure 6.1. Oxidation of phenol by polyphenol oxidase. phenol oxidase (PPO). Commonly purified from mushroom, PPO catalyses the oxidation of phenols and catechols, as shown in Figure 6.1. These two activities of PPO, the oxidation of phenols and catechols are termed cresolase and catecholase activity respectively, and in the mushroom the catecholase/cresolase activity is about

5:1 (Dawson and Magee, 1958). Cresolase activity is characterised by an induction period, which can be shortened by the presence of reducing agents, small amounts of catechol or the presence of an endiol group (Estrada et al., 1991). The oxidation of catechol proceeds faster than cresolase oxidation. Mushroom tyrosinase has a copper content of less than 0.1 % and a molecular weight in excess of 200,000 daltons. In the absence of crystals sufficiently pure for X-ray crystallographic analysis, the solid-state structure remains undefined (Burton, 1994). PPO contains a pair of cupric ions that presumably act as the active site for electron exchange (Jolley et al., 1974; Himmelwright et al., 1980). These metal sites shuttle between the Cu++ to the Cu+ state. The exact mechanism of phenol oxidation has not been elucidated yet, but Smit and Rechnitz, (1993) proposed the following mechanism; Electron transfer from a suitable substrate (phenol/catechol) effects the reduction of the Cu++ to the Cu+ state. The reduced copper then binds O2- Subsequent electron transfer from an additional electron donor (phenol/catechol) results in the release of two molecules of water. Substances known to complex with Cu such as KCN, CO and British antilewisite (BAL) inhibit the enzyme, while 4-nitrocatechol and 4-nitrophenol are competitive inhibitors. Cresolase activity is less stable than catecholase activity in general (Dawson and Magee, 1958). Purified PPO solutions with more than 1 mg/ml show little loss in activity over several months when buffered at pH 7 with a few drops of antiseptic and stored at 5°C. Highly dilute solutions lose a significant proportion of activity within 15 to 29 minutes even at 5°C. A characteristic feature of PPO is the marked inactivation of the enzyme during the course of the reaction. The inactivation of the enzyme, especially during the early course of the reaction, has been widely observed (Asimov and Dawson, 1950; Ingraham et al., 1952), indeed PPO was one of the first enzymes to have the term “suicide enzyme” applied to it (Burton, 1994). PPO is thought to be inactivated by the quinone polymers formed in aqueous media during the course of the reaction (Ingraham et al., 1952). Some evidence also points to the existence of a complex between the enzyme and the products of oxidation (Wood and Ingraham, 1965). The catecholase sites of PPO seem to have little or no involvement in the oxidation of monophenols (Dressler and Dawson, 1960). 6.3.5. BIOSENSORS FOR PHENOL MONITORING

There have been many reports in the literature of the application of biosensors to the detection of phenols in aqueous and non-aqueous media. The vast majority of these biosensors for aqueous and non-aqueous phenol detection use PPO as the catalytic enzyme. PPO catalyses the oxidation of phenols to catechol and then to quinones (Figure 6.1). Oxidation of phenols is concurrent with quinone generation and oxygen depletion. Electrochemical phenol biosensors measure either the depletion of oxygen or the generation of quinones. Oxygen monitoring using the Clark oxygen electrode is a well established technique, while the electrochemical properties of quinones are also well documented. Direct electroreduction of the product of phenol oxidation, benzoquinone, is probably the most widely used method of measuring phenol concentration. The quinone product can be directly reduced at between −100 mV to −200 mV (versus Ag/AgCl reference), or indirectly via a

mediated system. Phenol can be oxidised at high anodic potentials (Canete et al., 1988), but this results in electrode fouling and is also susceptible to electrochemical interferents (Berchmans et al., 1988). The formation of melanin (a complex polymer of quinones and catechols), leading to the formation of a tar-like solid on the electrode surface during phenol electro-oxidation is a well characterised phenomenon (Hedenburg and Freiser, 1953; Koile and Johnson, 1979). Cosnier and Innocent (1992) immobilised PPO in an electrochemically generated polypyrrole film and obtained a detection limit of 5×10−9 M (0.47 µg/L or 0.47 ppb). Skladal (1990) adsorbed PPO at a carbon paste electrode and protected it with a dialysis membrane, also using electrochemical quinone reduction. He could detect aqueous phenol concentrations of 1.3 ppb/w (1.2 µg/L). Schiller et al. (1978) used PPO co-immobilised with ferrocyanide in polyacrylamide for phenol detection. Bonakdar et al. (1989) used PPO with hexacyanoferrate ions immobilised in poly(4-vinylpyridine) in a flow-through system. Phenol detection limits were in the ppb range. A problem with using ferrocyanide is that PPO is inhibited by ferricyanide (Macholan, 1990), leading to stability problems. Kulys and Schmid (1990) overcame this problem by using TCNQ (tetracyanoquinodimethane) as a mediator giving detection limits of 22 ppb (22 µg/L). The use of biosensors in organic solvents for phenol detection presents a number of advantages. There seems to be very little electrode fouling, presumably because of the low water content. This is because water is involved in the polymerisation process which leads to melanin formation (Dressler and Dawson, 1960). Also, PPO does not seem to be inactivated as it is in aqueous solutions by the products of phenol oxidation (Kazandjian and Klibanov, 1985). Oxygen is usually more soluble in organic solvents—it is approximately ten times more soluble in chloroform than in water (Buckland et al., 1975). The use of an organic-phase biosensor was first described by Hall et al. (1988). PPO was adsorbed on a nylon membrane and used to measure phenol in chloroform solutions. Detection limits were 1.5ppm (1.5mg/L), using direct electrochemical detection of quinones. Much work on biosensors for detection of phenols in the organic phase has been carried out by Wang. Wang has successfully applied the use of phenol biosensors to the detection of phenols in pharmaceutical products (Wang, Lin and Chen, 1993a) and also in commercial olive oils (Wang and Reviejo, 1992), using quinone detection as a basis. Exploiting the fact that some plant tissue is naturally rich in PPO, Wang and Naser (1992), used thin layers of mushroom and banana spread onto rough graphite discs to detect phenol in chloroform obtaining detection limits of 2.8 ppm (2.8 mg/L). While Mazzei et al. (1992) used avocado and mushroom tissue to detect catecholamine neurotransmitters in aqueous solutions. Another way of measuring phenol oxidation is to use an oxygen electrode. As phenol is oxidised by PPO, oxygen is consumed, and this reduction in oxygen concentration can be monitored with an oxygen electrode. While Macholan (1990) also used an oxygen electrode, he introduced substrate cycling. As phenol was oxidised, quinone was produced and oxygen was consumed. However, introducing hydrazine into the solution brought about the non-electrochemical oxidation of quinone back to catechol. This catechol was then oxidised to quinone by PPO, with the further consumption of oxygen. This substrate cycling resulted in a 3–5 fold increase in sensitivity, although Macholan did not directly apply the sensor to the detection of phenol, but to the detection of substrate inhibitory aromatic acids. Unchiyama et al. (1993) used the same

principle for a catechol sensor, but using ascorbic acid to recycle the quinone back to catechol, giving detection limits of 5×10−8 M (5.5 µg/L or 5.5 ppb). Ciucu et al. (1991), immobilised Rhodotorula yeast cells in buffer with a dialysis membrane. This yeast catalyses the oxidation of phenol to catechol and then to cis, cis muconic acid, with the concurrent reduction of oxygen. Ciucu could detect phenol levels of 0.8 mg/L (800 ppm). However, stability was a problem, as with most cell-based sensors. The sensor lost 90 % activity over 12 days. Novel applications of PPO based sensors include a cyanide detector (Smit and Cass, 1990). As PPO is a copper based enzyme, it is very sensitive to cyanide inhibition. Cyanide can be detected as the decrease in oxygen consumption, as the oxidation of tyrosine by PPO is inhibited by cyanide. Wang and Reviejo, (1993) used the fact that tyrosinase activity in organic solvents is strongly dependent on water content to construct an organic-phase enzyme electrode for the determination of water in non-aqueous media. 6.3.6. PHENOL-VAPOUR BIOSENSORS

Most previous gas-phase biosensors comprised large bioreactor type formats, which dissolve the biological agent in a buffer reservoir and then actually pump the vapour or gas into the system. For many applications, however, a miniature portable system is required without the need for active pumping. The logical choice of biological agent for a phenol vapour biosensor is limited to PPO, an enzyme which can be purified to high activity, is stable, has been relatively well characterised and is widely available and cheap. The choice of transducer and immobilisation agent remain more open. Oliver et al. (1988), immobilised cytochrome C into two hydrogels, polyethylene oxide and polyacrylamide, and found that the sensors were very sensitive to changes in relative humidity and gel water content. Conducting polymers had been used as supporting electrolytes for organic phase electrodes and Saini et al. (1992; 1995) further investigated one of these, TBATS (tetrabutyl ammonium-4-sulfonate) as an immobilisation media for phenolic vapour biosensors. Initial experiments showed promising results. A series of experiments were described, resulting in a sensor that was responsive to phenol vapours. The sensor was based on ionically conducting films that incorporated a biological redox catalyst at the surface of an array of interdigitated microband electrodes. Exposure to phenol vapour drove the bioelectrochemical reaction, providing a basis for a current signal under constant potential conditions. Ionic materials included Nafion and films based on tetrabutylammonium toluene-4-sulphonate (TBATS). The quasi-reversible electrode reaction of potassium hexacyanoferrate (II) within TBATS was investigated as a function of drying time. E°, and k° were determined at a TBATS modified microdisc electrode under steady-state conditions. Drying time (water loss) from the TBATS film had the effect of increasing the film ionic strength. It was shown that as the film ionic strength increased, E°, for potassium hexacyanoferrate (II) shifts towards positive potentials (becuase of ion pairing) and there was a corresponding increase in the heterogenous rate constant k°. The latter effect was attributed to increasing ion-ion (cation-ferrocyanide) interactions as the film dried and the enhancing effect this had on the prevention of surface poisoning reactions at the electrode. This study demonstrated a plausible basis for the construction of a bioelectrochemical sensor that can operate directly in gases, but the practical lifetime of the device was short, with the operational life of many sensors not exceeding 35 minutes. This was

most likely due to enzyme dehydration and/or gel rigidification. A similar problem had been encountered by Tierney and Kim (1993), who used Nafion as an immobilisation media for carbonic anhydrase for gas phase detection of CO2. They were only able to achieve stable responses using artificially humidified air of between 70 %–80 % RH. Tierney and Kim overcame this problem by incorporating a water reservoir which continually kept the Nafion hydrated. They also incorporated a commercially available hydrogel, “medtronic” into a CO2 sensor. This sensor also had a short lifetime due to water loss. A more viable approach for industrial application was reported by Dennison et al. (1995) who described a microbiosensor capable of measuring very low levels of phenol vapour directly in the gas phase. Polyphenol oxidase was immobilised in a glycerol-based gel which did not dehydrate significantly over time. An interdigitated microelectrode array was used as transducer. Phenol vapour partitioned into the glycerol gel, where it was enzymatically oxidised to quinone. Signal amplification was achieved by redox recycling of the quinone/catechol couple. This redox recycling produced a biosensor capable of measuring phenol vapour concentrations of 30ppb. The biosensor produced a constant signal after 5 days of continuous use at room temperature and has potential application in the field of health and safety monitoring, where its ease of use, selectivity, and real-time monitoring would provide personnel with accurate data. 6.4. FORMALDEHYDE

Formaldehyde is a ubiquitous airborne pollutant and exists as a dilute vapour at room temperature. It is colourless with a pungent odour, the odour threshold for humans being 0.5ppm (Committee on Toxicology, 1980). It is only stable over the temperature range 80°C–100°C, at temperatures below this it spontaneously polymerises (Bardana and Montanaro, 1991). It is also very unstable in water, commercial solutions of formaldehyde needing approximately 14 % methanol to prevent polymerisation. Formaldehyde is an important industrial chemical, being extensively used in the manufacture of resins which are in turn widely used in the manufacture of building materials such as floor coverings and plywood. Formaldehyde is also a strong disinfectant and is used as a bactericide and a preservative in goods as diverse as toothpaste, washing-up liquid and air fresheners (Bardana and Montanaro, 1991). Formaldehyde was ranked tenth in United States production of organic chemicals in 1990 (Noble et al., 1993), and its widespread use in industry means that a large proportion of workers will come into contact with it during their lifetime. Major formaldehyde contamination results from the incomplete combustion of fuels such as wood, alcohol, gasoline and refuse (Stupfel, 1976), while the widespread use of formaldehyde in building materials has given rise to reported indoor formaldehyde concentrations of up to 0.37 ppm–0.55 ppm in new homes (Environmental Protection Agency, 1984). Higher formaldehyde concentrations of between 0.12 ppm–1.6 ppm have been reported in mobile homes (Main and Hogan, 1983), while the highest concentrations have been measured in cigarette smoke with concentrations of 30 ppm–40 ppm (Higgenbottam et al., 1980). The American Conference of Governmental Industrial Hygienist’s (ACGIH) threshold limit value (TLV) has been lowered from a 1 ppm 8 hr TWA and a 2 ppm 15min short term exposure

limit to a 0.3 ppm ceiling (Noble et al., 1993). Most countries now have guidelines recommending indoor formaldehyde concentrations of not higher than 0.1 ppm–0.2 ppm (Larsen et al., 1992). 6.4.1. HEALTH EFFECTS OF FORMALDEHYDE

Formaldehyde is a highly reactive chemical and rarely penetrates further than the lower oesophagus, interacting with the mucous membrane coating the oesophagus. Airway irritation of the nose and throat has been reported at concentrations as low as 0.1 ppm (National Research Council, 1981). Several reports have linked inflammatory bronchitis and pneumonia to excessive levels of formaldehyde (Bardana and Montanaro, 1991). Formaldehyde is also widely known for causing dermatitis, with a 1 % formalin solution in water producing dermatitis in 5 % of the population (Maibach, 1983). Formaldehyde can also combine with human self-protein to form antigenic conjugates which induce hypersensitivity reactions (Bardana and Montanaro, 1991). Formaldehyde is also a suspected carcinogen (Fan and Dasgupta, 1994). 6.4.2. FORMALDEHYDE DEHYDROGENASE

Formaldehyde dehydrogenase (EC 1.2.1.46) from Pseudomonas putida catalyses the oxidation of formaldehyde in the presence of its cofactor NAD+:

Formaldehyde dehydrogenase (FDH) will catalyse the dehydrogenation of formaldehyde and acetaldehyde, but it is inactive towards longer chain aldehydes. The enzyme will also act on nbutanol, n-pentanol and n-hexanol, but is completely inert towards methanol and ethanol (Ogushi et al., 1986). The enzyme is composed of two subunits, each of which has 2 Zn++ atoms. FDH only catalyses the forward reaction unlike alcohol dehydrogenases, and fails to catalyse the reverse reaction (Ogushi et al., 1984). The enzyme has a pH optima of 8.5, a Km of 0.5 mM for NAD+ and a Km of 0.2mM for formaldehyde (Hohnloser et al., 1980). The exact mechanism of formaldehyde dehydrogenation by FDH has not yet been elucidated. 6.4.3. ENZYMATIC ASSAYS FOR FORMALDEHYDE

Ho and Samanifar (1988) reported on a spectrophotometric method for the determination of aqueous formaldehyde. Formaldehyde was collected by passing formaldehyde vapour through distilled water in an impinger. FDH, NAD+ and collected formaldehyde were mixed in a cuvette and the formation of NADH was monitored spectrophotometrically at 340 nm. The range of determination for aqueous formaldehyde was 1 mM–27 mM (300 ppb/w–800 ppm/w). Weng and Ho (1990) described a fluorometric method for the determination of formaldehyde. The procedure was similar to that outlined above, but NADH was monitored fluorometrically

with an excitation wavelength of 348 nm and an emission wavelength of 467 nm. The limit of determination was 0.09 mM aqueous formaldehyde (27 ppb/w). Weng et al. (1990a) also reported an amperometric system for determination of aqueous formaldehyde. NADH produced during the FDH catalysed dehydrogenation of formaldehyde was monitored amperometrically at 400 mV vs Ag/AgCl using a hexacyanoferrate mediated system. The use of a mediated system for the determination of NADH avoided the problem of fouling associated with the high potential needed for NADH oxidation. The limit of determination was 0.01 mg/ml (3 mM or 0.9 ppm/w) aqueous formaldehyde. Lazrus et al. (1988) reported on a system for the automated fluorometric determination of formaldehyde vapour. Formaldehyde was stripped from air into water by means of a glass coil through which the sample air was passed. The formaldehyde solution was then mixed with NAD+ and FDH. The concentration of NADH was determined fluorometrically at excitation and emission wavelengths of 340 nm and 460 nm respectively. The detection limit was 120 ppt (0.l47 mg/M3) formaldehyde vapour. 6.4.4. BIOSENSORS FOR FORMALDEHYDE VAPOUR

Guilbault (1983) described an enzyme-coated piezoelectric crystal detector for the determination of formaldehyde. FDH (EC 1.2.1.1), which uses glutathione as well as NAD+ as a cofactor, was dissolved in distilled water along with its two cofactors. This solution was then dropped on to the piezoelectric crystal and allowed to dry. On exposure to formaldehyde vapour, FDH bound formaldehyde causing a change in frequency at which the piezoelectric crystal oscillated, a 100 Hz change in frequency corresponding to a 1 mg change in weight. This biosensor gave a linear response over the range 10 ppb to 10 ppm formaldehyde at 50 % RH and the lifetime was 3 days or 100 analyses. Little or no response was observed when the biosensor was exposed to alcohols and longer chain aldehydes. The effect of relative humidity on the biosensor response was not reported in this publication, but a later paper (Luong and Guilbault, 1991) reported that the humidity of the test gas was extremely important. A high humidity caused condensation on the crystal, while the biological component would not function at lower humidities. Biosensors capable of directly detecting low levels of formaldehyde were reported by Dennison et al. (1996). The biosensors were based on formaldehyde dehydrogenase which produces reduced nicotinamide adenine dinucleotide as part of the oxidation of formaldehyde. The enzyme was immobilised in a reverse micelle medium which did not dehydrate significantly over time, and allowed direct gas-phase monitoring. A screen-printed electrode was used as transducer. Formaldehyde vapour partitioned into the reverse micelle media, where it was acted upon by the relevant enzyme. Reduced nicotinamide adenine dinucleotide was oxidised at the working elecrode at a potential of 800 mV versus an Ag/AgCl reference electrode. Formaldehyde could be measured over the concentration range 1 ppb–1.3 ppm. 6.5. ETHANOL-VAPOUR SENSING

The fact that ethanol is involved in many manufacturing systems, especially in the food and drink industries, necessitates the determination of ethanol concentrations in liquid and gas

phases. Legal stipulations require the accurate measurement of ethanol vapour. These applications have given the commercial impetus to the development of ethanol vapour sensors, and these areas of application are reviewed briefly below: Monitoring of ethanol vapour is important for two legal reasons: • The legal limit (8 hour TWA) for exposure of workers to ethanol vapour is 1,000ppm (Mitsubayashi et al., 1994). • The permissible legal limit of blood ethanol is 800mg/L for driving in the European Union (Royal Automobile Club, 1993). Blood ethanol concentration can be determined with blood or urine samples, but non-invasive techniques are much more popular for initial testing. Saliva is particularly unsuitable for taking samples, due to contamination by orally ingested ethanol (whether from alcoholic drinks or medicines) (Ruz et al., 1986). A more attractive method of assessing blood ethanol concentration is the measurement of ethanol in a person’s breath. Ethanol in the blood will partition into the breath in the lungs, which have a large surface area. The amount of ethanol in the breath will depend on the concentration of ethanol in the blood, according to Henry’s law. A blood/breath ethanol partition ratio of 2,000 is widely accepted (Mitsubayashi et al., 1994), which gives a legal limit for breath ethanol concentration of approximately 209 ppm. Ethanol is an important product of the food and drinks industry, leading to a need for sensing of ethanol vapour. In the UK brewing industry, ethanol concentration determination is important for the calculation of excise duty. Beers with an original gravity over 1030°, pay excise duty for each extra degree of ethanol (Griddle et al., 1984a). Assessing the strength of the beer is also an important part of quality control. Calculation of aqueous ethanol concentration by determination of headspace ethanol vapour concentration is particularly attractive due to the fact that there is no contact with the sample, so there is no contamination or cleaning of the probe between samples. Ethanol vapour determination is also extremely important in the controlled atmospheric storage of fruit, especially apples. Production of ethanol vapour is indicative of fruit going off (Griddle et al., 1984b) and the probable loss of the batch unless action is taken. Non-invasive techniques to determine ethanol vapour concentration, enable rapid assessment of fruit quality and are particularly attractive to the industry. Hence for practical applications, an enzyme electrode would need to be able to measure ethanol vapour over the concentration range 100 ppm–1100 ppm. 6.5.1. BIOLOGICAL ELEMENTS FOR SENSING ETHANOL

The choice of the biological sensing element for a biosensor for ethanol vapour is limited to two enzymes. Although bacteria such as Acetobacter xylinum or Trichosporon brassicae which metabolise ethanol are available, the low selectivity and long response times (Riedel, 1991; Gaisford et al., 1991; Rawson et al., 1987) associated with biosensors based on these bacteria makes them unattractive for practically orientated applications. Antibodies are expensive and not particularly suitable for small molecules such as ethanol. Quinoprotein alcohol dehydrogenases

are available, but the need for ammonium ions, stability problems (Loughran et al., 1996) and high cost, suggest that other alcohol metabolising enzymes might be more suitable. Alcohol oxidase (AOX) and alcohol dehydrogenase (ADH) are enzymes which catalyse the oxidation of ethanol. They are commercially available and are relatively well characterised enzymes. Each one is discussed below: 6.5.1.1. Alcohol oxidase

AOX (EC 1.1.3.13) catalyses the oxidation of ethanol to acetaldehyde, with the production of hydrogen peroxide:

AOX can be purified from a number of different yeasts and all AOX enzymes characterised to date contain a flavin adenine dinuceleotide prosthetic group. The enzyme consists of eight subunits (Woodward, 1990) although the exact structure of the enzyme and mechanism of alcohol oxidation has not yet been elucidated. AOX oxidises short chain linear alcohols, up to six carbons long, but it displays poor activity towards secondary or tertiary alcohols (Woodward, 1990) and displays no activity towards glycerol (Barman, 1974). For example, AOX from the yeast Pichia pastoris displays 100% relative activity towards methanol, 82% relative activity towards ethanol and 43 % relative activity towards isopropanol (Coderc and Baratti, 1980), although different authors have claimed somewhat different activities. AOX also catalyses the oxidation of formaldehyde, although not as efficiently as alcohols (Mitsubayashi et al., 1994). Commercially, AOX is usually supplied from either P. pastoris or C. boidinii. AOX from P. pastoris seems to be more stable (Kunnecke and Schmid, 1990) and displays more activity towards ethanol (Varadi and Adanyi, 1994) and was hence chosen for this study. AOX from P. pastoris has been reported to have a Km of 3.68mM ethanol (Woodward, 1990). 6.5.1.2. Alcohol Dehydrogenase

ADH (EC 1.1.1.1.) catalyses the oxidation of alcohols to aldehydes without the requirement for molecular oxygen:

The reaction occurs by an ordered bisubstrate mechanism—the coenzyme first binds to the apoenzyme (to give a complex referred to as the haloenzyme). The substrate then binds to the haloenzyme and the reaction occurs between the bound coenzyme and the bound substrate. This is followed by dissociation of the product and then dissociation of the reduced coenzyme to

complete the catalytic cycle (Bartlett, 1990). The enzyme only functions in the presence of NAD+/NADH. A different ADH (E.C. 1.1.99) which catalyses the oxidation of alcohols uses NADP+ as cofactor:

This ADH (E.C. 1.1.99) will also use 2,6-dichlorophenolindophenol, phenazine methosulphate or potassium hexacyanoferrate as the electron acceptor (Gotoh and Karube, 1994). ADH is commercially available from two sources: horse liver and yeast. Yeast ADH (E.C. 1.1.1.1) is preferred to horse liver ADH because of its higher selectivity and activity (Dickinson and Monger, 1973). Yeast ADH (E.C. 1.1.1.1) (YADH) has a molecular weight of approximately 150,000 and contains 4–5 tightly bound zinc atoms. It oxidises all primary straight chain alcohols, but displays poor activity towards secondary and branched chain alcohols (Sund and Theorell, 1963). YADH has also been reported to catalyse the oxidation of formaldehyde (Kuwabata et al., 1994). YADH has a Km of 21 mM for ethanol (Green et al., 1993). The stability of YADH is reported to be poor (Pal et al., 1994). 6.5.2. BIOSENSORS FOR MONITORING LIQUID-PHASE ETHANOL

The vast majority of publications concerning biosensors for monitoring ethanol use either AOX or ADH as the biological component, with either amperometry or spectrophotometry used as the transduction mechanism. The consumption of molecular oxygen or production of hydrogen peroxide due to the AOX catalysed oxidation of alcohols can be monitored electrochemically, while the production of NADH due to the ADH catalysed oxidation of alcohols can be monitored electrochemically or spectrophotmetrically. There have been many publications of AOX and ADH based enzyme biosensors for monitoring ethanol in the literature over the last few years (approximately 20, between 1990–1995). Most reports concern the monitoring of aqueous ethanol, with a few reports of organic-phase sensing and gas-phase sensing. This short review is intended to present an outline of the status of AOX and ADH based biosensors at present: 6.5.2.1. Enzyme biosensors based on alcohol oxidase

AOX produces hydrogen peroxide during the oxidation of ethanol and the concentration of hydrogen peroxide is directly proportional to the concentration of ethanol provided that oxygen is present in excess. This hydrogen peroxide can be detected amperometrically, either directly or indirectly via a mediated system. Hydrogen peroxide can also be made to react with an indicator which changes colour on oxidation. This colour change can then be assessed by eye or spectrophotometrically.

Kunnecke and Schmid (1990) described a FIA system for on line monitoring using glutaraldehyde immobilised AOX, which could detect ethanol over the range 0.0006 %–60 %(v/v) (0.1 mM–10 M). Hydrogen peroxide produced during the oxidation of ethanol, further oxidised a mediator (2,2′-azino-di-(3-ethylbenzthiazoline-6-sulphonic acid)) which was then detected amperometrically at 700 mV vs Ag/AgCl. Under continual operation the half life of the enzyme electrode was 44 hours, or 8,000 injections. Varadi and Adanyi (1994) reported a FIA system using AOX, which directly monitored the production of hydrogen peroxide electrochemically at 600 mV vs Ag/AgCl. AOX (2.5units/biosensor) was immobilised on pig intestine and could monitor ethanol over the range 1 %–8 %(v/v) (170mM–1.4M). The life time of the enzyme electrode was 250 samples or 3 weeks. The Yellow Springs instrument (The Yellow Springs Instrument Company Inc., Ohio, USA) which uses AOX immobilised in a cellulose acetate membrane in conjunction with a platinum electrode to detect hydrogen peroxide can measure ethanol concentrations up to 5 g/L (64 mM). 6.5.2.2. Enzyme biosensors using alcohol dehydrogenase

NADH produced during the oxidation of alcohols by ADH can be monitored amperometrically directly at approximately 700 mV vs Ag/AgCl (Malinauskys and Kulys, 1978). The concentration of NADH produced is directly proportional to the ethanol concentration, provided that it is the ethanol concentration which is rate limiting and NAD+ is present in excess, to maintain a pseudo-first-order reaction. The requirement for a high potential can invite interference from other species, such as ascorbate or urea, and can lead to electrode passivation. This problem can be overcome by reducing the operating potential. This has been accomplished using a variety of methods to chemically modify the enzyme electrode: using conducting organic salt films, such as NMP.TCNQ (N-methyl phenazinium tetracyanoquinodimethane) (Albery and Bartlett, 1984), meldola blue (7Dimethylamino-1,2, benzo phenoxazinium) films (Gorton et al., 1984), 4(2-(Naphthyl) vinyl) catechol films (Jaegfeldt et al., 1981) or by using metallised-graphite electrodes (Wang et al., 1993). Mediation via ruthenium red has also been reported to lower the oxidation potential (Somasundrum et al., 1994). Another problem associated with ADH enzyme electrodes is the vast disparity in size between the enzyme and the cofactor-YADH has a molecular weight of approximately 150,000, while NAD+ has a molecular weight of 663- NAD+ will leach out from an immobilisation matrix more readily than the enzyme. This fact has necessitated either the need for diffusion membranes which prevent/delay the loss of NAD+ from the matrix, or the direct addition of NAD+ to the sample. Gotoh and Karube (1994) immobilised ADH/NAD+ in a PVC matrix with a cellulose triacetate diffusion membrane. NADH was monitored directly at 600 mV vs Ag/AgCL. A linear response was obtained over the range 0.05 %-10 %(v/v) (8.5 mM-1.7M) ethanol. The response time was fast with steady state kinetics appearing within 1 minute. Stability was good with only a 5 % decrease in sensitivity after 4 weeks storage at 4°C. Miyamoto et al. (1991) immobilised separate layers of NAD+ and ADH onto a gold electrode with glutaraldehyde. The lower layer consisted of immobilised ADH (10 units) and the top layer contained NAD+. A BSA/glutaraldehyde membrane was used to cover the enzyme electrode. This membrane

prevented substrate saturation and also prevented leaching out of the cofactor. NADH was monitored at 750mV vs Ag/AgCl. A linear response was obtained over the concentration range 10mM–50mM ethanol (0.05 %–0.3 % v/v). The enzyme electrode was stable for up to 10 assays. When stored at −20°C, activity declined by 40% over 10 days. Mizutani et al. (1993) described an enzyme electrode based on ADH and NAD(P)H oxidase. Oxidation of ethanol catalysed by ADH produced NAD(P)H. NAD(P)H was then oxidised by molecular oxygen, the reaction being catalysed by NAD(P)H oxidase. Oxygen consumption during the reaction was monitored with a Clark electrode. Ethanol in the concentration range 5 mM to 1.5 mM (0.00003 %–0.009 % v/v) could be measured, the limit of detection being 50 nM (S:N ratio of 5). The stability of the enzyme electrode was not reported. Ruthenium-dispersed graphite electrodes were used by Wang et al. (1993) to lower the potential of NADH oxidation to 600 mV vs Ag/AgCl in a flow injection analysis (FIA) system. This lowering of potential reduced interferences and electrode surface passivation due to accumulation of reaction products. The enzyme electrode responded to ethanol concentrations up to 50mM (0.3 % v/v) and had an LOD of 0.12 mM (0.0007 %) ethanol. The enzyme electrode showed stable responses for over 60 repetitive injections, indicating that the electrode surface was not passivated during prolonged periods of NADH oxidation. The paste used to construct the enzyme electrode was stable for 2 weeks at 4°C. Langmuir-Blodgett films of stearic acid were used to immobilise ADH and NAD+ on the surface of a polypyrrole film modified electrode (Pal et al., 1994). The oxidation potential of NADH was reduced to 240 mV vs a saturated calomel electrode (SCE) by means of the polypyrrole film. The response of the enzyme electrode was linear over the range 1 mM to 40 mM (0.000006 %– 0.00024% v/v) ethanol. Stability was good, being attributed to the stabilising effect of the Langmuir-Blodgett film, with only a small decrease in activity over 10 days when stored at 0°C. Zhao and Buck (1991) described an all solid state amperometric ethanol enzyme electrode based on ADH and NAD+ immobilised in polyvinyl chloride. NADH was monitored amperometrically via a NMP.TCNQ modified electrode at 0 mV vs Ag/ AgCl. This enzyme electrode could measure ethanol concentrations from 0.1 mM to 10 mM (0.0059 %–.059%) with a 5 minute response time. Stability was poor with losses of 10% per hour during continuous operation. Bartlett (1990) described an enzyme electrode for ethanol which used a NMP.TCNQ modified electrode to lower the oxidation potential of NADH to 0 mV vs Ag/AgCl. ADH/NADH was retained at the electrode surface with a dialysis membrane. Lysine was incorporated to remove the acetaldehyde and shift the equilibrium of the reaction towards the products. The electrode response was linear from 20 mM to 160 mM (0.00012 %–0.00096 %) ethanol. Stability was very poor, 5 hours being the average lifetime for the enzyme electrode. Organic-phase sensing of alcohols with an enzyme electrode has been reported by Wang et al. (1994). ADH from the thermophillic bacteria Ta. brockii, which has high thermal stability, was immobilised with NAD+ on a glassy carbon electrode with Eastman-AQ-55Q polymer film. The working electrode was poised at 900 mV vs Ag/ AgCl to detect NADH. The enzyme electrode

response was strongly affected by the water content and electrolyte concentration, with a 15 % (v/v) increase in water content increasing the response 1000 fold. This particular ADH only responded to secondary alcohols, giving a linear response over the range 2 mM–11.5 mM, with no response being obtained from ethanol. The electrode was stable for up to 3 days when stored at 4°C. In reviewing biosensors for ethanol sensing it is often difficult to make direct comparisons. In many cases the quantity or activity of enzyme immobilised is unknown. This makes it difficult to assess performance or stability, as enzyme loading will significantly improve stability. Loss of stability could be due to enzyme denaturation or mediator leach-out. Besides, some of the above publications failed to measure or mention stability, one of the most important factors, if not the Achille’s heel of biosensing. 6.5.3. BIOSENSORS FOR MONITORING ETHANOL VAPOUR

The importance of measuring ethanol vapour for assessing the suspected intoxication of motor vehicle drivers, has given impetus to the development of ethanol vapour biosensors, with most publications stressing their ability to measure ethanol vapour in the relevant range. Barzana et al. (1989) reported the use of AOX for direct determination of ethanol vapour. AOX, peroxidase and a coloured indicator (dichloroindophenol) were packed into a column. When ethanol vapour was forced through the column, NADH was produced. NADH was then oxidised by the dye which produced a colour change, this last step being catalysed by peroxidase. The colour change was assessed either visually or with a transmittance densitometer. The device functioned well at the legal limit of ethanol breath concentration. Water content was found to have a substantial effect on activity, an increase in water content from 20 % to 30 % increased the response 1000 fold. The stability of the assay was not reported. A biosensor which could monitor ethanol vapour at the ppb range, has been reported by Matuszewski and Meyerhoff (1991). This system trapped ethanol vapour by passing ethanol vapour over a celgard gas permeable tubing containing buffer. Ethanol partitioned into the buffer through the gas permeable tubing. The ethanol/ buffer was then passed through a column of glass beads onto which was immobilised AOX. Hydrogen peroxide produced from the oxidation of ethanol was detected at 400 mV vs SCE. The limit of detection (LOD) was 0.5 ppb ethanol vapour. The biosensor was active for at least one month when stored at 4°C. The authors reported that the relative humidity of the ethanol vapour affected the magnitude of the response. Mitsubayashi et al. (1994) described an enzyme electrode using AOX for the determination of ethanol vapour. AOX was immobilised in an acrylamide membrane and retained at the surface of a Clark oxygen electrode with a polycarbonate membrane. Consumption of molecular oxygen during the oxidation of alcohols was measured with the oxygen electrode. The enzyme electrode was kept hydrated by means of a circulating buffer system connected to a reservoir. The LOD was 0.36ppm ethanol vapour and the maximum ethanol concentration measurable was 1000 ppm. The stability, however, was poor, with activity losses of 50% after 2 days.

Recently, Park et al. (1995) described an enzyme electrode using ADH/NAD+ immobilised in hydroxyethyl cellulose for monitoring ethanol vapour. NADH produced from the oxidation of ethanol was monitored amperometrically at 650mV vs Ag/AgCl. Before use the enzyme electrode was activated by dipping in buffer and was then exposing to ethanol vapour. The response was linear over the range 50ppm– 800 ppm ethanol vapour, once readings were taken quickly (i.e. tens of seconds). The sensor was designed to be disposable and hence, wet stability was not an issue. The biosensor was basically the same as many aqueous-phase biosensors, such as the glucose biosensor with glucose oxidase immobilised in hydroxyethyl cellulose, described by Marcinkeviciene and Kulys (1993). No provisions were taken to extend the lifetime of the biosensor in the gas phase. The main problem with using enzyme electrodes for monitoring alcohol vapour is water loss, which seriously affects enzyme performance. One other related problem is the stability of the enzymes. ADH and AOX are both reported as having poor stability, water having a significant positive effect on the initial enzyme activity, but having a significant detrimental effect on long term enzyme stability (Pavaresh et al., 1992). These problems were tackled by Dennison et al. (1996) using a reverse micelle medium which was resistant to dehydration. The steady-state amperometric response of an ADH biosensor produced a linear response up to approximately 250 ppm ethanol vapour. The apparent ability of the reverse micelles to concentrate the vapour was ideal for sensing low levels of ethanol, but was not suitable for sensing the high levels of ethanol vapour routinely encountered in everyday applications (100–1000 ppm). Alternatively, the ADH biosensor could be used for measuring ethanol vapour, if the exposure times were short, ie. the concentration of ethanol partitioned in the gel phase was very low and ADH was not substrate saturated. Enzyme stability remains a major problem owing to the poor stability of ADH. Improvements in enzyme purification and stabilisation would greatly enhance further development of practical ethanol vapour biosensors. 6.6. CONCLUSIONS

Gas-phase biosensing offers both opportunities and new challenges. The requirement for the analyte to be present or pass through the gas or vapour phase eliminates many potential interferences. Indeed, the introduction of an air gap in electrochemical sensors is one strategy to overcome interference by non-volatile electrochemically active species in solution. The relatively clean nature of air also reduces many fouling problems associated with solutions such as the adsorption of proteins. Practical opportunities for gas-phase biosensors have been neglected by most commentators who regard this application is unsuitable for biological systems. The advantages of selectivity and specificity combined with inexpensive instrumentation, however, clearly warrant more effort in overcoming the remaining hurdles. Stability of both the biological component and the supporting matrix under dry conditions needs further attention. A compromise approach might be to exploit biomimetic catalysts which capitalise on the selective design of biological molecules while avoiding the instability of protein structures. Absolute selectivity might not be essential since biosensors could be combined with chemical sensors in arrays to produce extended capability in electronic nose configurations. There is also considerable scope, however, for improving the stability of natural enzymes for incorporation in inexpensive, portable devices capable of use by untrained personnel in a variety of commercial, domestic and defence applications.

ACKNOWLEDGEMENT

The authors are grateful to Mrs E.Sarney for her help in compiling this text. REFERENCES

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7. CHEMICAL ANALYSIS Though the book is devoted to biosensor system applied to environmental analysis this chapter dealing with chemical methods is included. It is aimed at a description of the state of the art in these more established methods to allow a judgement of required instruments and efforts but also of possibilities and limitations. As different methods are used for the determination of organic and inorganic compounds, these are treated separately (Chapts. 7.1 and 7.2., respectively). 7.1. SAMPLE HANDLING AND ANALYSIS OF ORGANIC POLLUTANTS IN WATER MATRICES

SÍLVIA LACORTE, DAVID PUIG and DAMIÀ BARCELÓ 7.1.1. INTRODUCTION

Pesticides and phenolic compounds account for 43 % of the total amount of organic chemicals used in Europe. These compounds are constantly introduced in the environment mainly as a consequence of agricultural and industrial activities and can produce toxic effects towards non target organisms and flora. Moreover, once they have reached the earth surface, they can suffer biotic and abiotic degradation (Pritchard et al., 1987), with the subsequent formation of transformation products (TPs), such are the oxo derivatives and sulfoxides, which are more toxic than their parent compounds (Miyamoto et al., 1978). Besides, chloro and nitrophenols are the main degradation products of many chlorinated phenoxyacid herbicides and organophosphorus pesticides, respectively (Marcheterre et al., 1988; Lacorte et al., 1994). Due to the toxicity and persistence of some of these compounds, the National Pesticide Survey of the United States (NPS-US) and the the EEC Directive on the Quality of Water Intended for Human Consumption (CEC 76/464/EEC) has included different pesticides and phenolic compounds in their environmental monitoring programs and have elucidated the need of analyzing these organic micropollutants and TPs under levels of 0.1 µg/l in drinking water (Fielding et al., 1990) and between 1 to 10 µg/l in surface water. Moreover, the NPS has published a list which included all pesticides and their TPs which were detected in ground water (Munch et al., 1990; Munch et al., 1992). As a consequence, the achievement of analytical methods which permit the unequivocal identification and confirmation of pesticides along with their TPs in the environment in a quick and reliable way are emerging. In general terms, pesticide and phenolic compound determination include four main steps: (i) sampling, (ii) extraction of the analytes from the water sample, (iii) concentration of the analytes and (iv) detection. The sampling step has to be performed in an efficient way which maximizes recovery and avoids sample contamination. Barceló et al. (1997) have recently reviewed different sampling strategies. For the isolation of pesticides, many different procedures have been described. Dichloromethane liquid-liquid extraction (LLE) methods have been reported in the literature covering several groups of pesticides and being also recommended by the US EPA through their NPS (EPA Method 553; Barceló, 1993). As an alternative to LLE, liquid solid extraction (LSE) procedures, also known as solid phase extraction (SPE), are being implemented in the last few years, and can

be performed both off-line and on-line. LSE methods can be easily converted into fully automated on-line systems coupled to LC or GC. Such systems, also referred to as precolumn technology, show additional advantages such as lower detection limits (analysis of eluate instead of an aliquot) and that sample manipulation is minimized, which is translated to no evaporation losses, no contamination, no need to concentrate the sample, easy automation and use of small amounts of toxic solvents. The great availability of sorbents and configurations permit to efficiently trap compounds of diverse polarities with the percolation of only 50 to 100ml of water. Recently, besides the well known C18 and polymeric nature sorbents, immunoaffinity precolumns have appeared as an alternative to selectively preconcentrate the analytes of interest. The antibodies are immobilized in a silica based stationary phase which is used as packing material for either precolumns or cartridges. Prominent results have been reported (Pichon et al., 1995) since limits of detection (LOD) are lowered due to the efficiency of the preconcentration step and the elimination of matrix interferences. As regards to the analysis of pesticides of different families and phenolic compounds, the traditional detection technique has been gas chromatography (GC) using a selective detector such as the nitrogen-phosphorus (NPD) or the electron capture (ECD). Classically, identification of the analytes was done through retention time comparison with a standard solution. Errors and lack of reproducibility often appeared due to variations in the response of the detector which lead to retention time shifts. This is specially relevant when GC-NPD or GC-ECD are used, and therefore, duplicate analysis using two columns of different polarity or otherwise the addition of internal standards or surrogates is needed in order to meet quality control requirements (Barceló, 1993). The use of GC with mass spectrometric (MS) detection is a valid alternative to confirm the results obtained by other techniques. However, GC based techniques are not suitable for the analysis of polar, non-volatile and thermolabile compounds, since for these compounds, a derivatization step prior to GC analysis is compulsory. The use of two different techniques and the difficulty to analyze both the degradation products along with the parental pesticides limit the applicability of GC based techniques for environmental analysis. Liquid-chromatographic techniques are preferred for the analysis of organic pollutants since they cover a wide range of polarities and permit the identification of pesticides and phenolic compounds along with their transformation products. LC with diode array detection (LC-DAD) or fluorescence has successfully been used to monitor pesticides of various natures, such as organophosphorus (Lacorte et al., 1994), carbamates (Chiron et al., 1994), phenoxyacids (de Kok et al., 1992), and phenolic compounds (Nielen et al., 1985). The main advantage of LCDAD is related to its easy use and to the fact that it renders some absorbance spectra that can be used to identify parent organic compounds through spectral comparison. However, limitations arise for compounds exhibiting poor chromophore and to the impossibility to identify unknowns in real water samples. Other problems that arise from the use of this technique for environmental water analysis are related to coelution of two or more compounds, and the presence of interferences, mainly due to humic and fulvic material. These problems are solved when using LC with mass-spectrometric detection (LC-MS) which is a more selective detector, and they can be used both for qualitative and quantitative analysis. Coupling LC to MS has been achieved through many interfaces, being thermospray interface (TSP) (Barceló, 1988; Barceló et al, 1991; Volmer et al, 1994), which produces scarce fragmentation and particle beam (PB) (Voyksner et al., 1990) which gave high detection limits and poor reproducibility of the results, the most used

ones up to now. The advent of atmospheric pressure (API) liquid chromatography-mass spectrometry interfaces has overcome the disadvantages of GC-MS and other LC-MS interfacing devices such as thermospray (TSP), because they can provide structural information similar to chemical ionization and very good sensitivity. All electrospray (ESP), ionspray (ISP) and atmospheric pressure chemical ionization (APCI) have up to day been extensively used and their applicability for pesticide monitoring has been demonstrated (Crescenzi et al., 1995; Chiron et al., 1995; Molina et al., 1994; Lacorte et al., 1996). These two techniques permit the achievement of limits of detection (LOD) of few ng/l, and the linear response range over two orders of magnitude. This chapter will describe the different techniques used for the extraction of pesticides and phenolic compounds, showing the advantages and disadvantages of each, and discussing the parameters which influence the extraction step. On a second instance, an overview of the most common detection techniques used is given. This will permit to evaluate which is the preferred technique according to the nature of the different pollutants, and in which cases it can be used and the information that one will gather. In this section, emphasis will be given to immunodetection techniques, an approach that has been recently arisen due to its selectivity and sensitivity. The final section will consist in a review of the different validation steps that have been performed to evaluate each chromatographic technique. This is specially relevant since all techniques have to be validated for qualitative parameters before they can be applied to determine organic pollutants from environmental water samples. Finally, a comparison of chromatographic and biological detection methods will be made. These techniques are emerging as low-cost, quick and easy to use, and it has been demonstrated that they give comparable results to conventional chromatographic techniques. 7.1.2. STRATEGIES FOR SAMPLE HANDLING

Organic micropollutants are found in the environment at very low concentrations and it becomes necessary to perform a preconcentration step prior to the chromatographic analysis. Briefly, sample pretreatment involves the extraction of organic pollutants from the water matrix with an adequate solvent. Traditionally this was carried out by LLE but nowadays there is a general trend to change to LSE procedures. Both approaches will be discussed below. 7.1.2.1. Extraction of pesticides and phenols from water samples

There are several methods for extracting pesticides and phenolic compounds from water samples. LLE is still the sample preparation technique preferred by the Page 312 Table 7.1. Average percent recovery (av) and coefficient of variation (CV) of pesticides in river water using C18 Empore extraction disks and dichlormenthane LLE. Pesticide

Empore disks av

CV

LLE av

CV

Aldicarb

83

7

62

10

Aldicarb sulfoxide

35

21

18

24

Aldicarb sulfone

30

20

36

18

Aldrin

51

10

n.d.

n.d.

100

5

99

4

Bentazone

72

6

81

7

Carbaryl

87

8

109

2

Carbofuran

74

7

90

4

Chlorpyrifos

94

4

86

3

Cyanazine

84

7

92

14

Deethylatrazine

76

13

90

9

Fenamiphos

95

5

87

9

Fenamiphos sulfoxide

97

11

98

10

100

5

97

6

3-ketocarbofuran phenol

60

19

89

6

Linuron

96

6

94

5

Propanil

95

7

94

3

Simazine

80

10

97

8

Tetrachlorvinfos

96

6

92

4

Atrazine

Fenamiphos sulfone

environmental analyst because of its extensive implementation in official methods. Most of the current US EPA methodologies for the analysis of priority pollutants in water samples involve sample acidification to pH 2 and extraction with various solvents such as dichloromethane, butyl acetate (Afgan et al., 1993) or hexane (Abrahamsson et al., 1983). On the other hand a different approach using ion pair has been described by adjusting the pH to a basic value and additioning tetrabutyl ammonia (Kwakman et al., 1991). Table 7.1 shows the average percent recovery values obtained at spiking levels of 1–5 µg/l into 11 of river water using LLE according to the National Pesticide Survey (NPS) Method 4 described by Chiron et al. (1993). For a complete extraction of the more acidic pesticides, sulphuric acid at pH 2 and 50 ml of dichlormethane were added to the water sample, which was shaken and extracted. Recoveries of most of the compounds were within the NPS US-EPA range, who accept recoveries between 70 and 130% for samples spiked at µg/l level. However, LLE approach have some drawbacks such as it requires large amounts of generally toxic and inflammable organic solvents, emulsions can be generated and further clean up is often necessary. All these factors lead to losses during the concentration step which results in poor recoveries and bad reproducibility, with risk of sample contamination. Moreover, its automation requires the use of expensive robots. Hence, there is a general trend to change current LLE procedures with LSE protocols. Liquid-solid extraction (LSE) has been successfully applied to extract organic pollutants from environmental matrices. The procedure is based in extracting the pesticides from water and

elution with an organic solvent. LSE methods include extraction using off-line methods with cartridges (Borburgh et al., 1992; Castillo et al., 1997), Empore extraction disks both off-line (Durand et al., 1992) and on-line (Chiron et al., 1993) or using precolumn technology (Brinkman, 1994; Nielen et al., 1988). The principle of LSE is the same for both off- and on-line extraction methods and is shown in Figure 7.1. The method involves a condition step with an organic solvent, percolation of the water sample throught the sorbent, washing the sorbent to remove the more polar matrix interferences and final elution of trapped analytes. With off-line methods, the preconcentration, elution and chromatographic analysis are done in discrete steps. In order to eliminate residual water, such methodologies require complete drying of the sorbent (under vacuum) before proceeding to the elution step. Elution is performed with 10–20ml of solvent, which must be evaporated before getting a final extract of 0.1–1 ml, from which an aliquot is injected into the chromatograph. Table 7.1 reports the recovery values after preconcentrating 11 of river water spiked at 1–5 µg/l onto Empore extraction disks. Values are similar to those obtained with LLE, indicating that the method offers similar recoveries as the NPS-Method, and so it can be recommended for monitoring studies due to its simplicity and easy use. It is worth mentioning that aldrin was not recovered with LLE due to the fact that this compound has a high log Pow value and has a tendency to be adsorbed in the particulate matter. In general, off-line practices are well-accepted due to the large variety of packing materials available in the market, with different sizes and volumes, which allows a great operational flexibility. In the cartridge format, the sorbent (40–150 µm particle size) is usually packed in a Teflon syringe and percolation of water samples must be done manually or with automated devises such as the ASPEC XL from Gilson (France) or the Zymark system (U.S.A), making the technique useful for routine analysis. In the case of Empore disks, the sorbent particles are meshed in Teflon fibrils to form strong sheets or membranes which can be used in standard filtration devices. Since the channeling phenomena does not occur in the disk format, higher sample flow rates can be applied in comparison to cartridges. This induces to a very efficient adsorption as a result of the reduction of the linear velocity of the water of particle size and their high packing density, although their automation is not straightforward. The main advantage of off-line methodologies is that the final extract can be analyzed with various techniques. However, when the technique is not automated, off-line methodologies are tedious and fail with risk of contamination due to intense sample manipulation and losses of the most volatile analytes during the concentration of the extract. Hence, a soft evaporation process is usually recommended and dryness should be avoided to prevent important analyte losses. Most of the problems which appear when using off-line methodologies are solved with the online approach. The set-up is very simple and is illustrated in Figure 7.2. The trace enrichment is performed on a small precolumn which is placed at the loop position of a six port valve. After preconcentration of the water sample, the valve is electrically switched from the preconcentration position to the elute position and the

Figure 7.1. LSE process which includes (1) conditioning of the precolumn, (2) sample loading or preconcentration step, (3) elimination of the interferences and (4) elution of the analytes. pesticides are desorbed by the mobile phase and are directed to the analytical column where separation will take place. Most common fully-automated devices include the Prospekt (Spark Holland, The Netherlands) and the OSP-2 (Merck, Germany). The two systems differ by the fact that while the former has only one position for each

Figure 7.2. General diagram of the system used for on-line preconcentration and determination of organic micropollutants in water samples. precolumn, the OSP-2 can be operated in such a way that while one sample is preconcentrated in the preparation position, another precolumn is being eluted. This option is very interesting since it saves time. The two systems have their own precolumn design, which covers a large variety of packing materials and include the possibility to elute in normal and backflush mode. However, in order to achieve optimal performance with on-line LSE, the sorbent of the precolumn should be as similar as possible to the analytical column packing in terms of type of packing, particle size etc. Band broadening can be minimized by using a suitable gradient which causes peak compression on the top of the analytical column. The size of the precolumn is also of importance because elution profile of the analytes should be as narrow as possible, specially at the beginning of the separation, where the high water content tend to cause peak distortion. For a classical analytical column of 15 cm× 0.46 cm I.D., common sizes are 1.2 cm long and 2 to 3 mm internal diameter, and are packed with 10 to 60 µm sorbent material which efficiently trap the analytes while precolumn clogging is prevented. In general, limits of detection (LOD) at levels of ng/l and better reproducibility values can be obtained by using the on-line approach because the entire sample is transferred to the analytical column and losses during sample manipulation are minimized. An additional advantage of using coupled technologies is that degradation studies can be followed with almost no manipulation of the water sample and therefore, further degradation of pesticides does not occur during the extraction procedure. At the same time, on-line methodologies are more sensitive since it is possible to analyze pesticides at a level of ng/l with only 100 ml of sample. Even though in

routine analysis there is a tendency to replace off-line methods to automated methods, the former method will still be preferred in some specific applications due to their higher versatility. For instance, with on-line methods, breakthrough of the more polar compounds is originated by the restricted size of the precolumns (Puig et al., 1995; Pocorull et al., 1995; Brouwer et al., 1994). For these compounds, with off-line methods better LOD’s are usually achieved, since no limitation on the amount of sorbent exist. The use of solid-phase microextraction (SPME) with polyacrilated coated fibers has been reported by Buckholz et al. (1994). Organic pollutants are adsorbed from the matrix by the solid phase coating. The analytes are then directly transferred to the injector of a GC by using a modified syringe assembly. They are thermally desorbed and analysed. SPME has important advantages such as its higher sensitivity, versatility and no solvents, sophisticated apparatus or sample work-up are required. Moreover, contrary to classical LSE, no sample filtration is required although salting out is usually needed. This protocol has permitted the determination of phenol at level of 0.13 µg/l with a precision of 5 % RSD (Buckholz et al., 1993). Recoveries for the rest of phenols range from 77 to 100 % with detection limits below 0.1 µg/1. The protocol is combined with GC methods, thus derivatization is usually required. SPME has advantages such as time and cost, avoids some of the risks of LSE waste such as channelling or sorbent clogging and permits fully automated systems coupling to GC. However, additional research is needed on new fibers which can handle large sample volumes and into automation with LC systems. 7.1.2.2. Types of sorbent materials

A wide range of sorbent materials are today available in different configurations. Even though bonded silica such as C18 or C8 are still the most used material for environmental analysis, polymeric sorbents have become a good alternative to bonded silica for an effective preconcentration for moderately to polar organic compounds (Liska et al., 1993; Hennion et al., 1994). Disposable prepacked columns, cartridges or Empore disks are made available by most of the manufacturers under various trade names such Envi-chrom, PLRP-S, Lichrolut EN, Isolute ENV having few differences among them. XAD resins has been used for extraction and stabilization of phenols (Arthur et al., 1992) and pesticides (Berkane et al., 1977) from water. However, this sorbent needs an extensively clean up prior to the preconcentration step (James et al., 1981). On the other hand, recoveries higher than 90% for priority pollutants were found using Amberchrom resins (Mubmann et al., 1994) and higher than 80 % were obtained when using column switching systems and PLRPs sorbent (Pocurull et al., 1995). The main problem of this sorbent material when the on-line approach is used, is that band broadening can appear, specially when normal flush elution is used. Highly crosslinked phases such as Lichrolut EN or Isoelute ENV have an open structure (high porous material) which maximizes the active surface as compared other sorbents such as PLRP-S thus leading to recoveries higher than 80%, although when using Lichrolut EN considerable band broadening was observed with column switching technology (Puig et al., 1996). Modifications such as acetylation (Powell, 1995) or sulfonation (Fritz et al., 1995) lead to increased recovery values. A comparative study between an unmodified polymer (SDB) and a sulfonated one (SDB-RPS) in Empore disk format (Puig et al., 1996) showed the excellent

performance of the latter sorbent giving recoveries for phenol and catechol ranging from 80 % to 86 % when processing 1 L of water. This values are a good improvement as regards of the data obtained when using the SDB disks (from 40 % to 50 %). The sulphonated disks have a mixed retention mechanism which includes hydrophobic and ionic interactions which facilitates the trapping of the most polar phenols. DiCorcia et al. (1991 and 1993) describe the use of graphitized carbon black (GCB), available in cartridge format, and report recoveries higher than 90 % except for phenol. However the excessive retention makes the desorption difficult, and some of them e.g. 2,4- dimethylphenol were irreversibly adsorbed. Elution in backflush mode can overcome this problem, but the automation in off-line mode is not straightforward (DiCorcia et al., 1994). The poor mechanical stability of GCB has prevented their routine application in the on-line approach. This problem was solved by the development of porous graphite carbon (PGC) where the graphite is immobilized on a silica structure and the phase is pressure-resistant and shows better stability (Forgacs et al., 1995). This sorbent has been successfully applied for on-line trace enrichment of aminophenols and catechols, but recoveries for phenol were lower than those obtained with polymeric sorbents (Coquart et al., 1992). In general, the PGC precolumns must be coupled with a PGC analytical column to prevent band broadening. However, excessive retention occurs even when working with mobile phases with methanol ratios up to 80% (Puig et al., 1996). Hence, the use of this sorbent will be restricted to the most polar phenols e.g. catechols and other sorbent materials will be preferred for the rest of phenolic compounds. Anion exchange sorbents are also applied for the analysis of very polar analytes, as such aminophenols and polyhydroxyphenols, which are not trapped using polymeric phases. Combination of various sorbent materials such C18, GBC or PLRP-S with anion exchanger has also been described to determine analytes of different polarities using both on-line and off-line procedures. Even though it allowed to monitor a broad range of analytes with recoveries higher than 90 % for all of them (Nielen et al., 1985), complex designs are required and the application is not common. On-line preconcentration using a two step approach with a PRP 1 in combination with an ion exchange precolumn has allowed the determination of various chlorotriazines and urons in water at 10 ng/L level (Nielen et al., 1987). In this way PRP-1 acts as a filter to remove many neutral interferences present in drinking water samples. Some attempts to couple LSE with supercritical fluid extraction (SFE) has been carried out (Pocorull et al., 1997). This has the advantage against on-line LSE-LC that by using CO2 as a desorption agent a more selective elution can be achieved. With LSE-SFE, identification and quantification of polar phenols can be achieved, with LOD’s ranging from 2 to 6 µg/l with UV detector. Even though this data is far higher to those obtained with on-line LSE-LC-DAD, it can be successfully applied to analyze waste water, as regards the cleaner chromatographic profiles. However, a really promising feature is the development of immunoaffinity sorbents for LSE. By taking advantage of cross reactivity, trapping capacity and selectivity, families of compounds or single analytes can be extracted thus avoiding the matrix interferences. This approach has been recently applied for pesticide analysis and Pichon et al. (1995) report the breakthrough volumes obtained with different sorbents.

7.1.2.3. Parameters involved in liquid-solid extraction (LSE)

Due to the large variety of packing materials, sizes and formats, the extraction efficiency, both off- and on-line will vary depending on the nature of the analytes. In this respect, it is of prime importance to establish which compounds can be successfully analyzed with each type of sorbent and what are the optimum analytical conditions to attain maximum sensitivity. The most critical parameter in LSE efficiency is the breakthrough volume, or the maximum volume of water that can be preconcentrated upon an adsorbent without producing looses of a particular analyte. The breakthrough volume is different for each analyte, and it depends mainly on their polarity and on the affinity for a particular type of sorbent and on the amount of sorbent. Different methods for calculating the breakthrough volumes are described in a recent review by Barceló et al. (1995) and involve the study of the breakthrough curves or the empirical estimation from elution chromatography (Hennion et al., 1993). A different way is by measuring the peak areas or heights of increasing volumes of water spiked with a decreased concentration so that in each analysis the amount of analytes preconcentrated is the same (Subra et al., 1988) and calculate that volume where the areas (or hights) start to decrease. The estimation of the breakthrough volumes, either with on-line or off-line techniques, offer information about the optimal sample volume that can be percolated through the sorbent to gather optimal sensitivity. When 100 % of recovery is required, the percolated volume must be lower than the breakthrough volume. However, in environmental analysis it is a common practice to surpass the breakthrough volume; in such case, the total amount of analyte preconcentrated is higher and therefore the sensitivity is increased at the expenses of recovery. The presence of interfering materials in the water sample, mainly humic and fulvic, can bind organic contaminants (Porchmann et al., 1993) and will notably affect analytical performance, which should be considered when calculating breakthrough volumes. Figure 7.3 shows the chromatographic profiles of three different water matrices spiked with some phenolic compounds at 4 µg/l and analyzed using the sorbent LiChrolut: drinking water (chrom. A), ground water (chrom. B) and river water (chrom. C). When working with drinking water there is not any problem to detect and quantify all target compounds but in the case of analyzing ground water quantification of cathecol is quite difficult at this level because of the early elution of a matrix peak. As a result, a change in the type of water can lead to considerable variations of breakthrough volumes and LOD’s (Scott et al., 1995). Moreover, adsorption of analytes onto humic substances can result in a decrease of breakthrough volumes and recoveries, since only the dissolved fraction will be enriched. Acidification of the sample is a common practice in environmental analysis because it can

Figure 7.3. LC-DAD chromatographic profile at 280 nm of phenolic compounds spiked at 4 µg/l level after on-line LSE of 100 ml of sample using PLRP-S sorbent. A) HPLC water, B) ground water and C) river water. Peak identification (1) 4-nitrophenol, (2) 4-methylphenol, (3) 2, 4dinitrophenol, (4) 2-nitrophenol, (5) 4-chlorophenol, (6) 2, 4-dimethylphenol, (7) 4-chloro-3methylphenol, (8) 2, 4-dichlorophenol, (9) 2, 4, 6-trichlorophenol, (10) pentachlorophenol. avoid the deprotonation of the most acidic compounds and inhibit microbiological degradation. However, in the case where the sample is acidified, adsorption of humic material into the sorbent is increased because their hydrophobic character raise so a large unidentified complex matrix (UCM) interfering peak appears somewhere in the chromatogram (Liska et al., 1993). Therefore this can result in a decrease of breakthrough volume of analytes which lack strong affinity for the sorbent since there is a strong competition between analytes and humic substances. For instance, important differences against working at pH 7 or pH 2.5 were found when analyzing river water samples spiked with priority phenols, where cresols or 2, 4-dimethylphenol were displaced with humic substances, so their breakthrough volume and recoveries were reduced. Contrary to that, higher recoveries than expected were found when analyzing polar pesticides like aldicarb sulfoxide or aldicarb sulfone in drinking water. This could be explained by the fact that absorbed humic and fulvic substances increases the surface of the sorbent thus raising recoveries of some polar analytes. As a result of the variations found in the recovery of the different organic pollutants in the different types of waters, prior to HPLC analysis, the extraction of pH should be optimized to maximize analyte recovery and detection limits. Quantitation in real samples is in any case difficult because humic substances appear at earlier minutes so making identification and quantification of low retention time analytes difficult. In conclusion it should be mentioned

that calibration studies, with calculation of breakthrough volumes, recoveries or detection limits, should be carried out in a similar water matrix as the sample. When analyzing samples with high percentage of humic material another relevant parameter to be optimized is the clean-up step. Humic material can be partially removed from the sorbent by passing a little amount of water through the sorbent bed thus providing a chromatographic profile void of interferences. But the water volume should be carefully optimized specially when working with low breakthrough volume analytes. When using an on-line approach, precolumns are normally packed with about 20 µg so no more than 1–1.5 ml are required. On the other hand it should be taken into consideration that some analytes can be adsorbed onto humic substances which are, at the same time, adsorbed onto the sorbent. This is specially true when acidification of river samples rich in humic substances is carried out before the analysis. In this situation washing step will lead to a decrease in recovery because when removing humic material analytes will also be removed. 7.1.2.4. Stabilization of water samples

One issue that is gaining interest is the use of solid-phase materials as an alternative for storing water samples, with the main purpose to improve the quality assurance parameters in relation to sample handling, transport and storage of pesticides in environmental water analysis. Solid phase extraction sorbents are advantageous in front of acidification of water samples or freeze-drying with the addition of glycine (Barceló et al., 1994) since SPE is less laborious and ensures the stability of most of the pesticides for an acceptable period of time. A recent review on preservation techniques for organic compounds showed a 100% loss of many pesticides after 14 days in biologically inhibited water at 4°C, while they were stable in the stored sample extracts (Jeannot et al., 1994). The study of the stability of the organic pollutants on different sorbents is mandatory before sample storage on LSE sorbents can be applied to on-going monitoring programs. In this sense, Empore Extraction disks (Senseman et al., 1993; Barceló et al., 1994; Johnson et al., 1994) and cartridges (Hinkeley et al., 1989) have been used to test the stability of different organic pollutants. Results indicated that pesticides had equivalent or greater stability on solid phase extraction disks compared to their storage in water at 4°C. Temperature is probably the main cause which affects the stability of the pesticides in C18 disks and Senseman et al. (1993) found a higher rate of degradation of various pesticides when stored at 4°C than at −20°C. Additionally, the data obtained suggested that storage at −20°C after pesticide loading was the most favorable storage option, with recoveries of 79–93 % after 180 days of storage. Problems of stability during storage at 4°C, were attributed to a combined process of hydrolysis and volatilization due to the remaining water on the disk not removed by vacuum filtration (Senseman et al.,

Table 7.2. Average percentage recovery (n=3) of pesticides stored at room temperature (RT) during 1 month, 4°C during 3 months and −20°C during 8 months. Analysis were performed using on-line LSE-LC-DAD. Volume of water preconcentrated=26ml, spiked at 10ng/ml. Compound

λ

RT (1 month)

4°C (3 months)

−20°C (8 months)

Mevinphos-cis

220

n.f.

35

22.7

Mevinphos-trans

220

n.f.

19

58.0

Dichlorvos

220

59

n.f.

55.5

Fensulfothion

254

123

74

89.3

Azinphos-methyl

220

115

100

111.5

Fenamiphos

254

n.f.

n.f.

101.7

Phosmet

220

39

61

34.7

Pyridafenthion

254

84

n.c.

100.8

Parathion-methyl

280

117

109

105.8

Malathion

220

116

n.c.

124.9

Fenitrothion

254

112

91

108.0

Azinphos-ethyl

254

112

91

108.0

Chlorfenvinphos

254

114

90

106.2

Fenthion

254

89

85

103.8

Parathion-ethyl

280

111

104

109.9

Coumaphos

280

117

103

113.5

Fonofos

254

n.f.

n.f.

107.2

EPN

220

99

103

83.7

Chlorpyrifos

220

88

104

133.1

n.f.=not found n.c.=not calculated/impossible to quantify 1993). Johnson et al. (1994) indicated that storing the disk at −20°C was the most proper way to obtain good stability data for pesticides but at 4°C losses of 25 to 35 % for carbofuran were noticed. Relationships were established between storage stability with the coefficient of adsorption for unity of mass of organic carbon (Koc) values and solubility of the different pesticides. Recently, the stability of various pesticides upon the C18 precolumns of the Prospekt has been examined (Lacorte et al., 1995). Storage conditions included 4°C, −20°C and a combination of two conditions where precolumns were stored at 4°C for 1.5 months and held at room temperature until analysis (0.5 and 1 month). Table 7.2 shows the pesticides selected and the percentage recovery after 3 months at 4°C, 1.5 months at 4°C followed by 1 month at room temperature and after 8 months of storage at −20°C. It was demonstrated that many

organophosphorus pesticides which showed stability problems in water matrices were stable under disposable LSE precolumns for a period up to 8 months at − 20°C and many of them for a period of 3 months at 4°C. That study contributed significantly on sample handling since it means that after collection and preconcentration of the water samples containing

Figure 7.4. (A) On-line LSE-LC-DAD chromatogram at 220 nm corresponding to time=0 analysis of groundwater (26ml) spiked with a mixture f pesticides at a level of 10ng/ml. (B) Online LSE-LC-DAD chromatogram at 220 nm corresponding to the desorption of the precolumns kept at −20°C during 8 months. (C) Same chromatogram as A at 280 nm and (D) Same chromatogram as B at 280 nm. Column used: Waters Symmetry 250×4.6mm packed with 5 µm C8. Peak identification: (1) cis-mevinphos, (2) trans-mevinphos, (3) dichlorvos, (4) fensulfothion, (5) azinphos-methyl, (6) fenamiphos, (7) phosmet, (8) pyridafenthion, (9) parathion-methyl, (10) malathion, (11) fenitrothion, (12) azinphos-ethyl, (13) chlorfenvinfos, (14) fenthion, (15) parathion-ethyl, (16) coumafos, (17) fonofos, (18) EPN, (19) chlorpyrifos and (20) temephos.

pesticides, the precolumns can be transported and stored at 4°C for a period up to 1.5 months, showing no degradation for 16 of the studied pesticides and for a period of half month if the precolumns were stored at room temperature. This accounts for the most apolar compounds exhibiting low solubility and low vapor pressure. It was also observed that the stability upon the C18 phase was related to higher Koc values, which favored the partitioning of such compounds in the C18 phase from the water phase. Figure 7.4 shows an LC-DAD chromatogram at different wavelengths of a precolumn loaded with ground water sample spiked with 19 pesticides and kept at −20°C for 8 months before elution. Mevinphos, dichlorvos and phosmet were the least stable pesticides since degradation occurred when precolumns were stored at −20°C The physico-chemical parameters such as water solubility of the pesticides, the vapor pressure (VP) and half life measured with the pesticide in solution affect the degradation of organophosphorus pesticides upon the C18 phase. These parameters are reflected in Table 7.3 for the pesticides which underwent degradation. High VP accounted for looses for dichlorvos, fonofos and mevinphos, which explain the low recoveries encountered during the off-line preconcentration step (Molina et al., 1994). In this sense, preconcentration on C18 precolumns is advantageous since losses of the more volatile compounds (dichlorvos) during the drying step of the C18 disks are minimized. Fonofos and fenamiphos dissipated from precolumns stored at 4°C and at room temperature due to their high vapor pressure and high solubility in water respectively, thus favoring losses by volatilization, hydrolysis and microbial breakdown. With on-line LSE-LC-DAD it was possible to detect the pesticide degradation products formed in the precolumns stored at 4°C and at room temperature by spectral matching since the UV spectra of the degradation products is similar to the parent compounds (Lacorte et al., 1995). A recent work of Molina et al. (1996) involve the study of the stability of 3 priority pesticides, fenamiphos among them, with LSE styrene-divenylbenzene cartridges followed by LC-ESP-MS. Degradation of fenamiphos occurred after 80 days of storage at −20°C, and fenamiphos sulfoxide was unequivocally identified. The degradation product was detected during all the study period, and its concentration increased as the concentration of fenamiphos decreased. It was found that the use of a drying step after loading the cartridges and prior to storage increased the stability of fenamiphos. The use of a drying step permitted to recover 45 % of the compound 45 days after storage as compared to a complete loss obtained without the drying treatment. Table 7.3. Physico-chemical properties of the unstable pesticides. Compound

Solubility

koc(CC/g)

Half life (days)

VP (mPa)

10g/l

n.f.

n.f.

7000

700 mg/l

1.8 (water) (7)

267

0.13

Fonofos

17mg/l

40 (soil) (27)

870

28

Mevinphos

600 g/l

3 (soil) (27)

44

17

Phosmet

20 mg/l

7 h (water) (24)

243

0.20

Dichlorvos Fenamifpfos

n.f.=not found

To conclude, it can be said that the great advantage of using disposable solid-phase extraction precolumns for stabilizing pesticides in water samples is the storage space, since usually bottles of 1 liter are needed for sampling and storage, which can be replaced by disposable SPE precolumns. The easy shipping of the disposable SPE precolumns containing pesticides to the central laboratory for the final analysis is another advantage, being unnecessary to perform the analysis immediately after sampling. These results are encouraging since many pesticides which were withdrawn from the NPS-EPA list because they degraded in water samples stored in the dark at 4°C after 14 days, were recovered when stored upon C18 precolumns. However, since the stability of the pesticides is pH and temperature dependent, it is possible that in different stability studies variations in recoveries using types of water samples of various sources can be expected. 7.1.3. CHROMATOGRAPHIC TECHNIQUES 7.1.3.1. Gas Chromatography (GC)

Gas chromatography (GC) plays an important role in trace analysis. It is the official method adopted by the Environmental Protection Agency of the United States (EPA-US) (EPA Method 604, 1984) and it is a well-known and widely established analytical technique. One of the main advantages of GC is that it can be coupled to a large variety of selective and sensitive detectors, such as nitrogen-phosphorus, flame ionization detector (FID) or electron capture detector (ECD), atomic emission detector or pulsed-flame photometric detector which lead to the achievement of very low detection limits. Moreover, the combination of the high separation efficiency of the capillary columns and the selective detectors make GC analysis very suitable for pesticides and phenolic compounds since it permits the multidimensional analysis and minimize the effect of the water matrix. All these GC detectors provide a linear range over various orders of magnitude, and detection limits at the low ng/l level. The EPA method for the analysis of pesticides and phenols in water samples indicate the need to confirm the results by using two different GC columns, usually a DB-5 and a DB-1701 (Graves, 1989). Lacorte et al. (1993) carried out a systematic study with the aim to study the retention times of 26 priority organophosphorus pesticides and various degradation products in three different capillary GC columns. It was seen that the use of different columns solved the risk of coelution and it avoided false positive determinations in environmental water analysis. Another way to confirm the results is the use of GC with mass spectrometry as detection technique (Munch et al., 1992), which besides providing an excellent separation technique, it provides structural information which is used for both qualitative and quantitative purposes. GC-MS has been performed either with electron impact ionization technique (EI) and negative chemical ionization (NCI), and has been applied in various different cases (Barceló et al., 1990; Barceló et al., 1991; Durand et al., 1989; Durand et al., 1991). One of the main advantages of EI is the existence of libraries which make it possible to use spectral match. This is interesting from the view point of compound identification as well as to confirm the presence of a pollutant in an environmental sample. Information that can be obtained with GC-MS is summarized below. 7.1.3.1.1. GC-MS with electron impact (EI) In the literature, various references with GC-MS data using EI have been published (Stan et al., 1991; Stan et al., 1977; Durand et al, 1992; Desmarchelier et al, 1985; Singh et al., 1986). The

so-called US-EPA indicate the need to identify one compound at least at 3 different ions. It is known that each family of pollutants, organophosphorus pesticides, phenols, etc., produce characteristic fragment ions, also known as diagnostic ions, which aid in identification. It is worth, thus, to characterize the specific ions of each family of pollutants and their abundances. An extensive study reported by Wilkins and coworkers (1985) was based in the identification of the various organophosphorus compounds by 5 typical rearrangements, with diagnostic ions corresponding to m/z values of 93, 97, 109, 121 and 125. A more recent work (Lacorte et al., 1993) also concerning organophosphorus pesticides, give information of diagnostic ions of this type of compounds, as well as compound specific ions. The GC-EI diagnostic fragment ions are indicated in Table 7.4. Various possibilities of tentative ion identification for a same fragment ion e.g. m/z 97, 109, 127 and 137 is given. This qualitative information is valuable since it can be used for identifying degradation product of organophosphorus compounds. It was concluded that (i) the formation of these typical fragment ions reported in Table 7.4 depend on the molecule type. In this sense it is possible that two compounds will have an ion at the same m/z values, but with different composition. This is the case of organophosphorus pesticides of different classes, e.g. the m/z at 109 corresponds either to ion at 109 corresponds either to (CH3O)2PO+ or to (C2H5O)OHPO+ or to (C2H5O)PSH+. The rearrangement ion at m/z 97 usually corresponds to (OH)2PS+ but in the case of diethyldithiophosphorothioates, it corresponds to (SH)2P+. For all these above mentioned reasons, it is useful to have the chemical structures of the different compounds since some of the fragment ions can then be predicted; (ii) the typical fragment ions correspond usually to a class of organophosphorus compounds. In this sense, m/z at 109 and 125 are base peaks for the dimethylphosphates and dimethylphosphorothioates respectively; (iii) the abundance of (M)+ increases with its ability to sustain a positive charge and is related to the ionization energy, which is lowered for S rather than O. Examples on this case can be noticed for parathion-ethyl and fenitrothion, that show higher relative abundances of (M)+ as compared to the oxo-derivatives; (iv) the chlorinated compounds exhibit as main peaks the corresponding fragment ions with chlorine looses; (v) specific fragments which are typical of some compounds are also noticed, e.g., McLafferty rearrangement involving proton extraction by an oxygen of the nitro group indicating the presence of CH3 adjacent to a NO2, for fenitrothion and fenitroxon. The purpose of all this qualitative GC-MS information will be the selection of the appropriate m/z ions for routine environmental monitoring studies. In general, the use of higher m/z values will be preferred since they will allow higher selectivity and will avoid matrix interferences. 7.1.3.1.2. GC-MS with negative chemical ionization (NCI) GC-MS with NCI has been proved to be a very selective (as compared to EI and positive chemical ionization (PCI)) and sensitive technique for the determination of various organophosphorus pesticides (Barceló, 1991; Stan et al., 1982; Stan et al., 1989; Durand et al., 1991). The molecules of the so-called parathion-like structure

Table 7.4. Typical fragment ions of organophosphorus pesticides in GC-MS with EI. m/z Ion

Other possibilities +

47 CH3S

62 CH3OP+ 63 CH3OPH+ 75 77 C2H5OPH+ 79 CH3OPOH+ 93 (CH3O)2P+ 96 97 (HO)2PS+ 109 (CH3O)2PO+

P(SH2)+ (CH2H5O)OHPO+(CH2H5O)PSH+

121 (C2H5O)2P+ 125 (CH3O)2PS+ 126 (C2H5O)OHPSH+ 127 137 (C2H5O)(C2H5)PS+

(C2H5O)2PO+

141 (C2H5O)OHPS+ 142 (CH3O)2POHS+ 153 (C2H5O)2PS 157 158 (CH3O)2PSSH+ 169 (C2H5O)2POS+ 171 (C2H5O)2POHSH+ 185 offered high sensitivity under the negative ion conditions due to the presence of an aromatic moiety which is accompanied by a nitro group thus forming a kind of pseudo acid by electron attachment which stabilizes the negative charge. When this aromatic moiety contains other electron withdrawing groups e.g., chlorine atoms, the stabilization of the negative charge and sensivity are also enhanced. Values around two orders of magnitude in sensitivity versus EI have been reported for such compounds (Barceló, 1991; Stan, 1982). Table 7.5 lists the diagnostic ions of the different organophosphorus pesticides, which are characteristic of the different chemical groups. The following general remarks can be made: (i) the diagnostic ions formed under NCI are, in many cases, the base peaks of the different compounds and also, in few cases, the only spectral information obtained. This is a typical characteristic on MS-NCI of organophosphorus pesticides, so their unequivocal identification should always be carried out in combination with the retention time; (ii) the formation of (M)*− has a 100% of relative

abundance for the organophosphorus of the so-called parathion group, and compounds having an aromatic moiety (with exception of Table 7.5. Diagnostic ions of organophosphate pesticides in NCI. m/z

Ion

Group

125

(CH3O)2PO2

Dimethylphosphates

141

(CH3O)2POS

Dimethylphosphorothiolates

153

(C2H5O)2PO2

Dimethylphosphorothionates

157

(CH3O)2PS2

Dimethylphosphorodithioates

169

(C2H5O)2POS

Diethylphosphorothionates

185

(C2H5O)2PS2

Diethylphosphorodithioates

chlorinated organophosphorus pesticides). This is due to the fact that (M)*− is rather stable under NCI conditions when an aromatic moiety exists in the molecule, and is even more important when a nitro group is present; (iii) the chlorinated organophosphorus pesticides with an aromatic moiety have intense or base peaks corresponding to looses of Cl due to facility of such processes under NCI conditions; (iv) the formation of thiofenolate versus fenolate ions for compounds such as parathion, fenitrothion, coumaphos, fenchlorfos is due to the strong acidity of thifenolate versus fenolate in the gas phase and there is a transfer from the aromatic moiety from the oxygen to the sulfur atom. Figure 7.5 represents one of the applications of GC-MS for the analysis of environmental water samples. Surface water that had been treated with the pesticide fenitrothion was analyzed both with GC-EI-MS and GC-NCI-MS in order to detect the maximum number of degradation products (Lacorte et al., 1994). Fenitrothion and 3 degradation products, which corresponded to fenitrooxon, S-methyl isomer of fenitrothion and 3-methyl-4-nitrophenol were detected at least at 3 different ions. 7.1.3.1.3. Liquid solid extraction coupled on-line with GC In order to increase LOD’s, LSE has been coupled on-line with GC (Kwakman 1992). This system, known as SAMOS GC includes the preconcentration unit Prospekt (Spark Holland, The Netherlands), a HP 6890 GC and a HP ChemStation which controls both the preconcentration program and the chromatographic analysis. The set-up of the system consists in preconcentrating the water sample upon the SPE precolumns and afterwards, elution takes place by coupling the preconcentration step with GC by switching the 6 port valve. Interfacing LSE with GC is the most critical part of the system and it includes a retention gap and a retaining column prior to the analytical column. On a first attempt, analytes adsorbed upon the precolumn were desorbed with 50–75 µl of ethyl acetate without performing any drying step and with LSE-GC and flame ionization detector (FID) it was possible to quantify nitrobenzene and w-cresol at 0.1–10 µg/l level using only 1 ml of water. Even though it was possible to carry out 140 analysis without changing any part of the system, it was found that the water (from the precolumn) dissolved in ethyl acetate destroyed the retention gap by hydrolysis. To solve this problem, two different

approaches have been undertaken. The first one was drying the precolumn with nitrogen during 10–15 min. at ambient temperature. Coupling LSE-GC with NPD permitted to achieve LOD’s between 10 to 30ng/l by preconcentrating 2.5ml of tap water, and LOD’s

Figure 7.5. Total ion current (TIC) obtained using (A) GC-EI-MS with a DB-1701 and (B) GCNCI-MS with a DB-5 of a water extract collected from an irrigation ditch 4 hours after fenitrothion had been applied and contained (1) 3-methyl-4-nitrophenol, (2) fenitrooxon, (3) fenitrothion and (4) s-methyl isomer of fenitrothion. between 50 to 100ng/l when analyzing river water. In all instances, the relative standard deviation was of 2 to 4 %, and the system behaved linearly from 0.06 to 3 µg/l (Brinkman et al., 1994). The second attempt to remove the excess of water from the precolumn was to insert a short drying cartridge containing anhydrous copper sulphate, sodium sulphate or silica between the LSE and GC parts of the system (Vreuls et al., 1992; Picó et al., 1994). LSE-GC was also coupled to MS with a HP 5973 Mass Selective Detector. In order to avoid large quantities of solvent to enter in the MS, a 2m×150 µm I.D. deactivated fused silica restriction capillary is used. The preconcentration of 1 to 10ml of river water is sufficient to quantify atrazine and simazine at concentrations of 30 to 100ng/l (Bullterman et al., 1993). It can be concluded, therefore, that GC is a powerful technique in water analysis, due to the separation efficiency and the high availability of different detectors with a further advantage of the easy coupling with mass spectrometry. Its use is spread and for example, the official method 604 of the US-EPA for phenolic compounds are based on liquid-liquid extraction followed by ECD or mass spectrometry. However, one of the limitations of GC for the analysis of phenols and polar or thermolabile pesticides is the need of a derivatization step (Haslová et al., 1988) which increase sample manipulation, time of analysis and introduce new sources of errors. Some

authors have used GC without derivatization (Mubmann et al., 1994; Chen 1991) but it has been reported the problem of peak tailing, even when highly deactivated columns were used (Puig et al., 1996). Moreover, the US EPA methods for phenols may often lead to incorrect results because derivatization of phenols, specially nitrophenols, it is not straightforward. Recently, the US EPA has reported a new protocol (method 8041) (EPA Method 8041) which recommends the derivatization to methylated phenols instead to pentaflouorobenzoyl ether derivatives. However, this method requires the use of diazomethane which is carcinogenic and explosive and the potential hazards associated with its use are well known. For such reason, there is a general tendency to switch to liquid chromatography (LC), which can overcome the aforementioned limitations 7.1.3.2. High performance liquid chromatography (HPLC) 7.1.3.2.1. Liquid-chromatography and diode array detection (LC-DAD)

Modern organic pollutants cover a wide range of compounds which differ in their chemistry. Pollutants susceptible to absorve at UV are those which present a suitable chromophore. This characteristic permits their detection by UV detection provided a proper sample preconcentration technique has been carried out. Most pesticides present a typical UV spectra with UV maximum between 230 and 280 nm while phenolic compounds are preferably detected at 280 nm except for nitrophenols and pentachlorophenol, which show better signal at 310nm. Pesticide transformation products can also be detected through UV spectra due to absorbance similarities towards the parental compound. Peak identification with LC-DAD is usually carried out by means of retention time in comparison with a standard and by spectral match through library search, which is an option which is nowadays included in most softwares. Selectivity enhancement is obtained through UV selection and can be used to identify and quantify pesticides at very close retention time. In this sense, it is recommended to perform quantitative analysis at the wavelength which provides better calibration adjustment. In order to reduce quantification errors, modern softwares include the peak purity analysis of each compound, which permits the detection of potential coelution problem with another pesticide or with matrix interferences. Due to variations of the results reported by the various laboratories, method testing, based on repeatability, reproducibility and calibration data should be performed routinely to evaluate the performances of an analytical method, and should be specifically aimed to provide reliable quantitative results. Most important sources of method error concern the sample pretreatment step and method of quantification. In general words, for environmental analysis the long-term reproducibility should not exceed a 10 % variation, and the triplicate analysis should have a maximum error of 3%. It is clear that the use of on-line devices decrease the percentage of variation since the risks of sample looses or contamination are minimized. However, the type of water and analytical methodology used have a straight influence on the results obtained. A recent project which involved various european countries was aimed to examine the performances of the SAMOS system for pesticide monitoring. The SAMOS system includes a sample preconcentration unit (Prospekt, Spark Holland, The Netherlands) connected on-line with a Hewlet Packard model 1090 equipped with a diode array detector. The whole set-up is programmed with a workstation. This system is extensively described in (Brinkman et al., 1994) and has been applied to monitor pesticides in European rivers. The performance of the system

has recently been tested in industrial effluent water and errors varying from 1 to 15% have been encountered after the preconcentration of 100ml of surface water spiked at 1 ng/ml through PLRPs precolumns of the Prospekt (Lacorte et al., 1997). The authors concluded that the highest errors were due to breakthrough of the more polar compounds and to the presence of interferences. The repeatability and reproducibility of on-line LSE-LCDAD using the Samos system were tested with Milli-Q and river water involving the preconcentration of 100ml of sample onto C18 precolumns. The repeatability and reproducibility of the method are closely linked to the type of water. The overall values, measured as the % coefficient of variation, were below 10% error indicating the suitability of the method for water control analysis. Better values were obtained with Milli-Q water than river water since in the former case, matrix interferences were not present. To sum up, system testing with Milli-Q water indicate the method capabilities but do not provide quantitative data to be extrapolated to field measurements. A more realistic approach is gathered if method performance is firstly evaluated with surface water since the complexity of the determination of pesticides is increased due to the water matrix, presence of particles and of humic and fulvic material. Since water matrix accounts for variations in method performance, it is expected that differences in quality parameters will be found. On the other hand comparison with direct injection is not advisable when performing on-line experiments because band broadening always occurs although imperceptible. Pichon et al. (1994) indicated a 5 % of error if quantification of on-line samples was contrasted to direct injection. Table 7.6 reports the calibration data of 8 pesticides obtained after the preconcentration of effluent river waters. Linearity was observed for all the compounds Table 7.6. Calibration data using Llobregat river water spiked with a mixture of triazines and organophosphorus pesticides at a level from 0.3 to 1.5ng/ml. nm=wavelength used for quantitation; R2=coefficient of correlation; Rep.=repetitivity (n=5, spiked sample at 1 ng/ml); Repro=reproducibility (n=5, spiked sample at 1 ng/ml); LOD=limit of detection. nm

Desethylatrazine

215 n.d.

n.d.

3

10

120

Simazine

215 n.d.

n.d.

23

50

89

Atrazine

215 Y=485603X−14495

0.997

4

4

10

Propazine

215 Y=657625X+16098

0.996

9

13

10

Parathion

275 Y=177910X−4062

0.994

4

5

13

Fenitrothion

275 Y=168103X+23745

0.987

5

6

18

Diazinon

250 Y=83159X+11072

0.972

5

10

105

Chlorpyrifos

215 Y=92692X+16050

0.974

4

10

22

n.d.=not determined

Calibration curve

R2

Compound

Rep. (%)

Repro. (%)

LOD ng/l

studied over a concentration level from 0.3 to 1.5 ng/ml. Coefficients of correlation were around 0.99, which are acceptable if one takes into consideration that river water was used. The worst values were for diazinon and chlorpyrifos, which eluted at high percentage of acetonitrile, together with the more lypophylic components in the water matrix. The high LOD s of diazinon contributed to the low coefficient of correlation of this compound. Desethylatrazine and simazine could not be detected due to early elution at the interval where humic and fulvic substances abound. The system has been applied routinely to screen pesticides from the Llobregat river at the Water Depuration Plant in Barcelona (AGBAR, Sant Joan Despí). Figure 7.6 indicates the presence of terbuthylazine, which corresponded to a local spill produced by an industry who use this compound as an algaecide in their refrigerating circuit. 7.1.3.2.2. Liquid Chromatography and Electrochemical Detection (LC-EC) Electrochemical detectors include various devices such as conductivity detector and amperometric, coulimetric and polarographic detectors. Since most phenols are electrochemically active, LC coupled to EC can provide a great improvement on sensitivity. Table 7.7 shows the LOD’s obtained using UV (280 nm), EC (1000 mV) and coulimetric detection (E1:300mV, E2:650mV). For instance one order of magnitude enhancement on sensitivity was found with amperometric detection as compared with UV (Ruana et al., 1993; Baldwin et al., 1988). Moreover, the high sensitivity of EC allows to reduce the sample volume thus avoiding the percolation of low breakthrough volume analytes such as phenol. LOD’s of 0.02 µg/L were found when processing 10ml of river water which could not be accomplished by UV (Puig et al., 1995). This can be seen in Figure 7.7, where by reducing the sample volume it was possible to detect phenol, although nitrophenols could not be monitored because optimal working potential is slightly higher for these compounds. Despite all these obvious advantages, a problem arises from the cleaning requirements of the electrochemical cell which results in response instability. EC detection of phenols requires the use of high potentials (around 1 V), which give the possibility for other matrix components to be oxidized thus increasing the background current which leads to lower reproducibility values as compared with UV detection. The development of amperometric detectors (PAD) has improved signal stability. However, even in this case the working electrode should be cleaned regularly, specially when processing dirty samples, in order to get the initial response. Since this is some times very difficult to achieve, new calibration of the system should often be carried out. This is specially true when working in on-line LSE where the amount of interferences introduced into the chromatographic system is higher. This is obviously time consuming and make EC detectors less suitable for unattended use which should be taken in consideration when high number of samples have to be monitored. In summary, EC detection is a good choice to monitor relatively clean samples, such as drinking water, where electrode fouling is not a critical problem. Galceran et al. (1995) have applied LC-EC for the analysis of phenols in seawater and report LOD’s between 0.01 and 0.04 µg/l after preconcentration of 250 ml of seawater onto polymeric PS-DVB disks. However, the analysis of complex samples, such as river or waste water, the more robust UV will be preferred, although EC may be required to detect the low breakthrough volume analytes.

Figure 7.6. On-line LSE-LC-DAD chromatogram obtained with the SAMOS system of a surface water sample that contained terbuthylazine at a concentration of 13 µg/l.

Figure 7.6. On-line LSE-LC-DAD chromatogram obtained with the SAMOS system of a surface water sample that contained terbuthylazine at a concentration of 13 µg/l.

Table 7.7. Detection limits (ng/l) of phenolic compounds obtained after on-line LSE followed by spectophotometric (UV) amperometric (EC) and coulimetric (screen out mode) detection. UV (280 nm)

EC (1 V)

Screen out mode (E1:350mV) (E2:650mV)

1200

20

1.5

n.d.

—

1.2

1500

10

1.6

800

30

2-NITROPHENOL

1200

2000

2

4-NITROPHENOL

800

3000

2.3

2 ,4-DINITROPHENOL

500

3000

3

4,6-DINITRO-2-METHYLPHENOL

n.d.

—

2.5

2-CHLOROPHENOL

1500

50

2.5

3-CHLOROPHENOL

1700

50

5.4

4-CHLOROPHENOL

1500

40

0.6

2,4-DICHLOROPHENOL

2000

30

0.9

4-CHLORO-3-METHYLPHENOL

2000

25

2.4

2,4-DICHLOROPHENOL

2000

30

n.d.

2,4,6-TRICHLOROPHENOL

2000

50

n.d.

PENTACHLOROPHENOL

1000

30

n.d.

PHENOL CATECHOL 4-METHYLPHENOL 2,4-DIMETHYLPHENOL

Sample volume 5 ml (10ml for amperometric detector) Recently coulometric array detectors have been introduced. Unlike common electrochemical detectors in which electrodes typically react at 10% or less of the injected sample, coulometric sensors convert 100% of the analyte because oxidation of phenols occurs in a high porosity electrode. Even though this obviously leads to higher background currents, sensitivity was one order of magnitude higher than for amperometric devices. In those systems the detector cells are designed so that the eluent flows through a porous graphite electrode rather than flowing by the electrode as in traditional electrochemical detectors. This leads to a large cell constants that means that even if a significant portion of the electrode surface is contaminated the response will remain constant. Consequently, cleaning requirements are less critical hence better reproducibility values are obtained. In the most sophisticated instruments, a row of array of electrodes at increasing potentials provide 3-dimension chromatograms (similarly to diode array detectors) where analyte voltammogram facilities peak identification. Up to three order of magnitude increase on sensitivity was obtained as compared by diode array detectors and LOD’s ranging from 0.03 ng/l to 0.38 ng/l were obtained when combined with LSE (Achilli, 1995), although the high price of such systems has prevented their spread application. Less

sophisticated devices are available equipped with only two electrodes connected in series. In general they can be operated in two main operational modes usually called screen out and

Figure 7.7. LC-EC (1 V) chromatograms of phenolic compounds spiked at 1 mg/l after online LSE of ground water onto PLRP-S sorbent. (A) 50ml and (B) 10ml. Peak identification: (1) 4nitrophenol, (2) phenol, (3) 2-nitrophenol, (4) 2,4-dinitrophenol, (5) 4-methylphenol, (6) 4chlorophenol, (7) 2-chlorophenol, (8) 3-chlorophenol, (9) 2,4-dimethylphenol, (10) 4-chloro-3methylphenol, (11) 2,4-dichlorophenol, (12) 2,3,4-trichlorophenol, (13) 2,4,6-trichlorophenol, (14) 2,4,5-trichlorophenol, (15) 2,3,5-trichlorophenol, (16) pentachlorophenol. redox mode. When using the screen out approach, the first electrode (E1) is set at low potentials to eliminate interferences and only the second one (E2) is used for analytical purposes. Alternatively the system can be run in redox mode. In this case E1 is set a high positive potentials to ensure that all compounds of interest are oxidized.

Afterwards the oxidation product is reduced in a second step. This approach is interesting in the case of analytes which require high oxidative potentials such as phenols because these can be reduced by using potentials around −200 mV where background and chromatographic interferences are reduced (Galletti et al., 1990). When combined with on-line LSE LOD’s below 100ng/l were obtained for all priority phenols when processing 5 ml of water (Table 7.7), which is better than the data found with other detection devices. This approach has been successfully used in food and pharmaceutical industry but few applications have been reported for environmental samples mainly because no gradient elution can be performed since it produces distortions in the baseline and long stabilization times (Goulan et al., 1996). In this sence, Jáuregui et al. (1997) have optimized different mobile phases to achieve a good separation of chlorophenols and at the same time report qualitative data as regards to LOD’s, precision and calibration. 7.7.3.2.3. Liquid chromatography and fluorescent detection (LC-FD)

Similarly to electrochemical detection, fluorescence detection (FD) is a high sensitive and selective detector. However, the main drawback of this approach is that only few compounds are naturally fluorescent hence post column derivatization is generally needed. Post-column derivatization with fluorescence has been applied for the determination of N-methylcarbamates and O-(methylcarbomoyl)-oxyme pesticides and it is the official US-EPA method for the determination of these compounds (US-EPA Method 531.1). When on-line LSE is coupled to FD, water volume can be reduced to 10ml, thus avoiding percolation of the low breakthrough volume analytes (Chiron et al., 1993). Even though peak interferences can also occur, since the proposed system also detect substances with natural fluorescence (e.g. 1-naphthol), the postcolumn fluorescence detection system was extremely selective as compared to LC-UV at 229 nm. This, explains the lack of matrix peak interferences at the beginning of the gradient elution. Figure 7.8a corresponds to the analysis of 10 mL of river water spiked at 0.2 µg/L without any kind of clean-up. Figure 7.8b corresponds to the analysis of 10 mL of river water spiked at 0.2 µg/L with an trifluoroacetic acid mobile phase (pH=3). The chromatogram front and the peak tailing was reduced and the peak shape was enhanced. Fluorescence detection was also applied to the monitoring of phenolic compounds using direct (Ruiter et al., 1988) or indirect (Lamprech et al., 1994) fluorescence detection. LOD’s below ng/l level were obtained in both cases but derivatization to dansyl derivatives was required for the former approach and tubular flow through reactor for indirect detection. 7.1.3.3. Liquid chromatography and mass spectrometry (LC-MS)

LC-MS has become popular for the analysis of polar contaminants which are difficult to determine by GC. Moreover, it can provide useful structural information which can be used for the unequivocal identification of pesticides and their degradation products in environmental matrices. The coupling of LC-MS is not as obvious as with GC-MS, since the mobile phase has to be eliminated before entering the MS and at

Figure 7.8. LC postcolumn fluorescence derivatization chromatogram obtained after preconcentration on 10×0.2 mm diameter C18 Empore disks of Ebro river water spiked at 0.2 mg/l. (A) without any sample pretreatment, (B) after sample pretreatment and (C) water blank. Peak identification (1) aldicarb sulfoxide, (2) aldicarb sulfone, (3) oxamyl, (4) methomyl, (7) 3hydroxycarbofuran, (8) mathyocarb sulfoxide, (10) methyocarb sulfone, (12) butocarboxim, (13) aldicarb, (14) 3-ketocarbofuran, (17) baygon (propoxur), (18) carbofuran, (20) carbaryl, (22) 1naphtol, (26) methiocarb.

the same time, ions have to be generated. There are two main types of interfaces: trace enrichment (particle beam and moving belt) and nebulization (thermospray and atmospheric pressure ionization interfaces). Trace enrichment interfaces have the advantage that they can provide electron impact mass spectra but their application in the environmental field has been reduced due to their low sensitivity. For this reason these interfaces will not be treated in this work and all the discussion will be focused towards nebulization devices. 7.1.3.3.1. Liquid chromatography and mass spectrometry with thermospray interface (LC-TSPMS) LC-TSP-MS has been widely used to determine organic contaminants in water matrices (Puig and Silgonier, 1996; Barceló et al., 1993; Lacorte and Barceló, 1995) and has been adopted by the US-EPA (Method 8321) for the analysis of pesticides in different types of water matrices. LC-TSP-MS interface consists in sample nebulization and ionization through a heated capillary which renders molecular peak spectra and lacks of fragment ions. Since it is a soft ionization technique, identification of unknowns becomes difficult. To enhance fragmentation, additives, mainly ammonium acetate or formate, are added to the mobile phase. Ionization is due to gasphase protonation reactions between the analyte and the ammonium (D.Barceló et al., 1991; Honing et al., 1994 and Volmer et al., 1994). Filament-on or discharge assisted ionization generates solvent mediated ionization similar to direct TSP ionization (without additives), but sensitivity is enhanced (Volmer et al., 1993). The best choice to enhance fragmentation is the use of LC-TSP-MS-MS (Abián et al., 1993) which renders collision induced dissociation (CID) spectra and is used both for identification and quantification purposes. Common trends in ion formation in TSP in positive mode (PI) are the favored formation of (M+NH4)+ as base peak for pesticides, which indicates that the proton affinity for these compounds is slightly lower than ammonia (858KJ/mol). The formation of (M+H)+ ion as the second abundant ion with relative abundances varying from 12 to 93 % indicates that these compounds exhibit intermediate basicity, with equal or less proton affinities values than ammonia, favoring both the formation of (M+NH4)+ and (M+H)+ ion. The characterization of several pesticides under LC-TSP-MS in positive and negative mode is detailed in by Lacorte et al. (1995), who remark that little or no fragmentation is observed for many of the pesticides. Translated to an environmental sample, identification of unknowns using this technique is rather difficult since at least 3 different ions are needed to unequivocally confirm the presence of a pesticides in a real water sample. Under full scan conditions, instrument detection limits (IDL) are around 1 ng for pesticides (Voyksner et al., 1984). With negative mode of ionization (NI), the analytes which produced strongest signal and fragmentation were the electronegative compounds. For these compounds, NI mode of ionization is advantageous, since it yields more structural information and it is usually more selective. Under NI mode of ionization, organophosphorus pesticides yield specific fragment which correspond to molecular ions or adducts with formate as base peaks. For example phenols exhibit in general good response in TSP NI, except for phenol, 4-methylphenol and 2, 4-dimethylphenol because current buffers cannot deprotonate them even when working at high buffer concentration level.

Phenolic compounds were extensively studied using TSP interface in negative ion mode (Vreeken et al., 1990). High chlorinated phenols were deprotonated by the acetate ion with the subsequent formation of the (M−H)− ion, or underwent resonance electron capture to form the (M)− ion which produces, via hydrogen abstraction from a solvent molecule, the (M+H)− ion which usually is the base peak of the spectra because overlapping of the isotopic patterns. On-line LSE-LC-TSP-MS has been coupled to simultaneously identify pesticides and their TP in environmental matrices. This technique can also be used for quantification purposes. In this line of research, latest works concerning the analysis of pesticides of different nature with on-line LSE-LC-TSP-MS with positive mode of ionization include those of Bagheri (1993), of Lacorte et al. (1995) and Sennert et al. (1995). Linear relationship between the area of each peak versus concentration was found with correlation coefficient (R2) around 0.99 calculated from the LOD, implying that quantitation can be performed at levels of few µg/l. Most recent works that have included various TPs in their analytical methods, such as Chiron et al. (1994) who characterized several phenylurea pesticide and triazines, along with their oxons and sulfoxides and those of Lacorte (Lacorte, Lartigues et al., 1995) who included the identification of various degradation products of organophosphorus pesticides. Lacorte et al. (1995) have applied on-line LSE-LC-DAD and on-line LSE-LC-TSP-MS to unequivocally identify the parental pesticides and the TPs formed by degradation under semi-natural conditions (Ebre river water spiked at a low concentration level, and exposed outdoors for 4 weeks). Online LSE-LC-DAD was used to follow the degradation of the pesticides. Half life measured by T1/2=ln 2/k indicated that pesticides persisted in the environment for 6–12 days. However, since degradation occurred, confirmatory analysis were carried out by means of MS detection with TSP interface. The oxons of chlorpyrifos-methyl, diazinon, isofenphos, pyridafenthion and temephos were detected 4 weeks after sunlight exposure. In general, the oxygen analogues could be identified since they followed the same adduct formation as the parental pesticide and eluted before. The presence of sulfoxide derivatives was found for disulfoton, fenamiphos and fenthion. Figure 7.9 shows the LC-DAD and LC-TSP-MS chromatograms of water sample spiked with chlorpyrifos-methyl and analyzed after 4 weeks. While DAD detected chlorpyrifos and a transformation product not identified, TSP-MS confirmed the presence of chlorpyrifos and its oxon. These sample was analyzed under both PI and NI mode, to gain more structural information. NI mode showed good sensitivity for chlorpyrifosmethyl and could be determined involving chlorine losses. The TIC in PI and NI ionization mode and the ion traces at m/z 323, 324 and 198 are presented, which correspond to the parental compound and the 2 TPs formed, chlorpyrifos-methyl oxon (m/z 324) and 3,5,6-trichloro-2-pyridinol (m/z 198). 3,5,6-trichloro-2pyridinol exhibited losses of chlorine atoms and proton abstraction, similarly to the parent compound. The toxicity of 3,5,6-trichloro-2-pyridinol is greater than that of chlorpyrifos, with EC50 values of 18.6 and 46.3 µg/ml respectively, calculated with the Microtox system (Somasundaram, 1990). Also it has been reported that this compound is toxic to soil microorganisms and results in less mineralization and therefore enhanced persistence of chlorpyrifos in soil. Although LC-TSP renders structural information, often it is not sufficient to identify unknowns for which there is no previous information, referring basically to

Figure 7.9. Reconstructed ion chromatogram obtained with on-line LSE-LC-TSP-MS with PI and NI mode of ionization of a Ebre river water sample spiked with chlorpyrifos-methyl at 50mg/l, and analyzing the water sample 4 weeks after spiking. Peak identification: (1) 3,5,6trichloro-2-pyridinol, (2) chlorpyrifos-methyl oxon, (3) chlorpyrifos-methyl. (B) Same water sample analyzed by on-line SPE-LC-DAD at 280 nm.

transformation products of pesticides and phenols that might be present in real water samples. This problem can be aborded from different perspectives which include MS-MS techniques or API techniques which produce spectra by collision induced fragmentation which aids the identification of unknowns. 7.1.3.3.2. Liquid-chromatography and mass spectrometry with ionspray interface (LC-ISP-MS) The advent of API has opened a new window in environmental analysis. API includes several interfaces, i.e. electrospray (ESP), the high flow pneumatically assisted electrospray, commonly named ionspray (ISP); the heated pneumatic nebulizer (HPN) and atmospheric pressure chemical ionization (APCI). The main advantage of these interfaces is their higher sensitivity compared to TSP or PB (Straub et al., 1992; Pleasance et al., 1992). This can be seen in Table 7.8 where the different sensitivities of phenolic compounds and pesticides obtained in SIM mode using different interfaces are shown. A few applications using ESP have been undertaken for organo Table 7.8. Instrumental detection limits (ng) in SIM mode using various LC-MS interfaces TSP =thermospray, APCI=atmospheric pressure chemical ionization and ISP=ionspray. Compound

MDLs [ng] TSP

APCI

ISP

CATECHOL

2

0.004

0.740

2-NITROPHENOL

1.5

0.050

0.045

4-NITROPHENOL

0.4

0.002

0.120

2,4-DINITROPHENOL

0.7

0.004

0.256

2-AMINO-4-CHLOROPHENOL

3.1

0.050

0.500

2-CHLOROPHENOL

5

0.085

3

3-CHLOROPHENOL

4

0.045

2

4-CHLOROPHENOL

4

0.040

2

2,4-DICHLOROPHENOL

3

0.007

1.310

2,4,6-TRICHLOROPHENOL

0.95

0.004

0.330

2,3,5-TRICHLOROPHENOL

0.90

0.003

0.350

2,4,5-TRICHLOROPHENOL

0.90

0.003

0.330

3,4,5-TRICHLOROPHENOL

0.90

0.002

0.300

PENTACHLOROPHENOL

0.5

0.001

0.100

CHLORPYRIFOS-METHYL

0.08

0.001

n.d.

DIAZINON

0.01

0.002

n.d.

FENAMIPHOS

0.01

0.004

0.01

FENITROTHION

0.1

0.018

0.2

DICHLORVOS

0.15

0.012

0.06

MALATHION

0.03

0.002

n.d

n.d.=not determined

phosphorus poesticides (Molina et al., 1994), chlorophenoxyacids (Chiron, Papilloud et al., 1994), triazines (Molina et al., 1995), pentachlorophenol (Crescenzi et al., 1995), chloronitrophenols (Hughes et al., 1993) and a wider range of phenolic compounds (Puig et al., 1996; Jáuregui et al., 1997) and carbamates (Honing et al., 1996). The main advantages of ESP/ISP techniques are related to the ionization efficiency due to the fact that ionization of the molecules takes place at atmospheric pressure and therefore, ions are efficiently formed in the liquid phase. Other advantages relay to the fact that no heat is applied to ionize the samples, eliminating thermal assisted degradation, as happens when using TSP interface. This allows the LC-MS analysis of thermolabile analytes such as trichlorfon (Betowski et al., 1988) which is a compound that has been shown to suffer thermal degradation under TSP process caused by the probe tip and gas-phase temperatures higher than 200°C. ESP/ISP consists in applying a voltage to a capillary that ionizes the sample, which emerges from the capillary as a spray. This spray contains microdroplets which are positively or negatively charged, depending on the difference of potential between the capillary and the counter-electrode. In the desolvation chamber, the droplets undergo ion evaporation and ions escape to the gas phase. Such ions are therefore focalized towards the quadrupole of the mass spectrometer. ESP has been applied to the analysis of pesticides by using a reduced mobile-phase flow rates (10–80 µl/min) using syringe LC pumps, or otherwise when using conventional LC pumps a splitting device must be used (Crescenzi et al., 1995 and 1997). Recently, high-flow ESP also called Ionspray (ISP) has been developed and it is commercially available. ISP can handle flow rates up to 300 µl/min by applying a gas flow, normally nitrogen, which aids the formation of the spray on one hand and on the other, solvent evaporation is facilitated by breaking the analytesolvent clusters at the desolvation chamber. With ISP, ions emerge from the capillary due to the simultaneous action of the nitrogen and the capillary voltage of 2–4kV. In ISP techniques, as the ions are transported through the desolvation chamber, ion evaporation takes place as a result of an increased Columbian repulsion forces which are superior to the superficial tension of the droplets and ions escape to the gas phase. These ions have very little internal energy and therefore, molecular ion spectra are obtained. To enhance fragmentation, an extraction potential of 40–100 V is applied at the extraction cone. This potential accelerates the ions and as a result, the total ion current increases and fragmentation is induced via collision induced dissociation (CID). However it should be noticed that increasing the cone voltage also leads to a decrease on sensitivity. Therefore careful optimization of these parameters is required and generally a compromise between both factors (structural information and sensitivity) has to be achieved. When working in positive ionization mode (PI) and 20 V of cone voltage, the (M+Na)+ ion is obtained as base peak. The Na+ ions are due to the sodium ions present as impurity in the methanol solution and it means that more than 90 % of the observed ions are due to ions present in solution. High flow pneumatically assisted electrospray (ESP) under PI permitted to achieve

LOD’s at the picogram levels for selected pesticides. Sensitivity problems for the parathion group (parathion-methyl, parathion-ethyl, fenitrothion and fenitrooxon) were noticed when using ISP or conventional ESP (Molina et al., 1994). The ionization of these compounds under ESP conditions offers problems and generally it is difficult to achieve low ng/L LOD’s in water samples. The repeatability and the long-term reproducibility (n=9) for the organophosphorus pesticides varied from 12–17% to 22–30%, respectively when injecting 1 ng of each compound. Such values are acceptable since usually repeatability in LC/TSP/MS is performed by injecting higher amounts, e.g., 0.2 µg. A remarkable fact is that typical diagnostic ions of organophosphorus pesticides are formed in LC-ISP-MS, similar to electron impact ionization. This corresponds to diagnostic ions at m/z 109, 110, 125 and 141 or to adducts of these diagnostic ions with Na+, such as 133 and 164. This is a very important feature of ISP since it is a technique that can be used for identification of unknown pesticides, contrary to most of the TSP that usually gives very poor structural information and consequently it is used for confirmation purposes of target analytes. Moreover, when working at 40 V cone voltage more structural information is obtained as compared to 20V. Consequently higher voltage will be recommended when identification of unknown pesticides in environmental samples is required. The use of ISP in negative ion (NI) mode has been scarce due to the poor negative ion stability, and the problems of electric (corona) discharge, presumably caused by electrons emanating from the sharp edges of the ESP capillary needle held at a few thousand volts negative relative to a counter electrode. A breakdown to discharge at the tip of the capillary needle occurs at much lower field strength in the case of negative polarities than for positive polarities. Once the corona discharge occurs, the extraction efficiency of the ions from the solution to the gas-phase decreases dramatically. This is because the plasma itself is a good electric conductor and the high electrical field for ion separation at the tip of the capillary disappears with the occurrence of the discharge. For aqueous solutions, it becomes very difficult to keep stable electrospray ionization (ESI) in the case of negative polarities due to the higher voltage needed to electrospray the liquid. The signal instability of ESI can be reduced by adding chloroacetonitrile to the LC eluent which acts as a electron scavenger. By adding these, there is a suppression of the electrical (corona) discharge phenomena leading to a stable ESI with finer charged liquid droplets. Nevertheless, the improvement in ion stability are obtained at the expense of sensitivity (one order of magnitude less) due to the (M+Cl)− adduct ion formation and to the higher cluster ions intensity. Chlorine attachment occurred in a similar way as in TSP-MS for the phenoxy acid with a relative abundance of 8 % in the best case. Since the major analytical requirements of environmental analysis is to achieve a low detection limit, chloroacetonitrile was not used for further analysis. Acid pH is normally required for the LC separation of phenols and post column addition of a 0.1 M solution of triethylamine (TEA) was necessary. Other authors reported the use of ion pair chromatography which allows the analytes to be separated as a preformed ions (Crescenzi et al., 1995) although this option is not so attractive because of the more restricted chromatographic requirements. By raising the percentage of methanol it was possible to detect phenol, 4methylphenol, 2,4-dimetylphenol and 2-amino-4-chlorophenol, which at high percentages of

water could not be monitored because of their low pKa and their hydrophilic character. These analytes cannot be determined by TSP or APCI. Specially the detection of phenol at low µg/1 levels is still an unsolved problem, as shown by the results of an intercalibration exercise organized by Aquacheck, where only 1–2 laboratories out of 16–19 participants gave correct results for phenol. However a problem arises from the need to use

Figure 7.10. Reconstructed SIM chromatographic profile obtained using ISP interface and Hypercarb analytical column (i.d.: 2mm) which corresponds to a standard at 0.1 mg/l of (1) phenol, (2) catechol, (3) 4-methylphenol, (4) 2, 4-dimethylphenol, (5) 4-chlorophenol, (6) 4nitrophenol and (7) 2, 4-dichlorophenol. Mobile phase: 100 % methanol. Flow rate: 0.2 ml/min (post column additon of 0.1 ml/min of 10 g/l triethylamine). 100% of methanol in the mobile phase because in these conditions no retention on typical bonded silicas such as C8 or C18 occurs. Porous graphitic carbon (PGC) analytical columns are an excellent alternative because they allow to effectively separate polar phenolic compounds, using 100% of methanol as a mobile phase (Figure 7.10). Even though the restricted mobile phase conditions did not allow to monitor the entire range of analytes, and excessive retention occurs for some analytes such as pentachlorophenol, in our knowledge it is the only reported way to monitor phenol in LC-MS experiments. Moreover, since ion evaporation is favored by low surface tension mobile phases such as methanol, the use of PGC columns leads to significant increase in sensitivity for the rest of target compounds. Hence, their use will be preferred when analyzing polar micropollutants with ISP interface. On-line LSE-LC-ISP-MS coupling was developed for the determination of acidic herbicides (Chiron et al., 1994) and phenolic compounds (Puig et al., 1997) in water samples. The best results were obtained with narrow bore LC columns (3 mm i.d.) using an eluent flow rate of 0.25 ml/min and the post-column addition of the buffer at a flow rate of 0.1 ml/min. In this way the final LC carrier stream does not exceed the critical values of 0.4 ml/min which will cause a relevant decrease in sensitivity in LC/ISP-MS. The use of 2.1 mm i.d. narrow bore LC columns

appeared more suitable for flow rates of 0.3 ml/min. Unfortunately, extra peak band broadening was observed when the analytical column was coupled on-line with a 2 mm i.d OSP-2 precolumns, so this option was discarded. Under full scan conditions, LOD’s for acidic herbicides ranged from to 1–3 µg/1 which combined with the abundant structural information makes the online LSE-LC/ISP-MS a powerful tool as an early warning system for the screening of polar pollutants in river water. Data for phenolic compounds was slightly worse but values under 0.1 µg/1 were found for all of them under SIM conditions. This is specially remarkable because the determination of priority phenols (specially phenol) at these levels is still not solved, and because is the only way to detect the presence of phenol, 4-methylphenol, 2,4-dimetylphenol by LC-MS. Relative standard devistion (RSD) values are in the range of 20 % (n=6 at spiking level 0.2 µg/1) and are comparable to those obtained under on-line LSE-LC/TSP-MS although sensitivity, already cited above, and selectivity are considerable improved by the use of LC/ISP-MS as compared to LC/TSP-MS. 7.1.3.3.3. Liquid-chromatography and mass spectrometry with atmospheric pressure chemical ionization (LC-APCI-MS) APCI technique differs from ESP and ISP by the fact that a spray is generated as a result of applying nitrogen gas and heat at the interface. The spray, which contains the mobile phase and the analytes, is afterwards ionized at the nebulizing chamber after applying a corona discharge of 2–4 kV. Contrary to TSP where high percentages of water increased sensitivity, in APCI no significative differences were observed when working at different ratios of water and organic modifier and no buffer addition is required. On the other hand, no significant increase in sensitivity was found at temperatures in the range from 350–550°C when analyzing pesticides and phenolic compounds. From the practical point of view, there are two main parameters to be optimized in APCI: the corona discharge voltage and the cone extraction voltage. For the corona discharge, a voltage between 2.5 kV and 3 kV is usually chosen, as at lower discharge voltages, weak ionization is achieved and above 2.5–3 kV the ionization efficiency decreases dramatically. Similar than in ISP interface by raising the cone voltage structural information can be obtained via collision induced dissociation (CID), at the expense of sensitivity. This can be seen in Figure 7.11 where mass spectra of 2,4-dinitrophenol and pentachlorophenol obtained using APCI interface at 30 V and 60 V are shown. LC-APCI-PI interface has been recently applied to monitor organic pollutants in drinking and ground water matrices. The main advantage of this technique is that it is totally compatible with conventional HPLC since flow rates of 1–2 ml/min can be employed and conventional columns can be used. Moreover, most analytes can be ionized because ionization of the sample is facilitated by the fact that it takes place in the gas phase. The former works include those of Kawasaki et al. (1992) who obtained structural information under APCI but with poor limits of detection, varying between 2–50 ng under selected ion monitoring (SIM).

Even though information concerning the use of APCI interface for pesticide monitoring is scarce, it is clear that structural information is gathered at expenses of sensitivity, and that optimum analytical conditions must be selected in order to gain both in structural and quantitative results. In this sense, the technique has recently been applied to the identification of unknowns, which include basically degradation products of some pesticides (temephos and fenthion). At 40 V of extraction voltage, oxo analogues, sulfoxides and the isomeric forms of the above mentioned pesticides

Figure 7.11. Mass spectra of (A) pentachlorophenol and (B) 2,4-dinitrophenol obtained using APCI interface at 30V and 60 V cone voltages. Corona discharge voltage: 2.5kV. Concentration 1 µg/ml. Carrier: methanol/water 1:1 (1% acetic acid). Flow rate: 1 ml/min. were successfully identified. This means that in the near future, this technique can be implemented in routine work for the analysis of real water samples, since it can potentially detect both parental and transformation products of pesticides at levels of ng/l. However, more research is needed in the field of characterization of oxo analogues and other metabolites before optimal analytical conditions can be defined. In NI and 20 V of extraction voltage, (M – H)− ion was the base peak and no structural information was obtained except for high chlorinated phenols and nitrophenols, where (M – HC1)− and (M – NO – H)− ions were observed, respectively. Contrarily to that, pesticides exhibited the fragment ion of the specific group as the base peak. Abundant fragmentation via CID was obtained for phenolic compounds and pesticides when increasing the cone voltage to 60 V, giving in most cases fragmentation patterns similar to those obtained with MS-MS. For example, in the case of 2,4-dinitrophenol (Figure 7.11), at cone voltage of 40 V (data not shown) the base peak was still (M – H)− ion (m/z 183), but abundances of (M – NO – H)− ion (m/z 153), (M – NO2 – H)− ion (m/z 137) and (M – NO2 – CO)− ion (m/z

109) changed to 30 %, 70 % and 32 %, respectively, resulting in a 50 % loss of sensitivity. However, some pesticides showed no differences on the formation of fragment ions under the two different cone voltages (20 and 40 V). This is probably due to the fact that most of the organophosphorus pesticides studied offered quite high fragmentation already at 20 V cone voltage. Pesticides of the so-called parathion group underwent strong fragmentation at low extraction voltages, rendering fragment ions at low m/z as base peaks. Response was linear for all compounds in the concentration range investigated (0.5 to 100 ng) and the repeatability values varied from 12 % to 20%, when lOOng of each compound were injected. Jáuregui et al. (1997) report repeatability values of 7 % and reproducibilities varying from 7 to 14 % for chlorophenols under LC-APCI-MS-NI. However, the main operational problem of this interface and in general of all API interfaces arises from the frequent necessity to remove the sample cone and skimmer assembly for cleaning, specially when relatively dirty water samples are analyzed (Cresenzi et al., 1995). In such cases, the cleaning step should be done every 15–20 injections, and system response should be corrected afterwards. This represents a major drawback of these new API interfaces when applied to environmental analysis. Since the system offers high sensitivity, it should be calibrated very accurately, and therefore maximum cleaning is essential. Similar as with TSP, sensitivity strongly depends on the number of electron-attractive substituents capable to stabilize the negative charge in the aromatic ring. Hence, regarding phenolic compounds high chlorinated phenols and nitrophenols gave the best results. Also in APCI worse values for phenols substituted in ortho position than for the other isomers were noticed, similar as in TSP. For example, IDLs for 2-chlorophenol and 4-chlorophenol in SIM were 0.085 ng and 0.040 ng, respectively. The difference was still more important for 2-nitroand 4-nitrophenol with instrument limits of detection (IDLs) of 0.045 ng and 0.002 ng, respectively. This can be explained by the formation of a 5 or 6 units ring via hydrogen bonding between the hydroxy group and the nitro group in 2-nitrophenol, which hinders the deprotonation of the analyte in gas phase. This effect will be favored in molecules with electronegative substituents in ortho, having the ability to obtain electronic density from the aromatic ring either by inductive or electron resonance effects. When there are more substituents on the aromatic ring the electron density will be distributed among all electron-attractive groups, thus preventing the formation of the above mentioned rings. On-line coupling of LSE with APCI-MS has been successfully performed for the determination of pesticides (Lacorte et al., 1996) and phenolic compounds (Puig et al., 1997) using C18 and Lichrolut sorbent, respectively. A sample volume of 50–100 ml was used in order to avoid percolation of low breakthrough volume analytes. In the case of phenolic compounds recoveries ranging from 70 % to 106 % were found for all target phenols. However, coefficients of variation (CV) were higher than those currently obtained using on-line LSE-LC-UV. It was attributed to the frequent necessity (each 2–3 days) to remove the sample cone and skimmer assembly for cleaning. However, initial response can be usually recovered if a careful cleaning protocol is applied. In general, those CV values meet the Quality Acceptance Criteria of the US EPA methods for phenols reported in the method 604 which range from ±14.1 (phenol) to ±36 (2,4dinitrophenol) (EPA Method 604).

Figure 7.12 shows a typical chromatographic profile of 50ml river water sample spiked with phenolic compounds at 10 µg/l. An interesting feature of the present system is that it can be operated under full scan conditions for “alarm” of organic contaminants in water samples. This can be seen in Table 7.9 where LOD’s of selected phenols and pesticides are shown in full scan and SIM mode. The good data obtained

Figure 7.12. LC-APCI-MS chromatogram obtained after on-line LSE of 50ml of water spiked at 5 mg/l level using Lichrolut EN sorbent in full scan mode. Peak identification (1) catechol, (2) 4nitrophenol, (3) 2,4-dinitrophenol, (4) 2-dinitrophenol, (5) 4,6-dinitro-2-methylphenol, (6) 2,6dinitro-4-methylphenol, (7) 2,4-dichlorophenol, (8) 2,3,4-trichlorophenol, (9) 2,4,6trichlorophenol, (10) 2,4,5-trichlorophenol, (11) 2,3,5-trichlorophenol, (12) pentachlorophenol. Cone and corona voltages set at 30V and 2.5 kV, respectively. in full scan mode which combined with the abundant structural information provided by APCI interface allowed the screening of unkown samples at concentration level 0.7 to 6 µg/l in the case of phenolic compounds and below 0.1 µg/l in the case of pesticides. On the other hand values ranging from 0.05 to 65 ng/l were obtained when working in SIM mode. In summary future trends will lead to a more extensive use of API interfaces due to their high sensitivity and the more structural information. However, the main operational problem of ISP and in general of all API interfaces arises from the often cleaning requirements of the sample cone and skimmer assembly and in general, system response had to be corrected after every cleaning step, which leads to reproducibility values which often exceeds 25 %. However, it should be noticed that this is a common problem in most of the LC-MS interfaces currently available.

7.1.4. BIOLOGICAL TECHNIQUES

The time and expenses involved in the detection of environmental pollutants (e.g. sample acquisition, sample preparation or laboratory analysis) have placed limitations on the number of samples that can be analyzed. For this reason, during the last years Page 348 Table 7.9. Detection limits for selected phenols and pesticides in river water using on line LSELC-(APCI/ISP)-MS in negative and positive ion mode. Volume of water preconcentrated equal to 100ml. Full scan (µg/1)

SIM (ng/l)

NI mode 2-NITROPHENOL

0.8

1

4-NITROPHENOL

0.3

0.2

2,4-DINITROPHENOL

0.7

0.8

4-CHLOROPHENOL

13

60

1

5

2,4,6-TRICHLOROPHENOL

0.5

0.5

PENTACHLOROPHENOL

0.1

<0.1

PHENOL(*)

—

—

7

49

2,4-DIMETHYLPHENOL(*)

12

54

2-AMINO-4-CHLOROPHENOL(*)

—

120

MEVINPHOS-C18

0.5

2

MEVINPHOS-TRANS

0.4

2

DICHLORVOS

0.8

0.6

AZINPHOS-METHYL

0.4

12

PARATHION-METHYL

0.6

9

MALATHION

0.4

3

FENITROTHION

0.8

9

AZINPHOS-ETHYL

0.3

14

PARATHION-ETHYL

0.5

15

FENTHION

0.3

10

CLORFENVINFOS

0.2

1

DIAZINON

0.2

2

2,4-DICHLOROPHENOL

4-METHYLPHENOL(*)

PI mode

(*) data obtained using ISP interface the interest in developing fast, portable and cost effective field analytical methods has grown rapidly. The EPA’s Office of Research and Development is leading efforts to develop this promise and to extend the range of analytes which can be monitored with biological techniques (Rogers et al., 1995). Standard operating protocols are written in formats such as those found in EPA solid waste (SW-846) protocols (EPA Method 4010A). Biosensors and immunoassays (Enzyme Linked Immunosorbent Assay, ELISA) are really promising in this area. They take advantage of the high specificity of biological recognition to selectively monitor target analytes in complex samples. Even though there are some immunoassays commercially available, future trends are focused towards biosensor technology due to their faster response (several seconds against 45 minutes to 1 hour in chromatography) and easy automation. However, several problems such as biosensor stability or their low sensitivity to environmental levels remain unsolved. Technical requirements are higher for biosensor configurations because a physical transducer is required. 7.1.4.1. Immunoassay

Immunoassays were initially applied to pesticide analysis but nowadays some work has been directed toward industrial chemicals such as phenols. Enzyme Linked Immunosorbent Assay (ELISA) has become popular in the recent years for screening purposes since there is a wide variety of commercially available immunoassays. However, immunoassay can be also used as a selective detection unit for LC. There is a problem of incompatibility of antibodies and organic solvents such as methanol or acetonitrile, which are currently used in LC separations. Microbore columns are recommended, followed by elimination of organic solvent prior to the immunoassay reaction. This approach has been applied to the analysis of nitrophenols using the immunoassay method (Kramer et al., 1994). LC immunoassay was 8- to 10-fold more sensible than UV detection, and performance was not affected by matrix interferences when analysing spiked soil samples although other techniques such as mass spectrometry should be applied for peak confirmation. 7.1.4.2. Biosensors

Similar to immunoassay techniques, biosensors take advantage of the intrinsic specificity of enzyme-substrate reactions to selectively monitor pollutants in environmental samples. Any biosensing device can be divided in three parts: the biological recognition unit, the signal transducer and the detection system which depends on the transducer chosen. Most of the works published in the literature refer to amperometric biosensors because they have advantages such as higher sensitivity or selectivity. Hence, an electrical transducer and a potentiostat for detection are used. Phenol oxidases (Tyrosinases, Laccases) or peroxidases are the most current enzymes used for analyzing phenols (Varga et al., 1995). The mechanism of amperometric biosensors can be illustrated with a general reaction sequence which lead to an amplification of the signal (Figure 7.13). Most of the papers are referred to Tyrosinase which shows a response mainly for catechol,

phenol, 4-chlorophenol and 4-methylphenol (Wang et al., 1994; Lutz et al., 1995). Other enzymes such as horseradish peroxidases can be used to analyze a broad range of phenols but their use is not so extended (Wang et al., 1993). Pesticides are inhibitors of the enzyme acethylcholinesterase which is responsible for neural transmission. Therefore, the enzyme activity is inversely correlated to the concentration of pesticide. The method is well described by Mionetto et al. (1994). Various different electrochemical transducers i.e., solid graphite (Ortega et al., 1994) or composite electrodes such carbon paste (Lutz et al., 1995; Ortega et al., 1994), epoxi-grafite (Wang et al., 1990) or teflon/graphite (Wang et al., 1993) were used with the enzyme tyrosinase. Solid graphite electrodes have the advantage of the

Figure 7.13. Performance of enzyme modified electrodes for the determination of phenolic compounds. Ered and Eox are the reduced and oxidized forms of the enzyme, respectively. Ph, Ph* and Q are the phenolic molecule, its phenoxyradical and its quinone, respectively. higher sensitivity as compared to composite electrodes but they show some operational drawbacks such as storage conditions or response instability. Using tyrosinase enzyme detection limit 0.25 µg/l were obtained for phenol and catechol, respectively (Ortega et al., 1994). In the last years efforts have focused on the development of composite electrodes which can be easily customised. Also they have the advantage of lower background currents than solid graphite electrodes and the surface can be renewed by polishing. Mixtures of graphite and oil, currently named carbon paste (CP), are still the most popular composite electrode. The main problem of CP electrodes are their low signal stability when exploited for a long time and the low compatibility with aqueous solvents such as methanol or acetonitrile. However, this can be overcome by bulk modifying the CP electrodes with different types of activators and/or stabilisers. The use of different chemical additives has been reported (Lutz et al., 1995). On the other hand, Tween 20 non ionic detergent can be added to increase enzyme activity and stability into the carbon paste (Ortega et al., 1994). Previously, bovine serum albumin (BSA), a catalytic inactive protein, was added in order to protect Tyrosinase from the inactivating groups of the support. Alternatively the use of epoxy/graphite and specially teflon/graphite composite electrodes improve biosensor stability.

Biosensors can be used as a selective detection units in LC and can be combined with automated LSE devices. A solid graphite configuration was chosen for the first application because a more stable signal was obtained than with composite electrodes although the problem of compatibility with the aqueous solvents currently used in LC still remains unsolved. On the other hand the combination with automated LSE appears to be promising since it facilitates the fast screening of high number of samples. This has been reported in a recent paper using an amperometric tyrosinase based biosensor (Burestedt et al., 1995). Since LSE normally uses hydrophobic supports such as styrene divynylbenzene polymers, a high strength solvent such as methanol and acetonitrile is generally required. An interfacing design capable of separating phenol fraction from the organic solvent was therefore developed. LOD’s at the 1 µg/1 range were obtained. The most important feature was that when screening seven water samples, three of them spiked with phenol, catechol, 4-methylphenol and 4-chlorophenol, at various concentration levels (1 µg/l, 10 µg/l and 25 µg/l) no false negatives were obtained, thus showing the high discriminatory power of biosensor and its suitability for sample screening prior to chromatographic analysis. 7.1.5. QUALITY ASSURANCE 7.1.5.1. Interlaboratory studies

As new methodologies appear, validation becomes a key issue before method approval and implementation can be done. The analytical method should provide statistical documentation of its capacity rendering accurate quantitative parameters. Interlaboratory validation studies are used to evaluate the performance of an analytical method by comparing the results of each laboratory with those of the rest of parti-cipants to reach a true value, with the aim to provide unanimity and reliability of the results provided by different laboratories. Various papers have published results on the validation of on-line LSE-LC-DAD for pesticides (Lacorte and Barceló, 1994; Lacorte and Barceló, 1995) and phenolic compounds (Puig and Barceló 1995). As an example, Table 7.10 shows the results of the interlaboratory studies after analyzing spiked ground water samples by on-line LSE-LC-DAD and on-line LSE-LC-APCI-MS, and the % of error in comparison to the certified value from Aquacheck. Results were evaluated according to the AOAC (Mesley et al., 1991) who indicate a 22 % as maximum permissible error between laboratories. Levels varying from 0.02 to 0.2 µg/1 were encountered for each individual pesticide. The presence of isomeric forms, matrix interferences, coelution of compounds and poor chromophore were the main causes of error. In waste water samples, levels varied from 0.15 to 0.8 µg/l, being the percentage of error from 4 to 65 % (Table 7.10). The method was found not suitable to detect organophosphorus pesticides at such low levels, due to matrix interferences and to an unresolved complex mixture (UCM) peak of an industrial source that appeared at the beginning of the chromatogram. The results reported in the interlaboratory exercise suggested that on-line LSE coupled to LCDAD is a robust method for the analysis of organophosphorus pesticides, and it is equivalent to conventional GC techniques in many aspects, as shown by flagged and double flagged results given by many laboratories who used the well-known and widely applied GC based techniques. From the results obtained in the interlaboratory studies and from data published in the bibliography, it is evident that one of the major problems in the on-line analysis of pesticides at low levels in environmental waters is the presence of interfering substances. Such interferences,

namely humic and fulvic material, appear as an early eluting UCM peak in the chromatogram, and are specially relevant in the case of analyzing surface and estuarine river waters. The water type is a relevant parameter in the quantitation of pesticides at these low levels, and differences in calibration and quantitation have been found depending on the water type. The second problem that arises when analyzing pesticides at these low levels, is derived from the coelution of two compounds in a mixture. Since the LC runs usually contain a mixture of 30 Table 7.10. Mean concentration (ng/l) and % of meanc difference (n=4) in relation to reference values of organophosphorus pesticides from 3 intercalibiration studies. Results are obtained from spiking ground water with the certified material from Aquacheck. Compound

Ground water

Waste water

LC-DAD

LC-DAD

ng/L

% Error

Ground water LC-APCI-MS

ng/L % Error

ng/L

% Error

Phenol

1649

–15

n.r.

n.r.

3413

35

2,4,6,trichlorophenol

4372

8

n.r.

n.r.

2381

–16

pentachlorophenol

1120

12

n.r.

n.r.

2449

14

Azinphos-methyl

97.8

6

594

4

62.9

2

Dichlorvos

54.9

69

n.r.

n.r.

48.9

2

Fenitrothion

47.3

14

638

16

24.7

10

Malathion

94.2

24

391

21

60.2

10

Mevinphos-trans

74.3

4

n.r.

n.r.

51.1

12

Chlorfenvinfos

31.4

22

717

6

53.9

3

Diazinon

n.r.

n.r.

n.r.

n.r.

n.r.

n.r.

Azinphos-ethyl

100

12

446

55

48.2

0.5

Fenthion

n.r.

n.r.

n.r.

n.r.

38.8

30

Parathion-ethyl

78.0

6

342

40

9.09

63.5

Parathion-methyl

69.7

24

437

19

50.9

21.5

n.r.=not reported or unnable to quantify with the certified material from Aquacheck compounds, it is difficult to achieve baseline separation between all analyte peaks and matrix interferences which appear at this low level of concentration. The determination of co-eluted pesticides is even more problematic in the case of analysis environmental waters at low concentrations (µg/l) when on-line solid-phase preconcentration techniques are used. Then, interferents at very low concentrations and mobile phase effects become more significant than for direct injection analysis of more concentrated samples (µg/l level). One way to solve coelution problems is by using a different LC column with different polarity and optimize all the parameters involved in the separation. This will probably improve a certain separation of analytes, but can affect other mixtures and new coelution of analytes may appear.

Multivariate self modelling curve resolution (Tauler et al., 1993; Tauler et al., 1996) has been proposed to improve the resolution of strongly coeluting compounds in liquid chromatographydiode array detection. The development of such a software system that allows quantitation of peaks at these trace-level is particularly relevant since this problem is not solved in the automated routine measurement of pesticides in water samples by automated LSE methods. The incorporation of such software systems into the diode array detector (DAD) software will be a consideration for the future and would be of help for the laboratories involved in the routine measurement of pesticides at trace level using automated systems. Other studies refer to the use of the automated on-line LSE followed by LC-MS using various interfaces, by participating in the Aquacheck inter-laboratory exercise organized by the Water Research Center, at Medmenham, UK. This is specially useful because until now API interfaces are not so commonly used in environmental analysis as TSP, PB and other MS techniques. In Table 7.10, the results obtained in one of the inter-laboratory exercises using on-line LC-APCIMS are reported. The percentage of error as regards to the target values reported by Aquacheck is also indicated. It can be pointed out that in PI mode most of the compounds gave acceptable values (with standard deviation below 22%) with the exception of parathion-ethyl and fenthion. This can be attributed to the poor LOD’s of these two compounds as compared to the other analytes being the levels determined close to the LOQs. A chromatogram which corresponds to the analysis of the certified samples is shown in Figure 7.14. Under NI mode, parathion-ethyl gave better results as compared to PI mode, but fenthion could not be determined which can be attributed to spiking values close to the LOD. Fenthion exhibited additional problems due to its poor stability in water during the preconcentration step and degradation. Some of the other compounds (mevinphos trans, dichlorvos and chlorfenvinphos) could not be

Figure 7.14. On-line LSE using the OSP-2 followed by LC-APCI-MS under time-scheduled PI mode of operation of 100ml of ground water sample spiked with a certified solution from Aquacheck containing 11 organophosphorus pesticides. Peak identification number: (1) mevinphos-cis, (2) mevinphos-trans, (3) dichlorvos, (4) azinphos-methyl, (5) parathionmethyl, (6) malathion, (7) fenitrothion, (8) azinphos-ethyl, (9) parathion-ethyl, (10) fenthion, (11) chlorfenvinphos and (12) diazinon.

determined by NI which was mainly attributed to a matrix effect that enabled quantification at ng/L level. For the determination of mevinphos cis and dichlorvos under NI it was needed to use the m/z 125 ion which makes difficult its quantitation in real samples caused by interferences with the matrix background. In the case the case of phenolic compounds, acceptable values for trichlorophenol and pentachlorophenol were obtained with all the MS interfaces. 7.1.5.2. Validation of biological techniques

The development of new biological techniques for the determination of pesticide and phenolic compounds, including both biosensors and immunosensors, has lead to the need of qualifying these techniques in terms of precision and accuracy. A preliminary study carried out by the EPA was performed in order to compare the response of immunoassay and EPA GC Method 604 for the determination of pentachlorophenol in surface, drinking and groundwater (EPA/600/x907146, 1990. Within a linearity between 30 to 400 ppb, the two methods correlated strongly, and the immunoassay generated only 9 % of false positives and no false negatives. In view of these promising results, a large quantity of immunoassays have been developed for environmental applications. A report on Immunochemical Methods enumerate the different immunoassays for environmental analysis, the applications and the implementation of these new techniques (Van Emon et al., 1992). Even though biological detection techniques have arose for their selectivity which permits the detection of a specific family of compounds, such as atrazines, organophosphorus, etc., or even are directed to determine one single compound (chlorpyrifos), still some uncertainty appears, due to the presence of a variety of external paramenters, sometimes related to the water matrix, which may influence the final results. Gascon et al. (1995) indicate the important influence of estuarine water matrix in the selectivity of ELISA test. The presence of structurally similar compounds, including halogens and dissolved organic carbon, that can weakly interact with the antibody and give a false positive, as has been reported for atrazine in estuarine water samples (Gascon et al., EST, 1995). The presence of humic and fulvic substances in the water matrix, which account for the majority of dissolved organic carbon in water (Thurman et al., 1985) is still a topic of controversy since it can represent a problem for the detection of pesticides with immunosensors. Thurman et al. (1990) indicate that the presence of up to 100 mg/l of humic and fulvic substances did not produce any cross reactivity with a polyclonal antibody and did not affect the immunoassay response. However, the analysis of tropical surface waters, containing humic and fulvic material at concentrations as high as 40 mg/l produced a positive response with waters void of atrazine. This may be due to the fact that the humic material, which presents carboxylic, phenolic, amino groups, among others, can be recognized by the antibody, thus responding positively to the sensor. Biological based detection techniques are also affected by water pH. The working pH should be such that it does not decompose the analyte of interest and at the same time gives maximum response and stability of the sensor. In the case of immunosensors, a further parameters which may interfere with the determination is due to the cross reactivity of other compounds. Oubiña et al. (1996) report that chlorpyrifos-methyl, diazinon and pyridafenthion gave cross reactivity between 3 and 14 % in the determination of chlorpyrifos-ethyl with Magnetic Particle-Based ELISA. In a word, the limitations of the biological detection techniques arise due to the complexity of the environmental water samples that may produce false positives due to the presence of interferents or to the presence of similar chemical structures. The use of this detection techniques is, therefore, not straightforward, and for such reason, it is important to validate the method before it

is routinely implemented. Validation includes the comparison between a biological technique and a conventional chromatographic or mass spectrometric technique for the determination of a specific or class-specific group of contaminants. This approach is interesting since lately much effort is being done to use biological techniques not only for screening purposes but also to determine the final concentration of a specific pesticide (Ferrer et al, 1997) Enzyme linked immunosorbent assay (ELISA) as a field measurement technique has been particularly applied to atrazine in various water matrices (Gruessner et al., 1995; Brady et al., 1995), specially in the corn belt area, where this pesticide is commonly used (Thurman et al., 1992). The use of ELISA in combination with chromatographic techniques is not common. Thurman et al. (1990) pioneering this field of study, compared the ELISA assay with GC/MS for the determination triazine herbicides in natural waters. A good correlation between ELISA and conventional GC-MS analysis was found for atrazine, simazine and propazine, which makes the technique useful for screening this family of herbicides at concentrations between 0.2 to 2 µg/L It was concluded, thereafter, that the application of ELISA in environmental monitoring of pesticides could de described as rapid, inexpensive and precise. Figure 7.15 shows an example of the good correlation obtained by ELISA and GC-NPD from the determinations of atrazine in estuarine water samples from the Ebre delta, Tarragona, Spain (Gascon et al., 1995 EST). Two immunoassays directed to the determination of carbaryl and 1-naphtol have also been validated and applied to determine the distribution of these 2 pesticides in groundwater (Marco et al., 1995). Excelent correlations were found between ELISA and LC with postcolumn reaction and fluorescent detection. The day-to-day variation of the carbaryl microtiter-plate immunoassay was of 8 % compared to the 3 % of LC, being both acceptable. A recent work by Oubiña et al. (1996) has been published on the comparison of two methods, Magnetic Particle Base ELISA and on-line solid-phase extraction coupled to LC-DAD, for determining chlorpyrifos ethyl in natural waters. Calibration curves were performed at concentrations varying from 0.22 to 3 µg/1 and the correlation between the two methods appeared to be of 0.991 when HPLC water was used and 0.958 with surface river Ebre water sample. In both cases, the recovery was around 110% when spiking the water samples at a concentration of 0.5 µg/l level. Moreover, the same authors indicate that no differences were found in the response of the ELISA for chlorpyrifos between filtrated and non-filtrated water samples, increasing thus the applicability of such method for in-situ monitoring of this compound in surface waters. To sum up, there are several issues that make immunological detection techniques convenient for screening purposes: little amount of water needed to run the immunochemical tests and to the possibility to process a high number of samples simultaneously, inexpensive compared to chromatographic techniques, easy use, and rapid. Moreover, once the methods have been validated, they can be directly applied

Figure 7.15. Comparison of atrazine concentrations in estuarine water samples from the Ebre delta (Tarragona, Spain) determined with GC-NPD and RaPID ELISA assay. The regression equation is indicated. as a screening technique and the confirmation of positive samples with conventional techniques, basically mass spectrometric techniques, is done in order to elucidate the specific pesticide present in the water sample. Enzyme sensors (Rouillon et al., 1992; Kindervater et al., 1990; Meulenberg, 1995) have been developed for the detemination of pesticides and phenols (Varga et al., 1993) among other pollutants. For organophosphorus and carbamate pesticides the reaction is based on the inhibition of the acethylcholinesterase (Mionetto et al., 1994). The biosensor technique operating in an aqueous medium (flow injection system) or organic solvent (batch system) was compared to either off-line or on-line solid-phase extraction followed by LC-DAD for the determination of organophosphorus pesticides and carbaryl in certified freeze-dried water samples (Barceló, Lacorte and Marty, 1995). The biosensor, in both modes of operation, permitted to distinguish between water samples containing 4 to 18 µg/l of total pesticides. Moreover, further experiments were performed to asses the effect of oxo metabolites on the biosensor. It has been reported that the biosensor gives a higher response when pesticides are oxidized. This indicates that the enzymatic biosensor is based on the socalled paraoxon equivalent, and that the sample should be oxidized, otherwise there is no appreciable response in the biosensor. In this case, the enzymatic biosensor has the task of providing an early warning system for pesticides in the environment, which provides a way to save time and costs, with the possibility of taking rapid decisions about local environmental problems. Validation of the positive samples should always take place.

7.1.6. CONCLUSIONS

The analysis of pesticides and phenolic compounds in water samples include two main steps: extraction and analysis. Water samples can be extracted by many different ways. Liquid-liquid extraction, which used to be the most popular method, has been replaced by liquid solid extraction (or solid phase extraction) that has the advantage that it is less laborious, quicker, diminishes solvent consumption, produce more reproducible results and represent a way to stabilize pesticides. Moreover, there is a large variety of packing materials, that range from the so-called C18 sorbent to the recently appeared polymeric materials such as LiChrolut ENV and finally the outcome of immunosorbents which provide an extremely selective way to trap a specific family of compounds. As a result, analytes of high polarity can be trapped by using a polymeric sorbent, thus increasing the breakthrough volume, or it is also possible to combine two sorbents, in a way that there is a fractionation of the different compounds depending on their polarity. Liquid solid extraction can be performed both off-line and on-line. Off line methods include the use of extraction disks or cartridges and have the advantage that a final extract is obtained and that can be analyzed by different techniques. However, depending on the chromatographic method chosen, loss of sensitivity can be observed due to the fact that only an aliquot is injected. In contrast, on line methods have the advantage that the total amount of analyte preconcentrated is injected, and therefore, it lowers the detection limits. As a result of the implementations of new regulation on water monitoring, there is a growing tendency to use automated methods for the surveillance of organic pollutants in environmental water samples. Both off-line and on-line methods can be now-a-days automated by sophisticated equipment such as the Prospekt, the OSP-2 or the ASPEC. Since manipulation of the water sample is minimized, these techniques render extremely precise and accurate results. Most commonly, pesticides and phenols are analyzed by gas-chromatography, which is the official method by the US-EPA and it is well known and settled. At the same time, the great availability of different detection devises make GC a common technique. Among other advantages, the high separation efficiency and speed of analysis favors multidimensional analysis and routine monitoring. However, GC cannot handle polar compounds. This fact represent a limitation of the technique for environmental water samples since the new legislation claims the need to monitor the pesticides degradation products, which are often more toxic than the parental compounds. In the last years, new technologies based on HPLC systems have been developed to determine organic pollutants in the environment. The large variety of detectors available, such as DAD, fluorescence, electrochemical or mass spectrometry cover the majority of priority pesticides and phenolic compounds that are included in EU monitoring programs. One of the main advantages of LC methods is that there is no need to derivatize the sample to detect the polar, non-volatile or thermally labile compounds. Moreover, provided an efficient preconcentration technique is applied, it is possible to quantitate the analytes at ng/l level, similar to what is obtained with GC. As a consequence, it is becoming a highly robust technique and the preferred option by many laboratories.

The analysis of environmental water samples need confirmation before a final report can be made. In this sense, GC analysis have to be performed with two columns of different polarity or either use mass spectrometric detection. GC-MS is easily coupled and it can be performed with electron impact or negative chemical ionization. The former technique produce abundant fragmentation and spectra can be compared with that of the library. Interfacing LC with MS is not so evident and different types of interfaces, such as particle beam, thermospray and the newly appeared atmospheric pressure ionization techniques have been applied for the analysis of organic pollutants. API interfaces have slowly replaced the other ones since they can produce abundant fragmentation by a phenomena of collision induced dissociation by increasing the extraction voltage. In contrast to PB and TSP, API techniques are highly sensitive, reproducible and have a linear range over various orders of magnitude. With regards to qualitative assurance, all the analytical techniques have been validated in order to provide reliability of the results. This is important to meet qualitative control and to allow the comparison of the results provided by different laboratories. The analysis of certified water samples is important in order to know the precision of each method and it is necessary before a technique can be implemented in routine monitoring programs concerning organic pollutants. The analysis of pesticides and phenols from water samples is nor strictly limited to the use of chromatographic techniques. Environmental monitoring generally requires the analysis of a large numbers of samples, and there is a need for low cost, rapid and automated methods of analysis. The use of sensors, either immunosensors and biosensors, is a way to screen organic pollutants in the field in a faster and cheaper way. These methods cannot replace traditional chromatography; however, they can discriminate between polluted and unpolluted water samples and as a consequence, they help in making immediate decisions. Enzyme Linked Immunosorbent Assay (ELISA) is the best known field test and has been applied both in situ and in the laboratory for analyzing several pesticides and also phenol. Quantitative results have been obtained and they correlate perfectly with the chromatographic results. The main problem is to establish the cross reactivities of the analyte of interest with other present in the water matrix or with the water matrix itself. Biosensors have emerged for environmental monitoring, and even though they represent an efficient way to determine if a water sample contains organophosphorus pesticides, still much effort has to be directed to increase sensitivity of this method. ACKNOWLEDGEMENTS

This work was supported by the Environmental Commission and the Environmental and Climate Program (contract No ENV4-CT97–476) and CICYT (AMB97–2083-CE). REFERENCES

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7.2. INORGANIC COMPOUNDS 7.2.1. HEAVY METALS

K.CAMMANN, W.BUSCHER, C.B.BREER, H.G.RIEPE, B.ROSENKRANZ and T.TWIEHAUS In the field of trace metal analysis there are some typical determination methods which have become the most important over the last few years. In this chapter a short introduction to these most established determination methods will be given. Besides the principles, the fields of application for analytical quests will be presented. 7.2.1.1. Atomic Absorption Spectrometry (AAS)

One of the classical methods for the determination of trace metals is atomic absorption Spectrometry (AAS). It is based on light absorption by free atoms. While passing a sample of gaseous atoms light of defined wavelengths interacts with outer electrons of the elements to be determined and excites them to higher energy levels. This energy absorption results in a decrease of the light intensity at this wavelength which constitutes the measurement principle in AAS. The measurement quantity is the absorbance A which is defined as the negative logarithm of the transmission , where is the flux of radiation after and the fluz without absorption. The absorption is according to the Lambert-Beer law directly proportional to the concentration c of absorbing atoms and to the thickness t of the atomic cloud in the optical path:

where ε is the element specific extinction coefficient. This fundamental effect has been known for a long time from the Fraunhofer lines in the spectrum of the sun. Colder atoms in the outer zone of the sun or somewhere else on the track of the observed light beam to earth selectively absorb certain wavelengths emitted i.e. by hot atoms in the centre of the sun. This effect was first utilised for analytical purposes by Walsh who developed the first atomic absorption spectrophotometer (Walsh, 1955). Walsh found that the absorption intensity is correlated with the number of atoms in the absorbing cloud and thus also with the concentration of the respective element in a corresponding sample or sample solution. 7.2.1.1.1. Atomisation

The function of an atomisation unit is the generation of a maximum number of analyte atoms in the electronic ground state from a given sample. The efficiency of the atomisation step strongly influences the analytical performance of an A AS system. The required free atoms for the light absorption process in AAS are generated thermally. There are different techniques of heating the sample to produce atoms: Flame(F)-AAS

In flame AAS there are different kinds of flames, e.g. different combinations of acetylene or propane with oxygen. This technique is the oldest one in AAS and is based on the introduction of sample solution into the flame which is generated from a liquid by a nebulizer producing an aerosol. Depending on the analyte to be determined different temperatures of flames are required. Some elements form thermal stable compounds like Al2O3, TiO2 or ZrO2 and thus require the use of an acetylene/ dinitrogenoxyde flame which delivers temperatures of about 2800°C. Graphite furnace(GF)-AAS Another technique of atomisation is the introduction of gaseous, liquid or solid samples into a graphite furnace which is heated electrothermally very fast to temperatures up to 2500°C. It is possible to heat the furnace according special temperature programs allowing the careful vaporisation of e.g. solvents or the mineralisation of organic matrices before the atomisation phase. To avoid losses of volatile analytes (e.g. Pb, Cd) special modifiers like palladium nitrate are added to the furnace as a thermochemical reagent. Another advantageous effect of these modifiers is the accelerated destruction of the matrix by oxidation. The graphite furnace (GFAAS) technique permits very good limits of detection and is widespread in chemical laboratories for routine analytical applications. Its limits of detection exceed those of the flame AAS by a factor of 103. One great advantage of the GF-AAS is the very small sample volume. Only microlitres need to be injected into the furnace. Hydride generation(HG)-AAS Some elements, especially Sn, Pb, As, Sb, Se, Te show the tendency to form volatile hydrides, e.g. SbH3, by reaction with sodium borohydride in an acid medium. Typically a quartz cell is used as an atomisation unit. The generated hydrides are introduced in the cell and atomized at temperatures of up to 1100°C. A further development is the use of a graphite furnace as atomisation unit. Even extreme traces of these elements can be matrix separated by this technique and excellent limits of detection are reached. Cold vapour(CV)-AAS Similar is the direct introduction of gaseous mercury (Hg0) into the graphite furnace after chemical reduction with sodium borohydride or tin(II)chloride to elementary mercury. Its volatility is sufficiently high to allow the effective purge-out from the sample and the transport to the atomisation unit for which similar to the HG-AAS quartz cells are used. For further increase of the sensitivity of mercury, detection of its tendency to form an amalgam with gold can be utilised and extreme traces of mercury are detectable (low ng/L-level). A comparison of the detection limits for these different techniques is shown in the following table for some example elements. 7.2.1.1.2. Instrumental

A basic atomic absorption spectrometer is shown schematically in Figure 7.16. This type uses a graphite furnace as atomization unit. Hollow cathode lamps (HCL) or electrodeless discharge lamps (EDL) are commonly used as primary light source. These types of light sources generate light only at defined wavelengths. The exact element characteristic emission lines are excited in a special plasma for illumination purposes depending on the element inside the lamps. Usually, there is one special primary light source for each element to be measured with the AAS. The following figure shows the schematic assembly of a HCL in comparison to an EDL. Unfortunately, the light emission of the primary source is not really monochromatic. Thus a monochromator filters the element resonance line out of the spectrum allowing the precise measurement of the current element to be determined. The conversion of the measuring light into electronic signals is performed by photomultiplier tubes which consist of photosensitive material and a special arrangement of amplifier stages. The total measurement of the absorbance and the direct calculation of the results is usually carried out today by personal computers which additionally control the entire AAS device including sample injection, heating measurement and calculation. To achieve correct results from the measurement of the absorbance inside the atomisation unit the calculated values have to be corrected from signal portions that are not generated by analyte absorption but have their origin in unspecific absorption by the background. There are several different methods of such background corrections. The most important methods are the Deuterium, the Smith-Hieftje and the Zeeman background correction (Welz, 1983). The latter is the method with best results of correction compared to the others. All correction methods have in common that the unspecific absorption of the background is precisely determined with a special respective technique and the element signal is corrected by according calculations. The classical AAS is a typical single element method due to the use of hollow cathode lamps. Their size makes it difficult to guide the element specific light through the atomisation unit, especially through the small graphite furnaces. This fact is a great disadvantage compared to other modern analytical methods like e.g. the inductively coupled plasma optical emission spectrometry (ICP-OES) which is known as a simultaneous multielement method (Montaser and Golightly, 1992). Several

Figure 7.16. Principle scheme of an atomic absorption spectrometer.

Figure 7.17. Schematic assembly of an EDL (a) and a HCL (b). groups of researchers tried to develop multielement AAS systems. But the analytical performance of these devices could not reach the single element systems. Today a few multielement-AAS systems have been developed with an analytical performance which equals single element AAS (Harnly, 1986; Cammann et al., 1986; Winter et al., 1991). One of these systems still requires optical equipment of high complexity to separate the element lines from each other and is relatively expensive. The other solution avoids such high resolution polychromators and separates the element channels via modulation of the hollow cathode lamps with different frequencies and demodulation after passing the atomisation unit with lock-in technology. This enables the use of special fibre optics as light guide instead of expensive and dejustable optical systems. Due to the measuring principle the analytical dynamic range is limited up to two decades which often makes the dilution of the sample necessary. This general aspect leads to the conclusion that multielement AAS systems are only meaningful up to a maximum of four simultaneously determined elements. 7.2.1.1.3. Analytical Application of AAS Atomic absorption spectrometry is widespread over the worlds chemical laboratories. It is used for the determination of nearly 70 different metals in medium, trace and extreme trace concentrations in liquids, dissolved solids, solids and gases or vapours. In combination with a suitable sample preparation almost every type of sample can be analysed with AAS.

The greatest analytical application fields of AAS are environmental, medical and forensic analyses. Traces of mercury in air can be measured with the extreme sensitivity of the cold vapour method combined with an amalgam enrichment step at a gold net. In the semiconductor producing industry the extremely low limits of detection offered by the graphite furnace-AAS are urgently needed to control and guarantee the product quality. Also in processes where the dosage of extreme traces of metals i.e. as catalysts (10−9 g/mL) is required the GF-AAS is applied (i.e. polymerisation processes). 7.2.1.2. Inductively coupled plasma optical emission spectrometry (ICP-OES)

When an electron of an atom is located on an upper energy level and descends to a lower one the energy difference between those two levels is emitted as electromagnetic radiation which is characteristic for each single element. This is the basic functional principle of optical emission spectrometry. In a plasma those element species with electrons on upper energy levels are generated. This chapter tries to describe plasmas, the processes of generating certain element species, the relation between atomic number and radiation, and methods to handle that radiation in order to obtain the maximum information. 7.2.1.2.1. The state of “Plasma”

A state of gaseous material is called plasma, when its properties are determined by the existence of charged particles (ions and electrons) (Seshradi, 1973; Pai, 1962). To initially start a plasma free carriers of charge are needed which are introduced into the gas to be excited as electrons (Mierdel, 1974; Laqua, 1983; Boumans, 1987). The permanent supply of energy allows the start of a chaotic process of colliding particles and transferred energy quants that constantly generates new charge carriers. Energy can be fed in form of alternating electromagnetic fields (Seshadri, 1973; Pai, 1962; Mierdel, 1974). By ionizing impacts charged particles are formed again and again to build a dynamic ionization equilibrium (Sharp, 1987). The main processes will be demonstrated on the example “helium plasma”: (a) ionizing impact resp. triple impact recombination:

(b) radiation recombination resp. absorption:

using: e=electron e*=electron with high kinetic energy

He=Helium atom He*=Helium atom in excited state He+=Helium cation, single positive v=frequency of emitted electromagnetic radiation Because of the high temperatures sample compounds brought into a plasma are atomized firstly. Involved in impacts with charged and/or excited plasma particles the analyte atoms are forced into higher energy levels and/or ionized, and emit radiation (Pai, 1962; Laqua, 1983; Boumans, 1987). The occurrence of these processes is mainly influenced by physical parameters, e.g. pressure, temperature, forwarded power, and by element specific potentials of excitation and ionization. 7.2.1.2.2. Relation between radiation and atom number density in a plasma The basis of emission spectrometry is a spontaneous transition from an upper energy level k to a lower level i that leads to an emission of electromagnetic radiation. The emitted radiation corresponds to an exactly defined difference of energy originated by a transition between two exactly defined levels, k and i, and thereby is characteristic for each single element (Boumans, 1987; Sharp, 1987; Slickers, 1992): (1) The frequencies at which this occurs reach from near infrared (NIR) to ultraviolet light (UV), e.g. fluorine 95,48 nm, caesium 894,35nm. Such emissions are called spectral lines; if the lower level is the ground state they are called resonance lines. As the radiation is characteristic for each element the wavelength (resp. the frequency) gives us information about the existence of single elements in a sample! Einstein was the first to speak of a transition probability Aki which gives the probability of a spontaneous transition per second (Boumans, 1987; Slickers, 1992), and thereby is proportional to the intensity of the radiation. The radiation power P is the product out of radiation energy, transition probability, density of atoms nk in an excited state k, and the volume of plasma gases ∆V: (2) But, a measurement of the radiation power P is only valid for a plane observation area ∆F. The spheric symmetry of the radiation and the Boltzmann distribution (which describes line broadening. Because of the Doppler effect, the Stark-, and the Lorentz-broadening (Boumans, 1987)) taken into account, the measureable radiation power B (brightness) gives:

(3)

using: N=number density of all energy levels Z(T)=atomic partition function Ek=energy of upper level k gk=atomic state degeneracy of level k kB=Boltzmann constant The spectral depth L is the quotient of ∆V and ∆F. This equation gives a linear relation between the brightness of the radiation and the number of emitting atoms in a plasma, and thereby the concentration of an analyte. Unfortunately, the analyte concentration cannot be calculated out of the measured brightness, because on deriving equation (3) we silently assumed a complete thermodynamic equilibrium (CTE) in the entire plasma. Indeed, plasmas are dominated by various local thermodynamic equilibria (LTE) which are difficult to quantify. But after calibrating an ICP-OES system we can say by approximation: The analyte concentration in a sample introduced into a plasma is directly proportional to the intensity of its element characteristic electromagnetic radiation! 7.2.1.2.3. The inductively coupled plasma Among all types of plasma sources ICP is the one with the widest acceptance in analytical laboratories (Montaser, 1992). Energy is supplied in form of an alternating electromagnetic field at radio frequency (RF), usually 27.12 or 40.8MHz. The ICP consists of a RF-generator feeding a water-cooled induction coil, a system of concentric quartz tubes, the plasma torch, and a gas supply. The schematic construction is shown in the figure below (Figure 7.18).

Figure 7.18. Construction of a standard ICP torch. In most cases the (liquid) sample is introduced as an aerosol produced by a nebulizer at a velocity of 1 l/min. The outer gas flow reaches up to 15 l/min Ar, the inner one up to 5 l/min. The greatest advantages in comparison to other devices are a huge dynamic range of more than three decades, the low limits of detection, and, most importantly, the possibility of a simultaneous determination of all metals and some non-metals. 7.2.1.2.4. Separation and detection of the radiation To determine an element via ICP-OES it is necessary to observe an isolated wavelength. This means the separation of wavelengths prior to their detection is a must. There are different methods of wavelength separation: 1. Fabry-Perot-Interferometry The FPI consists of a pair of precisely orientable, high-reflectivity mirrors. It achieves high spectral resolution through the principle of interference (Edelson, 1992), but offers very poor spectral selectivity. That is, all lines of a region and all different orders of interference are transmitted simultaneously without discrimination. 2. Grating Spectrometry The basic functional principle of this kind of wavelength separation is a grating that causes the dispersion of radiation, similar to a prism. By turning this grating there is always only one part of

the one-dimensionally resolved spectrum (monochromator) that targets the exit slit to be detected by a photo multiplier tube. The advantage is a high spectral resolution, the possibility to scan major parts of a spectrum and to operate in one order over the entire spectral region of interest. 3. Echelle Spectrometry An Echelle spectrometer consists of a grating and an additional dispersion component, a prism (Edelson, 1992). This allows a two-dimensional resolution of wavelengths. The 2D-picture is projected on a charged coupled device(CCD)-camera. Here, every pixel corresponds to a single wavelength. Thereby, the simultaneous detection of various elements is achieved. 7.2.1.2.5. Applications Different forms of applications can be characterized by the way of sample introduction. Nebulizers (e.g. ultra sonic n. USN, direct injection n. DIN, and pneumatic n. like the MeinhardNebulizer) allow the introduction of liquid samples as aerosol or spray (Greenfield and Montaser, 1992). They are used to analyse aqueous or organic samples, or dilutions of digested solids. Solid samples can be introduced directly, too. The “Slurry technique” needs grinded material which is suspended with water. The mixture is stirred by an ultrasonic finger and inserted into the ICP by peristaltic pumps (Broekaert, 1994). Moreover, dry solid samples may be filled into a graphite crucible that is lifted up into the hotter plasma zones. A very elegant coupling is chromatography and ICP-OES which offers the opportunity to perform speciation analysis (Uden, 1994), i.e. the determination of an element depending on its form of chemical bonding. 7.2.1.3. Inductively coupled plasma mass spectrometry (ICP-MS)

As described in chapter 7.2.1.2. an inductively coupled plasma is not only a source of radiation but also of charged particles, electrons and cations. Since mass spectrometry was recognized by Thompson in 1910 as an analytical method it obtained enormous significance for multielement and component determinations in a wide field of applications with different varieties of ion sources. Today it has been developed to a powerful and mature spectrometric technique. The physical principle of mass spectrometry is based on the generation of analyte ions by electrical discharge followed by separation of the ions due to their mass-to-charge ratio caused by the influence of electric or magnetic fields on their way of flight. By the end of the 1970s the extraction of ions generated in an inductively coupled plasma could be managed for the first time. Consequently, in 1980 Gray, Date and Houk made use of the ICP

as an ion source for mass spectrometry and obtained an efficient multielement-method with detection limits even superior to ICP-OES and GF-AAS (Houk et al., 1980). Because of its high temperatures ICP is characterized by a high excitation efficiency and subsequently low detection limits in the range of 1–100 pg/mL (Gray and Date, 1983a). Furthermore, the lingering period of the particles is sufficient for a nearly quantitative vaporisation and dissociation, and beyond that a high ionisation efficiency is obtained. Moreover, because of the stability of the plasma and its atomization efficiency the sample can be introduced as a solution as well as in solid form (Broekaert and Tölg, 1987). In the case of plasma emission spectrometry the spectra exhibit a lot of different lines and many spectral interferences may occur (Parsons et al., 1980), so that difficult correction methods must be worked out. On the contrary, in ICP mass spectrometry (ICP-MS) the spectral background is low and almost determined by the dark current of the detector and scattering of ions in the mass spectrometer, and it slightly subjects to the “high frequency-noise” of the plasma (Broekaert et al., 1994). Thereby the limits of detection can be depressed to the sub-ng/mL-range (Date and Gray, 1985). ICP-MS shows a high sensitivity and even the isotopes of the elements can be determined. 7.2.1.3.1. Instrumentation

The sample introduction and the plasma For the-analysis with ICP-MS the samples are mostly dissolved and diluted and with the help of a pneumatic nebulizer (Ebdon and Cave, 1985; Layman and Lichte, 1982; Brotherton et al., 1987) inserted into the plasma. The use of an ultrasonic nebulizer (Fassel and Bear 1986; Schramel et al., 1979, 1982) increases the efficiency of nebulization of liquid samples but especially in presence of higher salt concentrations memory effects occur (Zhu and Browner, 1988). The introduction of solid samples was studied in 1992 by Dark and Tyson. This can be managed with spark and laser ablation as well as the insertion of suspensions (Dark and Tyson, 1994; Jakubowski et al., 1992). And finally, electrothermal vaporisation (ETV) is useful for the analysis of solid micro-samples, and as a result of the introduction of dry analyte vapor into the plasma the detection limits can be improved with this method (Park et al., 1987). The construction of an inductively coupled plasma is shown in Figure 7.18. Extraction of ions The generated ions are extracted from the analytical zone with a special interface developed by Date and Gray (Date and Gray, 1983b) as shown in Figure 7.19. This interface consists essentially of two conical apertures made of copper, nickel or platinum. The diameter of the first aperture (cone or sampler) is between 0.3 and 1 mm and a cone angle of 120° shows the best efficiency for ion extraction. The ions are extracted into an intermediate vacuum of only a few mbars which is performed with a powerful rotation pump or a

turbomolecular pump. There the beam of ions expands so that a central part must be sampled with a second aperture (skimmer) with a similar diameter and a cone angle of 55°. The distance of 5–10 mm between sampler and skimmer guarantees a high ion transmission. The ions are finally led into a vacuum of less than 10−5 m bar inside the mass spectrometer where they are separated. Mass spectrometer In commercial systems usually a quadrupole mass spectrometer is applied. A scheme is presented in Figure 7.19. The ion beam leaving the interface is focused by several electrostatic lenses, and the transmission is further improved by the use of a so-called “beam stop”, an aperture which absorbs neutral particles. Beyond that it prevents

Figure 7.19. Principal setup of an ICP-MS. UV-radiation from entering the detector. Then the beam of ions is led lengthwise between four parallel rods. On opposite rods a DC field with a 180° shifted phase is applied, a high frequency field is superimposed on this field. The transmission for cations with a given m/z is optimal at a certain value of the field, so that by a scanning variation of the voltage the different masses can be separated continuously. With quadrupole mass spectrometers a resolution of only 1 dalton can be reached, the resolving power of most instruments lies at 300 (Schramel, 1997). Better resolving power is obtained by the use of high resolution double focusing mass spectrometers. These rather expensive instruments are able to separate masses down to < 0.1 dalton, their resolving power lies at 7500 (Schramel, 1997), so many interferences can be eliminated. Detection

The separated ions are usually detected by electron multipliers or pulse counters. Beside these, micro-channel plates or photographic emulsions are used. The evaluation of data often needs correction models for interferences which today can easily be handled by the use of suitable computer programs. 7.2.1.3.2. Interferences and their correction There are five different types of interferences leading to systematic faults with deficient correction. They are described in the following sections. m/z-interferences This type of interference is constructed of the following five effects: (a) Formation of polyatomic species This type especially gains significance with the use of quadrupole spectrometers because of their unit mass resolution. The polyatomic species are formed with the plasma gas, the principal component or the solvent (e.g. ArO+, ArCl, ClO+) (For example 40Ar16O+ interfers with 56Fe). These interferences affect especially on the analysis of lighter elements in the range of masses up to 80 dalton, and the species are preferably built up with the elements Cu, Fe, Cr, Mo, Se, V and Zn. By optimizing the operating conditions the formation of the polyatomic species can be suppressed (Fisher and Ebdon, 1997; Tittes et al., 1994). (b) Isobaric elements This interference is based on the existence of various stable isotopes of different elements with the same nominal mass (e.g. 54Cr and 54Fe). To overcome this problem alternative isotope peaks of the element must be observed. (c) Doubly charged particles The ions are separated due to their m/z-ratio. A doubly charged ion appears in a spectrum at half of its mass. This effect occurs when an element has a very low second ionization energy (e.g. Ba, Sr, Mg). This effect can also be influenced by optimization of the operating parameters. (d) Mass discrimination effect An element in high concentration delivers an enlarged peak covering peaks of elements with a vicinal mass. This interference can be eliminated by a dilution of the sample—if sensitivity of the spectrometer permits this. (e) Formation of oxides

In the plasma and the interface some thermally stable oxides may be formed with oxygen in solvents or surrounding gases. The analyte peak then can be found at a mass 16 units higher in the spectrum. Variation of operating parameters affects on this source of disturbance, too. Transport interference The density and the viscosity of a sample influences the efficiency of nebulization and the rate of sample reaching the plasma. The use of an internal standard normally corrects this effect (Thompson and Houk, 1987). Interference by high salt concentration The analysis of sample solutions containing a salt concentration of about 1 % (w/w) or more often suffers from troublesome memory effects in the nebulizer or the interface, and a blockage is even possible (Broekaert, 1994; Schramel, 1997). While pneumatic nebulizers may cope with a concentration of about 1% (w/w), ultrasonic nebulizers require a dilution of the sample. Matrix interference Interferences based on a change of the matrix composition occur with the subsequent changes in nebulization, in the geometry of the aerosol channel, in the ionisation or in the ionisation energy. The influence of matrix compounds on the ionisation energy was discussed by Crain et al. (Crain et al., 1988), and especially the easily ionized heavy elements alter the ionisation and excitation processes in a plasma. To overcome these effects the sample is spiked. The internal standard should preferably show an ionisation energy close to the interesting analyte and should have a similar molecular mass. Variation of the composition of isotopes This interference only occurs with the element Pb because it is the last link in most radioactive disintegration series. The composition of isotopes in a sample may differ from composition in a standard. The effect is eliminated with the integrated calibration of all Pb-isotopes. 7.2.1.3.3. Applications A superior determination of heavy trace elements is achieved by ICP-MS compared to ICP-OES because of improved detection limits and minimized interferences with mass spectrometry. A comparison of the limits of detection (LOD) of some selected elements is shown in Table 7.12. Today the fields of application for ICP-MS are widespread. Because of its low LODs this method is often used for diverse analytical studies in the field of environmental as well as medical questions. Beyond that with the demand for greater sensitivity, ICP-MS was coupled to different techniques, and instrumentation was developed concerning this aspect. The coupling of chromatography with ICP-MS was reviewed in 1993 (Hill et al., 1993) and Uden (Uden, 1995) studied the capabilities of HPLC and GC-ICP-MS. Sheppard and Caruso (Sheppard and Caruso, 1994) succeeded in overcoming polyatomic ion interferences with the use of mixed gas

Table 7.11. Limits of detection (LOD) for different elements (Welz, 1983). Element

LOD of F-AAS (ng/mL)

LOD of HG-AAS (ng/mL)

LOD of GF-AAS (ng/mL)

As

20

0.3

0.02

Bi

20

0.2

0.02

Pb

10

0.05

0.5

Sb

30

0.2

0.1

Se

100

1.0

0.02

Sn

20

0.2

0.5

Te

20

0.2

0.02

Table 7.12. Limits of detection for different elements in comparison of ICP-MS and ICP-OES (Fisher and Ebdon, 1997; Tittes et al., 1994). Element

LOD of ICP-MS (ng/mL)

LOD of ICP-OES (ng/mL)

Cd

0.06

3

Pb

0.05

40

Hg

0.02

20

W

0.05

30

As

0.04

50

Se

0.8

70

plasmas. Further studies on the use of various plasmas have been reported (Ebdon et al., 1994; Hill et al., 1992). Also today high resolution spectrometers are becoming more widespread as interference-free determinations are necessary. Environmental analysis A typical field of application for ICP-MS is the determination of trace and ultra-trace elements in different kinds of water. For drinking water a determination of relevant elements is performed directly, waste water first needs a fusion process (e.g. with HNO3/H2O2). The determination of waste water of the Ruhr was studied in detail (Herzog and Dietz, 1987). The determination of sea water requires liquid-liquid extraction or a sorption technique to eliminate the high salt content. Bauchemin et al. isolated the analytes by an adsorption on an 8-hydroxychinolin loaded SiO2column (Beauchemin et al., 1988a). This technique is transferable to the determination of river water. Marine sediments and according standard reference materials were characterized by ICPMS as well as biological marine samples (Ridout et al., 1988; Beauchemin et al., 1988b). Brzezinska-Paudyn determined Sn in environmentally relevant samples with ICP-MS (Brzezinska-Paudyn and Van Loon, 1988) and by coupling with HPLC even speciation is possible with this technique. Speciation in aquatic and biological environments has been

discussed (Lespes et al., 1992) and with the quest for knowledge on the speciation of analytes it seems obvious that this field of research will increase. Clinical analysis Most trace elements occur in very low concentrations in body fluids and serum (<1µg/L). In comparison to ICP-OES, ICP-MS enlarges the number of elements which can be directly determined, but the determination of the elements Cu, Fe, Cr, Mo, Se, V and Zn is hampered considerably by polyatomic interferences which can only be controlled with the use of ETV. Some reviews concerning clinical applications have been published (Barnes, 1993; Vanhoe, 1993; McKay, 1993). ICP-MS allowed research into the bioavailability of trace elements and their biological function in organisms (Serfass et al., 1988). So proteins were investigated for some elements (e.g. Cr, Mn, Fe, Zn a.m.), in urine heavy metals like Pb, Cd, Hg and Tl have been determined with a good accuracy and Pb could be detected in blood. Flow injection is a very promising introduction technique for samples of a small volume or a high salt content (Dean et al., 1987; Szpunar et al., 1997), and with isotopic solution metabolic studies can be performed (Ting and Janghorbamo, 1987). Geological Samples For determination of trace elements in a geological sample usually a total fusion process with HF is necessary. The trace elements Pb, Cd or Hg can be obtained with a aqua regia extract in a yield of about 90 %, which is sufficient for routine analysis. Calibration in most cases is done using the standard addition method. With the determination of Pb in sediments the interference as a result of variation of isotopes has to be considered. The analysis of these samples can be easily performed with the use of alternative sample introduction techiques such as ETV (Park and Hall, 1988). Analysis of metals and ceramics ICP-MS is useful for metallic samples with linerich emission spectra, and LODs down to the sub-µg/g range can be achieved. Beck determined high temperature alloys used in reactor technology or in aeronautics (Beck and Farmer, 1988). McLeod et al. recognized the influence of the matrix on the limit of detection on base of a nickel alloy analysis (McLeod et al., 1986). So matrix removal brought progress in determination (Palmieri et al., 1986) as well as direct solid sampling or laser ablation (Jiang and Houk, 1986) which improved detection limits to a range of 0.1–1 µg/g in steel. Isotopic dilution This method can be used well in ICP-MS for each element with two stable or long living isotopes. Within this technique a known amount of an element with a known but different isotopic composition to the sample is added and mixed intensively. The method enables the elimination of a series of systematic errors as well as the performance of tracer studies. A precision of determination of about 1 % can be achieved when respective isotopic concentrations do not differ more than one order of magnitude (Ebdon et al., 1992).

7.2.1.4. X-ray fluorecence spectroscopy (RFA)

X-ray fluorescence spectroscopy (RFA) is based on the excitation of atoms by primary X-rays. The excited atoms emit fluorescence of characteristic wavelengths for each element. All elements, beginning with the element number nine can be detected by using this method, which is free of material loss and requires only a small amount of substance. Therefore it can be used for multi-element analysis, although for quantitative determination a large variety of interferences from matrices occur. 7.2.1.4.1. Theory

When an inner electron is excited by the photoelectric effect it is turned out of the atom and leaves the excited ion behind. After about 10−8 seconds the ion returns the to ground state, by an emission of energy. This mechanism can be explained by two different models: A higher electron fills the gap from the removed electron. The difference of their energy is completely delivered as X-ray with the frequency υ. In this case we talk about X-ray fluorescence:

The energy of the emitted X-ray fluorescence is a characteristic for the corresponding element and for the observed transition in the electron sphere (Kohlrausch, 1989).

Figure 7.20. Model of fluorescence ray generation.

The relation of the frequency of the emitted X-ray, ordinal number of the element and the quantum number is described by the law of Moseley (1913):

where λ is the wavelength of emission and Z is the ordinal number of the characteristic element. S is an element specific quantity, that can accepted to be constant for qualitative analysis (for example the value 1 for the emission lines of the K-series) and R is the Rydberg constant (Musiol, 1988). By using this fundamental relationship it is possible to get further information about a sample by the detection of the emitted X-ray. The emission lines of the emitted spectra can be divided into K-, L- and M-series, due to their original electron shell, where it is necessary to always use the same kind of emission lines in one analysis. The intensity of these lines differs from each other due to their different quantummechanical transition probability. Usual the emission from the K-series is detected (Källne, 1991). The energy which is set free may also be transmitted to another electron of a higher electron shell, which is able to leave the electron sphere after the absorption of the free energy. The atom left behind will be double ionised. This process is called the auger-effect. The kinetic energy of the auger-electron depends—in a similar way as the wavelength of the emitted X-ray—on the ordinal number of the element and the characteristic transition of the electron shells concerned. Both mechanisms—the emission of X-ray and the auger-effect—occur at the same time and can not be separated from each other. One process is the competing reaction of the other process. The Auger-effect is quite important for elements up to phosphorous because it is more probable than the emission of fluorescence radiation, that could be detected in this kind of spectroscopy. 7.2.1.4.2. Instruments Generation of X-ray The classical way of generating X-rays is the bombardment of metals with accelerated electrons in a X-ray tube, which is evacuated (Figure 7.21).

Figure 7.21. X-ray tube.

Figure 7.22. Typical X-ray spectrum. The electrons are accelerated by a high voltage supply (UH in the cathode) and hit onto the surface of the metal which is used as anode, this is called the target. The high voltage supply is typically up to 100 kV and usually targets are made of W, Cr, Rh, Cu, Mo or Ag. One part of the electrons is slowed down by interaction with the anode material and another part is able to excite an electron in the inner electron sphere and X-ray emission is generated in the way mentioned above. Most of the energy is lost by the production of heat, therefore the X-ray tube has to be cooled down, which is very important for the technical set-up of these instruments. The efficiency of the generation of X-rays is poor so that only less than 1% of the whole energy is transmitted to this form of radiation. The result of these different processes leads to typical spectra (Figure 7.22) which contains mainly two kinds of emission: The continuous spectrum is created by the reduction of speed of the electron by the interaction with the atoms of the anode material. These electrons have not enough energy to remove an electron from the anode. Some of the accelerated electrons are able to ionize the target and the refilling of the electron shell leads to the characteristic emission which can be seen as a peak in the spectra above. There are still other possibilities to remove an electron from an electron shell. Beside accelerated electrons it is also possible to use other light particles such as protons or the helium-ion He2+. If the X-ray emission is induced by a concussion with another particle it is called primary X-ray emission. On the other hand it is also possible to induce X-ray emission by another electromagnetic emission with a high energy level. In this case we are talking about secondary X-ray emission. The spectra of a secondary X-ray emission experiment contains only

the element-characteristic emission lines and the frequency of the emissions (Kuwana, 1983). This is called X-ray fluorescence emission (XRF). Detection of X-ray A XRF-spectra covers the wavelength area from 0.02 nm up to 2 nm (0.6 to 60 keV). There are several kinds of detection units for this radiation. The most common are the flow-through and the scintillation detector. Both are shown in Figure 7.23. In all kinds of detection units the photoelectric absorption of the incident X-rays by atoms on the surface of the detection system is used. The linear relation between the quantum energy of the Xray and the energy of the resulting photo-electron, which induces a photo current, is of fundamental importance for the quantification of an unknown sample concentration. The operation mode of these most common types is briefly explained. The scintillation detector (a) contains a crystal of sodium iodide doped with thallium in a non translucent gear box coupled with photo multiplier. After the absorption of a x-ray quantum free photo electrons are built in the crystal, which are able to excite further electrons until their energy is used up. When these electrons come back to their ground state, they emit a short light induced impulse, which can be detected and recorded by the photo multiplier tube (PMT). Scintillation detectors can be used in the wavelength area from 0.02 up to 0.15 nm. For the detection of radiation above this wavelength the use of a gas-flow-through detector is more suitable (up to 5 nm). The electrons— generated by the photo electric effect—produce secondary ions and secondary electrons in a gas atmosphere (e.g. argon). As a

Figure 7.23. Different types of detectors.

result of the strong electric field in the surrounding of a live wire the electrons are able to reach a higher energy level with the consequence that by impact ionisation further ions can be generated which lead to a current that can be measured. Other detection units are based on the semiconductor technology but they all have the utilisation of the photo electric effect in common. Within the combination of different types of detectors it is possible to cover a wide range of wavelengths for many different samples and operation modes. Technical set-up for analysis In Figure 7.24 the principle of X-ray analysis is shown. The reflected fluorescence radiation is paralleled by a collimator (Michette, 1986) before it hits the analyser crystal that is used for diffraction before the X-ray beam reaches the detector (Hosoya, 1986). Very important for a correct analysis is the texture of the sample surface and the constant angle of the X-ray and the sample. In contrast to the faultless theory for X-ray spectroscopy, there are some hidden problems left in the common use of this technique for chemical analysis. As mentioned before the generation of the photo effect is not the only possibility when a sample is radiated with fast particles. The auger effect and first of all an energy loss in kind of heat are the two dominant side effects in this technique. Also several kinds of interferences are possible, effected by the matrix of the sample. For this reason the angle between the radiation beam and the sample is made very small with the aim to create a reflection of the X-ray on the surface of the sample. The idea is to minimise the penetration depth so that only a few layers of the target atoms are measured and the number of interference atoms is reduced to a minimum. This technique is called total reflective X-ray fluorescence analysis (TRFA) and is mostly used nowadays because of its good limits of detection.

Figure 7.24. Spectrometer set-up.

Every element specific TRFA spectra consists—in contrast to the complex optical spectra—of only a few characteristic lines hence it is quite easy to identify an element in the sample. For quantitative analysis not only the characteristic wavelength is detected but also its intensity, which is proportional to the concentration of the element (Jenkins, 1981). That means a relationship between the product of the thickness of the sample layer and the concentration of the element and the intensity of radiation can be constructed. For the exact determination a comparison of the investigated sample and samples with a known concentration is made. Another possibility is to spike the sample and use a kind of standard addition, although this requires a very homogeneous sample preparation after the doping. 7.2.1.4.3. Applications Analysis with XRF or TRFA is able to detect and quantify elements beginning with the element fluorine. Up to the element phosphorous the detection limits are not very good because of the high noise/signal-ratio due to the low yield of the fluorescence ray of these elements (Johansson, 1981). The analysis time is about half a minute for one element per sample, which is quite fast compared to other common techniques. A multi-element analysis lasts about two hours. A typical spectra that can be obtained from an aqueous solution containing the same concentrations of vanadium, chromium, manganese, iron, cobalt, nickel, copper and zinc is shown in Figure 7.25. It can be noticed that the energies relating to the different elements increase due to their position in the periodical system and hence to their electron bonding energy. RFA and the TRFA are widespread in industrial quality assurance in the field of steel industry, cement works and fertiliser industry (Griffin and Vincent, 1986). For the execution of the analysis mainly solid samples are used because of the advantage of a

Figure 7.25. Spectra of different metals.

Table 7.13. Detection limits for several elements using TRFA. element

detection limit (pg/g)

element

detection limit (pg/g)

nickel

45

lead

28

strontium

16

platinum

37

chromium

181

iron

62

nondestructive analysis. This advantage leads also to the use of TRFA for the analysis of works of art for example (Graham and Eddie, 1985). Quite important is the consistency of the analyte. The surface of metals has to be polished very carefully and other samples like cement, glass or minerals must be reduced to powder of a determined particle size (an usual particle size is about 50 µm) (Nefedov, 1987). In environmental analysis aerosols and other airborne particles are melted with lithium borate to a colliquation. Aqueous solutions are concentrated on a quartz carrier before analysing. The reachable detection limits are very low, especially when using TRFA. This again leads to another problem for the determination of minor components, because in this case the major component causes a very high signal that superimposes on the other one. Typical detection limits of pure metals using a tungsten anode and an analysis time of 1000 seconds are given in Table 7.13. 7.2.1.5. Further advisable references

• Bonelle and Mande (1982) Advances in X-Ray Spectroscopy. Pergamon Oxford. • Fabian et al. (1981) Inner-Shell and X-Ray Physics of Atoms and Solids. New York: Plenum. • Jenkins (1987) X-Ray Analysis, Encyclopedia of Physical Science and Technology. 14, pp. 657–674. New York: Academic Press. • Mitchell and Barfoot (1981) Particle-Induced X-Ray Emission Analysis. New York: Harwood. • Russ (1984) Fundamentals of Energy Dispersive X-Ray Analysis. London: Butterworth. REFERENCES

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Schramel P. (1997) Anwendung der ICP-MS für die Spurenelementbestimmung in biologischen Materialien. In Analytiker Taschenbuch, Günzler, H. (ed.), Berlin, Heidelberg: Springer-Verlag. Schramel, P. and Ovcar-Pavlu, J. (1979) Dependence of the signal on acid concentrations of the sample in ICP emission spectral analysis. Fresenius Z. Anal. Chem., 298, 28–31. Schramel, P., Klose B.-J. and Hasse, S. (1982) Efficiency of ICP emission Spectroscopy for the determination of trace elements in biomedical and environmental samples. Fresenius Z. Anal. Chem., 310, 209–216. Serfass, R.E., Thompson, J.J. and Houk, R.S. (1988) Isotope ratio determinations by inductively coupled plasma/mass spectrometry for zinc bioavailability studies. Anal. Chim. Acta, 188, 73– 84. Seshadri, S.R. (1973) Fundamentals of Plasma Physics. New York: Elsevier. Sharp, B.L. (1987) High Frequency Electrodeless Plasma Spectrometry. Aberdeen: Macauly Institute for Soil Research. Sheppard, B.S. and Caruso, J.A. (1994) Plasma mass spectrometry: consider the source. Invited lecture. J. Anal. At. Spectrom., 9, 145–149. Slickers, K. (1992) Die automatische Atom-Emissions-Spektralanalyse. Self Distribution, 2nd Edition. Szpunar, J., Bettmer J., Robert, M., Chassaigne, H., Cammann, K., Lobinski, R. and Donard, O.F.X. (1997) Validation of the determination of copper and zinc in blood plasma and urine by ICP-MS with cross-flow and direct injection nebulization. Talanta, 44, 1389–1396. Thompson, J.J. and Houk, R.S. (1987) A study of internal standardization in inductively coupled plasma-mass spectrometry. Appl. Spectrosc., 41, 801–806. Ting, B.T.G. and Janghorbamo, M. (1987) Application of ICP-MS to accurate isotopic analysis for human metabolic studies. Spectrochim. Acta, 42B, 21–27. Tittes, W., Jakubowski, N., Stüwer, D., Tólg, G. and Broekart, J.A.C. (1994) Reduction of some selected spectral interferences in inductively coupled plasma mass spectrometry. J. Anal. Atom. Spectrom., 9, 1015–1020. Uden, P.C. (1994) Determination of trace elements by chromatographic methods employing atomic plasma emission spectroscopic detection. In Determination of Trace Elements, Alfassi, Z.B. (ed.) pp. 426–455. VCH: Weinheim. Uden, P.C. (1995) Element-specific chromatographic detection by atomic absorption, plasma atomic emission and plasma mass spectrometry. J. Chrom. A, 703, 393–416.

Vanhoe, H. (1993) A review of the capabilities of ICP-MS for trace element analysis in body fluids and tissues. J. of Trace Elements and Electrolytes in Health and Disease, 7, 131–139. Walsh, A. (1955) The application of atomic absorption spectra to chemical analysis. Spectrochim. Acta, 7, 108. Welz, B. (1983) Atomabsorptionsspektrometrie. Weinheim: VCH. Winter, F., Quick, L., Bradter, M. and Cammann, K. (1991) Frequenzselektive simultane Multielement-Atomabsorptionssoektrometrie. In Colloquium Atomspektrometrische Spurenanalytik, Welz, B. (ed.) 6, 489–495. Zhu, G. and Browner, R.F. (1988) Study of the influence of water vapor loading and interface pressure in inductively coupled plasma mass spectrometry. J. Anal. Atom Spectrom., 3, 781–789.

7.2.2. DETERMINATION OF NITRATE IN WASTE WATER WITH CHEMICAL SENSORS AND MODERN SEPARATION TECHNIQUES

KARL CAMMANN, UDO KRISMANN, BERND ROSS and WOLFGANG KLEIBÖHMER 7.2.2.1. Introduction

Concern about the environment has reached new heights in recent years. Many environmental guidelines, regulations and remedies are being initiated which require sound chemical monitoring techniques and analysis methods in order to ensure that risks are accurately assessed and mandates are properly enacted. Environmental analytical chemistry provides the means to separate, identify and quantify pollutants found in a variety of matrices including air, soil and water (Clement et al., 1991). Therefore, only with inexpensive sensors and fast chromatographic methods or separation techniques with great demands on selectivity, sensitivity, reproducibility and correctness is a reasonable and effective enforcement of environmental protection possible. For this purpose a wide variety of reliable working analytical systems and methods have to be developed to facilitate continuous or quasi-continuous monitoring. In this chapter the different features of three competing modern techniques for the determination of inorganic compounds will be highlighted. Chemical Sensors, Ion Chromatography and Capillary electrophoresis are compared in terms of selectivity, efficiency, suitability, reproducability and in dependency of their analytical parameters. An analytical chemical sensor is a miniaturized transducer that responds selectively and reversibly to chemical compounds or ions and yields electrical, thermal or optical signals which depend on the concentration. In addition non chemical interaction with the analyte of interest is possible in optical sensors and modern dip sticks working by visual detection of a coloured bar (Niessner, 1993). Around the turn of the century it was discovered that certain types of glasses were sensitive to pH. Subsequently by using suitably designed pH electrodes made with glass membranes, it was possible for the first time to determine the hydrogen ion concentration in aqueous solutions with high selectivity and remarkable precision. A further breakthrough in chemical sensor technology came with the development of ion selective electrodes for several anions and cations (Haber, Klemensiewicz, 1909; Ross, Frant, 1966). The technology of chemical sensors was not confined to ionselective potentiometry and other electrochemical methods of detection such as polarography, voltammetry or amperometry, which gained considerably in importance as a result of the development of gas membrane covered oxygen electrodes by Clark (Clark, 1959). The largest market for chemical sensors at present is the automobile industry for controlling the operating conditions of the three way catalytic converter with the help of a potentiometric

oxygen gas sensor (lambda sond). A similarly large market exists for semiconductor sensors based on SnO2 for detecting oxidizable gases such as CO, NOX and CH4. Fast separation techniques e.g. chromatography with supercritical fluids, ion chromatography and especially capillary electrophoresis are important competitors of chemical sensors in environmental monitoring and process control. These methods show high selectivity and low interferences and it is possible to determine several parameters within a single chromatographic run. With regard to practical problems a comparison of ion chromatography (IC), capillary electrophoresis (CE) and electrochemical sensors is given for a special example, ion analysis in waste water. Authentic water samples with a high surfactant content from a car-wash are examined, prooving the suitability of IC, CE and electrochemical sensors in terms of specificity, sensitivity, reproducibility, analysis time and calibration linearity. The results show that the chromatographic methods are useful techniques in water analysis, yielding good sensitivity, high resolution and short analysis times. In comparison the chemical sensor also shows short analysis times, good sensitivity and a simple instrumental set up. The disadvantage is the lack of selectivity and the instability of the sensor signal, when the sensor is exposed to the extremely complex matrix. Good results could only be achieved by pretreatment of the sample solution. 7.2.2.2. Measurement principles 7.2.2.2.1. Chemical Sensors

The essential principle of a chemical and biochemical sensor is described in terms of three basic components. The receptor (the recognition system) generates an energetic interaction specific to the substance in question (the analyte). Regarding complex matrices like waste water or other heavily polluted systems there are different attempts to construct sensors without any receptor (Panne, Niessner, 1992; Niessner, 1991). The second component of any chemical and biochemical sensor is the transducer, that transforms an energy quantity into a proportional electrical signal. A third component, consisting of a further electronic unit (a preamplifier, impedance converter, multiplexer, analog to digital converter) is placed directly after the transducer, to suppress external influences caused by interfering electric or magnetic fields, or to feed the separate signals from several recognition systems simultaneously to the data processing unit through a single electrical connection. A typical set up is shown in Figure 7.26. Chemical sensors can be classified according to the type of sensor element used for molecular recognition or according to the type of transducer. If the emphasis is on analytical selectivity, the most important component is the recognition system. If on the other hand the limit of detectability or the signal to noise ratio is crucial, the

Figure 7.26. Schematic set up of a chemical and biochemical sensor. critical component may be the physical or electronic transducer. A detailled classification is given in (Cammann et al., 1991). 7.2.2.2.2. Fast Separation Techniques Fast separation methods like CE, HPLC and IC are the most important competitors of chemical sensors in water protection control. Even in very complex matrices separation, identification and quantification of pollutants of interest are possible with these methods within a few minutes. Among these methods IC and HPLC are the most evolved and established ones. The quality of pumps, columns and detectors is high and consequently IC and HPLC became elements of many national and international analytical regulations (DIN, ISO, EPA). Ion Chromatography Ion chromatography (IC) is an ion exchange-based separation system introduced by Small and coworkers in the mid-1970s (Gerdje et al., 1987) that has revolutionized the analysis of inorganic and organic ions. IC has replaced many tedious wet chemical analysis with a simple, automated instrument that can determine several ions simultaneously in a single method. Typical ions that can be separated by ion chromatography are cations (group I and II of the periodic table), , 3 halide anions, , NO2–, NO3– and PO –. Ion chromatography is performed on high efficiency pellicular ion-exchange columns and a universal detection with a flow-through conductivity detector and suppressed conductivity of the eluent so that the resulting background conduction is near zero.

Capillary Electrophoresis Capillary electrophoresis, a modern separation technique which combines high separation efficiency and resolution power with short analysis times. Generally capillary electrophoresis can be divided in several different separation methods which are tabulated below. Free zone electrophoresis (charged analytes)

(CZE)

Capillary gel electrophoresis (molecular weight based separations)

(CGE)

Isoelectric focusing (separation of proteins)

(IEF)

Isotachophoresis

(ITP)

Micellar electrokinetic capillary chromatography (neutral analytes)

(MECC)

In spite of different separation principles the basic instrumental configurations are identical (Figure 7.27). Separations of both small and large molecules are facilitated in narrow-bore capillaries (20–200 µm i.d.) which are placed together with the electrodes in two buffer reservoirs. When high voltages are applied between the electrodes separation of charged species occurs due to their differential electrophoretical mobilities. Depending on the hardware the sample injection (nl range) can be done electrokineticly using high voltages or hydrodynamicly (pressure, vacuum or gravity injection). The detection of the separated analyte fractions is realized by optically measuring UV-absorbance or fluorescence emission directly on-capillary using special focussing optics. Electrochemical detector systems like conductometric (Ewing et al., 1998; Huang et al., 1991) or amperometric detection (Wallingford, Ewing, 1988; Haber et al., 1991) have been further developed and coupling of CE with mass spectrometry has been successfully applied to using the electrospray technique (Loo et al., 1998; Hernandez et al., 1991; Smith et al., 1991).

Figure 7.27. Basic instrumental configuration of a capillary electrophoresis system Components: 1: Capillary; 2: Oven; 3: Detector; 4: High Voltage Supply; 5: Buffer Reservoir; 6: Data Acquisition

In free-zone electrophoresis separation results from differential electrophoretic mobilities which depend on the analyte specific charge-to-mass ratio. Simultaneous analysis of cations and anions is possible due to the electroendoosmotic flow (EOF) which draws the complete buffer solution towards the cathode. In aqueous solutions at higher pH-values the fused silica capillary walls are negatively charged due to ionization of the silanol groups at the surface. Counterions, which build up near the surface to maintain charge balance, form a doublelayer and create a potential difference very close to the wall, the zeta potential. The EOF results from the effect of the applied electric field on this solution double layer (Heiger, 1993). EOF depends on the strength of the applied voltage, the pH value, the ionic strength and the viscosity of the buffer solution. The total velocity of a molecule in the capillary can be derived from the superposition of the analyte specific electrophoretic velocity and the electroosmotic velocity (Yeung, Kuhr, 1991). The development of the micellar electrokinetic capillary chromatography (MECC) by Terabe et al. in 1984 enabled the analysis of neutral solutes as well as of charged ones. MECC can be described as an electrical driven partition chromatography in which the migration velocities of the analyte depends on its partition coefficient between the micellar and the nonmicellar (aqueous) phase. Separation is accomplished by the use of surfactants like sodium dodecylsulphate (SDS) as buffer additives. Surfactants are molecules which exhibit both hydrophobic and hydrophilic character. Above their specific critical micelle concentration the surfactants self-aggregate and form a “pseudo-stationary phase”. The separation depends on the hydrophobicity of the analytes which influences the specific partition of the neutral solutes between the lipophilic micellar phase and the hydrophilic nonmicellar (aqueous) phase. The combination of micellar electrokinetic capillary chromatography and capillary zone electrophoresis offers simple and efficient separation possibilities for charged and non-charged molecules. This great variability provides a wide application range which extends from unpolar solutes like polycyclic aromatic hydrocarbons (Brügemann, Freitag, 1995) and polar phenols or explosives (Kleiböhmer et al., 1993) in the environmental analysis over carbohydrates (Garner, Yeung, 1990) and amino acids (Engelhardt et al., 1993) up to the determination of cations and anions in complex matrices. We have chosen the latter example to compare the former presented sensor system with rapid separation methods like ion chromatography and the upcoming capillary electrophoresis. The capabilities and principal limitations of sensors or separation systems cannot be demonstrated with standard solutions but in the analysis of real samples like waste water of a car wash. The complex matrix with a great number of unknown and possibly interfering substances like surfactants are real challenges for the selectivity of sensors systems and the susceptibility of separation systems against sample overloading. 7.2.2.3. Determination of nitrate

The determination and monitoring of ionic compounds in water is a common analytical problem which can be solved in different kinds of ways.

The simplest method is the electrochemical analysis with the help of potentiometric sensors. The determination of nitrate shows relatively short response times between 15 to 30 seconds and a linear concentration range between 1 to 6000 mg/l. The instrumental equipment is very simple and can be built up with a reference electrode and a mV-meter. For quantitative measurements a calibration curve is necessary or the standard addition method is used. In this experiment the first method was carried out. The nitrate sensor showed a drift of about 10 mV per hour, when measuring the sample solution. As a result one can say that the sample matrix has a significant influence on the membrane that causes changes in membrane composition and leads to an unstable signal so that no quantitative analysis was possible. In order to get quantitative results from the sensors, the sample solution had to be pretreated by extracting the organic compounds with n-hexane. After that procedure the sensors showed no drift and a quantitative analysis could be made (Figure 7.28) in good correlation with the chromatographic methods, as can be seen in table 1 at the end of this chapter. In comparison with analyte specific sensor systems the chromatographic separation techniques make possible complicated analyses and ion chromatography is the most established of them. IC can be used for the quasi-continuous monitoring of relevant inorganic anions in groundwater, freshwater and surface water. Sample preparation is reduced to filtering and sometimes diluting of the sample. This can automatically be done by modern autosamplers. As can be seen in the chromatogram in figure 4 the simultaneous control of 4 anions in 6 minutes is possible. Further

Figure 7.28. Potentiometric determination of nitrate in a waste water sample of a car wash.

Table 7.14. Concentrations of anions in a waste water sample of a car wash determined with three different analytical techniques. Anion

IC Amount (mg/l)

CE RSD (%)

Amount (mg/l)

Sensor RSD (%)

Amount (mg/l)

RSD (%)

Chloride

45.0

1.0

41.9

0.4

45.6

3.8

Nitrate

20.9

1.1

20.1

1.0

3.0

3.5

Sulfate

62.6

1.2

67.3

1.1

–

–

more, also nitrite and bromide would be separated and detected, if their concentration rises above 5 µg/l. The identification of the peaks is possible according to the retention time, because no coelution with other ions occur. The within a day reproducibility of the retention time is about 0.2 % (R.S.D.) and the week to week reproducibility is 0.3 % (R.S.D.). Concentrations found with the presented method are listed below in Table 7.14. The required time for one chromatographic run and so for the simultaneous control of six different anions is much shorter than every change in concentration of these anions in real systems. So IC offers the possibility for a quasi-continuous monitoring of inorganic anions, although the system has to be controlled daily by hand, to check the system and to refill buffer and regenerant. However, direct measurements of water samples with a high content of organic substances e.g. humic acids and surfactants as in the sample from a car-wash is possible only for a short period of time, because after some injections the column is ruined. Modern and organic solvent-inert ion-exchange columns can reduce these problems because they can be flushed with organic solvents (methanol, acetonitrile) to eluate organic contaminations from the column. Capillary electrophoresis with cheap fused silica capillary which can be easily cleaned with sodium hydroxyde solution can be also the method of choice for the analysis of highly contaminated samples. Direct measurement can be done without any further sample pretreatment. In capillary electrophoresis with indirect absorbance for the detection of non absorbing compounds like inorganic anions an absorbing anion is incorporated in the electrolyte to produce a background signal. Anions present in the sample will displace the absorbing anion in the electrolyte and produce a negative peak. For getting good separations and well shaped peaks without tailing or fronting background anion and analyzed compounds should have identical electrophoretical mobilities. Thus the speed and quality of the separation of anions depends on the choice of the absorbing background anion. With the use of the highly mobile pyromellitate and hexamethonium hydroxyde as electroosmotic flow modifier the separation of all inorganic anions (Br−, Cl−, , , , F−) is accomplished in less than 6 minutes (see figure 5). Due to the low mobility of organic anions peaks are highly tailing and their simultaneous quantification with pyromellitic acid is not possible. Gravity injection of the sample was used to

ensure a sample loading with the precision of electromigration but without it’s electrokinetical discrimination.

Figure 7.29. Ion-chromatographic determination of inorganic anions in a waste water sample of a car wash.

Figure 7.30. Electrophoretic separation of anions in a car wash sample. The reproducibility in migration times varies from 0.5 % (R.S.D.) within a day to 2 % (R.S.D.) from week to week. Nevertheless an identification of the analytes according to their migration times, determined with standard solutions, is not possible because of its shift in real samples. Organic substances like surfactants of the sample can alter the microenvironment of the capillary walls and influence the migration and separation of the components. So identification in the present case was achieved by sample spiking with individual substances. Normally method development and optimization is done by the determination of standard solutions. Separation parameters of CE were not suited to the specific problems of the varying samples in order to make an objective judgement about the properties and problems of the compared analysis

techniques in the reality of a laboratory. In the present case the resolution of sulfate and nitrate is poor without any modification of the method and the quantification of the latter anion very uncertain. Concentrations of the anions determined in the sample are given in Table 7.14. Better results for nitrate would be obtained by adaptation of the separation to the sample matrix and by addition of octansulfonic acid as a matrix stabilizer (Dionex Corporation, 1993). 7.2.2.4. Summary

Environmental monitoring in general presents an extremely complex matrix in which the analyte has to be measured. Regarding this, one of the main problems with chemical sensors is the unsatisfactory selectivity. In the experiment described above potentiometric nitrate and chloride sensors were used. Depending on the membrane composition the possible interfering ions in general can be perchlorate, jodide, chlorate, bromide, carbonate, chloride, phosphate, hydrogenphosphate, acetate, flouride, sulfate according to the lipophilic Hoffmeister series (Sollner, Schean, 1964). To overcome this problem sensor arrays (Müller, 1989) consisting of several relatively unspecific but reproducible working sensors have been constructed and optimized by using chemometrics. The selectivity will be increased by using multi-variant calibration methods. For this purpose the number of sensors has to be at least the number of components to be analyzed. There are great problems realizing this because until now it is extremely difficult to make an exact analysis of more than three components. Different interfering components can lead to unforeseen following reactions and influences. A permutation of only few possibilities of combinations would lead to an increase in time during the learning phase of the sensor array. Further problems will come up when different components are not additive but multiplying. Until now measurements can only be made in similar concentration ranges or for calibration. Drifting signals, which shift the zero point of the calibration curve and change the sensitivity of the measuring ion as well as the interfering ion, have to be taken into account (Cammann, Heising, 1991). A different method to improve the selectivity of chemical sensors is the combination with flow injection techniques. Interfering ions can be eliminated by prereactions. Furthermore this method facilitates a high sample frequency and small sample volumes. Meanwhile a lot of chemical sensors in combination with flow injection are commercially available. Mainly they are used in medical, environmental and industrial fields. In summary one can say that chemical sensors have the advantage of short response times, long term stabilities and the possibility of on-line measurements, but they are of minor relevance for environmental monitoring in complex matrices without sample preparation because of the selectivities. To overcome this problem the development of biochemical sensors has increased markedly during the last ten years. They show improved selectivities due to the interaction of the analyte with a more or less specific biological component, i.e. an enzyme or an immunological antibody. Besides the more specific biochemical sensors different immobilized microorganisms can be used to detect environmentally interesting classes of compounds i.e. volatile organic

carbons, polycyclic organic hydrocarbons and others and most relevant sum parameters like the biological oxygen demand (BOD). The long term stabilities of those biochemical sensors strongly depend on the stability of the biological compound, the method of immobilization and the surrounding matrix the sensor has to measure in. For example most enzymes are extremely sensitive towards heavy metals and loose their activity completely whereas some microorganisms are resistent in the presence of heavy metals and show no significant interferences. The response times of the biochemical sensors depend strongly on the sensor set up and geometry of the sensor (diffusion control). Simple enzymatic catalyzed reactions take place in very short times and lead to respones times of a few seconds. Enzymatic systems with different immobilized enzymes (cascade of enzymes) and different reaction steps may prolong the response time significantly. More complex systems with antigen/antibody reactions or aspiration of microorganisms take more time so that the response time may be in the area of several minutes. In conclusion the application of chemical as well as biochemical sensors depends on the matrix to be used and will be limited by the instability of the polymeric ion selective membrane on the one hand and of the biological compound on the other hand. Routine analysis can be done either in less complex matrices or by frequent exchange of insensitive sensors. In contrast to analyte specific sensor systems chromatographic methods or modern separation techniques enable simultaneous analysis of various compounds within a single run. Yielding high sensitivity and selectivity in short analysis times from the point of view of sensitivity and the technical state-of-the-art IC is the most developed method. The only limitation of the system is the possible contamination of the column which can occur in the repeated analysis of high loaded samples with complex matrices. Nevertheless in combination with fully automated systems for “on-line” sample pretreatment IC and other chromatographic separation techniques like HPLC show unlimited suitability in the “quasi-continuous” monitoring of for instance surface water control. Capillary electrophoresis is a very complementary technique to ion chromatography. While in most cases IC offers lower detection limits and better reproducibility than CE, CE often provides faster analysis and different selectivities. The unique combination of short analysis times with high efficiency and resolution provides higher number of theoretical plates for CE than for IC. Additional advantages in the determination of diffcult matrices like toothpaste and faster method development (Weiss et al., 1993) would promise excellent suitability of this separation technique. Disadvantages of capillary electrophoresis are its small dynamic range and its unsatisfactory detection limits mainly due to the use of indirect detection methods. The total ion concentration of the capillary is limited but memory-effects due to sample overloading can be avoided by flushing of the capillary after each run. Further

Table 7.15. Analytical parameters of IC, CE and chemical sensors. Anion

Ion chromatography limit of detection*

working range

regression coef.

Chloride

5 µg/l

0.005–50 mg/l

0.998

Nitrate

5 µg/l

0.005–50 mg/l

0.9991

Sulfate

10 µg/l

0.010–35 mg/l

0.998

* threefold signal to noise ratio Anion

Capillary electrophoresis limit of detection*#

working range

regression coef.

50 µg/l

0.050–50 mg/l

0.9992

Nitrate

200 µg/l

0.200–50 mg/l

0.997

Sulfate

50 µg/l

0.050–50 mg/l

0.9993

Chloride

# without electrokinetical sample enrichment Anion

Chemical sensor system limit of detection

working range

regression coef.

Chloride

300 µg/l

1–6000 mg/l

0.9997

Nitrate

500 µg/l

1–3500 mg/l

0.9998

Sulfate+

4.8 mg/l

5–2000 mg/l

0.9988

+

Indirect measurment by potentiometric titration with a barium sulfate electrode

disturbances of organic sample compounds can produce strong shifts in the migration times which leads to decreased peak resolution and to difficulties in the peak identification. Capillary electrophoresis as a hyphenated technique is still growing and the development of commercially available systems has not finished yet. The recently introduced second hardware generation may have solved the technical problems which limit at the moment the applicability of the system in routine analysis. In Table 7.15 the analytical parameters of the presented systems are summarized. As one can see only ion chromatography can yield detection limits in the lower ppb range while the main application of chemical sensors can be the analysis of higher concentrations which would overload IC and CE. The regression coefficients for ion chromatography, capillar electrophoresis and the electrochemical sensors are comparable. The frequency of sensor calibration is relatively high because of the poor reproducibility especially in membrane construction. The sensors vary significantly so that each one has to be calibrated before use. Once a chemical sensor is established the necessity for calibration depends on the sample frequency and the matrix to be measured in. The higher the content of interfering ions and surfactants the higher the reqirement for sensor calibration or even sensor exchange.

Concerning the calibration in chromatographic techniques each standard solution has to be measured at least thrice due to varying peak areas in single runs. So regression quality depends firstly on the repeatability of the measurement and secondly on the total number of measured standard solutions. Fortunately in chromatography and electrophoresis calibration of several analytes can be carried out simultaneously. Current state-of-the-art in chromatography are systems which allow calibration via auto sampling. Once a calibration is established quite a number of measurements can be done with the help of internal standards without recalibrating the system. Nevertheless chromatographic systems should be controlled daily with standardized test solutions and methods to ensure the quality of the analytical data. Lifetime of instrumental analytical systems only depends on the deduction of the technical equipment in the laboratory and on new developments in the analytical field. Concerning sensor systems the situation must be described differently. Lifetime of sensors is limited and long term stabilities of about 45 weeks can only be achieved in standard solutions or samples with simple matrices like ground water. Otherwise the lifetime of a sensor decreases rapidly or, as the experiment has shown, no measurement could be done without pretreatment of the sample solution. REFERENCES

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8. CONCLUSION A.P.F.TURNER and U.BILITEWSKI The previous chapters have illustrated biosensor systems designed to answer a variety of questions in environmental analysis, ranging from instruments for the quantification of single analytes to those recording groups of compounds or reflecting the natural mode of action of pollutants on living organisms. The focus has been on systems for the determination of organic compounds in water, which is at least partly due to experience with biochemical reactions, which has generally been gained in the aqueous phase. Biosensor methodology has to compete with alternatives. The quantification of compounds is usually performed using chemical methods, which are well established and applied routinely. They are based on physical or chemical features of compounds, such as mass, charge, electron excitation energies, polarity, reactivity, etc. The specificity of these methods is derived either from the chemical properties of the compound of interest, as for example for the determination of nitrate, or through a combination of properties. For example, the interactions of compounds with sorbent phases due to polar or hydrophobic interactions led to a separation of compounds even in complex mixtures, which is utilised in all chromatographic or electrophoretic methods. In combination with an unspecific on-line detector (photometer, fluori-meter, electrode, etc.), even single compounds can be quantified. Thus, routine chemical analytical methods are often based on instrumental analysis, such as (HP)LC, GC(-MS) or AAS. In some cases the chemical methods have been packaged as easy-to-use test-kits or dipsticks, allowing rapid on-site analysis. The major advantage of the instrumental analytical methods is the possibility to analyse mixtures of compounds even when not all constituents of the mixture are known prior to the analysis. Together with improved sensitivities of detectors this leads to the increasing number of compounds found in environmental samples with on-going improvements of achievable lower detection limits. However, often the analytes of interest are well-defined and have to be determined on a routine basis. For these situations biochemical alternatives, which promise to be faster, less expensive, and less time-consuming than the instrumental analytical methods, have been under development for some time. Moreover, total analysis of environmetal samples is not achievable and some parameters of interest cannot be determined by conventional chemical analysis at all. Examples are the toxicity of compounds, which is taken here as generic term for all damaging effects, the determination of endocrine disrupters, and the total load with biologically degradable compounds or with nutrients for microorganisms, algae, animals or plants. Due to the definition of these parameters biological or biochemical analytical methods are essential. In biochemical analysis, and this includes biosensor systems, the analytes are determined via their interaction with biochemical compounds, such as enzymes, whole cells, antibodies (receptors), or DNA, which means that in contrast to some bioassays no highly-organized living beings such as fish or mussels are used. Thus, the recognition of the analytes is achieved by specific biochemical interactions, which are in principle well understood:

• Antibodies are known to bind very specifically and with high affinity to their antigen. Thus, corresponding immunoassays and immunosensors have been developed. However, most of the analytes of interest in environmental analysis are low-molecular weight analytes and require some knowledge and experience to obtain specific antibodies, because suitable immunoconjugates have to be synthesized. An exciting alternative to natural antibodies is the design and synthesis of artificial ligands which may offer the same or improved affinity, be quicker and easier to produce and offer greater stability and consitency. • Receptors show binding characteristics comparable to antibodies, as they bind specifically their ligands and transfer signals from the outside of cells to the inside or initiate directly DNAtranscription. This is used in pharmacology for the screening for pharmaceuticals, and investigations with respect to the applicability of corresponding assays in environmental analysis were already initiated, however relevent receptor sensors are not yet available. • Enzymes containing SH-residues are usually sensitive to inactivation by heavy metals. This feature was utilized in sensors for metals. • Double-stranded DNA is formed through specific hybridisation of complementary single strands. Thus, if sequences typical for a given microbial strain or for a required capability are known, a corresponding probe can be synthesized and used in the search for the complementary sequence. Sometimes biological elements can be chosen to mimic the reaction of the ecosystem to compounds of interest or to represent the natural site of action of the pollutants: • Microorganisms, which are able to degrade compounds such as polychlorinated biphenyls or dioxins and are used for their determination, were originally isolated from highly polluted areas and thus represent a natural defense strategy. • Sensor systems and assays based on the inhibition of cholinesterases utilise the natural site of action of most of the common insecticides. As this class of enzymes is present also in vertebrates the inhibiting power of these respective compounds is also the reason for their toxic behaviour. • Receptor-based systems are under investigation mainly for the determination of estrogen disrupters. They utilise for analyte recognition the protein’s binding domain for the ligand, which is the site of action of respective compounds in animal and men. These features of biochemical reactions are often already utilised, although for different purposes or in other formats: • The capability of microorganisms to degrade compounds, which are usually considered as persistent and toxic, is the basis for the biological clean-up of polluted areas. • The specific interaction between complementary DNA-strands is the basis of all genomic analysis, which is applied to the characterisation of biofilms by in situ-hybridisation or which is

performed by a combination of the polymerase chain reaction (PCR), electrophoretic separation of the PCR-products and finally detection through suitable markers. • The antigen-antibody-interaction is not only the natural defense reaction of vertebrates to eliminate or inactivate high-molecular weight foreign compounds, but also the basis of all kinds of immunoanalysis. Immunoassays are well-known from medical applications for the determination of hormons or antibodies or other indicative proteins using microtiter plate assays or even dipstick formats. Moreover, antibodies are used to identify proteins after separation of protein mixtures by electrophoretic or chromatographic procedures. • The investigation of receptor-ligand interactions is a well-established method in biochemical research, mainly in the elucidation of signal transduction reactions, where receptors are identified through their strong binding of radioactively labelled ligands. Biologically active proteins are determined via bioassays with cells which are selected with respect to the availability of suitable receptors. • The aerobic microbial turnover of compounds is the basis of the index of the biochemical oxygen demand (BOD5), and genetic repair mechanisms of cells are utilised in assays to indicate the mutagenic potential of samples. Thus, the characteristic feature of all biosensor systems developed for environmental analysis is not the utilisation of biochemical recognition per se, but it is the way in which it is formated and how it is used which lead to new areas of applications. Again, only examples can be mentioned here: • Biochemical oxygen demand is usually determined by measuring the oxygen consumption of a mixed culture over 5 days (BOD5). Use of the same principle, i.e. a combination of oxygen determination in the presence of microorganisms, but with cells immobilised directly in front of an oxygen electrode, leads to microbial sensor systems which allow the evaluation of a parameter within twenty minutes or so. This BOD sensor does not measure exactly the same parameter as the BOD5, but it often correlates to this official index. Due to the reduced analysis time it is possible to use this parameter for active process control and not just for a retroperspective process monitoring. • Conventional immunoassays are performed in microtiter plates, which is a highly suitable format for the analysis of large numbers of samples in centralized laboratories. Immunosensor systems open the possibility to analyse samples on site. Here the border between immunodipsticks or screening assays based on antibodies and immunosensors is now not well-defined, as some screening assays are just a transfer of the microtiter plate assay to another format, e.g. an assay performed in tubes, with all solutions in individual bottles to avoid the use of pipettes, etc. However, all solutions have still to be added and incubated manually. Automation of assays on the other hand at present still results in rather large and complicated instruments. Nevertheless, these instruments offer the chance of on-line monitoring of waterways, etc. More technical effort and perhaps the use of microsystem technology could help to develop really easy-to-use immunosensor systems, which could replace the manual screening assays and could also simplify the on-line instruments.

• Automation of assays together with integration of sample pretreatment procedures widens the applicability of biosensor systems to soil and air analysis. At present analytes in soil samples usually have to be extracted manually by conventional methods, with the extract being analysed not chemically but biochemically. This of course could be improved, if the extraction can be adapted to the biochemical needs and integrated in the resulting system. However, it has to be realised that a variety of chemicals, in particular those present in soil, are not readily soluble in water and that only some biochemical recognition elements are active in organic solvents. • Automation of assays is combined not only with a controlled and reproducible dosage of reagents but also with a controlled timing of the assays. This may allow the assay time to be shortened, as the assays can be performed in the kinetic, time-dependent, regime, which may offer new areas of applications, e.g. quasi-on-line process monitoring based on more than the established parameters including perhaps not only sensors for single defined compounds, but also sensors based on bioassay principles indicating toxicity or other effects on ecosystems. • Shortening of analysis times, automation and application of non-radioactive detection principles, as introduced by biosensor system, may also allow combination of biochemical methods with separation principles taken from chemical analysis. This could generate a new quality of environmental analysis, as the toxic or biological potential of certain fractions of the environmental sample could be identified or compounds could be identified being responsible for a certain effect in the bioassay. At present, the list of compounds found in ecosystems is continuously increasing not allowing an evaluation of the relevance of these compounds for the ecosystem. On the other hand, biochemical assays though indicating a biological or biochemical effect often do not allow an identification of the relevant compound. Thus, the chemical and the biochemical analysis methods could profit from a combination. Some of the above mentioned instruments are already commercially available, some are under development and for some only the biochemical principle is known. However, as the systems have either to compete with alternative analytical methods or to create new markets, their widespread application is dependent on legislation, which influences the need for analysis, of technological availability and user demand. This in turn influences the readiness of companies to invest in the development and commercialisation of biosensor instruments.

INDEX

2, 4-dichlorophenoxyacetic acid (2, 4-D) 101, 154, 157, 201, 255, 274 2-PAM 82, 85, 145 2-pyridinealdoxime methiodide 82 4-aminophenol 142, 144 4-parameter model 120 AAS 55, 217, 368–372, 405 Flame (F) 369 Cold vapour (CV) 369 Graphit furnace (GF) 369 Hydride generation (HG) 369 Multielement 371 absorbance, absorption 5, 30, 33, 121, 310 acceleration 65 acceptor 54, 56, 63, 286 accumulation 132, 206, 299 acetic acid, acetate 142, 195, 196, 201, 259 Acetobacter xylinum 296 acetolactate synthase (ALS) 76, 145, 146, 147, 256, 257 acetylcholine 142, 259 acetylcholinesterase (AChE) 80, 81, 140, 141–145, 147, 257, 259, 260, 264, 270, 271, 272 acetylthiocholine 144 acid phosphatase 76, 228, 256

activated sludge 165, 168, 169, 170 activator 85 active site 62 acylase 76 adenine (A) 124 admittance 24 Aeromonas sp. 94 affinity 1, 2, 5, 30, 31, 34, 43, 55, 56, 77, 108, 110, 111, 114, 115, 116, 122, 129, 142, 156, 158, 161, 251, 268, 275, 406 affinity constant 77, 79, 112, 115, 116, 264 affinity sensors 5, 150–165, 250 aflatoxin 268 alachlor 261 Alcaligenes eutrophus 96, 101, 168, 170, 194, 198, 199, 255 alcohol dehydrogenase 200, 270, 285, 294, 296–301 alcohol oxidase 270, 285, 286, 296, 300, 301 aldehyde dehydrogenase 76, 145, 146, 200 aldicarb 256, 259, 260, 312 Aldridge, equation of 78, 82 aldrin 140 algae 256, 405 aliphatic hydrocarbons 192 alkaline phosphatase 76, 81, 227, 228, 230, 231 allyl thiourea 97, 99

aluminium (Al) 100, 243 amino acid side chains, pKa of 62 ammonia 10, 97, 100, 186, 241 ammonia/ammonium electrode 100, 101, 235 ammonium ions 10, 89, 90, 100 amperometry, amperometric 5, 12–20, 25, 74, 88, 89, 142, 146, 154, 166, 228, 236, 256, 257, 262, 271, 274, 297, 331 amplification 19, 75, 130, 185, 205, 233, 292 amylase 171, 174 analysis strategy 241 analytical process 239, 247 analytical range 2 aniline 194, 195 anthraquinone 133 antibodies 1, 3, 34, 45, 56, 59, 105–124, 141, 150–165, 203–211, 250, 261, 263, 272–274, 275, 405, 406, 407 monoclonal 110–112, 122, 157, 204, 251 polyclonal 108–110, 122, 156, 157, 251 recombinant 112–114, 153, 204, 251 antibody binding 115–116, 152, 154, 160 ntibody library 112–114, 122 antibody structure 105–108 anticholinesterase 142 antigen 106, 108, 109, 115, 122, 263, 272, 273, 407

antigen binding site 107, 116 antigenic determinant 106, 108, 109, 110 antiserum 109, 110, 116, 122 APCI 311, 340, 342, 344–347 API 311, 340, 344–347 aromatic hydrocarbons 192 aromatics, aromatic substances,—compounds 90, 132, 192–203, 211, 253, 266 arrays 220, 333 arsenic (As) 168, 214, 215, 219 Arxula adenintvorans (A. adinivorans) 169, 170, 172, 176, 177, 179 association constant 115, 116 atmospheric pressure chemical ionization (APCI) 311, 340, 342, 344–347 atmospheric pressure ionization (API) 311, 340, 344–347 ATR 33 atrazine 140, 146, 157, 186, 256, 263, 273, 275, 312, 330 ATSDR list 185, 192, 212 attenuated total reflection (ATR) 33 Auger-Effect 383 automated, automation 2, 3, 5, 51, 53, 54, 58, 151, 152, 154, 155, 162, 294, 310, 313, 316, 407, 408 avidin 128, 153, 155, 157, 162, 262, 263 avidity 116, 268 Azotobacter vinielandii 100, 194

B lymphocytes 108, 110, 111, 113 Bacillus sp. 169, 170, 171, 176, 177 Bacillus subtilis (B. subtilis) 94, 95, 169, 170, 171, 176, 177, 194 base pairs 124, 125, 132 benzene 95, 101, 195, 196, 270, 272 benzo(a)pyrene 268 benzoate (benzoic acid) 185, 187, 192, 193, 195, 197, 199, 271 benzoquinone 90, 154, 290 beryllium (Be) 76 β-galactosidase 171, 221 binding inhibition assay 151, 152, 153, 158, 159, 160, 161 bioavailability 214–216, 267, 268 biofuel cell 166 bioluminescence 95, 96, 267 biosludge 168, 169 biphenyl 91, 101, 192, 193, 195, 199, 201 blood ethanol 295 BOD (BOD5) 87, 97, 99, 137, 138, 165–181, 217, 266 Bode plot 24, 25 BOD-sensor 137, 165–181 bovine serum albumine (BSA) 109, 143, 299 breath ethanol 295 brewster angle 42

butyric acid 142, 257 butyryl thiocholine 144 butyrylcholine 142, 257, 258 butyrylcholinesterase (BuChE) 141–145, 257, 258

cadmium (Cd) 76, 96, 168, 215, 219–221, 243 Candida tropicalis 194 capacitance 20, 21, 22, 23, 24 capillary electrophoresis 395–396, 398 capillary gel electrophoresis (CGE) 395 carbamates, carbamic compounds, carbamate insecticides 76, 77, 140–145, 147, 192, 256, 257, 259, 272, 310 carbofuran 259, 312, 336 carbon electrode 129, 130, 144, 145, 259, 274 carbon monoxide 286 carbon paste electrode 129, 130, 182, 183, 268, 290 carbonic anhydrase 85, 221, 222, 286 carrier 52, 53, 56, 155, 264 catalytic antibodies 273 catechol 146, 192, 193, 195, 199, 201, 228, 288, 291, 333 CDR 107, 114 cell loading 91 cellulase 174 cellulose 171, 174, 183

centrifugation 91 CGE 395 characteristic emission 384 chemical reaction 51, 52 chemical sensors 394 Chlorella vulgaris 100 chloroaromatics 196–201 chlorobenzoates 101, 198 chlorobutane 201 chloroform 139, 182, 201, 269, 271, 290, 291 chloromercuribenzoates 95 chlorophenols 101, 185, 186, 187, 194, 195, 198, 199, 286, 309, 333, 340, 348 chlortoluene 196 chlotoluron 256 cholesterol oxidase 270 Choline 142, 259 choline oxidase (ChOD) 142, 257, 259 Cholinesterase 76, 77, 82, 85, 141–145, 257, 406 chromatographic method,—technique 144, 192, 311, 324–347, 405 Chromatography immuno 122 ion 394, 397 micellar electrokinetic capillary (MECC) 395, 396

chromium (Cr) 76, 214, 215, 217 chronopotentiometry 130, 132 chymotrypsin 76 circuit, equivalent 21–24 Citrobacter sp. 169, 171 Clark electrode 14–15, 97, 230, 231, 269, 286, 299 (see also “oxygen electrode”) Clostridium 166, 170 Co(phen)3+129 cobalt (Co) 76, 215 cobalt phtalocyanine (CoPC) 144, 145 cofactor 63, 85, 87, 221, 293, 294, 299 cold vapour(CV)-AAS 369 column 52, 53, 55, 57, 154, 156, 173, 174, 229, 230, 236, 259, 264, 267, 300, 310 affinity 52, 53, 54, 59, 156 catalytic or enzyme or reaction 52, 53, 58 combinatorial chemistry; synthesis 207, 274, 275, 276 competition assay 264 competition reactions 73 competitive immunoassay 112, 117, 118–119, 152, 204, 272, 274 competitive inhibition 77, 78–79, 151 complementary strand 127, 129, 130

complementary-determining regions (CDR) 107, 114 constant region 107 Constants affinity 77, 79, 112, 115, 116, 264 association 115, 116 dissociation 64, 77, 78, 115, 116, 152, 160, 272 inhibition 77, 78, 79, 81, 82 continuous flow 147 (see also “flow injection analysis”) continuous spectrum 384 copper (Cu) 76, 96, 100, 168, 211, 215, 218, 219, 220, 221, 289 cresol 195 cross-linking 142, 143, 144, 145, 275 cross-reactivity 111, 116, 120, 122, 253, 261, 263 Cryptosporidium sp. 129, 130 cyanide 101, 187, 286 cyanobacteria 146, 256 cytosine (c) 124 CZE 395

data processing 120–121 DDT 140 decentralised measurements 277

degradation 192, 193, 195, 196, 197, 199, 255, 309, 320, 323, 327, 406 dehydrogenase 77, 83, 85 deoxyribonucleic acid (DNA) 112, 113, 124–135, 405, 406 Desulfovibrio desulfuricum 100 Detectors diode array (DAD) 310, 317, 319, 322, 323, 329–331 electrochemical (EC) 331–335 electron capture (ECD) 310, 324, 328 flame ionization (FID) 324, 327 nitrogen phosphorus (NPD) 310, 324, 327 diagnostic ions 325, 326, 327, 342 diaphorase 146 diazinon 258 dibenzofuran 192, 193, 195, 199 dibromobutan 201 dibromopropane 201 dichloroethane (1, 2-) (DCE) 139 dichloromethane 101 dichlorophenylmethylurea (DCMU) 256 diethyldithiocarbamate 146, 217, 271 diffusion 12, 18, 19, 22, 35, 51, 54, 57, 58, 69, 70, 71, 83, 89, 91, 153 diffusion control 71, 72, 75, 228 diffusion limitation 12, 13, 74, 75, 83, 91, 153

dilution 2, 56 diode array detector (DAD) 310, 317, 319, 322, 323, 329–331 dioxane 266, 270, 272 dioxin 207 dip-stick 223, 263, 405, 407 direct injection nebulizer (DIN) 375 dispersion 30, 57–58 dissociation constant 64, 77, 78, 115, 116, 152, 160, 272 distribution coefficient 69 distribution patterns 243 dithiocarbamate 76, 79, 145, 146 dithiothreitol 83, 85 diuron 140, 157, 256 DNA 112, 113, 124–135, 405, 406 intercalator 126, 129, 130, 132, 206 melting 125 structure 124–126 DNA-chip 131–132 documentation 247 donor 56, 63 double-stranded DNA 132 drinking water 137, 182, 185, 226, 235

ECD 310, 324, 328 echelle spectrometry 375 EDTA 83, 85 electrochemical detector (EC) 331–335 electrochemical transduction 128, 154, 156, 182–185, 205, 290, 349 electrode 5–28, 57 carbon 129, 130, 144, 145, 259, 274 carbon paste 129, 130, 182, 183, 268, 290 current 12 enzyme 5, 16, 17–19, 57, 257, 258, 268, 285–308, 349–351 glassy carbon 183, 187, 300 ion selective (ISE) 7, 8, 9, 52 oxygen 5, 13, 14–15, 89, 100, 101, 165, 166–181, 194, 197, 221, 227, 229, 257, 286, 291 redox 6, 7 reference 7, 8, 10, 13 working 13, 14, 16, 259, 273 electrodeless discharge lamp (EDL) 370, 371 electroendosmotic flow (EOF) 396, 398 electron capture detector (ECD) 310, 324, 328 electron impact ionization (EI) 324, 325, 326 electrophoresis capillary 395–396, 398 capillary gel (CGE) 395

free zone (CZE) 395 electrospray (ESP) 311, 340, 342 electrothermal vaporization (ETV) 377 ELISA 111, 118, 140, 154, 155, 156, 204, 205, 206, 211, 251, 349 ellipsometry 43, 93 endocrine disruptor,—substance 45, 108, 405 end-point approach 66, 167 enrichment 2, 54, 141 ENT 91 Enterobacter sp. 94, 169, 171 ENTP 91 Environmental Protection Agency (EPA) 182, 204, 248, 251, 255, 268, 310, 312 enzymatic sensor 71, 72, 73, 74, 91, 141–149, 193, 194, 235–237 (see also “enzyme electrodes”) organic compounds in water 182–191 enzyme 1, 3, 14, 57, 58, 97, 154–157, 174, 192, 194, 197, 198, 221, 264, 268–272 Assay 1, 61–87 Electrode 5, 16, 17–19, 57, 257, 258, 268, 285–308, 349–351 hydration shell 271, 272 immunoassay (EIA) 118, 151, 154 inhibitors 59, 76–87, 141, 220, 221, 223, 227–228 loading 74, 77, 83, 146 membrane 21

substrate determination 61–75, 228–233 substrate recycling 75, 231, 232, 291 linear sequences of 73 competition reactions 73 enzyme-linked immunosorbent assay (ELISA) 111, 118, 140, 154, 155, 156, 204, 205, 206, 211, 251, 349 EOF 396, 398 EPA 182, 204, 248, 251, 255, 268, 310, 312 epitope 106, 108, 116, 117 equivalent circuit 21, 22, 23, 24 Escherichia coli (E.coli) 90, 95, 96, 97, 100, 101, 112, 113, 129, 194, 195, 219, 235, 236 estradiol 108, 109 estrogenic properties,—contaminants 45, 288 ethanol (ethyl alcohol) 169, 197, 201, 257, 270, 271, 285, 294 blood 295 breath 295 vapour 285, 286, 295–301 ethidium bromide 131, 132, 133 ethoxyphenol 195 ethylbenzene 196 ethyltoluene 196 evanescent field; wave 5, 31, 47, 120, 132, 133, 204, 205, 264, 265

extraction 2, 3, 54, 55, 182, 214, 246, 247, 248, 249, 251, 252, 253, 258, 264, 268, 273, 274, 309, 408 liquid-liquid (LLE) 249, 310, 311–320 liquid-solid (LSE) 249, 310, 311–320, 327–329, 333, 338 solid phase (SPE) 55, 253, 310, 320 (see also “liquid solid extraction”) supercritical fluid (SFE) 249, 253, 317

Fab (fragment) 106, 107 Fabry-Perot 43, 375 FAD 63, 229, 296 fast separation techniques 394–396 Fc part 106, 107 FCS 35 fenitrathion 258 ferbam 145 ferricyanide 90, 256, 274, 290 ferrocene 90 ferrocyanide 290 fibre optic, optical fibre 44, 130, 131, 132, 160, 204, 205, 221, 264, 265 FID 324, 327 field blank 240, 241 field effect transistor (FET) 10–11, 89, 90 FIIAA 156, 263, 264

filtration 2, 54, 56, 91, 249, 258, 274 flame ionization detector (FID) 324, 327 flame(F)-AAS 369 flow injection analysis (FIA) 51–60, 118, 122, 154, 155, 156, 157, 183, 187, 229, 230, 236, 251, 259, 262, 266, 268, 269, 298 fluorescence, fluorescent 5, 30, 31, 33, 34, 49, 130, 131, 132, 151, 156, 160–162, 221–222, 263, 265, 310 correlation spectroscopy (FCS) 35 detection (FD) 335 polarisation immunoassay (FPIA) 35 resonant energy transfer (FRET) 35, 48, 162 fluoride 8, 81 formaldehyde 186, 187, 285, 287, 292–295 dehydrogenase 285, 293–295 vapour 186, 285, 294–295 formic acid 101 fourier transform analysis 23 free zone electrophoresis (CZE) 395 frequency of analysis 1, 3, 5, 153 frequency, sampling 52, 58 Fresnel’s formula 31 FRET 35, 48, 162 fructose 201 fulvic acid 253

fulvic substances 311, 330 fungicide 76, 141, 192, 254

gas chromatography (GC) 141, 239, 263, 310, 324–329 gaseous analytes 285 gas-phase biosensors 285–308 gas-sensitive electrode 7 GC 141, 239, 263, 310, 324–329 gene 95, 96, 112, 195, 196, 206, 218, 219 gene manipulation 93, 95–96 genetic engineering 90, 95, 99, 147, 197, 206, 266 GGA 170, 171, 174 glassy carbon electrode 183, 187, 300 glucose 2, 89, 90, 94, 95, 171, 174, 185, 187, 193, 195, 201 glucose oxidase (GOD) 2, 5, 76, 221, 227, 230, 232, 233, 256, 270, 272, 273 glucose-6-phosphate dehydrogenase (G-6-PDH) 76, 230 glutamic acid 171, 174 glutaraldehyde 143, 144, 145, 229, 236, 298, 299 glycerol 94, 171, 173, 174 glycerol-3-phosphate dehydrogenase (G-3-PDH) 76 glycogen 230, 231 glycogenphosphorylation 231 glyphosat 140

graphite electrode 145, 182, 183, 236, 237, 269, 291 graphite furnace(GF)-AAS 369 grating coupler 37, 38, 158 grating spectrometry 375 grid 243, 244 groove binding substance 129 ground water 137, 235, 244, 254, 262, 322 guanine (G) 124

haloaliphatic compound 201 haloaromatics, halogenated aromatics 192–203 Hanes plot 77 Hansenula anomala 94, 179 hapten 106, 108, 115, 117, 121, 122, 153, 154, 157, 158, 160, 161, 251 HAT selection 110, 111 hazardous compounds 76, 185, 192, 212, 235 health effects 285, 288, 293 heavy chain 106, 107, 113 heavy metal 76, 77, 83, 84, 96, 140, 213–225, 241, 268 bioavailability of 214–216 current analytical methods for 216–218 inducible promoters 218–219

speciation of 214–216 substrate assays for 220 toxicity of 168, 214 whole-cell biosensors for 218 helical groove 126 helium plasma 372–373 helix 124, 125, 133 heptenophos 259 herbicides 6, 76, 140, 146, 192, 252, 254, 256, 287 heterogeneous immunoassay 118–119, 152 hexachlorobenzene (HCB) 139 hexachlorobutadiene (HCBD) 139 hexachlorocyclohexane (HCH) 139 hexacyanoferrate 146, 272, 292, 294, 297 hexokinase 76 high performance liquid chromatography (HPLC) 141, 239, 249, 262, 329–347, 405 hollow cathode lamp (HCL) 370, 371 homogeneous immunoassay 118, 151 horseradish peroxidase 154, 221, 263, 268, 269, 270, 271, 272, 274 (see also “peroxidase”) HPLC 141, 239, 249, 262, 329–347, 405 human health 76 humic acid 253, 254

humic substances 253, 259, 261, 263, 311, 319, 320, 330 humin 253 hybrid sensor 93, 97, 173, 174, 228 hybridization 124, 125, 126–129, 130, 131, 132, 133, 406 hybridoma cells 110, 111, 112 hydride generation(HG)-AAS 369 hydrocarbons aliphatic 192 aromatic 192 chlorinated 140, 141, 192 polycyclic aromatic (PAH) 138, 195–196, 206, 286 hydrogels 237, 256, 257 hydrogen peroxide 5, 9, 14, 15–16, 61, 142, 143, 144, 154, 186, 227, 228, 229, 230, 231, 232, 259, 271, 273, 296, 298 hydrolases 97, 141, 173, 179 hydrolysis 141, 142, 168, 169, 171, 174, 175, 197, 207, 220 hydroquinone 154, 194 hydroxylammonium sulphate 271 Hyphomicrobium 101, 201

IEF 395 Ig 105, 106, 107, 156, 157 imazethapyr 264 imidazoline herbicides 256

imidazolinones 146 immobilization 1, 2, 18, 36, 56, 57, 58, 59, 152, 154, 155, 157, 160, 256, 274, 291, 299 of enzymes 18, 72, 85, 144, 269, 272, 295 of enzymes, influence on kinetic parameters 68–72 of microorganisms 88, 92, 166 of probes 128, 131 immobilized enzyme 68, 69, 77, 83–84, 230 immobilized microorganism 88, 92, 166 immune system 105, 110, 112 immunoaffinity sorbents 310 immunoassay 1, 6, 105–124, 140, 150, 158, 159, 203, 211, 222, 249, 250, 266, 272, 275, 407 competitive 112, 117, 118–119, 152, 154, 261, 273 enzyme 118 fluorescence polarisation (FPIA) 35 heterogeneous 118–119, 152, 154, 162 homogeneous 118 non-competitive 117 immunoconjugate 108, 109, 110, 116, 154 immunogen 108 immunoglobulin (Ig) 105, 156, 157, 204, 263 (see also “antibodies”) immunoprobe 151, 152, 158–160, 161, 162 immunosensor 116, 117, 118, 119, 120, 141, 203–211, 251, 253, 260–265, 407

electrochemical 204, 205, 261 optical 28–51, 261–265 impedance, impedimetric 5, 6, 10, 20–24, 25 Warburg 21 index of toxicity,—toxicology 85, 142 indigo white 144 indium (In) 214, 215 indoxyl acetate 144 induction, inductor 93, 94, 168, 192, 289 inductively coupled plasma (ICP) 374 inductively coupled plasma optical emission spectrometry (ICP-OES) 372–381 inhibition 95, 140, 141, 187, 227–228, 250, 255–260, 271 assays for heavy metals 220 constant (Ki) 77, 78, 79, 81, 82 competitive 77, 78–79, 151, 257 irreversible 78, 82–83, 85, 145, 257 mixed-type 81 non-competitive 77, 79–80, 83, 257 reversible 77–81, 83, 257 uncompetitive 77, 80–81 inhibitor 6, 77, 78, 82, 83, 84, 97, 98, 141–145 injector 52–54 inorganic compounds 368–404

insecticide 76, 140, 141, 254, 257, 406 integrated Michaelis-Menten equation 67 integrated optics 41, 45 intercalator, intercalating 126, 129, 130, 132 interference, interfering 1, 8, 14, 15, 16, 54, 137, 248, 253–254, 255, 263, 277 isotope 379 M/Z 378 matrix 379 salt 379 transport 379 interferometer 41–42, 158, 263 interlaboratory studies 351–354 inuctively coupled plasma mass spectrometry (ICP-MS) 376–381 invertase 76 ion chromatography 394 ion electrodes 6 ion selective electrode (ISE) 7, 8–10, 52, 90, 228 Ionization atmospheric pressure (API) 311, 340, 344–347 atmospheric pressure chemical (APCI) 311, 340, 342, 344–347 electron impact (EI) 324, 325, 326 negative chemical (NCI) 324–327 ionspray (ISP) 311, 340–344

ioxynit 256 iron 100, 215, 387 irreversible inhibition 78, 82–83, 145 ISE 7, 8–10, 52, 90, 228 ISFET 10–11, 142, 221 isoelectric focussing (IEF) 395 isotachophoresis (ITP) 395 isotope interference 379 ISP 311, 340–344 Issatchenkia orientals 169, 171, 172, 173, 175, 176, 177

kcat 63, 64, 68 Ki 77, 78, 79, 81, 82 kinetic 77, 154, 158 approach 66, 93, 167, 407 constant 63–65, 112 constants, apparent 69, 70 control 71, 74, 83, 91, 228 parameters, influence of enzyme immobilization on 68–72 Km 64–74, 77–81, 94, 95, 294, 296 Kretschmann-type 38

label, labelled compound 34–36, 117–119, 130, 131, 151, 154, 160–162, 204, 205, 268, 272

label-free 118, 151, 158–160, 162 laccase 185, 271 lactate 89, 90, 185, 187, 235 lactose 94, 169 Lambert-Beer law 66, 368 Lamp electrodeless discharge (EDL) 370, 371 hollow cathode (HCL) 370, 371 LAPS 142 law of Moseley 383 LC 310, 311, 329–347 lead (Pb) 76, 96, 168, 215, 218, 220, 221, 387 legislation, legal 3, 137, 138, 140, 185, 205, 216, 251, 285, 295, 408 leucine aminopeptidase (LAP) 76 L-glycerophosphate oxidase 76, 80, 83 ligand design 274–276 light chain 106, 107, 113 limits of detection 130, 157, 159, 183, 184, 185, 187, 194, 195, 196, 197, 198, 199, 201, 206, 211, 228, 230, 231, 233, 241, 254, 256, 258, 259, 274, 290, 291, 294, 299, 310, 405 linear enzyme sequences 73 linear range, measuring range 74, 183, 197, 229, 230, 233, 237, 295, 299, 300, 301 linearization 120, 121 Lineweaver-Burk 72, 77, 79 linuron 256, 312

lipase 76, 271 lipids 97, 168, 179 Lipomyces sp. 171 liposome migration 261, 262, 268 liquid chromatography (LC) 310, 311, 329–347 liquid solid extraction (LSE) 55, 249, 310, 311–320, 327–329, 333, 338 liquid-liquid extraction (LLE) 55, 249, 310, 311–320 L-lactate dehydrogenase (LDH) 76 logit-log model 120, 121 luciferase 88, 95, 96, 195, 219, 267 luminescence 89, 90, 166, 219, 229, 260 lux genes 95, 96, 90, 196, 267

M/Z-interference 378–379 Mach-Zehnder 41, 45, 158 malathion 256, 257, 340 maltose 89, 94, 169, 206, 232 maltose phosphorylase 232, 233 mancozeb 145 maneb 145, 146 manganese (Mn) 214, 215 mass fabrication; production 6, 10, 20, 25, 110, 259, 275

mass spectrometry (MS) 310, 311, 325–327, 335–347, 376–381 mass transport limitation 153, 158, 159 matrix 1, 2, 5, 30, 31, 54, 120, 240, 248, 251, 254, 259, 260, 263, 275 matrix effects 68, 118, 137, 157, 254, 255, 263 matrix interferences 310, 325, 379 maximum values 242, 243 mean values 241–242 measureable radiation power 373 measuring frequency 5, 167 measuring range, linear range 74, 183, 197, 229, 230, 233, 237, 295, 299, 300, 301 MECC 395, 396 mediator 14, 16–17, 74, 90, 183, 236, 256, 271, 272, 274, 286, 290, 294, 298 membrane chamber 54, 56, 58 mercaptoethanol 271 mercuric reductase 220 mercury (Hg) 76, 80, 83, 100, 168, 214–216, 218, 219, 220, 221, 222, 372 promoters inducible by 218, 219 mesityloxide 194 metabolic sensors 250, 255 metabolism, metabolic 192, 193, 195, 197, 200, 248, 250, 266, 296 metalloenzymes 221 metallothionein 96, 220 methane 101, 286

-oxidising bacterium 286 methyl parathion 256 methylmercury 214, 215, 216 Methylomonas flagellata 101, 286 Micellar electrokinetic capillary chromatography (MECC) 395, 396 Michaelis-Menten kinetic 63–65, 70, 72, 78, 94, 95 microbial sensor 87–105, 137, 140, 165–181, 192–203, 266 microelectrodes 19–20 microorganism 89, 90, 97, 131, 165, 169, 172, 175, 211, 250, 406 Microtox, application for heavy metals 216, 218, 222 microwellplate, microtiter plate 110, 111, 150, 151, 152, 154, 157, 162, 273, 407 Mie scattering 30 mineral oil hydrocarbon 266 miniaturisation, microsystem 6, 8, 10, 15, 19, 20, 25, 38, 45, 46, 162, 205, 266, 407 mismatch 129 mixed-type inhibition 81 mobile homes 293 mode coupling 37, 39–41 negative ionization 337, 339, 342 positive ionization 337, 339, 341 TE-, TM- 32, 33, 37–40 thickness-shear (TSM) 131

molecular imprinting 274–276 molybdate method, phosphate determination 226 monoclonal antibodies 110–112, 122, 156, 157 MS 310, 311, 325–327, 335–347, 376–381 muconic acid 192, 193 multichannel, multianalyte 154, 204, 205, 211, 247, 251, 382 multielement-AAS 371 multireceptor 87, 99, 169 mutagenicity 87, 206, 216, 407 mutation 129, 130 myeloma cells 110, 111

NAD(P) 63, 97, 230, 293, 294, 299 NAD(P)H 17, 66, 146, 187, 230, 236, 294, 297–301 nanotiter plates 45, 48 naphtalene 95, 101, 192, 193, 195, 196, 197 N-BOD 97, 267, 268 NCI 324–327 nebulizer direct injection (DIN) 375 pneumatic 340, 375 ultrasonic 375 negative chemical ionization (NCI) 324–327

negative ionization mode 337, 339, 342 Nernst diffusion 70 Nernst equation 6, 10 nitrate 100, 228, 235–238, 241, 396–400 nitrate reductase 236–237 nitrification 97, 98, 99 nitrifiers 97, 98 nitrilase 187 nitrilotriacetic acid 101 nitrite 97, 100, 235–237 nitrite reductase 235–237 Nitrobacter sp. 97, 100 nitrogen phosphorus detector (NPD) 310, 327 nitrophenol 194, 309, 333, 340, 348 Nitrosomonas sp. 97, 100 NMP 237 non-competitive immunoassay 117 non-competitive inhibition 77, 79–80, 83 non-specific 192, 255 non-specific binding 128, 158 NPD 310, 327 nucleic acid 1, 3, 106, 111 (see also “DNA”)

nucleoside phosphorylase 230, 231 Nyquist plot 24, 25

oestrogenic properties,—contaminants 45, 288 oligomer, oligonucleotide 130, 131 OPEEs 147 optical sensor,—transduction 1, 5, 28–51, 128, 154, 158 optode, optrode 33, 34, 45, 58, 88, 95, 100, 101 organic acids 142, 169, 185 organic media 146, 147 organic pollutants 137, 138, 139, 140, 166, 169, 182–213, 248–284, 309–367, 405 organic solvent 3, 55, 147, 152, 184, 187, 248, 252, 259, 262, 263, 268–274, 275, 290 organic-phase biosensor,—enzyme electrode (OPEE) 147, 266, 269, 298, 300 organochlorinated compounds 138 organophosphorous compounds,—insecticides,—pesticides 76, 77, 81, 82, 83, 85, 140, 141–145, 147, 192, 256, 257, 258, 259, 272, 309, 321, 324, 325, 326 oxidase 14, 77, 83, 85 oxygen 14, 17, 52, 88, 89, 90, 93, 96, 97, 138, 142, 143, 166, 192, 229, 232, 255, 285, 289, 298, 290 oxygen electrode 5, 13, 14–15, 89, 100, 101, 165, 166–181, 194, 197, 221, 227, 229, 257, 286, 291

PAH 185, 195–196, 206, 250, 266, 268 pairs of bases 124, 125, 132 parallelization 47–49, 162

Paraoxon 81, 142, 144, 256, 259, 260 PCB 101, 200, 201, 205, 250, 266, 268 PCP 108, 109, 139, 186, 187, 194, 199, 287, 333, 340, 348 PCR 112, 114, 129 Penicillium decumbens 286 Pentachlorphenol (PCP) 108, 109, 139, 186, 187, 194, 199, 287, 333, 340, 348 peptide nucleic acid (PNA) 129 perchloroethylene (PCE) 139 peroxidase 76, 119, 142, 145, 185, 187, 229, 259, 300, 349 (see also “horseradish peroxidase”) persistence 196, 309 pesticide 6, 76, 84, 108, 140–165, 187, 204, 248–284, 287, 311–316 pH 10, 142, 247, 253 glass electrode 8, 9, 52, 258 phage display system 112 phase shift; difference 30, 33 phenazine ethosulphate (PES) 90 phenol 94, 100, 138, 146, 192, 193, 194–195, 199, 201, 268, 269, 285, 287–292, 311–316, 333, 343 vapour 285, 291–292 phenolic compounds 6, 19, 140, 182–185, 211, 241, 309 Phosphate 100, 140, 226–235, 256 as enzyme substrate 228–233

determination, enzyme inhibition 227–228 determination, molybdate method 226 occurrence 226 Phosphorescence 30 phosphorylase a 230 phosphorylase, maltose 232, 233 phosphorylase, nucleoside 230, 231, 232 photobacteria 89, 90 Photobacterium phosphoreum 166, 170 photoluminescence 89 photosynthesis 140, 146, 256 physiological response,—state 89 piezoelectric crystal 89, 128, 131, 294, 295 plasma cells 108, 109 plasmid 95, 96, 267 platinum electrode 215 pneumatic nebulizer 340, 375 poly(carbamoylsulfonate) (PCS) 237 poly(ethyleneglycol) (PEG) (ENT) 91, 269 poly(propyleneglycol) (ENTP) 91 polyacrylamide 142, 143, 236, 290 polychlorinated biphenyl (PCB) 199, 200, 201, 205, 250, 266, 268 polyclonal antibodies 108–110, 122, 157

polycyclic aromatic hydrocarbons (PAHs) 185, 195–196, 206, 250, 266, 268 polymerase chain reaction 112, 114, 129, 407 polymeric sorbents 316, 317, 318 polyphenol oxidase 268, 271, 285, 288–292, 349 polypyrrole-viologen carbon disk electrode 237 polypyrrole film,—membrane 146, 183, 290, 299 positive ionization mode 337, 339, 341 potential 6–9, 12, 14 potentiometric, potentiometry 5, 6–11, 24, 74, 88, 89, 142, 235, 257, 286 precolumn technology 310, 321, 324, 323 pre-incubation 78, 158, 160, 161, 171, 262 prism 38, 39, 120 probe, DNA-, PNA- 127, 128, 129, 131, 406 promoters, heavy metals inducible 218, 219 propionic acid 146 protease 107, 171, 174 protein A 107, 153, 156, 157, 275 protein G 107, 153, 156, 157 proteins 97, 106, 152, 153, 157, 160, 168, 171, 179, 269 Pseudomonas fluorescence 95, 96, 101, 196, 197, 266 Pseudomonas oxalaticus 101 Pseudomonas putida 101, 168, 170, 172, 194, 195 198, 199 Pseudomonas sp. 93, 170, 194, 255, 266, 286

purine 124 PVA-SbQ 143, 144, 145, 229 pyrethrins 140 pyrethroides 140 pyrimidine 124 pyrocatechol 194 pyruvate 89, 90, 94, 147, 197, 229 pyruvate kinase 76 pyruvate oxidase 76, 228, 229, 230

quadrupole 377 quartz-crystal microbalance (QCM) 131 quenching 34 quinoprotein alcohol dehydrogenase 296

radiation power 373 Ralstonia 198, 199, 201 Raman scattering 30 Randless equivalent circuit 22 Rayleigh scattering 29, 30 reaction chamber, reactor 56–57, 154, 155, 156 reactivation 78, 82, 84, 145 receptor 1, 3, 5, 31, 108, 161, 162, 250, 274, 275, 394, 405, 406, 407

recognition system 250, 274, 275, 407 recombinant antibodies 112–114, 153 recovery 258, 259, 312, 313, 321 recycling, enzyme substrate 75, 231, 232, 291 redox cycling 18 redox electrode 6, 7 redox indicator 129, 130 reference electrode 7, 8, 10, 13 reflection 31, 32, 38 total internal 31 total internal fluorescence 33, 151, 161, 162 reflectometric interference spectroscopy (RIfS) 43–44, 47, 158, 159, 263 reflectometry 42–43 refraction, refractive index 30, 31, 32, 33, 36, 37, 38, 119 refractometry 36, 262 regeneration 59, 129, 130, 152, 153, 155, 156, 157, 158, 204, 205, 207, 263 reliability, reliable 3, 19, 137, 157, 187, 204, 211, 228, 255, 277, 285 reproducible 53, 161, 169, 258, 277 resistance 21, 22, 23, 24, 91 resonant mirror 40, 131 respiration 88, 89, 91, 93 response rate,—time 13, 91, 194, 196, 197, 198, 204, 256 reverse micelles 146, 147, 269, 295, 301

reversible binding,—immobilization 59, 115, 156, 157 reversible inhibition 77–81, 98 Rhodococcus erythropolis 169, 171, 172, 173, 175, 176, 177 Rhodococcus sp. 94, 100, 101, 187, 192, 193, 194, 195, 198, 199, 201 Rhodotorula sp. 100, 194, 201 RIfS 43–44, 47, 158, 159

Saccharomyces cerevisiae 96, 226 salicylate, salicylic acid 95, 193, 196, 197, 228, 267 salt interference 379 SAMOS 332 Sample preparation 240, 246, 251–254, 255, 259, 277 pretreatment 2, 3, 54, 55, 58, 204, 235, 311, 336 transport 245–246 sampling 239–248, 309 depth 243–245 grid 243 plan 244 protocol 241 rate,—frequency 52, 58 schemes 243 step 240

strategies 3, 241–243, 246, 309 technologies 241 Sauerbrey equation 131 scattering Mie 30 Raman 30 Rayleigh 30 scintillation detector 385 screen-printed electrodes 129, 132, 154, 183, 184, 259, 274 selected ion monitoring (SIM) 344–346 selectivity 7, 14, 36, 87, 93–99, 108, 114, 116, 122, 129, 132, 142, 152, 160, 184, 192, 228, 255, 267, 292, 302, 311 selenium (Se) 214, 215 self-assembly, self-assembled 128 sensitive, sensitivity 1, 3, 5, 8, 10, 11, 13, 18, 25, 31, 36, 38, 47, 74, 83, 84, 87, 91, 93, 99, 116, 117, 128, 132, 141, 142, 150, 151, 152, 153, 156, 160, 162, 168, 169, 172, 192, 193, 196, 198, 226, 255, 262, 277, 285, 311 separation 54–56, 118, 119, 151, 154, 299, 324, 394–396, 397–400 sequence, (of nucleobases) 124, 126, 130, 133 Serratia marcescens 90 silver (Ag) 76, 215 simazine 159, 161, 312, 330 single photon counting 35 single-stranded DNA,—probe 127, 129, 130 skimmer 377

slurry 241, 243, 375 soil 239–284 solid phase extraction (SPE) 55, 253, 310, 320 sources of errors 241 spark and laser ablation 377 specific, specificity 1, 2, 5, 9, 17, 61, 65, 85, 87, 89, 106, 110, 128, 137, 141, 156, 192, 193, 195, 196, 220, 226, 277, 285, 302 speed of analysis 1 Sphingomonas 196, 197 SPR 32, 37, 38–39, 44, 112, 119, 159, 262 stability, stable 2, 17, 75, 87, 91, 99, 114, 128, 130, 137, 147, 153, 156, 157, 169, 182, 183, 198, 228, 231, 299, 300, 301 stabilization 320–324 starch 97, 168, 171, 174, 179 streptavidin 143, 153, 155, 157 Streptococcus sp. 94 substrate assays for heavy metals 220 substrate recycling 75, 231, 232, 291 sucrose 89, 94, 169 sulfate 100 sulfide 100 sulfite 100 sulfonylurea 76, 146, 256 sulfur dioxide 100

supercritical fluid extraction (SFE) 249, 253, 317 surface loading 153, 158 surface plasmon resonance (SPR) 32, 37, 38–39, 44, 112, 119, 159, 262 surface water 137, 182, 244, 256, 262, 397 surface-acoustic wave (SAW) 131 surfactant 83, 101, 138, 286, 396 synzymes 147

T lymphocytes 108 target (DNA) 127, 129 TCDD 108, 109 tellurium 214, 215 TE-modes 32, 33, 37–40 tetracyanoquinodimethane (TCNQ) 90, 144, 145, 230, 290, 298, 300 tetrathiafulvalene 90 thallium (Tl) 215 thermistor 89, 90 thermophile microorganism 147 thermospray (TSP) 337–340 thickness-shear mode (TSM) 131 Thiele module 71 Thiobacillus thiooydans 100 thiocarbamate 140

thiocholine 142, 144, 145 thiourea 79, 271 thylakoid membranes 146, 256 thymine (T) 124 time of analysis 137, 195, 262, 263 (see also “sampling frequency”, “frequency of analysis”, “measuring frequency”, “speed of analysis”) tin (Sn) 214, 215 TIRF 33, 151, 161, 162 TMB-4 82, 145 TM-modes 32, 33, 37–40 TNT 204, 266 TOL plasmid 195 toluene 196, 197, 270 Torulopsis Candida 170 total internal reflection 31, 160 total internal reflection fluorescence (TIRF) 33, 151, 161, 162 toxic, toxicity 3, 6, 85, 87, 99, 132, 137, 140, 141, 167, 168, 185, 192, 196, 199, 213, 216, 220, 222, 235, 250, 257, 285, 309, 310, 405 of heavy metals 168, 214, 218 index of-, toxicology index 85, 142 toxicology 97, 254 tracer 117–119, 121, 151, 152, 154–157, 160, 161, 264 transducer 154, 155, 158, 291

transformation products (TPs) 338 transition probability 373 transport 69, 70, 89, 93, 161 transport interference 379 triazine 76, 140, 146, 261, 262 trichlorobenzene (TCB) 139 trichloroethylene (TCE) 139 Trichosporon brassicae 296 Trichosporon cutaneum (beigelii) 94, 100, 101, 168, 170, 171, 172, 173, 176, 177, 194, 198, 199, 266 TSP 337–340 tyrosinase 76, 140, 145–147, 182–185, 187, 211, 268, 269, 271, 289, 291, 349

ultrasonic nebulizer 375 uncompetitive inhibition 77, 80, 81 unlabelled compound 119 unspecific 192, 255 urea 97, 100, 129, 186, 298 urea herbicides 140, 256 urease 76, 79, 81, 97, 100, 220, 221 uricase 231, 232

validation 133, 137, 140, 144, 159, 184, 354–356 vapour

ethanol 285, 286, 295–301 formaldehyde 186, 285, 294–295 phenol 285, 291, 292 variable region 107 Vibrio fischeri 96, 196, 218 Vibrio harvey 96 viologen 236, 237 Vmax 64–74, 78–81, 94 volatile organic carbons (VOCs) 286, 287 volatile, volatility 56, 99

Warburg impedance 21 waste water 97, 98, 137, 139, 165–180, 185, 226 water 137–237 drinking 137, 182, 185, 226, 235 ground 137, 235, 244, 254, 262, 322 quality 137 Watson-Crick base pair 126 waveguide 31–33, 36–39, 159–162, 262 whole cell 1, 3, 61, 405 biosensors for heavy metals 218 biosensors, bioluminescent 218 sensor 255, 256, 266, 267, 286

(see also “microbial sensor”) Woolf-Hofster plot 77 working electrode 13, 14, 16, 259, 273

xanthine oxidase 187, 230, 231, 232 Xanthobacter autotrophicus 200, 201 xylene 196

yeast 96, 169, 291, 296

zinc (Zn) 76, 85, 96, 168, 214, 215, 219, 220, 221, 222, 294, 297 zineb 145 ziram 145, 146

Colour plate 1. Production of monoclonal antibodies. See page 111.

Colour plate 2. Comparison of non-competitive (a) and competitive immunoassays (b). See page 117.