2015 nova advances in biosensors ch 3.pdf

7/21/2019 2015 Nova ADVANCES IN BIOSENSORS ch 3.pdf

http://slidepdf.com/reader/full/2015-nova-advances-in-biosensors-ch-3pdf 1/135Complimentary Contributor Copy


http://slidepdf.com/reader/full/2015-nova-advances-in-biosensors-ch-3pdf 2/135Complimentary Contributor Copy


http://slidepdf.com/reader/full/2015-nova-advances-in-biosensors-ch-3pdf 3/135

BIOTECHNOLOGY IN AGRICULTURE, INDUSTRY AND MEDICINE

ADVANCES IN BIOSENSORS

R ESEARCH

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no

expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No

liability is assumed for incidental or consequential damages in connection with or arising out of information

contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in

rendering legal, medical or any other professional services.

Complimentary Contributor Copy



BIOTECHNOLOGY IN AGRICULTURE,

INDUSTRY AND MEDICINE

Additional books in this series can be found on Nova’s websiteunder the Series tab.

Additional e-books in this series can be found on Nova’s website

under the e-book tab.




BIOTECHNOLOGY IN AGRICULTURE, INDUSTRY AND MEDICINE

ADVANCES IN BIOSENSORS

R ESEARCH

THOMAS G. EVERETT

EDITOR

New York




Copyright © 2015 by Nova Science Publishers, Inc.

All rights reserved. No part of this book may be reproduced, stored in a retrieval system or

transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher.

For permission to use material from this book please contact us:

[email protected]

NOTICE TO THE READER

The Publisher has taken reasonable care in the preparation of this book, but makes no expressed

or implied warranty of any kind and assumes no responsibility for any errors or omissions. No

liability is assumed for incidental or consequential damages in connection with or arising out of

information contained in this book. The Publisher shall not be liable for any special,consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or

reliance upon, this material. Any parts of this book based on government reports are so indicated

and copyright is claimed for those parts to the extent applicable to compilations of such works.

Independent verification should be sought for any data, advice or recommendations contained in

this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage

to persons or property arising from any methods, products, instructions, ideas or otherwise

contained in this publication.

This publication is designed to provide accurate and authoritative information with regard to thesubject matter covered herein. It is sold with the clear understanding that the Publisher is not

engaged in rendering legal or any other professional services. If legal or any other expert

assistance is required, the services of a competent person should be sought. FROM A

DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE

AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS.

Additional color graphics may be available in the e-book version of this book.

Library of Congress Cataloging-in-Publication Data

Advances in biosensors research / Editors: Thomas G. Everett.

pages cm. -- (Biotechnology in agriculture, industry and medicine)

Includes index.

1. Biosensors. I. Everett, Thomas G., 1962- editor.R857.B54A385 2015

610.28--dc232014045009

Published by Nova Science Publishers, Inc. † New York

ISBN: (eBook)


mailto:[email protected]

mailto:[email protected]



CONTENTS

Preface vii

Chapter 1 Molecular Imprinting Technology inAdvanced Biosensors for Diagnostics 1

Zeynep Altintas

Chapter 2 Electronic Tongue: Applications and Advances 31

Nadja K. L. Wiziack, Juliana Coatrini Soares, Benjamin D. Padovan, Osvaldo N. Oliveira, Jr.

and Fabio L. Leite

Chapter 3 Inorganic Hydrogels for Whole-Culture Encapsulation 57

Mercedes Perullini, Cecilia Spedalieri,

Matías Jobbágy and Sara A. Bilmes

Chapter 4 Biosensors for Atrazine Determination: A Review 75

M. T. Beleño, M. Stoytcheva, R. Zlatev,

G. Montero, R. Torres and B. Jaramillo

Chapter 5 Microbial Biosensors for Methyl Parathion:From Single to Multiple Samples Analysis 89

Jitendra Kumar and Jose Savio Melo

Index 113




PREFACE

This book discusses advances in biosensors research.Chapter 1 - The advances in biosensors have improved the current

diagnostics profile as giving possibility for point-of-care tests, development of personalised medicine and combination of diagnostics with therapeutics. Themost important improvements include biomarker discovery, affinity receptordesign, detection of infectious microorganism and disease diagnostics due toclose interaction of nanotechnology with other technologies which play criticalrole for the future of biosensors and health care. Biosensing technology is afascinating field which provides reliable, rapid and sensitive platforms forspecific and ultra-sensitive biomarker-based diagnosis of the diseases such ascancer, diabetes, infectious diseases and neurodegenerative disorders. Thistechnology can also be used for the detection and removal of toxic materialsfrom human body such as cadmium, iron, aluminium and mercury. However,the currently available recognition elements including antibodies, aptamers,DNA or RNA-based probes are not enough to cover all these research works.

Hence, there is a need to provide artificial affinity ligands for a wide range oftargets detection to improve the efficiency and utilization of biosensors.Molecular imprinting technology is an emerging technology to fulfil this gapin the area which supplies highly stable artificial receptors that show selectivemolecular recognition characteristics due to the recognition regions within polymer matrix which are complementary to the target in positioning offunctional groups and shape. Moreover, the binding affinities obtained forthese synthetic receptors are similar to the natural recognition systems such as

antibodies. The advances using molecular imprinting are to overcome thedrawbacks and limitations of current systems while improving the accuracy ofthe diagnosis and the development of personalised medicine which play vital




Thomas G. Everettviii

role in health care diagnostics. This chapter will cover molecular imprintingtechnology, the applications of molecular imprinting in the development ofrapid diagnostics such as bio-sensing devices for healthcare applications.

Chapter 2 - An Electronic Tongue (E-tongue) is an array of sensors ofvarying composition used in unison to analyze the electrical response and thus perform a quantitative and discriminative classification of a liquid sample. Aunique fingerprint is established from this electrical response using patternrecognition and data analysis methods. E-tongues can work according tovarious operating principles, based mainly on electrochemical methods andimpedance spectroscopy, while the sensing units are normally made ofnanostructured films. In this Chapter the authors discuss the fabrication and

use of E-tongues for various applications, including in the pharmaceuticalindustry, food and beverage sector, and monitoring of water quality. Anextension of the E-tongue concept to include highly selective sensing units isalso discussed, particularly with the possible use in clinical diagnosis whichrequires sophisticated computational and statistical methods.

Chapter 3 - Sol-gel encapsulation of living cells within inorganichydrogels, mainly silica, is a promising technology for the design of biosensors. These host-guest functional materials maintain specific biologic

functions of their guest while the properties of the host can be tuned to fulfillthe requirements of particular applications. Inorganic immobilization hostsexhibit several advantages over their (bio)polymer-based counterparts. While both hosts provide tailored porosity, the former offers enhanced chemicalstability towards biodegradation as well as higher physical stability (lowswelling). However, inone-pot encapsulations, the direct contact of cells with precursors during the sol-gel synthesis and the constraints imposed by theinorganic matrix during operating conditions may influence the biological

response. In order to prevent this, an alternative two-step procedure was proposed. Living cells are pre-encapsulated in biocompatible carriers based on biopolymers such as alginates that confer protection during the inorganic andmore cytotoxic synthesis. By means of these carriers, whole cultures ofmicroorganisms remain confined in small liquid volumes generated inside theinorganic host, providing near conventional liquid culture conditions.Moreover, this approach allows the encapsulation of multicellular organismsand the co-encapsulation of multiple isolated cultures within a single common

monolithic host, creating an artificial ecosystem in a diminished scale isolatedinside a nanoporous matrix that would allow ecotoxicity studies to be carriedout in portable devices for on-line and in situ pollution level assessment.




Preface ix

Chapter 4 - Atrazine is one of the most widely used herbicides for weedstreatment in crops. Nevertheless, its toxicity, high persistence and low biodegradation rate provoke serious environmental and health problems.

Having in mind that atrazine use is not restricted in USA and Latin America,the analytical determination of atrazine residues in food, drinking water, andenvironmental samples is of primary importance. Thus, in this report differentmethods currently applied for atrazine analysis are reviewed, emphasizingthose that use biosensor technology. The principle of functioning of theelectrochemical, optical and piezoelectric biosensors is detailed, consideringthese devices as a reliable tool for atrazine quantification.

Chapter 5 - Methyl parathion (MP) is an organophosphate (OP) compound

which is being used as non-systemic insecticide in agriculture to protect thecrops. However MP can cause many health problems in humans related toacetylcholinesterase inhibition such as impaired memory and concentration,disorientation, severe depression etc. Also, when inhaled its immediateadverse effects are a bloody or runny nose, coughing, chest discomfort anddifficulty in breathing. It is thus classified by the World Health Organization(WHO) as Category Ia (extremely toxic) and by the United StatesEnvironmental Protection Agency (US EPA) as Toxicity Category I (most

toxic) insecticide. Although banned in developed countries like US and Japanit is still being used in developing countries like India as a restrictedinsecticide. Presence of this insecticide is thus expected in the soil samples,water resources and even in food materials across countries still using this pesticide. Therefore, economically feasible, rapid, sensitive, selective andreliable methods for detection of MP are necessary. Also required are methodsto monitor a large number of samples in a short period of time. Thus there has been an intense effort to develop biosensors for the detection of methyl

parathion. Microbial biosensors are a good alternative to enzyme biosensors because they provide the benefits of low cost and improved stability to theenzymes.

This chapter thus aims to review the status of research in this field besidesthe work that is being carried out in our laboratory on microbial based biosensors for the detection of single to multiple samples of MP.




In: Advances in Biosensors Research ISBN: 978-1-63463-652-0Editor: Thomas G. Everett © 2015 Nova Science Publishers, Inc.

Chapter 1

MOLECULAR IMPRINTING TECHNOLOGY INADVANCED BIOSENSORS FOR DIAGNOSTICS

Zeynep Altintas

Biomedical Engineering, Cranfield University,Bedfordshire, England, UK

ABSTRACT

The advances in biosensors have improved the current diagnostics profile as giving possibility for point-of-care tests, development of personalised medicine and combination of diagnostics with therapeutics.The most important improvements include biomarker discovery, affinityreceptor design, detection of infectious microorganism and disease

diagnostics due to close interaction of nanotechnology with othertechnologies which play critical role for the future of biosensors andhealth care. Biosensing technology is a fascinating field which providesreliable, rapid and sensitive platforms for specific and ultra-sensitive biomarker-based diagnosis of the diseases such as cancer, diabetes,infectious diseases and neurodegenerative disorders. This technology canalso be used for the detection and removal of toxic materials from human body such as cadmium, iron, aluminium and mercury. However, thecurrently available recognition elements including antibodies, aptamers,

DNA or RNA-based probes are not enough to cover all these research

Corresponding author: Zeynep Altintas. Biomedical Engineering, Cranfield University,Bedfordshire, MK43 0AL, England, UK. E-mail: [email protected].




Zeynep Altintas2

works. Hence, there is a need to provide artificial affinity ligands for awide range of targets detection to improve the efficiency and utilizationof biosensors. Molecular imprinting technology is an emerging

technology to fulfil this gap in the area which supplies highly stableartificial receptors that show selective molecular recognitioncharacteristics due to the recognition regions within polymer matrixwhich are complementary to the target in positioning of functional groupsand shape. Moreover, the binding affinities obtained for these syntheticreceptors are similar to the natural recognition systems such asantibodies. The advances using molecular imprinting are to overcome thedrawbacks and limitations of current systems while improving theaccuracy of the diagnosis and the development of personalised medicinewhich play vital role in health care diagnostics. This chapter will covermolecular imprinting technology, the applications of molecularimprinting in the development of rapid diagnostics such as bio-sensingdevices for healthcare applications.

1. INTRODUCTION

Molecular imprinting is a technique for the formation of tailor-made

binding regions with the memory of functional groups, shape and size of thetarget molecules which is called as template in molecular imprintingtechnology (MIT). Molecularly imprinted polymers (MIPs) is synthesized bycopolymerisation of the functional monomers and cross-linkers with theinhesion of template molecules. The template needs to be removed after polymerisation and the imprints have recognition cavities complementary tothe template in size and shape with the chemical functionality as in enzyme-substrate interactions. The synthesized MIPs selectively bind to the target

template and lead to recognition of the template in the presence of mixedmedia which contains closely related compounds such as different pharmaceuticals, peptides, endocrine disrupting compounds and toxins [1].

MIPs show important advantages compared to the naturally occurredreceptors such as antibodies and enzymes. The average production cost ofthese artificial ligands is much less and the production is much easier than theantibodies and enzymes. Moreover, they are highly stable against harshconditions with a long shelf-life and it is possible to use MIT for the

production of a wide range of compounds with the aim of specific recognition,detection and separation [2]. Owing to these fascinating characteristics of theartificial recognition elements, MIPs have become attractive in various fields




Molecular Imprinting Technology in Advanced Biosensors … 3

including chromatographic separation, solid-phase extraction (SPE),membrane filter applications and the construction of biomimetic sensors [3-5].

They can be synthesized using two main techniques; one is based on non-

covalent interactions between the template molecule and the functionalmonomers whereas the other relies on reversible covalent bonds. Covalentimprinting provides more homogenous binding regions distribution due to thehigh stability of covalent bonds; however, this method is less flexible becauseof the creation of identical rebinding coupling that entails reversible covalentinteractions between functional monomers and the templates [6]. Although itis important to obtain homogenous binding sites distribution on thesynthesized imprinted polymers, a vast number of templates are not suitable

for covalent imprinting.Furthermore, the strong covalent interaction is a crucial problem to reach

the thermodynamic equilibrium which affects the speed of binding anddissociation. On the other hand, non-covalent imprinting is not subjected tothese drawbacks since the template-monomer interactions are based onhydrogen bonding, pi-pi interactions, ionic interplays and/or van der Waalsforces. When the polymerisation and the template removal are completed, the produced MIPs can then rebind to the template through the same non-covalent

interactions and this feature makes the method applicable for a great numberof compounds to be successfully imprinted without having major limitations[7]. Hence, non-covalent imprinting has been the most commonly used production technique in recent years with increasing achievement in manyscientific and industrial fields.

MIPs can be used as chromatographic support material for difficultseparations, catalytic polymers or artificial enzymes, the mimic of biologicalreceptors and recognition elements for biosensors. The usage of biosensors in

diagnostics has a high demand due to the rapid, cost-effective, highly sensitiveand specific detection principles without a time-consuming technology. Theadvances in nanotechnology enormously expand the profile of biosensing platforms with the contribution of biomarker discovery, microelectronics and polymer sciences. Recognition elements are one the most important parameters in sensor technology and it is not possible to find target specificantibodies, enzymes or DNA/RNA probes for the detection/recognition ofmany crucial compounds. Therefore, MIT has fulfil this gap as providing

synthetic receptors for the specific detection and separation of biomarkers,viruses, peptides as well as for chemical elements such as iron, copper,aluminium which are toxic for human body in particular levels. This chapterwill cover molecular imprinting, molecular recognition elements, biosensors




Zeynep Altintas4

and application of MIPs in advanced biosensors, and the future prospects in

the field.

2. MOLECULAR IMPRINTING

Molecular imprinting is a procedure where functional monomers and

cross-linking molecules are co-polymerised in the existence of the target

template which is aimed to imprint (Figure 1). The polymerisation reaction is a

complex process which is affected by various factors including the type and

amount of the monomer, cross-linker and solvent; the time and type of

polymerisation; the volume of polymerisation mixture and the polymerisation

conditions. For a successful synthesis, all of these parameters need to be

optimised and the polymerisation conditions should be carefully regulated to

prevent from batch to batch variations. Due to the time-consuming process of

MIP production, an enormous effort is given to investigate the effect of these

parameters on the recognition characteristics of the synthesized polymers [7].

Figure 1. General principle of MIP synthesis.





The template of interest should show some properties to be ideal forimprinting. The chemical groups belong to the template which can affect the polymerisation negatively should be got rid of and the template should

demonstrate accomplished chemical stability until the end of polymerisation.Moreover, the template should possess functional chemical groups which giveopportunity for assembling with functional monomers very well. Manydifferent molecules can be used as the template including toxins, pharmaceuticals, endocrine disrupting compounds, viruses, peptides and toxicmetal ions. The size of template is an important point for a successfulsynthesis and the imprinting of bigger molecules such as viruses and proteinsare quite difficult which requires more investigation, optimisation and

verification [8]. Although natural bio-recognition receptors are much morefavourable for the sensing, detection and separation of these molecules, it isnot possible to find a convenient natural ligand for many biologicalcompounds. Therefore, the further improvements in MIT area have beencontinuing to provide both usable and reliable synthetic receptors for thequantification and diagnosis of biological molecules.

Not only the laboratory based investigations, but also the computationalsimulation approaches are crucial to increase the possibility of successful

imprints of these compounds. Molecular modelling studies have beenconducted in recent years to model the interactions and binding sites betweenthe target analytes and monomers based on binding energy. The positive,negative or neutral charge of the target analytes is important not only duringthe computational simulation but also for the polymerisation process. Hence,the selection of the monomers to be used in synthesis should be doneaccordingly. The best possible candidate monomers can be found and ordered based on binding energy scores through modelling investigations. Later on,

MIPs for the target molecule need to be produced and tested using the selectedmonomers separately. The success of each MIP production depending on themonomer should be investigated and verified employing different analyticaltechniques and the performance of the MIPs should be compared for thedetermination of affinity between the target analyte and each MIP [9].

The monomer is responsible to provide functional groups that constitute acomplex with the analyte by covalent or non-covalent interactions. The typeand strength of the binding between monomer and analyte influence the

affinity of the synthesized polymers and designate the selectivity and integrityof recognition regions. The stronger interactions lead to more stable template-monomer complex which provides higher binding capacity for the MIPs. Theimportance of monomer selection is obvious in MIT and different tools such as




Zeynep Altintas6

nuclear magnetic resonance, fourier-transform infrared spectroscopy,isothermal titration calorimetry and computer modelling need to be employedto be ensure that the correct functional monomers are selected to obtain more

stable complexes with target templates. The molar ratio between functionalmonomer and template is crucial for MIP production since it affects theimprinting performance and affinity. Higher molar ratios cause more non-specific binding and decrease the selectivity of MIPs whereas lower molarratios provide less binding regions in MIPs owing to fewer monomer-templatecomplexes. Therefore, optimisation of molar ratios between functionalmonomers and templates is another significant point to take into considerationfor the fate of MIP production [7].

The physical, chemical and recognition properties of the synthesized MIPsstrongly depend on the degree of cross-linking and on the nature of cross-linkers. Cross-linkers control the morphology of the polymer matrix, stabilisethe imprinted binding sites and give mechanical stability to the polymer matrixto keep its molecular recognition ability. The concentration of cross-linkers isgenerally higher than those of the template and functional monomers. Due tothe high content of cross-linking monomers, the formed structure does notcollapse when the template is removed from inside. The shape is maintained

what results in ideally adapted pores. This means of course that a minimumamount of cross-liner is needed to form a rigid enough polymer network. The best choices of cross-linkers are those which give the lowest binding energyand thus are the most inert towards the template molecule.

This way, MIPs are generated with less non-specific binding sites and ahigher imprinting factor, leading to higher specificity. The right selection isone of the most crucial steps in the synthesis because cross-linkers play a hugerole in securing the functional groups of the functional monomers in specific

locations and directions around the analyte.This way, the structure of the cavity is preserved. Ethyleneglycol dimethacrylate (EGDMA), N,N-methylenebisacrylamide (MBAA),trimethylol-propane trimethacrylate (TRIM) divinylbenzene (DVB) are theexamples for most commonly used cross-linking molecules in MIT.

The role of solvent is also important in polymerization. Before and during polymerization, the solvent acts as a porogen at the same time. It brings all thecomponents into one phase and creates the pores in the polymers. This means

it determines the morphological properties of porosity and surface area for better access of the imprinting binding sites. Large pores in the polymer matrixare necessary to ensure good flow-through properties. Therefore the solvent isalso known as the porogen.





Most common solvents used are chloroform, toluene, dichloromethaneand acetonitrile. Non-covalent imprinting is performed in aprotic andlow polarity organic solvents, for example chloroform, toluene or

dichloromethane. Complex formation is increased by facilitating polar non-covalent interactions. Polar protic solvents should be excluded because theylead to competition for interactions with both monomers and template and tendto dissociate the non-covalent interactions. Organic solvents are commonlyused, since they preserve the hydrogen and electrostatic interactions betweentemplate and monomer. To optimize rebinding it should be carried out in thesame solvent as used for imprinting [10, 11].

2.1. Production Methods of MIPs

In this section, a brief outline about the MIP production techniques isgiven. MIPs can be synthesized as employing various techniques and eachtechnique can be further improved based on application, template and aim.Since each method is more convenient for particular applications and targets,the selection of production technique has crucial importance to obtain

successful and effective MIPs.

2.1.1. Monolith

Monolith is the oldest production technique for molecularly imprinted polymers in which the polymer components are mixed together in a glass testtube, along with the solvent. The tube is sparged of oxygen using nitrogen gasand then allowed to polymerise for about 24 hours. Upon completion, theresulting polymer is a solid bar (monolith) in the test tube. The polymer is

removed from the tube and then ground down using a pestle and mortar to givea fine powder. The template is removed from the polymer by extensivewashing until the template can no longer be detected in the wash solution [12].The disadvantage of this method is that the ground polymer particles have awide size distribution. Tiny particles can cause problems in the application ofthe polymer. The particles are also not completely shaped, and so can packtogether tightly in a column and prevent a liquid phase passing through.Another major problem is template bleeding. Assuming an even distribution of

template throughout the polymer, a small amount template will remain in thecentre of the particles regardless of any washing that is carried out on the polymer. This template could in theory diffuse out through the polymer overtime and cause contamination of the experiments [13].




Zeynep Altintas8

Since millimolar amounts of template are used to produce the polymer,and the sensitivity of an assay might be in the picomolar range, the possibilityof contamination is quite high by this method.

This problem is more prevalent in MIPs created against larger templates,such as proteins and viruses. Since the template is larger, there is reduced masstransport and the template is often trapped within a polymer structure that ishighly cross linked. If the extent of cross linking is reduced then the templatewill be slightly easier to extract, but this will have adverse effects on thestability and selectivity of the polymer. However, with the improvement of thetechnique using new approaches can lead to successful production. Szumski etal. worked on monolith based extraction columns for aflatoxins isolation and

the columns were prepared in fused-silica capilleries by UV or thermal polymerization in two-step procedure. The extraction capillary columns wereevaluated for hydrodynamic and chromatographic features. Retentioncoefficients for aflatoxin B1 and DMC were used for determination of theselectivity and imprinting factor. The obtained results indicate that thetemperature of photografting and concentration of the grafting mixture havekey role on the synthesized MIPs quality. From the MIP columnscharacterized by the highest permeability the column of the highest imprinting

factor was applied for isolation of aflatoxins B1, B2, G1 and G2 from themodel aqueous sample followed by on-line chromatographic separation [14].

2.1.2. Precipitation

A more recent development in the MIP community involves using thesame ratio of functional monomer(s), template and cross linker, but using agreater amount of solvent. The reaction mixture is then left for only two hoursto polymerise. In this method, the monomer/template complexes form into

considerably smaller entities as they are dispersed throughout the solvent. Thecross linker then forms these into particles which precipitate out of solutionand remain as small particles, not a single polymer monolith. The advantage ofthis method over the monolith method is that since the product is already particulate in nature it does not require grinding.

The particles are also more uniformly distributed with respect to particlediameter, so when used as a solid phase the packing will be more even. Theabsence of finer than average material greatly reduced the chance that the frit

at the end of the column will become blocked [15-17]. The same problemsexist with template removal as with monolith MIPs, but since the particles areconsiderable smaller the problem is somewhat reduced and there is a lowerrisk of assay contamination by template bleeding.





A new problem arises in that because the particles are so small, they havevery low mass. Due to this fact they can be very easily inhaled as they remainin the air for quite a long time.

2.1.3. Solid Phase

The removal of the template from the polymer matrix has proved to be a problem in both monolith and precipitation methods. A solution to this problem is the novel automated solid phase synthesis [18] in which the ratio ofmonomer, template and cross linker is similar to the other methods, but insteadof being free in solution, the template is chemically coupled to a silica particle.The solvent used is water or an organic solvent, and the synthesis takes place

inside a glass column. The monomers anneal to the template on the solid phaseand polymerisation occurs. The MIP nanoparticles are then removed from thesolid phase and taken out of the machine.

The silica particles containing the template remain inside the machine,meaning that no washing step is necessary. The advantage of this method isthat even if any template is removed from the machine the MIP nanoparticlesare so small that they only contain two or three binding sites, and so anyescaping template can be easily washed away.

Another advantage is that the MIP nanoparticles can be synthesized usingwater as the solvent, as opposed to chloroform. This allows for the use ofsolvent sensitive templates such as proteins or viruses. Same methodology canalso be applied manually instead of using automated solid phase reactor.

2.1.4. Covalent Attachment

In this method, the template is functionalised prior to the polymerisationstep by chemically attaching functional monomers to it by covalent bonds. The

polymerisation step is then carried with only a cross linker being used to jointhe functional monomers together.The template is then removed by chemically severing the covalent bonds

that hold it into the binding pore. Rebinding occurs via the same covalentmechanism. An advantage of this is that functional monomers are not presentanywhere in the polymer matrix except for in interactions with the template.This means that non-specific binding and chromatographic effects are reducedwhen compared with other types of polymer.

But the pre-treatment of the template can be problematic, and not allmolecules are suitable for this procedure [19, 20].




Zeynep Altintas10

2.1.5. Metal-Coordination

Metal-coordination bonding can also be used to set up the pre- polymerisation interactions between monomer and template.

After the associations have been set up the polymerisation step is carriedout in a similar fashion to other methods [21]. The applications of metal-coordination polymers are similar to other methods, but can also be used tocapture metal ions in solution. This application has been demonstrated by Sayand Denizli [22], who used a metal-coordinate polymer consisting of N-methacrolyl glutamic acid (MAGA) and hydroxyethyl methacrylate (HEMA)cross linked with ethylene dimethacrylate (EDMA) to selectively capture andfilter Fe3+ ions out of blood plasma which was overdosed with Fe3+ ions.

A complex was first formed between the MAGA and Fe3+ ions in solution,then HEMA was added forming the complex which was then cross linked withEDMA to form a rigid polymer. The template Fe3+ ions were then removedand then rebinding assessed using human blood plasma spiked with Fe3+ ionsat differing concentrations.

3. MOLECULAR R ECOGNITION ELEMENTS

For specific recognition of the target analytes in diagnostics, the bestrecognition materials need to be implemented as the receptor molecule in the biosensor design. These molecules can also be called as affinity ligands. Theyare small molecules which bind to other molecules to form complexes. Thisinteraction occurs via intermolecular forces such as ionic bonding, van derWaals forces and hydrogen bonding.

Molecular recognition elements can be specific and sensitive for only a

particular target. These molecules can be engineered and designed for a particular target of interest [23].

There are a number of affinity ligands that can be developed and used indiagnostics from disease detection to the microbiological quantification asemploying advanced biosensors. These include aptamers, antibodies andmolecularly imprinting polymers (MIPs).

Aptamers are molecules of DNA or RNA isolated from extremelycomplex libraries of nucleic acids, generated by combinatorial chemistry, by

an iterative process of adsorption, recovery and re-amplification [24-26].Additional sequence variation can be introduced at each cycle. Aftersufficient enrichment, aptamers can be cloned and studied as homogeneoussequence populations.





Their advantages over alternative approaches include the relatively simpletechniques and apparatus required for their isolation, the number of alternativemolecules that can be screened (routinely of the order of 1015) and their

chemical simplicity [27]. They have potential applications in analyticaldevices, including biosensors and therapeutic agents [28-34]. During the production processes, the desired property is generally the ability to bind to atarget molecule. According to the application, the desired binding propertiesmay be a fast association rate, slow dissociation rate, high affinity, low affinityto closely related molecules, or a combination of these. This property will be afunction of the three-dimensional structure of the folded nucleic acid and will be a combination of its van der Waals surface contacts, hydrogen bonds that

can form between the biosensing molecule and its target [35]. The affinity ofaptamers to their targets is so important in biosensor platforms and it has beenreported that aptamers have high affinity ( K d ~ 10-8 to 10-9 M) for targetmolecules [36]. However, their specificity is generally lower than antibodies.

Antibodies are one of the most commonly used affinity ligands indiagnostics with the combination of biosensor technology. They can bemonoclonal or polyclonal and they possess two light chains and two heavychains, bound together in a Y-shape. The N-terminal end of each light chain is

located at the top of the Y-structure called as Fab fragment. Fab fragmentsrepresent the antigen binding parts of immunoglobulins. They can be cleavedand used in place of a complete antibody. Their binding properties directlydepend of the amino-acid structure of the N-terminal end [37]. The other partof the protein is called the Fc fragment and defines the class of the antibody.Main classes are the IgG, IgM, IgA, IgE and IgD. The class determines thefunctional property of the antibody which implicates that antibodies fromdifferent classes can have the same binding specificity. The epitope is the part

of the antigen recognised by the binding site of the antibody. The interactionwith the antigen is just like the one of an enzyme with its substrate. Theepitope possess a tridimensional structure and functional groups that enable aspecific recognition of the antigen.

During the binding, numerous types of interactions are involved such aselectrostatic, van der Waals or hydrophobic interactions and hydrogen bonding[37]. Antibodies can be either polyclonal or monoclonal.

Polyclonal antibodies can be raised against any biomarker or cells and

with the introduction of high throughput techniques, applying these moleculesin sensors has been successful [38]. However, the use of monoclonalantibodies gives more specific results. They are more expensive than polyclonal antibodies to produce but provide important advantages.




Zeynep Altintas12

Their single-epitope selectivity is minimising cross-reactions occurringwith polyclonal antibodies and their production, by an immortalised cell-line,exhibits really low variations from batch-to-batch [37]. A range of antibodies

are now commercially available for specific diagnostic tests; however, thisnumber is still limited when compared to the required amount of affinityligands for particular targets. Moreover, this gap can be filled with the help ofMIPs which can be created for a vast number of analytes in diagnostics.

3.1. MIP Receptors in Diagnostics

The concept of molecular imprinting of polymers was first identified in1931 by the Russian scientist Polyakov, who discovered that the presence ofdifferent solvents during synthesis of silica caused alterations in the poreformation [39]. The basic concept is that if a polymer is allowed to form in the presence of another molecule which is not in itself involved in the polymerisation process, then this molecule will become trapped within thestructure of the polymer. If this “template” molecule is then removed from the polymer a pore will be left which is an exact three-dimensional imprint of that

molecule.The first molecular imprinting was performed as employing four different

coloured dyes in 1941 [40]. Since then similar methods have been used toimprint a large number of targets from small molecules [12, 41] to proteins[42-44] and bacteria [45, 46]. MIPs are synthetic receptor ligands which canrecognize and specifically bind to a target molecule. They are more resistant tochemical and biological damage and inactivation than labile antibodies [2]. Acharacteristic feature of MIPs is their hydrophobicity which allows for the

weak reversible interactions between the target and the MIPs. A crosslinkingagent is used in a polymerization reaction followed by the removal of thetemplate from the polymer which creates the specific binding sites for thetargets [47]. Formation of MIPs for small biomolecules is relativelystraightforward whereas it is quite challenging for large biomolecules such as proteins, viruses and bacteria [48]. Proteins are difficult to imprint due to thefeatures of their 3-D structures. These structures are flexible, complex andchange quite easily with minimal energy required to adjust their

conformations. Imprinting would prefer a more rigid type of structure [49].Efforts for direct imprinting of proteins have been reported in scientificresearch; however, these attempts are limited to the cost of the generallyexpensive template proteins.





A solution to this problem may be epitope imprinting. Epitope imprintingis the imprinting of only the epitopes (regions of molecules recognizable byaffinity ligands) of the template protein to create specific cavities which

recognise and selectively bind to the protein at these particular regions. Thecreation and manufacturing of these cavities is relatively easy and inexpensive[50, 51]. Several research groups have been able to produce excellentnanoparticles with negligible aggregation and with acceptable levels oftemplate removal. Cranfield University has produce papers illustrating thissuccess as evidence by the publications [52-54]. The University of Californiaalso has examples of high quality MIP research publications [43].

The detection and removal of various biological compounds using MIPs

have important applications in medicine, veterinary care, agriculture, biopharmaceuticals and biological warfare [55].

MIPs are a popular recognition element for biosensors and usable for biomolecule detection. The applications of MIPs with the combination ofsensor technology indicate a great hope in diagnostics since a limited numberof biomarkers, viruses and bacteria have available natural receptors today andthe production of these bioreceptors requires not only the long time but alsothe expensive procedures and ethical approvals. MIPs are artificial antibodies

which are responsive to the selected analyte because they interact non-covalently with the analyte [43, 56]. The comparison of natural bioreceptorsand synthetic receptors (MIPs) is given in Table 1.

Table 1. The comparison of natural bioreceptors and synthetic receptors

(MIPs)

Synthetic Receptors (MIPs) Natural Receptors

Easy preparation and cost-effective Long production process and high priceof receptors and proteinsStable against low/high pressure,temperature and pH

Low stability

MIPs can be prepared for anycompound

Natural receptors and enzymes exist foronly a limited number of importantanalytes

Design of MIP-based multisensors is arelatively easy task since they require

minimal operations

Various biomolecules have their ownfunctional requirements such as

temperature, substrate, pH, ionicstrengthMIPs are generally insoluble co-

polymers

Biomolecules shows solublecharacteristic




Zeynep Altintas14

4. BIOSENSORS

A biosensor is a device that has two main components including a receptorand a detector. The receptor is responsible for the selectivity of the sensor suchan enzyme, antibodies while the transducer translates the changes that can bechemical or physical by recognizing the analyte and relaying it through anelectrical signal [57]. The detector is also called as a transducer that is notselective, for instance it can be an oxygen electrode, a pH-electrode or piezoelectric crystal. The biological sensing element selectively recognizes a particular biological molecule through a reaction, specific adsorption, or other process as physical/chemical and the transducer converts the results of this

recognition into a usable signal that can be quantified. In this chapter, mostcommonly used sensor types will be briefly reviewed and detail informationand examples about MIP-based sensors will be given subsequently. The principle of a sensor assay using MIPs as affinity ligand and nanomaterials assignal enhancement agent is also given in Figure 2.

4.1. Optical Biosensors

The basis of optical sensors established on surface plasmon and today thedifferent types of the optical sensors are available. The optical biosensorsinclude optrode-based fiber optic biosensors, evanescent wave fiber optic biosensors, flow immunosensor, time- resolved fluorescence, the resonantmirror optical biosensor, interferometric biosensors and surface plasmonresonance biosensors (SPR) [57]. The SPR sensor responds to refractive indexnear the sensor surface and binding of the particular substances to the surface

lead to changes in reflectivity. In this type of biosensors, a surface plasmon isexcited at the interface between a metal film and a dielectric medium, changesin the refractive index of are to be measured. A change in the refractive indexof the dielectric medium (also called as superstrate) produces a change in the propagation constant of the surface plasmon. Optical methods are among theoldest and best-established techniques for sensing biochemical analytes. Theyhave been widely used to detect both small (nerve agents) and large (proteins)analytes [58-61]. Optical-based sensing platforms have been successfully used

not only with natural receptors but also with synthetic affinity ligands for awide range of analyte detection from drugs and other small molecules to proteins, viruses and bacteria. Some applications of MIP-based SPR sensorscan be seen in Table 2.





Figure 2. The principle of a sensor assay using MIPs as affinity ligand. Bare gold

sensor surface is coated with a thiol molecule to form self-assembled monolayer

(SAM) on the surface. The surface is activated using EDC-NHS coupling chemistry prior to the MIP immobilisation. Nanomaterial conjugated target is then injected onto

the MIP surface for the detection of target in trace amounts. Nanomaterials are used for

signal enhancement.

4.2. Electrochemical Biosensors

The electrochemical sensors are the fastest growing trend in the

development of new diagnostics systems due to their desirable characteristicssuch as suitability for miniaturisation, construction of highly sensitive and

specific methods. Electrochemical transducers can be coupled with different

surface chemistry approaches, receptors and a vast number of nanomaterials

for the detection of different molecules including proteins, antigen, DNA,

antibody and heavy metal ions. Many diseases such as cardiovascular system

disorders and cancers have been investigated with electrochemical biosensors

to provide early and simpler diagnosis [62, 63]. These sensors are extremely

sensitive with detection limits under 10-15

molar. Though the most commonlystudied biosensors are optical ones, the detection limits of the electrochemical

sensors are anticipated to better with simpler instrumentation that is not

required the special qualifications for applications [62-64].




Zeynep Altintas16

Table 2. Implementation of MIPs into the sensing platforms for the

detection of various analytes/targets

Sensor type Analyte ReferencesVoltammetric, impedancespectroscopy

Bacillus endospores [45]

Voltammetric Adenosine, inosine, ATP [65]Amperometric ATP [66]Voltammetric Paracetamol [67]

Amperometric Bovine leukaemia virusglycoprotein

[68]

QCM Caffeine [69]QCM Phenylalanine [70]QCM Glucose [71]Voltammetric Dopamine [72]Capacitive Phenylalanine [73]Voltammetric Rifamycin SV [74]QCM Histamine, adenine [75, 76]QCM Dopamine [77]

QCM Folic acid [78]

Impedance, voltammetric

Human ferritin and human papillomavirus derived E7 proteinand calmodulin

[79]

SPR L-histidine, L-aspartic acid, L- phenylalanine and L-glutamic acid

[80]

The successful implementation of MIPs into the electrochemical sensing platforms provides promising future in diagnostics and some examples fromthe literature are listed in Table 2.

4.3. Piezolelectric Biosensors

A quartz crystal microbalance (QCM) is a piezoelectric mass-sensingdevice that measures the change in frequency of a quartz crystal resonator as amass per unit area. In the QCM sensor, analyte detection is based on adsorbate

recognition where selective binding leads to a mass change that can beidentified by a corresponding change in the acoustic parameters of piezoelectric quartz crystal.





With applying electricity to the crystal the piezoelectric effect occurs incrystals and the crystal lattice is deformed [81]. Many types of crystals showthe piezoelectric effect; however, due to the mechanical, electrical and

chemical properties of the quartz it is the most commonly used crystal type inanalytical applications. QCM can be used in a wide variety of applicationsincluding the detection of small molecular weight ligands, carbohydrates, proteins, nucleic acids, viruses, bacteria, cells and lipidic-polymeric interfaces[60, 82].

4.4. Application of MIPs in Advanced Biosensors

Biosensors in which MIPs are applied as affinity ligand exhibit superioradvantages over the natural recognition elements due to their long self-life,reusability, stability and resistance against harsh condition and microbialspoilage. Moreover, MIPs can be designed and synthesized for a vast numberof targets which is so crucial in diagnostics. It is not easy to produce natural bioreceptors for the detection of all disease markers or cells not only due to theethical reason but also the complex procedures which require so long time.

An electrochemical biosensor was developed for 17β-estradiol (E2) basedon a molecularly imprinted polymer (MIP)-conducting polymer modifiedhybrid electrode. A bifunctional monomer, N -phenylethylene diaminemethacrylamide (NPEDMA), was used for the construction of theelectrochemical sensor and conducting films were prepared on the surface of agold electrode by electropolymerization of the aniline moiety of NPEDMA. Alayer of MIP was photochemically grafted over the polyaniline, via N , N -diethyldithiocarbamic acid benzyl ester (iniferter) activation of the

methacrylamide groups. The best monomer for preparation of MIPs for E2was selected as employing molecular modelling and assay conditions such ascyclic voltammetric (CV) scan cycles, deposition time and conditions for polymer accumulation were optimized. The detection limit of 6.86 × 10 –7 Mwas achieved in this study and the hybrid electrode was successfully used toanalyze E2 in water without complex sample pretreatment [5].

Xue et al. have recently reported an amperometric sensor for the detectionof dopamine in human serum based on gold nanoparticles (AuNPs) doped

molecularly imprinted polymers. A novel functional monomer bearing anilinemoieties on the surface of the AuNPs were prepared via a direct synthesismethod and then used to fabricate the conductive MIPs film on the modifiedelectrode by electropolymerization method in the presence of dopamin and p-




Zeynep Altintas18

aminobenzenethiol (p-ATP). The obtained electrochemical sensor based on theconductive film of AuNPs doped MIPs could effectively minimize theinterferences caused by ascorbic acid and uric acid. Amperopetric detection of

dopamine was successfully achieved in the linear range of 0.02- 0.54 μmol L−1 with the detection limit of 7.8 nmol L−1 [83]. Quantification of trace amountsof dopamine is important since it is widely distributed in the mammaliancentral nerve system [84], which plays a significant role in human metabolism both in the central nervous and renal systems [85].

It is involved in drug addictions, schizophrenia and Parkinson's disease[86]. As is well-known, ascorbic acid and uric acid usually coexist withdopamine in biological samples [87]. Hence, it is important to construct a

rapid, sensitive and selective for dopamine.Hydrogel-based molecularly imprinted polymers also show a promising

future in biosensor-based diagnostics. For example, a dual polarisationinterferometer (DPI) sensor based on this technique was developed for thedetection of bovine haemoglobin. A small amount of the protein (3 mg mL-1)was injected over the sensor to form a physisorbed layer typically of 3.5 ± 0.5nm thickness. Onto the pre-adsorbed protein layer, MIP and NIP (non-imprinted polymer) were separately injected to monitor the interaction of

bovine haemoglobin MIP or NIP particles under different loading conditionswith the pre-adsorbed protein layer. In the case of NIP flowing of the proteinlayer, there was negligible surface stripping of the pre-adsorbed protein. Whena protein-eluted sample of MIP particles was flowed over a pre-adsorbed protein layer on the sensor chip, the sensor detected significant decreases in both layer thickness and mass, suggestive that protein was being selectively bound to MIP after being stripped-off from the sensor surface. MIPs were alsotested after biofouling with plasma or serum at various dilutions. It was

observed that serum at 1/100 dilution allowed the MIP to still functionselectively. This is the first demonstration of MIPs being integrated with DPIin the development of synthetic receptor-based optical protein sensors [88]. Inanother study, Huang et al. combined the molecularly imprinted polymers withmultiwalled carbon nanotube-gold nanoparticle composites and chitosan to build an electrochemical sensor for the detection of tyramine. Sophisticatedcharacteristics of carbon nanotube allowed quantifying the target analyte in theconcentration range of 1.08×10−7 to 1×10−5 mol L-1, with a limit of detection

5.7×10

−8

mol L

-1

and showed good recovery for real samples [89].The integration of MIP technology into the field of microfluidic systems isalso possible and open gates to the novel diagnostics tools. The detection ofmacromolecules such as proteins and viruses are not easy based on MIP since





these tailor made recognition elements work much better for small size targets.However, a promising improvement has been made in this point during therecent years. Birnbaumer et al. integrated MIPs onto a microfluidics biochip as

employing contactless dielectric microsensors for the detection of viruses. Inthis study, the specific interaction between molecular imprinted polymer(MIP) and virus resulted in the elimination of non-specific interaction in thesensor configuration. The additional integration of the blank (NIP) polymerfurther allowed for the identification of non-specific adsorption events. Thenovel combination of microfluidics containing integrated native polymer andMIP with contact-less dielectric microsensors is evaluated using the TobaccoMosaic Virus (TMV) and the Human Rhinovirus serotype 2 (HRV2). Results

show that viral binding and dissociation events can be readily detected usingcontact-less bioimpedance spectroscopy optimized for specific frequencies.The optimum sensor response was obtained at 203 kHz within the appliedfrequency range of 5–500 kHz. Moreover, not only complete removal of thevirus from the MIP, but also device reusability was successfully shown.Evaluation of the microfluidic biochip revealed that microchip technology isideally suited to detect a broader range of viral contaminations with highsensitivity by selectively adjusting microfluidic conditions, sensor geometries

and choice of MIP polymeric material [90].The advances of molecular imprinting technology can also provide a

positive picture for cancer detection due to the possible development of newsensing elements for a wide range of substances. Protein and genetic markersconstitute the major part of cancer markers although some other moleculessuch as microRNAs and small materials have been used in cancer diagnosticsas employing polymerase chain reaction (PCR), sequencing and sensor basedtechniques. Wang et al. developed a potentiometric biosensors based on

surface molecular imprinting for the detection of cancer biomarkers andviruses. The principle of the method is given in Figure 3. They investigated thedetection of carcinoembryonic antigen (CEA) in both solutions of purifiedCEA and in the culture medium of a CEA-producing human colon cancer cellline in the concentration range of 2.5-250 ng mL-1. The cross-reactivity studiesusing haemoglobin as the control protein confirmed the specificity of theassays. Moreover, non-imprinted sensor was also used as negative control. Theresearchers obtained similar results for human amylase as the other protein

biomarker. The applicability of the developed assays was also investigated fordifferent biological molecules such as virus. Virions of poliovirus weresuccessfully detected and the cross-reactivity studies with adenovirus and alsowith non-imprinted sensor confirmed the specificity of the bioassays [91].




Zeynep Altintas20

Figure 3. Formation of biomolecule-templated thiol SAM, and the subsequent removal

of the template molecules to create the recognition sites in the SAM matrix.

This research work shows a great potential of molecular imprinting for the

development of novel techniques to detect protein biomarkers of cancer and

protein-based macromolecular structures such as the virion capsid. Moreover,

this approach can provide highly sensitive, specific, easy and cost-effective

methodology which plays a significant role in early cancer diagnosis. The

extensive examples of MIP-based biosensors in diagnostics can also be found

from current literature [92-98].

CONCLUSION AND FUTURE PROSPECTS

A vast number of MIPs have been studied and published in the last

decade. Many different analytes have been successfully printed to obtain

artificial molecular recognition elements to use in separation, catalysis, drug

delivery and sensing. Although a wide range of targets have been investigated

to create their molecular imprints, small analytes have dominated in the

production of MIPs due to the drawbacks in macromolecule imprinting. Thesechallenges include the structure, size and conformational fragility of

macromolecules such as proteins, viruses and bacteria.

However, important improvements have been recorded against these

limitations. For example, the epitope imprinting indicates that there is no need

to involve whole macromolecules as template during the synthesis of MIPs

[99-101]. Epitope is a particular region of a biological macromolecule and

capable of recognizing whole protein. SPR-based sensors were developed for

the detection of human immunoglobulin G based on epitope imprinting [97].These peptides can be immobilised on sensor surfaces or used as soluble

templates [101].





The detection of amino acid sequences and post-translational changes of proteins are also crucial in diagnostics using biosensors. The imprints of thesemodifications can be easily created and investigated as employing MIP

technology [102]. Despite of various developments to overcome drawbacks inmacromolecule imprinting, more investigation is required to provide a reliableand practical approach in sensor design for diagnostics.

Advances in chemical synthesis, computational modelling, molecularrecognition and nanotechnology will consolidate the MIP technology in biosensors. Further improvements in this area will enhance the selectivity,stability and reliability of these artificial receptors, and will give possibility forthe development of novel medical devices, drug delivery and diagnostics.

R EFERENCES

[1]

Haupt, K. and K. Mosbach, Molecularly imprinted polymers and theiruse in biomimetic sensors. Chemical Reviews, 2000. 100(7): p. 2495-2504.

[2]

Asliyuce, S., et al., Molecular imprinting based composite cryogel

membranes for purification of anti-hepatitis B surface antibody by fast protein liquid chromatography. Journal of Chromatography B, 2012.889: p. 95-102.

[3]

Piletsky, S. A., S. Alcock and A. P. Turner, Molecular imprinting: at theedge of the third millennium. TRENDS in Biotechnology, 2001. 19(1): p.9-12.

[4] Muhammad, T., et al., Rational design and synthesis of water-compatible molecularly imprinted polymers for selective solid phase

extraction of amiodarone. Analytica chimica acta, 2012. 709: p. 98-104.[5]

Des Azevedo, S., et al., Molecularly Imprinted Polymer-HybridElectrochemical Sensor for the Detection of β-Estradiol. Industrial and

Engineering Chemistry Research, 2013. 52(39): p. 13917-13923.[6]

Mosbach, K., Molecular imprinting. Trends in biochemical sciences,1994. 19(1): p. 9-14.

[7] Sellergren, B. and A. J. Hall, Molecularly Imprinted Polymers.Supramolecular Chemistry: from Molecules to Nanomaterials, 2012.

[8]

Li, S., et al., Size matters: challenges in imprinting macromolecules. Progress in Polymer Science, 2014. 39(1): p. 145-163.




Zeynep Altintas22

[9]

Tsyrulneva, I., et al., Molecular modelling and synthesis of a polymerfor the extraction of amiloride and triamterene from human urine. Analytical Methods, 2014. 6(10): p. 3429-3435.

[10]

Rushton, G. T. and K. D. Shimizu, Molecularly Imprinted Polymers(MIPs). Materials in Biology and Medicine, 2012: p. 77.

[11]

Luliński, P. and D. Maciejewska, Impact of functional monomers, cross-linkers and porogens on morphology and recognition properties of 2-(3,4-dimethoxyphenyl) ethylamine imprinted polymers. Materials Science

and Engineering: C, 2011. 31(2): p. 281-289.[12]

Wei Sun, B., Y. Zong Li and W. Bao Chang, Molecularly imprinted polymer for pyrazinamide. Analytical letters, 2003. 36(8): p. 1501-1509.

[13]

Lorenzo, R. A., et al., To remove or not to remove? The challenge ofextracting the template to make the cavities available in molecularlyimprinted polymers (MIPs). International journal of molecular sciences,2011. 12(7): p. 4327-4347.

[14]

Szumski, M., et al., Monolithic Molecularly Imprinted PolymericCapillary Columns for Isolation of Aflatoxins. Journal of

Chromatography A, 2014.[15]

Yu, J. Y., et al., Molecularly imprinted polymer microspheres prepared

by precipitation polymerization for atenolol recognition. Advanced Materials Research, 2011. 148: p. 1192-1198.

[16] Beltran, A., et al., Synthesis by precipitation polymerisation ofmolecularly imprinted polymer microspheres for the selective extractionof carbamazepine and oxcarbazepine from human urine. Journal of

Chromatography A, 2009. 1216(12): p. 2248-2253.[17] Chaitidou, S., et al., Precipitation polymerization for the synthesis of

nanostructured particles. Materials Science and Engineering: B, 2008.

152(1): p. 55-59.[18]

Poma, A., et al., Solid‐Phase Synthesis of Molecularly ImprintedPolymer Nanoparticles with a Reusable Template–“Plastic Antibodies”. Advanced Functional Materials, 2013. 23(22): p. 2821-2827.

[19]

Shea, K. J. and E. Thompson, Template synthesis of macromolecules.Selective functionalization of an organic polymer. The Journal of

Organic Chemistry, 1978. 43(21): p. 4253-4255.[20]

Bui, B. T. S. and K. Haupt, Molecularly imprinted polymers: synthetic

receptors in bioanalysis. Analytical and bioanalytical chemistry, 2010.398(6): p. 2481-2492.





[21]

Ge, Y. and A. P. Turner, Too large to fit? Recent developments inmacromolecular imprinting. Trends in biotechnology, 2008. 26(4): p.218-224.

[22]

Yavuz, H., R. Say and A. Denizli, Iron removal from human plasma based on molecular recognition using imprinted beads. Materials

Science and Engineering: C , 2005. 25(4): p. 521-528.[23]

James, W., Aptamers. Encyclopedia of analytical chemistry, 2006.[24]

Keefe, A. D., S. Pai and A. Ellington, Aptamers as therapeutics. Nature

Reviews Drug Discovery, 2010. 9(7): p. 537-550.[25]

Tan, W., M. J. Donovan and J. Jiang, Aptamers from cell-basedselection for bioanalytical applications. Chemical reviews, 2013. 113(4):

p. 2842-2862.[26] Li, W.-M., et al., Cell-SELEX-based selection of aptamers that

recognize distinct targets on metastatic colorectal cancer cells. Biomaterials, 2014. 35(25): p. 6998-7007.

[27]

Mok, W. and Y. Li, Recent progress in nucleic acid aptamer-based biosensors and bioassays. Sensors, 2008. 8(11): p. 7050-7084.

[28]

Jiang, Z., et al., An aptamer-based biosensor for sensitive thrombindetection with phthalocyanine@ SiO mesoporous nanoparticles.

Biosensors and Bioelectronics, 2014. 53: p. 340-345.[29] Hu, R., et al., Novel electrochemical aptamer biosensor based on an

enzyme–gold nanoparticle dual label for the ultrasensitive detection ofepithelial tumour marker MUC1. Biosensors and Bioelectronics, 2014.53: p. 384-389.

[30]

Fang, Z., et al., Lateral flow biosensor for DNA extraction-free detectionof salmonella based on aptamer mediated strand displacementamplification. Biosensors and Bioelectronics, 2014. 56: p. 192-197.

[31]

Sun, C., et al., A label-free and high sensitive aptamer biosensor basedon hyperbranched polyester microspheres for thrombin detection. Analytica Chimica Acta, 2014.

[32]

Simmons, S. C., et al., Anti-Heparanase Aptamers as PotentialDiagnostic and Therapeutic Agents for Oral Cancer . PloS one, 2014. 9(10): p. e96846.

[33] Zhou, J. and J. J. Rossi, Cell-type-specific, aptamer-functionalizedagents for targeted disease therapy. Molecular Therapy—Nucleic Acids,

2014. 3(6): p. e169.[34]

Lai, W.-Y., et al., Synergistic inhibition of lung cancer cell invasion,tumor growth and angiogenesis using aptamer-siRNA chimeras. Biomaterials, 2014. 35(9): p. 2905-2914.




Zeynep Altintas24

[35]

Drabovich, A. P., et al., Selection of smart aptamers by methods ofkinetic capillary electrophoresis. Analytical chemistry, 2006. 78(9): p.3171-3178.

[36]

Caygill, R. L., G. E. Blair and P. A. Millner, A review on viral biosensors to detect human pathogens. Analytica chimica acta, 2010.681 (1): p. 8-15.

[37]

Mikkelsen, S. R. and E. Cortón, Antibodies. Bioanalytical Chemistry: p.86-98.

[38]

Chambers, R. S. and S. A. Johnston, High-level generation of polyclonalantibodies by genetic immunization. Nature biotechnology, 2003. 21(9): p. 1088-1092.

[39]

Polyakov, M., Adsorption properties and structure of silica gel. Zhur Fiz Khim, 1931. 2: p. 799-805.

[40] Dickey, F. H., The preparation of specific adsorbents. Proceedings of the

National Academy of Sciences of the United States of America, 1949.35(5): p. 227.

[41]

Baggiani, C., et al., Molecularly imprinted polymers for corticosteroids:Analysis of binding selectivity. Biosensors and Bioelectronics, 2010. 26(2): p. 590-595.

[42]

Hoshino, Y., et al., Peptide imprinted polymer nanoparticles: a plasticantibody. Journal of the American Chemical Society, 2008. 130(46): p.15242-15243.

[43]

Hoshino, Y., et al., Recognition, neutralization, and clearance of target peptides in the bloodstream of living mice by molecularly imprinted polymer nanoparticles: a plastic antibody. Journal of the American

Chemical Society, 2010. 132(19): p. 6644-6645.[44] Guo, M.-J., et al., Protein-imprinted polymer with immobilized assistant

recognition polymer chains. Biomaterials, 2006. 27(24): p. 4381-4387.[45]

Namvar, A. and K. Warriner, Microbial imprinted polypyrrole/poly (3-methylthiophene) composite films for the detection of Bacillusendospores. Biosensors and Bioelectronics, 2007. 22(9): p. 2018-2024.

[46]

Ren, K. and R. N. Zare, Chemical recognition in cell-imprinted polymers. ACS nano, 2012. 6(5): p. 4314-4318.

[47] Poma, A., A. P. F. Turner and S. A. Piletsky, Advances in themanufacture of MIP nanoparticles. Trends in biotechnology, 2010. 28

(12): p. 629-637.[48]

Lu, C. H., et al., Sensing HIV related protein using epitope imprintedhydrophilic polymer coated quartz crystal microbalance. Biosensors and

Bioelectronics, 2011.





[49]

Bossi, A. M., et al., Fingerprint-Imprinted Polymer: Rational Selectionof Peptide Epitope Templates for the Determination of Proteins byMolecularly Imprinted Polymers. Analytical chemistry, 2012. 84(9): p.

4036-4041.[50] Bolisay, L. D., J. N. Culver and P. Kofinas, Optimization of virus

imprinting methods to improve selectivity and reduce nonspecific binding. Biomacromolecules, 2007. 8(12): p. 3893-3899.

[51]

Tai, D. F., et al., Epitope-cavities generated by molecularly imprintedfilms measure the coincident response to anthrax protective antigen andits segments. Analytical chemistry, 2010. 82(6): p. 2290-2293.

[52]

Chianella, I., et al., Rational design of a polymer specific for

microcystin-LR using a computational approach. Analytical chemistry,2002. 74(6): p. 1288-1293.

[53] Chianella, I., et al., MIP-based solid phase extraction cartridgescombined with MIP-based sensors for the detection of microcystin-LR. Biosensors and Bioelectronics, 2003. 18(2): p. 119-127.

[54]

Guerreiro, A. R., et al., Selection of imprinted nanoparticles by affinitychromatography. Biosensors and Bioelectronics, 2009. 24(8): p. 2740-2743.

[55]

Bolisay, L. D. and P. Kofinas. Imprinted Polymer Hydrogels for theSeparation of Viruses. In: Macromolecular Symposia. 2010. WileyOnline Library.

[56]

Jenik, M., et al., Sensing picornaviruses using molecular imprintingtechniques on a quartz crystal microbalance. Anal. Chem., 2009. 81(13): p. 5320-5326.

[57] Altintas, Z. and I. Tothill, Biomarkers and biosensors for the earlydiagnosis of lung cancer . Sensors and Actuators B: Chemical , 2013.

188: p. 988-998.[58]

Altintas, Z., et al., Development of surface chemistry for surface plasmon resonance based sensors for the detection of proteins and DNAmolecules. Analytica chimica acta, 2012. 712: p. 138-144.

[59]

Altintas, Z., et al., Surface plasmon resonance based immunosensor forthe detection of the cancer biomarker carcinoembryonic antigen.Talanta, 2011. 86: p. 377-383.

[60] Altintas, Z. and I. E. Tothill, DNA-based biosensor platforms for the

detection of TP53 mutation. Sensors and Actuators B: Chemical , 2012.169: p. 188-194.[61]

Heurich, M., Z. Altintas and I. E. Tothill, Computational Design ofPeptide Ligands for Ochratoxin A. Toxins, 2013. 5(6): p. 1202-1218.




Zeynep Altintas26

[62]

Altintas, Z., S. S. Kallempudi and Y. Gurbuz, Gold nanoparticlemodified capacitive sensor platform for multiple marker detection.Talanta, 2014. 118: p. 270-276.

[63]

Altintas, Z., et al., A novel magnetic particle-modified electrochemicalsensor for immunosensor applications. Sensors and Actuators B:

Chemical, 2012. 174: p. 187-194.[64]

Berggren, C., B. Bjarnason and G. Johansson, Capacitive biosensors. Electroanalysis, 2001. 13(3): p. 173-180.

[65]

Spurlock, L. D., et al., Selectivity and sensitivity of ultrathin purine-templated overoxidized polypyrrole film electrodes. Analytica chimica

acta, 1996. 336(1): p. 37-46.

[66]

Takeda, S., et al., A highly sensitive amperometric adenosinetriphosphate sensor based on molecularly imprinted overoxidized polypyrrole. Flow Inj. Anal ., 2008. 25: p. 77-79.

[67]

Özcan, L. and Y. Şahin, Determination of paracetamol based onelectropolymerized-molecularly imprinted polypyrrole modified pencilgraphite electrode. Sensors and Actuators B: Chemical , 2007. 127(2): p.362-369.

[68]

Ramanaviciene, A. and A. Ramanavicius, Molecularly imprinted

polypyrrole-based synthetic receptor for direct detection of bovineleukemia virus glycoproteins. Biosensors and Bioelectronics, 2004. 20(6): p. 1076-1082.

[69]

Ebarvia, B. S., S. Cabanilla and F. Sevilla III, Biomimetic properties andsurface studies of a piezoelectric caffeine sensor based onelectrosynthesized polypyrrole. Talanta, 2005. 66(1): p. 145-152.

[70] Peng, H., et al., Development of a thickness shear mode acoustic sensor based on an electrosynthesized molecularly imprinted polymer using an

underivatized amino acid as the template. Analyst , 2001. 126(2): p. 189-194.[71]

Malitesta, C., I. Losito and P. G. Zambonin, Molecularly imprintedelectrosynthesized polymers: new materials for biomimetic sensors. Analytical Chemistry, 1999. 71(7): p. 1366-1370.

[72]

Song, W., et al., Dopamine sensor based on molecularly imprintedelectrosynthesized polymers. Journal of Solid State Electrochemistry,2010. 14(10): p. 1909-1914.

[73]

Panasyuk, T. L., et al., Electropolymerized molecularly imprinted polymers as receptor layers in capacitive chemical sensors. Analytical

Chemistry, 1999. 71(20): p. 4609-4613.





[74]

Blanco-Lopez, M., et al., Electrochemical sensing with electrodesmodified with molecularly imprinted polymer films. Analytical and

bioanalytical chemistry, 2004. 378(8): p. 1922-1928.

[75]

Pietrzyk, A., et al., Selective histamine piezoelectric chemosensor usinga recognition film of the molecularly imprinted polymer of bis(bithiophene) derivatives. Analytical chemistry, 2009. 81(7): p. 2633-2643.

[76]

Pietrzyk, A., et al., Molecularly imprinted polymer (MIP) based piezoelectric microgravimetry chemosensor for selective determinationof adenine. Biosensors and Bioelectronics, 2010. 25(11): p. 2522-2529.

[77]

Pietrzyk, A., et al., Molecularly imprinted poly [bis (2, 2′-bithienyl)

methane] film with built-in molecular recognition sites for a piezoelectric microgravimetry chemosensor for selective determinationof dopamine. Bioelectrochemistry, 2010. 80(1): p. 62-72.

[78]

Apodaca, D. C., et al., Electropolymerized molecularly imprinted polymer films of a bis-terthiophene dendron: folic acid quartz crystalmicrobalance sensing. ACS applied materials and interfaces, 2010. 3(2): p. 191-203.

[79]

Cai, D., et al., A molecular-imprint nanosensor for ultrasensitive

detection of proteins. Nature nanotechnology, 2010. 5(8): p. 597-601.[80] Riskin, M., et al., Stereoselective and Chiroselective Surface Plasmon

Resonance (SPR) Analysis of Amino Acids by Molecularly ImprintedAu‐ Nanoparticle Composites. Chemistry-A European Journal , 2010. 16(24): p. 7114-7120.

[81]

Laschitsch, A. and D. Johannsmann, High frequency tribologicalinvestigations on quartz resonator surfaces. Journal of applied physics,1999. 85(7): p. 3759-3765.

[82]

Cooper, M. A. and V. T. Singleton, A survey of the 2001 to 2005 quartzcrystal microbalance biosensor literature: applications of acoustic physics to the analysis of biomolecular interactions. Journal of

Molecular Recognition, 2007. 20(3): p. 154-184.[83] Xue, C., et al., Amperometric detection of dopamine in human serumby

electrochemical sensor based on gold nanoparticles doped molecularlyimprinted polymers. Biosensors and Bioelectronics, 2013. 49: p. 199-203.

[84]

De Araujo, I. E., et al., The gut–brain dopamine axis: a regulatorysystem for caloric intake. Physiology and behavior , 2012. 106(3): p.394-399.




Zeynep Altintas28

[85]

Liu, A., I. Honma and H. Zhou, Amperometric biosensor based ontyrosinase-conjugated polysacchride hybrid film: Selectivedetermination of nanomolar neurotransmitters metabolite of 3, 4-

dihydroxyphenylacetic acid (DOPAC) in biological fluid. Biosensors

and Bioelectronics, 2005. 21(5): p. 809-816.[86]

Shiner, T., et al., Dopamine and performance in a reinforcement learningtask: evidence from Parkinson’s disease. Brain, 2012. 135(6): p. 1871-1883.

[87]

Noroozifar, M., et al., Simultaneous and sensitive determination of aquaternary mixture of AA, DA, UA and Trp using a modified GCE byiron ion-doped natrolite zeolite-multiwall carbon nanotube. Biosensors

and Bioelectronics, 2011. 28(1): p. 56-63.[88] Reddy, S. M., et al., Protein detection using hydrogel-based molecularly

imprinted polymers integrated with dual polarisation interferometry.Sensors and Actuators B: Chemical , 2013. 176: p. 190-197.

[89]

Huang, J., et al., A molecularly imprinted electrochemical sensor basedon multiwalled carbon nanotube-gold nanoparticle composites andchitosan for the detection of tyramine. Food Research International ,2011. 44(1): p. 276-281.

[90]

Birnbaumer, G. M., et al., Detection of viruses with molecularlyimprinted polymers integrated on a microfluidic biochip using contact-less dielectric microsensors. Lab on a Chip, 2009. 9(24): p. 3549-3556.

[91]

Wang, Y., et al., Potentiometric sensors based on surface molecularimprinting: Detection of cancer biomarkers and viruses. Sensors and

Actuators B: Chemical, 2010. 146(1): p. 381-387.[92] Whitcombe, M. J., et al., The rational development of molecularly

imprinted polymer-based sensors for protein detection. Chemical Society

Reviews, 2011. 40(3): p. 1547-1571.[93]

Sergeyeva, T., et al., Catalytic molecularly imprinted polymermembranes: Development of the biomimetic sensor for phenolsdetection. Analytica chimica acta, 2010. 659(1): p. 274-279.

[94]

Lian, W., et al., Electrochemical sensor based on gold nanoparticlesfabricated molecularly imprinted polymer film at chitosan–platinumnanoparticles/graphene–gold nanoparticles double nanocompositesmodified electrode for detection of erythromycin. Biosensors and

Bioelectronics, 2012. 38(1): p. 163-169.[95]

Kan, X., et al., Molecularly imprinted polymers based electrochemicalsensor for bovine hemoglobin recognition. Sensors and Actuators B:

Chemical, 2012. 168: p. 395-401.





[96]

Chen, H.-J., et al., Surface-imprinted chitosan-coated magneticnanoparticles modified multi-walled carbon nanotubes biosensor fordetection of bovine serum albumin. Sensors and Actuators B: Chemical ,

2012. 163(1): p. 76-83.[97] Ertürk, G., et al., Fab fragments imprinted SPR biosensor for real-time

human immunoglobulin G detection. Biosensors and Bioelectronics,2011. 28(1): p. 97-104.

[98]

Aghaei, A., M. R. Milani Hosseini and M. Najafi, A novel capacitive biosensor for cholesterol assay that uses an electropolymerizedmolecularly imprinted polymer. Electrochimica Acta, 2010. 55(5): p.1503-1508.

[99]

Rachkov, A., N. Minoura and T. Shimizu, Peptide separation usingmolecularly imprinted polymer prepared by epitope approach. Anal. Sci.,2001. 17: p. i609-i612.

[100]

Minouraa, N., et al., Study of the factors influencing peak asymmetry onchromatography using a molecularly imprinted polymer prepared by theepitope approach. Bioseparation, 2001. 10(6): p. 399-407.

[101]

Tai, D.-F., et al., Artificial-epitope mapping for CK-MB assay. Analyst ,2011. 136(11): p. 2230-2233.

[102]

Yamazaki, T., An Amperometric Sensor Based on Gold ElectrodeModified by Soluble Molecularly Imprinted Catalyst for FructosylValine. Electrochemistry, 2012. 80(5): p. 353-357.





Chapter 2

ELECTRONIC TONGUE: APPLICATIONS AND ADVANCES

Nadja K. L. Wiziack 1 , Jul iana Coatr ini Soares

2 ,

Benjamin D. Padovan 1 , Osvaldo N. Oliveira, Jr

2

and Fabio L . Leite 1

1Department of Physics Mathematics and Chemistry (DFMQ), Nanoneurobiophysics Research Group,

Federal University of São Carlos (UFSCar),Sorocaba, SP, Brazil

2São Carlos Institute of Physics,University of São Paulo, São Carlos, SP, Brazil

ABSTRACT

An Electronic Tongue (E-tongue) is an array of sensors of varyingcomposition used in unison to analyze the electrical response and thus perform a quantitative and discriminative classification of a liquidsample. A unique fingerprint is established from this electrical responseusing pattern recognition and data analysis methods. E-tongues can workaccording to various operating principles, based mainly onelectrochemical methods and impedance spectroscopy, while the sensingunits are normally made of nanostructured films. In this Chapter we

* Corresponding author email: [email protected].




N. K. L. Wiziack, J. C. Soares, B. D. Watson et al.32

discuss the fabrication and use of E-tongues for various applications,including in the pharmaceutical industry, food and beverage sector, andmonitoring of water quality. An extension of the E-tongue concept to

include highly selective sensing units is also discussed, particularly withthe possible use in clinical diagnosis which requires sophisticatedcomputational and statistical methods.

1. INTRODUCTION

New discoveries in sensing technologies [1,2] encompass the use of arraysof non-specific sensors to artificially measure taste [3,4], in what becameknown as an Electronic Tongue (E-Tongue). The name is an analogy to thehuman gustatory system due to commonality it shares with the E-tongue insensing taste. The human tongue contains sensors in the form of ~10,000 taste buds of 50–100 receptor cells each. Different proteins on the receptor cellsidentify the sweet, bitter, umami and sour tastes when interacting with thesample. Detection of the salty taste is also thought to occur in this manner[5,6,7]. The combination of signals generated by the receptor cells is thentransmitted to the brain and recognised as a specific flavour belonging to the

sample [8]. The E-Tongue works in a similar fashion, for sensors of varyingcomposition generate a unique electrical response when interacting with theliquid sample. The electrical responses are collected into a central processingunit where data is stored. Patterns are established by comparing each sensorresponse to a sample which gives a unique electrical fingerprint. By comparingfingerprints from different samples using multivariate analysis software, it is possible to discriminate and classify solutions.

The E-Tongue and human gustatory system both detect chemicals using a

“global sensing” method. That is to say, a sensor or receptor is not specific toany particular chemical; instead, it responds to the various chemicals within asolution, although with differing strengths in their responses to each chemical[9,10]. One of the earliest prototypes of the E-Tongue emerged in efforts todetect and quantify the 5 basic tastes: sour, salty, sweet, bitter and umamithrough chemical sensors [2,11]. This is an alternative to having human panellists to describe and measure tastes, which is limited due to thesubjectivity and low reproducibility obtained from the panelists [12,13]. The

human tongue is unable to register small changes in formulation and to tastecertain chemicals. A systematic, automated solution is required, the reasonwhy E-Tongues began to be used in the late 1980's [14]. Unlike human




Electronic Tongue: Applications and Advances 33

tongues, the E-Tongue is not restricted to sensing tastes in food. The globalsensing nature of sensors and the possible variety in sensing units have meantthat the E-Tongue may have multiple uses in chemical analysis [15,16,17],

including in clinical [18], environmental [19] and pharmaceutical [20] fields.The principle of operation of the E-tongue requires that an array of sensors

isimmersed in the sample of interest. For its operation, four additional itemsare required: i) a sample holder: ii) an array of sensors of differentselectivities; iii) a transducer; iv) software suitable for processing signal [8,21]. The combination of “global selectivity” sensors with a multi-sensor arrayis a unique method for providing chemical analysis and allows for analysis ofsolutions not possible using other methods. The E-Tongue is best suited for

analytical problems where signal overlapping due to different chemical speciesis present, making it hard to be determined using other analytical systems. Asthe E-Tongue measures a response from the overall chemical properties of asolution, it is capable of detecting changes in formulation. By looking at whichsensors have shown an increase or decrease in response it is further possible todetermine whether changes have occurred in specific chemicals or types ofchemicals. The E-Tongue offers many advantages over other analysistechniques, including re-usability of sensors, speed of analysis, low material

cost, short sample preparation times and the capability of measuring changeswithin complex solutions. The E-Tongue can be used in places where HighPerformance Liquid Chromatography is not possible or impractical due to its portability and low consumable requirements, equipment cost andinstantaneous sampling time. It can also be used in situations where UV-VISand IR methods are not capable of measuring the required chemicals withincomplex solutions due to interference from other chemicals.

The sensors for an E-Tongue are customizable and can be tailored to meet

various types of requirements, and therefore a wide range of chemicals can beexplored. The E-Tongue is not limited to size constraints that apply to someanalytical techniques; with nanotechnology the sensing units may becomesmall enough to fit within a cell phone or other handheld device and work indetection of harmful chemicals and diseases. To be employed in the E-Tongue,sensors should have low selectivity and high sensitivity. Thus, a sensor shouldrespond to a number of different chemicals in a solution at low concentrationsand generate a unique response to the solution. Since different sensors will

lead to different responses to the same solution, with the combination of thesesensors in an array one may discriminate similar samples. Increasing thenumber and variety of sensors allows for better discrimination, particularlywith the aid of statistical and computational methods [22]. The number of





publications on E-tongues is increasing, for the technology is gaining in popularity [23].

2. TYPES OF SENSORS

E-Tongues can detect flavours by using non-specific sensors appropriateto the analyte and principle of detection, whose limit of detection andselectivity depend on the composition and the properties of materials used[24]. For detection via potentiometry [22], the most used sensing materials arechalcogenide and oxide glasses [25], while noble metals have been more

suitable in amperometric detection [24]. Optimizing sensing performancerequires solving stability problems of the materials, particularly of thereceptor, in addition to amplifying the signal to be detected withoutinterference. Depending on the nature of the interaction with the analyte, atransducer should be adapted [26] to allow for the target solution or analytesto be measured clearly and consistently against background interference from thesample environment. Sensors are prone to interference due to their semi-specific nature; although sensors are designed to respond favourably to certain

chemicals they also respond to other factors. The sensor response can beinfluenced and limited by parameters such as temperature of the liquid, liquid pressure and viscosity. Sensitivity also depends on the area available in thesensing units to interact with target analytes [27]. In some cases thicker filmslead to higher sensitivity due to their larger surface roughness, but in othersthinner films offer higher sensitivity.

Various detection methods can be used in E-Tongues [28], including potentiometric method [22,23,28], voltammetry [29,30,31], amperometric, and

impedance spectroscopy [29,32], which are briefly described below.

2.1. Potentiometric Sensors

Potentiometry is the measurement of accumulation of load on the workingelectrode in comparison with a reference electrode when no substantial currentflows between them. In other words, potentiometry provides information about

ion activity in an electrochemical reaction. The first E-Tongue introduced byToko and collaborators [33,34] consisted of eight potentiometric electrodeswith lipid membranes. Legin et al., [35] presented an E-tongue with cross-sensitivity from chalcogenide glasses in the sensing units [36,37].





Potentiometric transducers were the first sensors to be employed in

multisensory systems for the analysis of liquid samples [22,28], and remain

the most used in E-Tongues.

For potentiometric analysis, the relationship between the concentration

and the potential is governed by the Nernst equation (Equation 1). The direct

determination of the analyte ions using Nernst's equation is called direct

potentiometry [36], in which the logarithm of the ion activity is proportional to

the observed potential. Thus, the sensitivity, which corresponds to the slope of

the relationship, depends on the temperature and ion charge [37,38,39,40]. The

logarithmic relationship between potential and ion activity (ai)indicates that

small changes in analyte concentration cause subtle changes in the potential

measured. Accordingly, potentiometry is a simple and direct method toconvert chemical energy into electrical energy [40,41].

(1)

where k is the is standard-state reduction potential ( E0), T is temperature, z is

the ion charge, R and F are the universal gas constant and the Faraday

constant, respectively.The ion selective electrodes most employed are those based on polymeric

membranes, being applied to determine electrolytes in wine samples [42],

body fluids and environmental samples [43]. Rudnitskaya et al., developed

different types of E-tongues formed by arrays of EISs glass and chalcogenide

PVC membranes [42]. Likewise, simultaneous multi-determination of metals

has been demonstrated in slurries and ions contained within human plasma.

Many potentiometric devices are based on field effect transistors of selective

ions (ISFET), which allows for the development of miniaturized sensors andas components of integrated circuitry. They are implemented in E-Tonguesto

analyze grape juice, wine, beer, green tea and mineral water [29,44]. The

potentiometric response depends upon the electroactivity of the material and

working solution, in addition to the film/solution interface. The main

disadvantage of this method is the influence from the temperature, which may

cause changes in solution and adsorption of compounds on the sensor

membrane [29].

However, these factors can be minimized by controlling temperature and

washing the electrodes. On the other hand, ion-selective electrodes are

advantageous for their size, low cost, low power consumption and portability

[22].





2.2. Amperometric Sensors

The amperometric E-tongue is so named because of the transduction

mechanism. During amperometric measurements, a potential is kept constant between the working (ET) and the reference (RE) electrodes. The currentgenerated by the redox process of electroactive species on the workingelectrode is proportional to the concentration of these electroactive species.Since not all analytes are inherently capable of producing redox couplingduring electrochemical reactions, these devices only measure electrochemicalreactions at the surface of working electrodes [36]. The principle of detectionis based on electron transfer between the active site of a receptor immobilized

on a working electrode and the analyte of interest. Upon detection, the reactionmodifies the oxidation state of the analyte and the receptor or even the reaction product [45,46].

There have been several examples of use for amperometric E-tongues,including analysis of white wines with caste discrimination and geographicalorigins, and rating orange drinks according to their natural juice content [44].Combined with an electronic nose and spectrophotometric methods, anamperometric E-tongue could predict sensorial descriptors of Italian red dry

wines of different denominations of origin. Genetic Algorithms wereemployed to select variables and build predictive regression models, and theresults demonstrate the possible handling of a large part of the sensorialinformation47. Commercial coffees have also been discriminated according tothe method of preparation and its variety [19, 48, 49].

2.3. Voltammetric Sensors

The voltammetric E-tongue consists of different working electrodesconnected to the measuring system, where analysis of liquid samples is madewith cyclic voltammetry. In this technique, a potential scan generates a currentresulting from electrochemical reactions. The voltage is measured between thereference electrode and the working electrode, while the current is measured between the working and the counter electrodes. As the voltage is increased tothe potential of electrochemical reduction of the analyte, the current will also

increase [36, 50]. The term voltammetry comprises a wide variety oftechniques, including linear voltammetry, cyclic voltammetry, differential pulse voltammetry and stripping voltammetry [51].





The cyclic voltammogram in figure 1 provides information about the

quantity of analyte at the electrode-solution interface on which the current

resulting from electron transfer in redox processes depends.

The current is made up of two components: a faradaic current on the redox

reaction of this species on the electrode and a capacitive current which is

required to charge the electric double layer at the electrode/solution interface

[50].

Figure 1. Cyclic voltammetry waveform (a) and typical cyclic voltammogram (b) [36].

Voltammetric techniques have become popular in the design of E-tongues[29]. Winquist et al., combined voltammetry signals from two electrodes, gold

and platinum, to classify various samples, such as fruit juices, non-carbonated

beverages and milk, in addition to being able to monitor ageing processes of

milk and orange juice stored at room temperature [30].

2.4. Impedance Sensors

Impedance spectroscopy is widely used to study electrical properties of

materials, which is attractive because of its simplicity [41]. It can be used in an

E-tongue system for liquid samples, as depicted in figure 2. Itinvolves the

application of an alternating current (AC) with variable frequency between

two electrodes, generating spectra for the real and imaginary components of

the impedance. The current measured results from movements of electrons,

holes and ions, also including polarization and depolarization currents due to

the motion of electric dipoles. The impedance spectrum depends on the properties of the film material itself, such as conductivity, dielectric constant,

chargemobility, charge generation and recombination, and on the interaction

with the liquid sample.





Figure 2. Experimental setup usually employed in impedance spectroscopy

measurements [23].

Such interaction affects the interfacial capacitance region, diffusion

coefficient, injection and charge accumulation [52]. The impedance data can

be interpreted using equivalent circuitsor the properties can be correlated with

microscopic mechanisms [53].

Riul and collaborators introduced E-tongues based on impedance

spectroscopy and with sensing units made with nanostructured films depositedon interdigitated gold electrodes. In one of the instruments employed, up to 10

different sensors could be used in less than half an hour using a software

interface that allows the statistical correlation of samples using principal

component analysis [54,55,56].

3. TYPES OF DATA ANALYSIS

The amount of data generated in E-tongue measurements is naturally large

because one deals with complex liquids and data are obtained with several





sensors. Therefore, computational and statistical methods are required tohandle such data. The most used belong to the class of tools in multivariatedata analysis, including Principal Component Analysis (PCA) [19,57,58,59],

Partial Least Square (PLS) [60,61] and other multidimensional projectionstechniques [62]. Also used are computational methods such asArtificial Neural Networks (ANN) [63,64,65], Principal Component Regression (PCR) [66],Cluster Analysis [67], Information visualization techniques [56,68], andHybrid Approaches [69]. A short description of some methods to analyze datain the context of E-tongues is given below.

3.1. Principal Component Analysis

The simplest and most widely used chemometric technique is PrincipalComponent Analysis (PCA) [65], which is used to correlate data statistically by reducing the dimensionality of the data space. It uses a linear combinationof the initial variables that contribute most to the variance in the data, whichmakes the samples distinct from each other. A small set of variables resulting

from these linear combinations (principal components) is identified in order toretain as much of the information contained in the original variables. WithPCA redundant information from the data is removed. Formally, theeigenvectors are the Principal Components (PC), and typically two or threePCs can characterize most experimental data sets. An example of a 3D PCA plot is given in figure 3, where data from samples of vinegar obtained with anE-tongue are represented [70]. Successful discrimination is noted by theestablishment of clusters for the distinct samples. From the first two

components (PC1 and PC2), the pure vinegars can be distinguished from waterand diluted vinegars. The results are clear demonstration that an E-tongue can be used to control the quality of a given product, and indeed avoidfalsifications. PCA is unable to analyse data properly in cases where thesensors behave in a non ideal manner, for example when there is hysteresisand the sensor response is highly nonlinear with regard to changes inconcentration of an analyte.





Figure 3. PCA classification of pure and diluted vinegars. Reprinted with permission

from ref. [70].

3.2. Partial Least Squares

Partial least squares regression (PLS) [60,61] is another method to

correlate data statistically, which combines features from principal component

analysis with linear regression. There is also a function for reducing the datadimensionality, but this requires a matrix of dependent variables in addition to

the initial data. PLS seeks factors that may capture the variance of the original

data and correlate with the dependent variables. The PLS algorithm uses

spectral decomposition techniques applied to calibration samples, where a

higher weight is attributed to the spectra for analytes with higher

concentrations. The PLS components are referred to as latent variables and do

not necessarily coincide with the major components. PLS is advantageous in

that it associates the spectral coverage with prediction and calibration, beinggenerally robust to be used in complex mixtures. A disadvantage is the need of





a proper selection of calibration samples, as these should not presentcolinearity in their properties.

3.3. Artificial Neural Networks

Artificial Neural Networks (ANNs) are used to analyze data with a largenumber of complex inputs, in a method that is analogous to brain functionswhereby data analysis is undertaken with a parallel architecture. In thiscontext, ANNs are unique in being capable of undertaking standard digitalcomputing calculations but also capable of data analysis that would be not be

possible using standard techniques. With ANNs onecan perform calculationswithout prior knowledge of a model to explain the data, and may also be usedto create such models (algorithms). They have found use in psychology,navigation, security, economics among other areas that require complexmathematical analysis of large systems [63]. ANNs have also been used inchemical and biological sensing, with designs that depend on the type ofsensors and analysis [65,71]. While the method based on ANNs may provideexcellent results in analysis large amounts of data, it exhibits disadvantages

such as long learning time and possible non convergenceto a solution.

3.4. Other Information Visualization and Artificial Intelligence

Methods

In addition to multidimensional projections techniques, other visualizationand artificial intelligence methods have been used [62], which has led to the

design of expert systems for clinical diagnosis [72]. Perhaps the most relevantfeature in the use of additional tools has been the possible optimization of biosensors and E-tongues, whereby sensing units, experimental conditions and projection techniques may be selected to maximize performance. For instance,the non-linear method referred to as Sammon´s mapping has been shown toyield superior performance than linear techniques for biosensing data [62].Though the reason for this superiority has not been found formally, it isspeculated that it is due to the capturing of subtleties in the highly nonlinear

response in biosensors. Another example of optimization is the use of theParallel Coordinates technique associated with genetic algorithms to scan thefrequency space in impedance spectroscopy measurements, which canimprove performance considerably [62,72].





4. APPLICATIONS OF E-TONGUES

The E-Tongue is used within different fields of research and industry as it provides a unique analytical solution. It is capable of measuring changes inindividual chemicals in complex solutions, it allows for the quantification oftaste and provides characterisation of a complex solution without the need forindividual chemical identification. Due to the customizability of sensorcomposition as well as different methods of data analysis, the E-Tongue iscapable of measuring a variety of chemical substances under varyingcircumstances. An important development in E-Tongueshas been the ability tomeasure samples through manual introduction or through flow-based analysis.

The latter used in tandem with the E-Tongue allows for continuous monitoringof the samples [73], which can be of two types, namely Flow InjectionAnalysis (FIA) and Sequential injection Analysis (SIA). Figure 4 shows aschematic diagram of FIA which is based upon the insertion of a reproduciblevolume of sample or standard onto the sensors in a continuous flow of carrieror reagent solution [74]. SIA works upon the same principle as FIA, but itallows for the amount of reagent, sample and/or standard to be altered. This provides further information about sensors response under varying

circumstances [75]. Flow-based analysis also eliminates costly manual procedures [76,77] and allows for rapid creation of a classification model forthe E-Tongue due to the ability to automatically measure a large quantity ofsamples, which may be a requirement for reaching a classification modeldepending on the complexity of the solution.

E-Tongue shave been combined with other liquid analytical techniquessuch as HPLC, UV-Vis and IR spectroscopy, for several purposes. Thiscombination of methods may be necessary to identify and quantify chemical

compounds, which is not possible with the E-tongue alone. Analytical methodsmay also serve to create classification models whichcould then allow the E-tongue to be used independently. When used in tandem with an Electronicnose, the E-Tongue may provide characterisation of a complex solutionincluding both volatile chemical analysis and liquid chemical analysis.

To provide an insight into the use of E-tongue in industry, examples aregiven in its main areas of use, including foodstuffs, pharmaceuticals, medicaldiagnostics, and environmental or agricultural monitoring.





Figure 4. Example of an SIA injection system. Reprinted with permission from ref.[78].

4.1. Foodstuffs Industry

Within the foodstuffs industry the E-Tongue has been used in qualitycontrol during processing and manufacturing, monitoring of biological processes, identification of foods and beverages and classification of artificial

flavours [79]. Xavier et al., developed an E-Tongue using 21 ion selectiveelectrodes capable of categorizing beer according to the type of beer and beer brands. The 5 main types analysed were Shwarzbier, lager, double malt,Pilsner, Alsatian and low-alcohol content beer. The responses were evaluatedusing two pattern recognition methods, principal component analysis (PCA),which identified some initial patterns, and linear discriminant analysis (LDA).The alcohol content of beer was also predicted from the data matrix byemploying a neural network model. A positive identification rate of 82% for

beer category was achieved when using the classification models4. In anotherstudy of fifty Belgian and Dutch beers, an E-tongue was able to predict realextract, alcohol and polyphenol content as well as the level of bitterness of the beers with a high level of accuracy [80].

Ciosek et al., used a voltammetric E-tongue with flow based analysis tomeasure different sources of milk. The information allowed for food qualitycontrol and the measurement of fat content in milk to protect againstadulteration and contamination [81]. A potentiometric sensor array consisting

of seven sensors using an Ag/AgCl reference electrode was able to monitorchanges in probiotic fermented milk during storage. The aim was to detectchanges in taste over a period of 20 days and compare with data from a human





sensory panel. Correlation was achieved between the different types of probiotic milk tasted by the E-tongue and that of the panel [82]. Mara et al.,classified monofloral honey with a high variability in floral origin with a

potentiometric E-tongue after making a preliminary selection of honeyaccording to their colours: white, amber and dark honey. The results pointed toa satisfactory sensitivity towards floral origin allowing for better separation ofhoney types [83]. Potentiometric and voltammetric E-tongues were combinedto classify honey samples of different floral and geographical origins. The potentiometric E-tongue consisted of seven chemical sensors, while thevoltammetric E-tongue comprised six working metal sensors. Four types ofhoney from different floral origins and four types of acacia honey from

different geographical origins were classified by both multi-sensor systems.Principal component analysis (PCA) and discriminant function analysis (DFA)were used to classify honey samples, with good results being obtained by bothkinds of E-tongues [84].

An array of polypyrole sensors was used to classify coffee samples [85].E-tongues have been used to identify green teas according to theirgeographical origin [86], and to determine the contents of catechins andcaffeine in green tea in comparison to reverse phase HPLC, where the array

consisted of seven silicon transistor sensors with an organic coating and anAg/AgCl reference electrode [87]. Gregorut et al., used an E-tongue composedof 8 polymer electrodes to measure differences in taste of 5 genetically distinctsoy bean varieties. Using PCA analysis the E-tongue was capable todistinguish the flavours of the 5 groups of Soy bean, while a panel of humanscould only distinguish flavours of Soy bean from 3 groups [88].

Much has been published with the use of E-Tongue in wine analysis, particularly due to the complexity of wine. Simões et al., used 10

potentiometric chemical sensors to measure the total Fe, Cu, Pb and Cdcontent in digested wine [89]. An E-Tongue was combined with an E-nose toanalyse the levels of oxygen and polyphenols in red wine by establishingcorrelations with chemical composition using partial least squares regression(PLS) [90]. Aging in wine was investigated with a voltammetric E-tonguemade with six modified graphite-epoxy electrodes, where classificationaccording to the vintage time could be obtained by treating the voltammetricdata with Linear Discriminant Analysis (LDA) [91]. A quantitative model was

constructed using ANNs for predicting the total quantity of sugar in the winesamples, which was also used to classify the samples [47, 92, 93, 94, 95].Apetrei et al., applied a voltammetric E-Tongue containing printed

electrodes modified with polypyroleto analyze phenolic compounds in





extravirgin olive oil [96]. Redox processes from both phenolic compounds and polypyrole were observed in the cyclic voltammograms, which were processedusing the Kernel method to determine polyphenol content. Also, the different

phenolic compounds in olive oil could be distinguished when added toemulsions of olive oil, and this could be confirmed with PCA and minimum partial squares [96]. A study was developed to detect adulteration of argan oilwith sunflower oil, along with an electronic nose and a voltammetric E-tongue. PCA, discriminant analysis factor (DFA) and support vector machines(SVMs) were used to distinguish between pure argan oil and those adulteratedwith sunflower oil, including the determination of the degree of adulteration[97]. An E-tongue comprising thirty potentiometric sensors was used to detect

spoilage of fish, for which the data were analyzed with PCA [98]. An E-tongue based on impedance spectroscopy was used for evaluation of thefermentation of bread dough, meat quality and to assess the level of foodcomponents such as water and lipid content of meat [29].

4.2. Pharmaceutical Industry and Flavour Assessment

In the pharmaceutical and food industries, E-tongues are used for flavourenhancement and flavour masking of products to help provide a more palatable formulation for human consumption. The aim is to identifyunpleasant tastes and then verify whether addition of chemicals can mask anundesired taste [99,100,101]. For example, the E-Tongue can detect inhibitionof bitterness by a sweetener, including optimization of the sweetener level in aliquid formulation [102,103]. An E-Tongue composed of lipids in a PVC arraywas able to determine umami, sweet, salty and bitter tastesusing

potentiometric methods. The voltammetric E-Tongue has been used togetherwith infrared spectroscopy to detect the umami taste. In particular, the signalsof the E-Tongue showed the highest correlation with the umami attribute[104]. An E-tongue with seven lipid membrane sensors was used to detect bitterness of quinine hydrochloride. The study found a low detection limit forquinine hydrochloride comparable to what human taste panels achieved [105].

A panel of human experts can be used to establish correlation with datafrom an E-tongue, thus also serving to train the E-Tongue with the creation of

a classification model. Hence, an E-tongue may effectively predict tastemasking or flavour in other formulations, making it unnecessary to employ ahuman panel in product development [106,107].





4.3. Medical Diagnostics

In diagnosis there are two types of application of E-tongues. In the first, a

usual E-tongue made of non-selective sensing units is employed to analyse the patient’s saliva, urine, sweat, blood and skin to identify a particular disease.Examples include clinical monitoring in vivo, as is the case of measurementsof urine from patients during dialysis, which were employed to determine ureaand creatinine in a range of concentrations where the initial and final phases ofdialysis could be differentiated [16,43]. Also, Lvova et al., could distinguish between urine samples of healthy patients, and those with malignant and non-malignant tumour diagnosis of bladders using an E-tongue [108]. In the second

type of application, one or more of the sensing units contain a biomoleculecapable of molecular recognition. Therefore, the sensing units may themselves be considered as biosensors, and the concept of E-tongue is extended toinclude highly selective sensing units. Obviously, the inclusion of biosensors based on interactions among antibodies, antigens, enzymes, nucleicacids/DNA and cellular structures/cells provides an increased capacity inmedical diagnostics [109].

Detection of diseases, such as celiac and cardiovascular diseases have

been made, as well as with identification of biomarkers for lung and bonecancer [62,72,110,111,112,113]. Recent nanomaterial-based electrochemical biosensors can detect specific biomolecules at previously unattainable ultra-low concentrations [114]. Research with E-tongues in medicine is relativelynew compared to that conducted with Electronic noses. However, E-Tonguescan measure chemicals that the E-nose cannot due to the higher boiling pointsof biomarkers associated with diseases only being present in the liquid phase.

4.4. Environmental and Agricultural Monitoring

In environmental monitoring E-tongues have been used to detectagricultural and industrial pollution in water, including identification of toxicsubstances. Hong et al., developed an E-tongue to automatically detect heavymetals in sea water, which was able to detect Hg, Fe, Cr [115]. Mortinson etal., used chalcogenide glass sensors with flow based analysis to measure heavy

metals in smoke from incineration plants [116]. The measurement of pesticides has also been successful including determination of pesticides usingchemical signatures. This could potentially lead to pesticide detection in foodsand waters. The detection of the insecticides chlorpyrifosoxon, chlorfenvinfos





andazinphos methyl-oxon at low limits of detection of 10 nM has beenachieved with E-tongues [117,118]. A voltammetric E-Tongue was used for predicting concentrations of ammonia and orthophosphate in wastewater

effluentwhere the voltammetric response was correlated with theconcentrations employing partial least squares analysis [119]. The differentgeographical origins of 7 classes of tap water have been distinguished by E-Tongue measurements [120].

Campos et al., used a voltammetric E-Tongue made with a set ofelectrodes of noble (Au, Pt, Rh, Ir and Ag) and non-noble (Ni, Co, and Cu)metals to analyze parameters of water quality of influent and effluentwastewater from a pilot plant. This E-tongue was relatively efficient for

determining concentrations of phosphate ions, sulphate and ammonia [121].Braga et al., used an E-tongue to detect the toxic sub products from algaedecomposition 2-methylisoborneol and geosmin (GSM) in water, which isrelevant for water treatment companies [122]. Also assessed in the latter workwas the possible low-cost monitoring for water treatment plants, especiallyshowing that the E-tongue was capable of reproducibly discriminating twocontaminants in distilled or tap water, in concentrations as low as 25 ng L−1

[122].

The extended concept of E-tongues to include selective biosensors in thearray has also been used for environmental applications. A voltammetric E-Tongue consisting of carbon paste electrodes modified with phthalocyaninescombined with immobilized tyrosinase or glucose oxidase was utilized tomonitor maturation of different varieties of grapes [123]. Such extended E-tongues can be used to detect endotoxins and other bacterial contaminatingspecies in purified water [124], and to analyse staphylococcal enterotoxin B,ricin, cholera toxin, botulinum toxoids, trinitrotoluene, and mycotoxinfumonis

in toxins at levels as low as 0.5 ng mL−1

[125].The E-tongue has been used in other areas of industry such as the analysisof petroleum products. For example, the E-tongue combined with an E-nosedisplayed enhanced discrimination of the main fuels used in flex-fuel enginesin Brazil, being also able to detect adulteration in commercial fuels [126].

5. ADVANCES

Advances in sensing materials combined with an increase in the ability tomanipulate data and sensing methods have paved the way for new branches of





study using the E-tongue. Below we highlight important progress in someissues in recent years, in addition to challenges to be faced.

5.1. Reliability

One of the problems with E-tongues is the variability of sensors madewith nanostructured films that causes a lack of reproducibility even fornominally identical units. This makes comparison between E-tongue unitsdifficult and means that each individual E-tongue needs to have aclassification model built. Available for purchase by laboratories and

industries are two Commercial E-tongues: the SA402B (Insent Inc., Atsugi-chi, Japan) and the ASTREE e-tongue (Alpha M.O.S, Toulouse, France). TheInstitute of Pharmaceutics and Biopharmaceutics, Heinrich-Heine UniversityDusseldorf undertook a study to determine compatibility betweencommercially produced E-tongues in different laboratories in 2014. Conductedtests indicated that several Insent E-tongues could perform comparably [127].Therefore, E-tongues could potentially be standardised and given standardclassification models to use. This would allow the E-tongue to perform testing

across multiple sensing units and increase the data gathering capabilityallowing for large libraries to be gathered.

A study in 2013 by Eckert using Human panellistsand an E-tongue andHPLC was undertaken to determine if the E-tongue was capable of completelyreplacing human panellists. What the experiment showed is that HPLC is theonly way to provide a quantitative and qualitative analysis of individualchemicals within the sample. However, E-tongues respond appropriately tolarge changes in formulations of herbal extracts whereas human panellists

were only able to notice a change in the lowest concentrations [13]. The mainconclusion was that the E-tongue is useful for determining changes within theformulation but a human taste panel is required as the E-tongue is unable toreplicate humantaste since it detects changes of chemicals within the samplethat the human tongue is unable to notice.

5.2. Sensor Materials

An important development in liquid sensing technologies has been theintroduction of graphene-based sensors, for detecting gases, heavy metals, biological molecules and proteins [128]. Publications on graphene-based





sensors have increased fast since 2009 [129]. The sensors are relatively stableover time, with little change in electrical response after repeated use [130], andhave already been used in E-tongues. Afkhami et al., developed a new nano-

composite potentiometric sensor made of graphene nanosheets/ thionine/molecular wire for nanomolar detection of silver ion in various real sampleswhere a detection limit of 4.17×10−9mol L−1 in liquid solutions was achieved.The sensor was able to determine silver in radiological filmsand drug samples[131]. Cooper et al., used sensors of graphene and carbon nanotubes to detect petroleum products in water over time [126]. Graphene may also be doped,thus allowing for increased selectivity [132]. Graphene prepared byelectrochemical reduction of graphite oxide was used in a modified glassy

carbon electrodeto detect hydroquinone with higher selectivity and sensitivitycompared to an unmodified glassy carbon electrode [133].

Many other nanostructured materials have been experimented to advancesensing capabilities of E-tongues. These include conducting polymer filmsofdifferent chemical structures, such as those of polyaniline and its derivatives as poly(o-ethoxyaniline) (POEA). A nanostructured film POEAcan be dopedwith other compounds to allow for high sensitivity and greater selectivity,which was the case of determination of heavy metals and hydrogen sulphides

in water. Furthermore, sensing units containing POEA and chitosannanoparticles could be combined to mimic human taste [134,135,136].

5.3. Robotics

The integration of E-Tongue and robotics systems is beginning to beexplored [137]. Russel et al., designed a mobile robot called TASTI equipped

with an E-tongue that dissolves ionic compounds in distilled water and thenmeasures the resulting ion concentration using a conductivity sensor. The E-tongue data allow the robot to follow trails of low-volatility chemicalsdeposited on the ground [138].

CONCLUSION

In this Chapter we described the principles behind the use of E-tongues,and included many of their applications, in addition to recent advances on dataanalysis techniques. Results from various research projects in many countrieshave proven that the E-tongue technology is capable of providing analytical





capabilities in the food, pharmaceutical, medical, environmental monitoringand agricultural areas. In such applications, E-tongues may mimic humantaste, but also be employed in cases where humans could not be exposed, as in

monitoring environmental changes. Of particular interest over the last fewyears was the extension of the E-tongue concept to include sensing unitscapable of molecular recognition, since this extended E-tongue can also beused in clinical diagnosis. We also discussed limitations of the methodsutilized in E-tongues, pointing to possible developments to make thetechnology widely available in the market place.

ACKNOWLEDGMENTS

The authors acknowledge the financial support from CAPES (PNPD Proc.23038006985201116) FAPESP (Proc. 2007/05089-9), CNPq (CNPq – Proc.471632/2012-0), and nBioNet network from CAPES (Brazil).

R EFERENCES

[1] del Valle, M., Electroanal 2010, 22 (14), 1539-1555.[2] Tahara, Y., Toko, K. IeeeSens 2013, 13, 3001-3011.[3]

Legin, A., Rudnitskaya, A., Vlasov, Y., DiNatale, C., Davide, F., D’Amico, A. SensActuat. B-Chem. 1997, 44, 291-293.

[4]

Cetó, X., M., G.-C., Calvo, D., M., d. V. Food Chem. 2013, 141, 2533-2540.

[5]

Huang, A. L., Chen, X.; Hoon, M. A.; Chandrashekar, J., Guo, W.,

Tränkner, D., Ryba, N. J. P., Zuker, C. S., Nature 2006, 442, 934-938.[6]

Nelson, G., Hoon, M. A.; Chandrashekar, J., Zhang, Y., Ryba, N. J.,Zuker, C. S. Semin. Cell Dev. Biol. 200, 106, 381-390.

[7]

Roper, S. D. Semin. Cell Dev. Biol. 2013, 24, 71-79.[8]

Peris, M., Escuder-Gilabert, L., Anal. Chim. Acta 2013, 804, 29–36.[9]

Scampicchio, M.; Ballabio, D.; Arecchi. A.; et al., Microchim Act 2008,163, 11-21

[10] Trivedi, B. P., Nature 2012, 486, S2–S3.

[11]

Chen, Q., Shen, C., Zhanh, S.,Gan, Z., Hu, R., Zhao, J. Food Eng 2013,116, 627-632.

[12]

Bartoshuk, L. M., Chem. Senses 2000,75, 447–460.





[13]

Eckert, C., Pein, M.,Reimann, J., Breitkreutz, J. SensActuat. B-Chem.

2013, 182, 294-299[14] Toko, K., Sensor Actuator , 2000, 64, 205-215.

[15]

Vlasov, Y., Legin, A.; Rudnitskaya, A. Anal. Bioanal. Chem. 2002,373,136–146.

[16]

Ciosek, P., Wróblewski, W., Ed. Analyst, 2007,132, 963–978.[17]

Campos, I., R., B.; Armero, R.; Gandia, J. M.; Soto, J.; R., M.-M.; Gil-Sánche, L. Food Res. Int , 2013, 54,1369–1375.

[18]

Di Natale, C., Mantini, A.; Macagnano, A.; Antuzzi, D.; Paolesse, R.;D’Amico, A. Physiol Meas, 1999, 20, 1-8.

[19] Krantz-Rülcker, C., Stenberg, M.; Winquist, F.; Lundström, I. Anal.

Chim. Acta, 2001, 426, 217-226.[20]

Mimendia, A., Gutierrez, J. M.; Leija, L.; Hernandez, P. R.; Favari, L.;Munoz, R.; Del Valle, M. EnvironModellSoftw, 2010, 25,1023–1030.

[21]

Dymindski, D. S., Takeda, H. H.; Mattoso, L. H. C.; Cândido, L. M. B. JFoodTechnol, 2005, 8,312-320.

[22] Bobacka, J., Ivaska, A.; Lewenstam, A. ChemRev 2008,108, 329−351.[23] Riul Jr, A., Dantas, C. A. R.; Miyazakic, C. M.; Jr., O.; O.N. Analyst

2010, 135, 2453–2744.

[24]

Latha, R. S., Lakshmi, P. K. J. Adv. Pharm Technol. Res. 2012, 3, 3-8.[25]

Vlasov, Y. U.; Legin, A.; Rudnitskaya, A. Sens Actuators B: Chem 1997, 44, 532-537.

[26] Deshpandet, M. V., Amalnerkar, D. P. ProgPolymSci, 1993, 18,623-649.[27] Wiziack , N. K. L., Paterno, L. G.; Fonseca, F. J.; Mattoso, L. H. C.

SensActuators B: Chem. 2007, 122, 484-492.[28]

Ciosek, P., Wróblewski, W. Sensors 2011, 11, 4688-4701.[29]

Alcaniz, M., Vivancos, J. L.; Masot, R.; Ibanez, J.; Raga, M.; Soto, J.;

Martínez-Máñez, R. J. FoodEng 2012, 111, 122–128.[30] Winquist, F., Wide, P.; Lundstrom, I. Anal. Chim. Acta 1997, 357, 21-23.

[31]

Ivarsson, P., Krantz-Rülcker, C.; Winquist, F.; I., L. ChemSenses 2005,30, 258–259.

[32]

Cabral, F. P. A., Bergamo, B. B.; Dantas, C. R. A.; Riul Jr., A.;Giacometti, J. A. RevSciInstrum, 2009, 80, 026107-1 – 026107-3.

[33] Toko, K., MaterSciEng 1996, 4,69-82.

[34]

Hayashi, K., Yamanaka, M.; Toko, K.; Yamafuji, K. Sensor Actuator1990, 2,205-213.[35]

Legin, A. V., Vlasov, Y. G.; Rudnitskaya, A. M.; Bychkov, E. A.SensorActuat. B 1996, 34, 456-461.





[36]

Grieshaber, D., MacKenzie, R.; Voros, J.; Reimhult, E. Sensors 2008,8,1400-1458.

[37] Sethi, R. S., BiosensBioelectron 1994, 9, 243-264.

[38]

Miyanaga, N., Inoue, A.; Ohnishi, A.; Fujisawa, E.; Yamaguchi, M.;Uchida, T. Pharm. Res., 2003, 20,1932–1938.

[39]

Pohanka, M., Skládal, P. J. ApplBiomed , 2008, 6,57–64.[40]

Bakker, E., Bhakthavatsalam, V.; Gemene, K. L. Talanta 2008, 75, 629-635.

[41]

Zhang, X., Electrochemical Sensors, Biosensors and their BiomedicalApplications. Ju, H.; Wang, J., Eds. Chennai, Índia, 2011; Vol. 1.

[42] A., R., Rocha, S. M.; Legin, A.; Pereira, V.; Marques, J. Anal. Chim.

Acta 2010, 662, 82-89.[43]

Ciosek, P., Grabowska, I.; Brzozka, Z.; Wroblewski, W., MicrochimActa 2008, 163,139-145.

[44]

Escuder-Gilabert, L., Peris, M. Anal. Chim. Acta 2010, 665, 15-25.[45]

Schuhmann, W., Zimmermann, H.; Habermuller, K.; Laurinavicius, V. Faraday Discuss 2000, 116, 245-255.

[46] Gorton, L., Lindgren, A.; Larsson, T.; Munteanu, F. D.; Ruzgas, T.;Gazaryan, I. Anal. Chim. Acta 1999, 400, 91-108.

[47]

Buratti, S., Ballabio, D.; Benedetti, S.; Cosio, M. S. Food Chem. 2007,100, 211-218.

[48]

Holmin, S., Bjorefors, F.; Eriksson, M.; Krantz-Rulcker, C.; Winquist,F. Electroanal 2002, 14, 839-847.

[49] Gutés, A., Ibánez, A. B.; Del Valle, M.; Céspedes, F. Electroanal 2006,18,82-88.

[50]

Brett, C. M. A.; Brett, A. M. O., Electroanalysis,. Oxford University,1998.

[51]

Winquist, F., 2008, 163, 3-10.[52] Barsoukov, E.; Macdonald, J. R., Impedance spectroscopy: theory,

experiment, and applications. Hoboken, N.J., 2005; Vol. 1.[53]

Gozzi, G., Chinaglia, D. L.; Schmidt, T. F. J. Appl. Phys. D 2006, 39,3888-3894.

[54]

Riul Jr, A., Malmegrim, R. R.; Fonseca, F. J. Artif. Organs 2003, 27,469-472.

[55] Riul Jr, A., Souza, H.; Malmegrim, R. R.; Santos Jr, D. S.; Carvalho, A.

C. P. L. F.; Fonseca, F. J.; Oliveira Jr, O. N.; Mattoso, L. H. C., Eds.Sensor Actuat B-Chem 2004, 98, 77-82.





[56]

Volpati, D., Aoki, P. H. B.; Dantas, C. A. R.; Paulovich, F. V.; deOliveira, M. C. F.; Oliveira, O. N.; Riul Jr., A.; Aroca, R. F.;Constantino, C. J. L., Eds. Langmuir 2012, 28, 1029-1040.

[57]

Ryan, M. A., Computational methods for sensor material selection

Springer: 2009.[58]

Potyrailo, R. A.; Mirsky, V. M., Combinatorial methods for chemical

and biological sensors. 2009.[59]

D’amico, A.; C., D. N.; Martinelli, E., Introduzione all’Analisi dei dati

sperimentali. 2006.[60] Wold, S. Chemometr Intell Lab 2001, 58, 109-130.[61] Barker, M.; Rayens, W. J. Chemometr2003, 17,166-173.

[62]

Oliveira Jr., O. N., Pavinatto, F. J.; Constantino, C. J. L.; Paulovich, F.V.; De Oliveira, M. C. F., Eds. Biointerphases 2012, 7, 1-15.

[63]

Haykin, S., Neural Networks. 2 ed.; Prentice Hall PTR Upper SaddleRiver, NJ, USA 1998.

[64]

Baratto, G. Classificador de aromas com redes neurais artificiais para umnariz eletrônico. Universityof São Paulo, São Paulo - Brazil, 1999.

[65] Hierlemann, A., Schweizer-Berberich, M.; Weimar, U.; Kraus, G.; Pfau,A.; Gopel, W. Sens Update 1996, 2,119-180.

[66]

Lvova, L. Anal. Chim. Acta 2002, 468, 302-314.[67]

Moreno, L.; Merlos, A.; Abramova,N.; Jimenez. C.; Bratov, A. Sens Actuators B: Chem 2006, 116, 130-134.

[68] Paulovich, F.; Moraes, M.L.; Maki, R.M.; et al., Analyst 2011, 136,1344-1350.

[69] Parra, V. Anal. Chim. Acta 2006, 563, 229-237.[70]

Lvova, L., Talanta 2006, 70, 833–839.[71]

Jurs, P. C., Bakken, G. A.; McClelland, H. E. Chem. Rev. 2000, 100,

2649–2678.[72] Oliveira Jr., O. N.; Iost, R. M.; Siqueira Jr., J. R.; Crespilho, F. N.;Caseli, L., ACS Appl Mater Interfaces 2014, 6, 14745−14766.

[73]

Martı nez-Máñez, R., Soto, J.; Garcia-Breijo, E.; Gil, L.; Ibáñez, J.;Llobet, E., Eds. Sensor Actuat B-Chem. 2005, 104, 302-307.

[74]

Ruzicka, J., Hansen, E. H. Anal. Chim. Acta 1980, 114, 19-44.[75]

Ruzicka, J., Marshall, G. D. Anal. Chim. Acta, 1990, 237, 329-343.[76] Gutés, A., Céspedes, F.; Del Valle, M. Anal. Chim. Acta 2007, 600, 90-

96.[77]

Ciosek, P., Wesoły, M.; Zabadaj, M.; Lisiecka, J.; Sołłohub, K.; Cal, K.;Wróblewski, W. Sensor Actuat B-Chem. 2014.





[78]

Cortina, M., Gutés, A.; Alegret, S.; Del Valle, M. Talanta 2005,66,1197-1206.

[79] Jamal, M., Khan, M. R.; Imam, S. A. J. Rev. Surv. 2009, 1,130-137.

[80]

Polshin, E., Rudnitskaya, A.; Kirsanov, D.; Legin, A.; Saison, D.;Delvaux, F.; Delvaux, F. R.; Nicolaï, B. M.; Lammertyn, J. Talanta 2010, 81, 88-94.

[81]

Winquist, F., Bjorklund, R.; Krantz-Rülcker, C.; Lundström, I.;Östergren, K.; Skoglund, T. Sens Actuat B-Chem 2005, 111, 299-304.

[82]

Winquist, F., Krantz-Rülcker, C.; Wide, P.; Lundströ, I. MeasSci Technol 1998, 1937-1946.

[83] Sousa, M. E. B. C., Dias, L. G.; Veloso, A. C. A.; Estevinho, L.; Peres,

A. M.; Machado, A. A. S. C. Talanta, 2014, 128, 284-292.[84]

Wei, Z., Wang, J. Con Electro Agr 2014, 108, 112–122.[85]

Almario, A., Cáceres, R. Am. J. Anal. Chem. 2014, 5, 266-274.[86]

Chen, Q., Zhao, J.; Vittayapadung, S. Food Res Int , 2008, 41, 500-504.[87]

Chen, Q., Zhao, J.; Guo, Z.; Wang, X. J. Food Compos Anal. 2010, 23,353-358.

[88] Gregorut, C., AIP Conference Proceedings of the 13th InternationalSymposium on Olfaction and Electronic Nose. Brescia (Italy), 533-534.

[89]

Simões da Costa, A. M., Delgadillo, I.; A., R. Talanta, 2014,129, 63-71.[90]

Rodriguez-Mendez, M. L., Apetrei, C.; Gay, M.; Medina-Plaza, C.; Saja,J. A.; Vidal, S.; Aagaard, O.; Ugliano, M.; Wirth, J.; Cheynier, V. FoodChem 2014, 155, 91-97.

[91] Parra, V., Hernando, T.; Rodriguez-Mendez, M. L.; Saja, J. A. Electrochim Acta, 2004, 49,5177–5185.

[92]

Cetó, X., Capdevila, J.; Puig-Pujol, A.; Del Valle, M., Eds. Electroanal 2014; Vol. 26, pp 1504-1512.

[93]

Rudnitskaya, A., Delgadillo, I.; Legin, A.; Rocha, S. M.; Costa, A. M.;Simões, T., ChemometrIntell Lab, 2007, 88, 125-131.[94] Buratti, S., Benedetti, S.; Scampicchio, M.; Pangerod, E. C. Anal. Chim.

Acta, 2004, 525, 133-139.[95]

Legin, A., Rudnitskaya, A.; Vlasov, Y.; Di Natale, C.; Mazzone, E.;D'Amico, A., Eds. SensActuat. B-Chem. 2000, 65, 232-234.

[96]

Apetrei, C., Apetrei, I. M., Ed. Food Res. Int. 2013; Vol. 54, pp 2075– 2082.

[97]

Bougrini, M., Tahri, K.; Haddi, Z.; al., e., Eds. J. Sensors 2014; Vol.2014, pp 1-10.[98]

Legin, A., Rudnitskaya, A.; Seleznev, B.; Vlasov, Y. Int. J. Food Sci.

Tech., 2002,. 37,375–385.





[99]

Jańczyk, M., Kutyła, A.; Sollohub, K.; Wosicka, H.; Cal, K.; Ciosek, P. Bioelectrochemistry 2010, 80, 94-98.

[100] Woertz, K., Tissen, C.; Kleinebudde, P.; Breitkreutz, J. Int. J. Pharm.

2011, 417, 256-271.[101] Kobayashi, Y., Habara, M.; Ikezazki, H.; Chen, C.; Naito, Y.; Toko, K.

Sensors 2010, 10, 3411–344.[102]

Zheng, J. Y.; Keeney, M. P. Int. J. Pharm. 2006, 310, 118-124.[103]

Du Hyung C. ; Nam, A. K.; Tack, S. N.; Sangkil, L.; Seong, H. J., Eds. Drug Dev. Inf. Pharm, 2014; Vol. 40, pp 308-317.

[104] Bagnasco, L.; Cosulich, M. E.; Speranza, G.; L., M.; Oliveri, P.; Lanteri,S. Food Chem. 2014, 157, 421-428.

[105]

Woertz, K.; Tissen, C.; Kleinebudde, P.; Breitkreutz, J. J. Pharmaceut Biomed. Anal. 2010, 51, 497-506.

[106]

Woertz, K.; Tissen, C.; Kleinebudde, P.; Breitkreutz, J., Eds. Int. J.

Pharm. 2010, 400, 114-123.[107]

Lorenz, J. K.; Reo, J. P.; Hendl, O.; Worthington, J. H.; Petrossian, V.D. Int. J. Pharm. 2009, 367, 65-72.

[108] Lvova, L.; Martinelli, E.; Dini, F.; Bergamini, A.; Paolesse, R.; Di Natale, C.; D’Amico, A. Talanta 200977, 1097-1104.

[109]

Bănică, F.;Chemical Sensors and Biosensors:Fundamentals and Applications. John Wiley & Sons: Chichester, UK, 2012; p 576.

[110]

Altintas, Z.; Tothill, I. Sens Actuat B-Chem. 2013,188, 988-998.[111] Cennamo, N.; Varriale, A.; Pennacchio, A.; Staiano, M.; Massarotti, D.;

Zeni, L.; D’Auria, S. Sens Actuat B-Chem. 2013, 176,1008-1014.[112] Altintas, Z.; Fakanya, W. M.; Tothill, I. E. Talanta 2014, 128,177-186.[113]

Perinoto, A. C., Maki, R. M.; Colhone, M. C.; Santos, F. R.; Migliaccio,V.; Daghastanli, K. R.; Stabeli, R. G.; Ciancaglini, P.; Paulovich, F. V.;

De Oliveira, M. C. F.; Oliveira Jr., O. N.; Zucolotto, V. Anal. Chem.2010, 82,9763–9768

[114] Yun, Y.; Collins, B.; Dong, Z.; Renken, C.; Schulz, M.; Bhattacharya,A. App Nanomat Sens Diagnos Spring Ser. Chem. Sens. Biosens 2013,14, 43-58.

[115]

Men, H., Wang, Z.; Jin, J.; Ge, Z., Eds. Contr Dec. Conf. 2008; pp 1768 – 1771.

[116] Mortensen, J.; Legin, A.; Ipatov, A.; Rudnitskaya, A.; Vlasov, Y.;

Hjuler, K. Anal. Chim. Acta 2000, 403, 273-277.[117]

Cortina, M.; Del Valle, M.; Marty, J. L. Electroanal 2008, 20, 54-60.[118]

Alonso, G. A.; Dominguez, R. B.; Marty, J. L.; Muñoz, R. Sensors 2011,11, 3791-3802.





[119]

Campos, I.; Sangrador, A.; Bataller, R. Electroanal 2014, 26, 588-595.[120]

Sipos, L.; Kovács, Z.; Sági-Kiss, V.; Csiki, T.; Kókai, Z.; Fekete, A.;Héberger, K. Food Chemistry 2012, 135, 2947-2953.

[121]

Campos, I., M. A.; Aguado, D. Water Res. 2012, 46, 2605-2614.[122] Braga, G. S. Sens Actuators B: Chem 2012, 171,181-189.[123]

Medina-Plaza, C.; Revilla, G.; Mino, R. J. PorphyrPhthalocya 2014,18,76-86.

[124]

Heras, J. Y. ; Pallarola, D.; Battaglini, F. Biosens Bioelectron 2010, 25,2470-2476.

[125] Ligler, F. L.; Taitt, C. R.; Shriver-Lake, L. C.; Sapsford, K. E.; Shubin,Y.; Golden, J. P. Anal. BioanalChem. 2003, 377, 469-477.

[126]

Wiziack, N. K. L. In AIP Proceedings of the 14th InternationalSymposium On Olfaction And Electronic Nose, New York City, Ed. NewYork City, 2011; p 178.

[127]

Pein, M.; Gondongwe, X. D.; Habara, M.; Winzenburg, G. J. Pharm 2014, 469, 228-237.

[128] Liu, J.; Liu, Z.; Barrow, C. J.; Yang, W. Anal. Chim. Acta 2014.[129] Chang, J.; Zhou, G.; Christensen, E. R.; Heideman, R.; J., C. Anal.

BioanalChem 2014, 406.

[130]

Cooper, J. S.; Myers, M.; Chow, E.; Hubble, L. J.; et al., J. Nanopart Res. 2013,16, 2173.

[131]

Afkhami, A.; Shirzadmehr, A.; Madrakian, T.; Bagheri, H., Eds. Talanta 2015,131,548-555.

[132] Pumera, M.; Ambrosi, A.; Bonanni, A.; Chng, E. L. K.; Poh, H. L., Eds.Trends AnalytChem. 2010, 29,954–965.

[133]

Li, S.; Y., X.; Wang, G. Microchim. Acta 2012,176,163-168.[134]

Borato, C. E.; Leite, F. L.; Mattoso, L. H. C.; Goy, R. C.; Filho, S. P. C.;

de Vasconcelos, C. L.; da Trindade Neto, C. G.; Pereira, M. P.; Fonseca,J. L. C.; Oliveira, O. N. Diel & Elect Insul 2006, 13,1101-1109.[135] Leite, F. L.; Firmino, A.; Borato, C. E.; Mattoso, L. H. C.; da Silva, W.

T. L.; Oliveira Jr., O. N. SynthMet. 2009, 159,2333-2337.[136]

Brugnollo, E. D.; Paterno, L. G.; Leite, F. L.; Fonseca, F. J.;Constantino, C. J. L.; Antunes, P. A.; Mattoso, L. H. C.; Thin Sol Film2008, 516, 3274-3281.

[137] Grasso, F. W.; Consi, T. R.; Mountain, D. C.; Atema, J. Robot Auton

Syst. 2000,15,115-131.[138]

Russell, R. A. IEEE Inter. Conf. Robo Biomim, 2006, 1, 257-262.





Chapter 3

INORGANIC HYDROGELS FOR WHOLE-CULTURE ENCAPSULATION

Mercedes Perul l ini ,* Cecil ia Spedalier i,Matías Jobbágy and Sara A. Bilmes

INQUIMAE-DQIAQF, Facultad de Ciencias Exactas y Naturales,Universidad de Buenos Aires. Ciudad Universitaria,

Buenos Aires, Argentina

ABSTRACT

Sol-gel encapsulation of living cells within inorganic hydrogels,mainly silica, is a promising technology for the design of biosensors.These host-guest functional materials maintain specific biologic functions

of their guest while the properties of the host can be tuned to fulfill therequirements of particular applications. Inorganic immobilization hostsexhibit several advantages over their (bio)polymer-based counterparts.While both hosts provide tailored porosity, the former offers enhancedchemical stability towards biodegradation as well as higher physicalstability (low swelling). However, inone-pot encapsulations, the directcontact of cells with precursors during the sol-gel synthesis and theconstraints imposed by the inorganic matrix during operating conditionsmay influence the biological response. In order to prevent this, an

alternative two-step procedure was proposed. Living cells are pre-encapsulated in biocompatible carriers based on biopolymers such as

* Corresponding author: Fax: 54 11 4576 3341; [email protected].




Mercedes Perullini, Cecilia Spedalieri, Matías Jobbágy et al.58

alginates that confer protection during the inorganic and more cytotoxicsynthesis. By means of these carriers, whole cultures of microorganismsremain confined in small liquid volumes generated inside the inorganic

host, providing near conventional liquid culture conditions. Moreover,this approach allows the encapsulation of multicellular organisms and theco-encapsulation of multiple isolated cultures within a single commonmonolithic host, creating an artificial ecosystem in a diminished scaleisolated inside a nanoporous matrix that would allow ecotoxicity studiesto be carried out in portable devices for on-line and in situ pollution levelassessment.

Keywords: Sol-gel, whole-culture encapsulation, two-step procedure,

biosensors, ecotoxicity

INTRODUCTION

The amazing development of sol-gel technologies for the encapsulation ofliving cells and microorganisms inside inorganic matrices opens up new possibilities for the design of advanced functional materials. [1] During the

last decade, many efforts have been made in order to optimize both the hostmatrix properties and the biocompatibility of the synthesis process allowingthe encapsulation of different cell types in a wide range of hosting matrices.This broad combination of host properties and guest biological responsesallowed the development of hybrid materials that fulfil the needs of particularapplications. As a case in point, the design of advanced biosensing platforms based on algae encapsulation, results in portable, fast and economical tools fortoxic compounds detection in the environment.

Sol-gel encapsulation of living cells is a promising technology, mainlydue to its flexibility in terms of chemical composition and processingconditions. In particular, the synthesis of inorganic, ceramic type materials atlow-temperature and physiological or biocompatible pH enables the possibilityof whole-cell entrapment, keeping the complex biological responses of theguest. However, in direct encapsulation procedures, independently of the so-called soft chemistry involved, cytotoxicity may arise from the contact withsynthesis precursors particularly those in solution with higher biodisponibilityand thus higher toxicity. On the other hand, this initial stress during thesynthesis step, together with chemical interactions and/or mechanicalconstraints of the surrounding host matrix during operation conditions mayalter the biological responses of cells. Even in procedures exhibiting




Inorganic Hydrogels for Whole-Culture Encapsulation 59

acceptable viability, different microorganisms exhibited a high level of cellularstress during and after direct encapsulation procedures. When developing a biosensor based on signals triggered by biological stresses from an external

stimulus such as a toxic compound present in low concentrations in thesample, this stress baseline due to host-matrix interactions raises the detectionlimit of the device, decreasing its performance and/or its reliability. [2,3]

For applications in which the entire biosynthetic machinery iscompromised, such as biosensors and bioreactors, the physiological status ofentrapped cells becomes a key factor for material scientists. Given that typicalresponses of living cells in nature are not to be reproduced unless in near-natural environments, many strategies were adopted to prevent strong cell-

matrix interactions. By means of macroporous scaffolds, cells can beentrapped inside an inorganic material retaining cell-to-cell contact and the possibility of performing cell division in liquid media. [4] However, theseapproaches fail to avoid the leakage of the biological material of interest aswell as the income of contaminating agents, both being main requirements ofcertain applications. Though offering good mechanical and chemical stability,the inclusion of cells in macroporous scaffolds cannot be regarded as a properencapsulation method, since cells are immobilized but not trapped inside the

host matrix. Another interesting strategy recently proposed is theencapsulation of living cells in low-concentration silica hydrogels, whereentrapped cells retain solution like properties, including the ability to dividewithin the pores of the silica matrix. Even more important for biosensingapplications is the fact that at least for the model microorganism Escherichia

coli, cellular pathways are regulated in a similar manner in both solution andthese sol–gel-derived materials. [5] Still, mechanical properties of hydrogelssynthesized with low total silica content could be appropriate for some

applications but below the requirements of most realistic devices, as stiffnessis directly related to the silica content.Based on the success of the first attempts of biosensing devices obtained

by immobilization of microalgae on (bio)polymer-based counterparts, a two-step procedure including pre-encapsulation in such polymers of the biologicalguest arises as a promising alternative for the development of advanced biosensing platforms (see Figure 1). The strategy to encapsulate whole cellularcultures inside an inorganic matrix has already been employed for the

encapsulation of different microorganisms (bacteria, yeast, and microalgae),[6, 7] and plant cell lines (carrot floematic cells and tobacco-BY2 stable line),[8] as well as for the encapsulation of multicellular organisms (filamentousfungi and small metazoans). [9]





The huge diversification of potential cell types is only one part of the

solutions offered by this two-step strategy, because by taking advantage of the

protecting function of the (bio)polymer pre-encapsulation matrix, it is now

possible to enhance the matrix properties from a broader range of synthesis

conditions. Thus, employing a two-step method, sol-gel synthesis can be

conducted at a wider range of pH or using more cytotoxic precursors than

tolerated in direct encapsulations, resulting in optical, mechanical or transport

properties that better suit application requirements.

Figure 1. Schematic representation of the two-step synthesis strategy. I- Cells pre-

encapsulated in the alginate bead are placed into a mold; II-III Synthesis of the sol-gel silica

matrix; IV-V Citrate or other Ca(II) quelling agent is added to dissolve the Ca(II)-alginate

matrix and the dissolved bead leaves a liquid spherical cavity (filled with cells) inside the

inorganic monolith, and VI- culture medium is added to allow cell growth. In green are

shown the steps in which the cellular stress is a key factor; in orange are shown the steps in

which the transport properties of the inorganic matrix are crucial.

PRE-ENCAPSULATION IN BIOCOMPATIBLE POLYMERS

The protection of cells by pre-encapsulation in fully biocompatible

matrices before contact with inorganic hydrogel precursors and by-products

offers an efficient shield to the entrapped cells providing the sol-gel process

occurs in few minutes in order to minimize diffusion of cytotoxic species. The

protected cells are immersed in the sol before gelation takes place. The

concept is to provide an optimal environment for the encapsulated cells bytrapping them in a biopolymer, while improving the transport and mechanical

properties for long term viability with the mineral matrix.





Encapsulation of cells in biocompatible polymers is mainly done with biopolymers that undergo cross-linking even in the presence of the cells. [10-12] Polysaccharides are the most used due to their low cost and proven

biocompatibility with the encapsulated cells and the target, [13] although proteins, such as collagen, gelatin or fibrin may also fulfill the requirements.[14-20] Calcium alginate is one of the most popular hydrogels for cellencapsulation. Alginates are polysaccharides isolated from brown algae foundworldwide in coastal waters. They are linear unbranched copolymers thatcontain homopolymeric blocks of (1,4)-linked -D-mannuronic acid (M) andits C-5 epimer, -L-guluronic acid (G) residues, whose average molecularweight, the relative amount of residues and its distribution depend on the

source. [21] The alginate polymer is easily crosslinked with Ca2+ or Sr 2+ andtransition metals (Co2+, Zn2+, Cu2+, Ni2+, Cd2+, Mn2+) [16]; even H+ interactwith the polymer chains forming an hydrogel in acid media. [22,23] Thestructure of the network and it mechanical performance depend on the alginatemolecular weight, the M /G ratio and the association constant of the cation-alginate complex. [24] The structure of Ca-alginate gels is well described bythe egg-box model (figure 2a) proposed by Rees et al. [25] On the basis ofresults of rheology, SAXS and spectroscopic experiments three steps were

proposed for the formation of the hydrogel: (i) interaction of Ca2+ with a singleguluronate unit forming monocomplexes; (ii) propagation and formation ofegg-box dimers via pairing of these monocomplexes; and (iii) lateralassociation of the egg-box dimers, generating multimers. [26] It has even beendemonstrated that MG-GG or MG-MG junctions are also possible. [27]

The main advantages of Ca-alginate hydrogels is that they are easilyformed upon contact between Na-alginate and Ca2+ aqueous solutions. Thisfast gelation kinetics allows to prepare beads of Ca-alginate by dropping the

alginate solution in a CaCl2 or CaCO3 solutions. The size of the formed beadsis a function of the drop, which in turn is given by the diameter of the tipemployed for dropping, the viscosity of the Na-alginate solution dependent onthe temperature and alginate concentration, the Ca2+ concentration and theresidence time of the bead in the Ca2+ solution, and the presence of other ions(figure 2b). Although gelation rate is hard to control, once the parameters arefixed it is possible to get very reproducible forms, such as beads or cylinders.In fact, automatic systems have been developed for producing cell loaded Ca-

alginate beads ranging from less than 100 m to several mm. [31-34]





Figure 2. (a) Scehme of Egg box model for Ca-alginate structures for M-rich and G-

rich alginates. (b) Dependence of the bead diameter (relative to the Na-alginate dropdiameter) formed in 0.1 M CaCl2 with the alginate concentration and the residence

time in the CaCl2 solution.[28] (c) Scheme of a Ca-alginate bead obtained by dropping

Na-alginate in CaCl2. Adapted from references [29] and [30].

The swelling degree and porosity of Ca-alginate beads (or fibers) is a

function of solution ionic strength and pH, and the beads degrade via a process

involving the loss of multivalent ions into the surrounding medium. [35]

Adsorption of N2 on aerogels derived from Ca-alginate beads gives a broadsize distribution of the mesopores, centered on 30−40 nm, [36] although

macropores of 10 m and mesopores ranging from 8 to 10 nm have been

reported for 3 mm and 160 m bead diameters, respectively. [37,38] These

findings are a consequence of a radial distribution of gelation where the

reaction front determined by Ca2+

diffusion is kinetically hindered, leaving the

inner part of the bead ungelled (figure 2c), thus cells enclosed in the bead are

in a liquid medium that lowers the confinement stress.

The first attempt to combine biopolymers with silica for cellimmobilization was achieved by Fukushima et al. [39] by dropping a mix of

soluble alginate salts (Na+, K

+, NH4

+) with 9-13 nm colloidal silica and a yeast

suspension in CaCl2. This hybrid matrix showed clear differences in the SEM





surface texture when compared to that of alginate, due to the participation ofsilica NPs in the alginate cross-linking. As both alginate and silica arenegatively charged, their interaction should be mediated by Ca2+ and other

cations present in the solution. The electrostatic repulsion between alginateand silica leads to low adherence for growing thin membranes over the cellcontaining alginate capsules, thus the system becomes unpractical for thedesign of bio artificial organs. A way for overcoming this situation is toderivatize the surface of alginate beads with neutral or positively chargedgroups. Surface modification of alginate beads with 3-aminopropyl-trimethoxysilane (APTMOS) may be done by dispersing the capsules in n-hexane. By addition of TMOS an ORMOSIL (organically modified silica)

develops on the surface of the bead (figure 3).[40] Here, the silica network isformed by hydrolysis and condensation with water inside the bead. Withoutsilane, silica is dispersed within the bead due to electrostatic repulsion betweenthe silica units formed and negatively charged alginate chains. In the presenceof APTMOS, the amino group of silane is anchored to carboxylate groups ofalginate by electrostatic interaction, and the Si(OMe)3 undergoes sol-gelchemistry at the surface with the added TMOS. The resulting composite hasnegligible swelling, is chemically stable and rigid with pores that allow the

diffusion of small molecules, such as insulin. The biocompatibility wasimproved by adding an external layer of alginate anchored to a secondAPTMS layer. This layer by layer architecture avoids any interaction of silicawith the target body that can produce unwanted reactions, such as cellular proliferation providing a way to design a microcapsule-shaped bio artificial pancreas when beads are loaded with pancreatic islets releasing insulin. [41]

This layer by layer approach can be also conducted in aqueous systemswith poly-lysine, a well-known polycation for alginate bead coating. [42 43]

As the surface is now positively charged, condensation of Si(OH)4 derivedfrom sodium silicate at neutral pH forms a shell attached to the alginate bead.This process made by spray drying produces 350 nm spheres that are promising for drug delivery. [44] Removal of Ca2+ by complexation with biocompatible ligands, such as citrate breaks the alginate gel leaving a liquidcore with a siliceous shell. This process can be carried out with diluted silicatesolutions giving beads with good mechanical resistance, whereas whenconducted with preformed silica nanoparticles the covalent Si-O-Si bonds

between them are not enough for generating a strong silica network. [45,46]





Figure 3. Scheme of layer by layer growth of a biocompatible silica layer on the

surface of Ca-Alginate (a) alkoxyde route: by silanization of alginate surface and

growth of silica layer by hydrolysis and condensation of TEOS with water within the

alginate bead. A second layer of alginate is deposited on the silica shell.[37] (b)

aqueous route: by derivatization of the alginate surface with poly lysine and

condensation of Si(OH)4 at neutral pH. The alginate core can be dissolved by

complexation of Ca2+

ions with citrate. [39]

Coating of Ca-alginate beads or silk fibers containing the cells can be alsoachieved by the Biosil process. [47] Cultured multicellular aggregates of

HepG2 (Human hepatocellular liver carcinoma) cells, pancreatic islets or

Jurkat cells were mixed with Na-alginate and the suspension was dropped

from a microbead nozzle under an air flow saturated with a mixture of TEOS

and MTEOS (methyltriethoxysilane) into a CaCl2 solution, forming silica

covered Ca-alginate microcapsules. [48-50] In this procedure hydrolysis and

condensation of silicon alkoxydes at the surface of the forming bead proceed

via a mechanism which involves the formation of non-hydrophilic siliceousoligomers accumulating on the droplet surface which reduce the surface

tension of the alginate solution favoring the formation of small droplets.

Inspired in this last procedure, the two-step synthesis strategy was developed

combining an alginate pre-encapsulation embedded in silica or other oxy-

hydroxide monolithic matrix.





TUNING THE PROPERTIES OF THE HOST

The main advantages introduced by oxy-hydroxide hydrogels as hostmatrices reside in their high bio-stability (inertness towards enzymatic biodegradation) and their mechanical stability (low swelling). [51-53] Theformer is a prerequisite when designing a device meant for in situ detectionconsidering the variability of possible microorganisms present in theenvironment when analyzing real samples. On the other hand it is worthmentioning that host-guest interactions must be taken into account since the biological guest itself can take part in biodegradability processes of the hostmatrix. The mechanical stability per se is necessary for the development of

portable and self-supporting devices. Nonetheless, the tuning of porosity thatcan be attained during the synthesis of (bio)-polymer based matrices ismodified by swelling of these materials during operation conditions. Porosityin turn determines transport properties of these matrices, which is of crucialimportance for many reasons, including the transport of analytes (from cationsof heavy metals to high molecular weight organic compounds) towards theinside of the sensing module, and the diffusion of oxygen and nutrients to theencapsulated cells (in the case of long-term applications). Another important

issue to take into account regarding physical stability is biosafety whendesigning a biosensor based on genetically modified organisms or foreignmicroorganisms in straight contact with a natural environment. Theintroduction of exotic strains implies an inherent ecological risk, and biosafetydepends on the success of the encapsulation matrix to keep the biological guestisolated from the environment. Lastly, as some microorganisms are highlysensitive to the presence of contaminants, very low detection limits can beattained provided the transduction of the biological signal can be accurately

measured. For this reason, fluorescent-based detection is one of the mostextended transduction systems. However, long-term optical transparency ofthe host is required to assure reliable results. The limiting step in thedevelopment of these biosensing devices is the immobilization of sensitivecells (mainly microalgae) in a mechanical stable matrix with good optical properties and tuned porosity through a biocompatible encapsulation method.

High biocompatibility not only understood in terms of viability but in amore comprehensive basis concerning cellular metabolism and stress is not

easy to attain, especially when dealing with eukaryotic cells more sensitivethan widely encapsulated bacteria. [54] In this scenario, the two step synthesis procedure offers the possibility of conferring protection to encapsulated cellsduring the inorganic synthesis of the host matrix. The pre-encapsulation can be





performed with synthetic polymers (acrylamide, polyurethanes), proteins(gelatine, collagen), or natural polysaccharides (agar, carrageenan oralginates), which are highly biocompatible. [55, 56] An important reduction of

the cellular stress in the model organism Saccharomyces cerevisiae wasdocumented for two-step encapsulations compared to the direct procedureusing the same inorganic synthesis. [57] On the other hand and as mentioned before, the second step can be accomplished in more cytotoxic conditions. Forinstance, the two-step process relying on cell encapsulation in alginate beadsfollowed by inorganic gelation from colloidal metal oxides was successfullyapplied to the immobilization of Escherichia coli bacteria in the presence of boehmite and zirconium oxyhydroxide particles. [58] In the first case, the

protection conferred by the Ca(II)-alginate pre-encapsulation matrix providesan efficient barrier against the encapsulation stress. In contrast, an increase inthe alginate concentration together with the phosphate-induced mineralizationof the biopolymer bead is found necessary to maintain the viability ofentrapped bacteria in Zr-based gels. This optimization of the two-stepencapsulation process allowed the first observation of cell growth within Aland Zr-based oxide hydrogels. Another interesting example of alginatereinforced pre-encapsulation is the simultaneous improvement of optical and

transport properties based on the acidic encapsulation of microalgae in silicamatrices synthesized by TAFR (tetraethoxysilane derived alcohol free route).It was shown that samples synthesized at pH < 4.0 resulted almost translucent[59] while satisfactory transport properties of the matrix were obtained in the pH range 4.0–6.0. [60] In this case, to optimize the device the synthesis had to be conducted at a restricted pH range resulting from a compromise betweenoptical and transport properties desired in the final material. Tuning thealginate protecting function with the aid of Tris–HCl buffer, the sol–gel

synthesis was conducted at pH 4.0 well below the tolerance limit imposed bythe encapsulated microalgae (Chlorella vulgaris, Pseudokirchneriella

subcapitata and Chlamydomonas reinhardtii). [61]The versatility of the two-step procedure will once again be apparent when

considering the possibility of modifying the host matrix itself by usingsynthesis additives that could be toxic in direct contact with entrapped cells.Taking profit from the spatial separation between matrix synthesis and biological guest, a silica hydrogel with embedded CeO2 nanoparticles was

specially design to confer protection to photosynthetic guests (filteringharmful UV-light and diminishing oxidative stress of C. vulgaris). [62] Asimilar approach was employed for the development of a silica matrixsusceptible of being sterilized by bactericidal UV-irradiation, based on the





electrostatic adsorption of Rhodamine B on silica preforming particles. Onceentrapped in the silica gel, Rhodamine B act as an inner cut-off filter, protecting the encapsulated organisms from UV radiation. This matrix allows

the sterilization of encapsulation devices without affecting the viability of theentrapped microalgae cells resulting extremely valuable for externalsterilization procedures in industrial applications. [63]

TOWARDS ADVANCED BIOSENSING PLATFORMS

A biosensor in its broadest sense can be defined as a device with

biological or biologically derived sensing elements, such as an enzyme orantibody, or any sensor used to measure a biological event. Of course there isno reason why it could not be both at the same time, such as a serum glucosesensor based on the immobilization of the enzyme glucose oxidase. However,in this review we are devoted to biosensors understood as devices (small hand-held systems) that rely on biological materials or processes to produce asignal, and more specifically on those based on whole-cell detection.

Unlike complex biomolecules such as enzymes, antibodies, or DNA

fragments, that can be extremely specific towards the detection of a certainanalyte (key-in-lock recognition), whole cells, even though they can be verysensitive, in general terms lack this level of specificity. Nevertheless, whole-cell derived biosensing platforms present a series of advantages over their biomolecule-based counterparts: i) in most cases, a transducer that detects the biochemical signal and transforms it into an electrical or optical signal is notrequired, this function being carried out by the cell itself; ii) in general termsthey are easier to produce, which is traduced as an extremely low cost and

high applicability; iii) their low specificity can be a huge advantage for certainapplications, for instance the development of early-warning procedures todetect water pollutants. It is not only difficult but also irrelevant to measure thetoxicity of certain individual chemicals contained in a given sample of water, because a wide variety of chemicals co-exist in environmental water, and amixture may have even higher toxicity. Whole-cell based biosensing devicesenable rapid, accurate and low-level detection of a variety of substances beforethey cause any damage. [64] Useful methods of measuring toxicity in

environmental and industrial wastewaters have been developed based onmicroalgae, bacteria, plant tissues, and animal cells. [65-71]





a b

Figure 4. Scheme of synthesis of a whole-culture encapsulation derived biosensing platform. (a) Sequence showing how pre-encapsulated cultures of differentmicroorganisms are placed on an appropriate substrate and covered by a precursor mix,

generating an inorganic hydrogel by sol-gel process. (b) Specificity can be achieved both by encapsulating different cellular types or organism (or even a mix of differentmicroorganisms) in each pre-encapsulation and by changing the properties of theinorganic host.

As mentioned before, the functionality of the biomaterial will be given by both the biologic function of the guest and the properties of the host matrix.The two-step procedure allows the compartmentalization of living cells inmacrocavities created inside the inorganic host. Moreover, this approachallows the encapsulation of different microorganisms co-existing inside asingle liquid volume or the co-encapsulation of multiple isolated cultureswithin a single common monolithic host (see Figure 4). Combining differentmicroorganisms in a single biosensor, offers the possibility of sensing a broader range of substances possibly present in the complex sample and/or toassess a certain pollutant in a wider range of concentrations (encapsulatingmicroorganisms with different sensibility). Going one step further, these biological systems can be entrapped in different host matrices, the later

conferring certain level of specificity to the detection, for instance allowing theselective transport of analytes by charge and/or molecular weight. Extendingthis in a microarray approach, an artificial ecosystem can be created in a





diminished scale that would allow ecotoxicity studies to be carried out in portable devices for on-line and in situ pollution level assessment.

ACKNOWLEDGMENTS

This work was supported by ANPCyT PICT 2013-2045, CONICET GI-PIP 11220110101020, and UBACyT 20020130100048BA from Argentina.MP, MJ and SAB are Research Scientist of CONICET (Argentina).

R EFERENCES

[1]

Blondeau, M; Coradin, T. Living materials from sol–gel chemistry:current challenges and perspectives, J. Mater. Chem., 2012, 22, 22335-22343.

[2] Depagne, C; Roux, C; Coradin, T. Analytical Bioanalytical Chemistry,2011, 400, 965.

[3]

Coradin, T; Nassif, N; Livage, J. Applied Microbiology and

Biotechnology, 2003, 61,429.[4]

Kataoka, K; Nagao, Y; Nukui, T; Akiyama, I; Tsuru, K; Hayakawa, S;Osaka, A; Huh, NH. Biomaterials, 2005, 26, 2509

[5] Eleftheriou, NM; Xin Ge, J; Kolesnik, SB; Falconer, RJ; Harris, C;Khursigara, ED; Brown, JD. Brennan, Entrapment of Living BacterialCells in Low-Concentration Silica Materials Preserves Cell Division andPromoter Regulation, Chem. Mater ., 2013, 25(23), 4798–4805.

[6]

Perullini, M; Jobbágy, M; Soller-Illia, GJAA; Bilmes, SA. Cellular

growth at cavities created inside silica monoliths synthesized by sol-gel.Chem. Mater., 2005, 17, 3806-3808.

[7]

Ferro, Y; Perullini, M; Jobbagy, M; Bilmes, SA; Durrieu, C.Development of a biosensor for environmental monitoring based onmicroalgae immobilized in silica hydrogels, Sensors (Switzerland),2012, 12(12), 16879-16891.

[8] Perullini, M; Rivero, MM; Jobbágy, M; Mentaberry, A; Bilmes, SA.Plant cell proliferation inside an inorganic host, J. Biotechnol ., 2007,

127(3), 542-548.





[9]

Perullini, M; Jobbágy, M; Mouso, N; Forchiassin, F; Bilmes, SA. Silica-alginate-fungi biocomposites for remediation of polluted water, J. Mater.Chem., 2010, 20(31), 6479-6483.

[10]

Jen, C; Wake, MC; Mikos, G. Biotechnol. Bioeng., 1996, 50, 357–64.[11] Rivest, C; Morrison, DWG; Ni, B; Rubin, J; Yadav, V; Mahdavi, A;

Karp, JM; Khademhosseini, A. 2007, 2.[12]

Hunt, NC; Grover, LM. Biotechnol. Lett., 2010, 32, 733–42.[13]

Nicodemus, GD; Bryant, SJ. Tissue Eng. Part B. Rev., 2008, 14, 149–65.[14]

Sglavo, V; Carturan, G; Dal Monte, R; Muraca, M. J. Mater. Sci., 1999,34, 3587–3590.

[15]

Muraca, M; Vilei, MT; Zanusso, GE; Ferraresso, C; Boninsegna, S; Dal

Monte, R; Carraro, P; Carturan, G. Artif. Organs, 2002, 26, 664–9.[16] Armanini, L; Carturan, G; Boninsegna, S; Dal Monte, R; Muraca, M. J.

Mater. Chem., 1999, 9, 3057–3060.[17]

Eglin, D; Mosser, G; Giraud-Guille, MM; Livage, J; Coradin, T. Soft

Matter , 2005, 1, 129.[18]

Ren, L; Tsuru, K; Hayakawa, S; Osaka, A. J. Sol-Gel Sci. Technol.,2001, 21, 115–121.

[19]

Coradin, T; Livage, J. Mater. Sci. Eng. C , 2005, 25, 201–205.

[20]

Benmouhoub, N; Simmonet, N; Agoudjil, N; Coradin, T. Green Chem.,2008, 10, 957.

[21] Augst, AD; Kong, HJ; Mooney, DJ. Macromol. Biosci., 2006, 6,623–33.

[22]

Mongar, IL; Wassermann, A. J. Chem. Soc., 1952, 492–497.[23]

Karakasyan, C; Legros, M; Lack, S; Brunel, F; Maingault, P; Ducouret,G; Polyme, P. 2010, 2966–2975.

[24] Ouwerx, C; Velings, N; Mestdagh, M; Axelos, MA. Polym. Gels

Networks, 1998, 6, 393–408.[25]

Hickman, GJ; Rai, A; Boocock, DJ; Rees, RC; Perry, CC. J. Mater.

Chem., 2012, 22, 12141.[26]

Fang, Y; Al-Assaf, S; Phillips, GO; Nishinari, K; Funami, T; Williams,P; Li, L. J. Phys. Chem. B, 2007, 111, 2456–62.

[27]

Donati, I; Holtan, S; a Mørch, Y; Borgogna, M; Dentini, M; Skjåk-Braek, G. Biomacromolecules, 2005, 6, 1031–40.

[28]

Perullini, M. PhD. Thesis, University of Buenos Aires, 2009, 145.

[29]

Braschler, T; Valero, A; Colella, L; Pataky, K; Brugger, J; Renaud, P. Anal. Chem., 2011, 83, 2234–42.[30] Bienaimé, C; Barbotin, JN; Nava-Saucedo, JE. J. Biomed. Mater. Res. A,

2003, 67 , 376–88.





[31]

Sugiura, S; Oda, T; Aoyagi, Y; Matsuo, R; Enomoto, T; Matsumoto, K; Nakamura, T; Satake, M; Ochiai, A; Ohkohchi, N; Nakajima, M. Biomed. Microdevices, 2007, 9, 91–9.

[32]

Lian, M; Collier, CP; Doktycz, MJ; Retterer, ST. Biomicrofluidics, 2012,6 , 044108.

[33]

Haeberle, S; Naegele, L; Burger, R; von Stetten, F; Zengerle, R; Ducrée,J. J. Microencapsul., 2008, 25, 267–74.

[34]

Delaney, JT; Liberski, AR; Schubert, US. Soft Matter , 2010, 6, 866–869.[35]

Liu, LS; Kost, J; Yan, F; Spiro, RC. Polymers (Basel)., 2012, 4, 997– 1011.

[36]

Mongar, IL; Wassermann, A. J. Chem. Soc., 1952, 492–497.

[37]

Klein, J; Stock, J; Vorlop, K. Eur. J. Appl. Microbiol. …, 1983, 86–91.[38] Scherer, P; Kluge, M; Klein, J; Sahm, H. Biotechnol. Bioeng., 1981, 23,

1057–1065.[39]

Fukushima, Y; Okamura, K; Imai, K; Motai, H. Biotechnol. Bioeng.,1988, 32, 584–94.

[40]

Sakai, S; Ono, T; Ijima, H; Kawakami, K. Biomaterials, 2001, 22, 2827– 2834.

[41]

Sakai, S; Ono, T; Ijima, H; Kawakami, K. Biomaterials, 2002, 23,

4177–83.[42] Coradin, T; Mercey, E; Lisnard, L; Livage, J. Chem. Commun. (Camb).,

2001, 2496–2497.[43]

Rajaonarivony, M; Vauthier, C; Couarraze, G; Puisieux, F; Couvreur, P. J. Pharm. Sci., 1993, 82, 912–7.

[44]

Boissière, M; Meadows, PJ; Brayner, R; Hélary, C; Livage, J; Coradin,T. J. Mater. Chem., 2006, 16, 1178.

[45]

Coradin, T; Mercey, E; Lisnard, L; Livage, J. Chem. Commun. (Camb).,

2001, 2496–2497.[46] Coradin, T; Nassif, N; Livage, J. Appl. Microbiol. Biotechnol., 2003, 61,429–34.

[47]

Carturan, G; Dal Toso, R; Boninsegna, S; Dal Monte, R. J. Mater.

Chem., 2004, 14, 2087.[48]

Boninsegna, S; Bosetti, P; Carturan, G; Dellagiacoma, G; Dal Monte, R;Rossi, M. J. Biotechnol., 2003, 100, 277–86.

[49]

Boninsegna, S; Dal Toso, R; Dal Monte, R; Carturan, G. J. Sol-Gel Sci.

Technol., 2003, 26, 1151-1157.[50] Magagna, C; Rossi, M; Bellavite, P; Carturan, G; Boninsegna, S; DalMonte, R; Dal Toso, R. Advances in Islet Cell Biology, 2002, 3–6.





[51]

Livage, J; Coradin, T. Living cells in oxide glasses, Reviews in

Mineralogy and Geochemistry, 2006, 64(1), 315-332.[52] Soltmann, U; Böttcher, H. Utilization of sol–gel ceramics for the

immobilization of living microorganisms, J Sol-Gel Sci. Technol ., 2008,48, 66–72.

[53]

Blondeau, M; Coradin, T. Living materials from sol–gel chemistry:current challenges and perspectives, J. Mater. Chem., 2012, 22, 22335.

[54]

Kuncova, G; Podrazky, O; Ripp, S; Trögl, J; Sayler, GS; Demnerova, K.Vankova, R. Monitoring of the viability of cells immobilized by sol-gel process. J. Sol-Gel Sci. Technol., 2004, 31, 1-8.

[55]

Moreno-Garrido, I. Microalgae immobilization: Current techniques and

uses, Bioresour Technol ., 2008, 99, 3949–3964.[56] Ionescu, RE; Abu-Rabeah, K; Cosnier, S; Durrieu, C; Chovelon, JM;

Marks, RS. Amperometric algal Chlorella vulgaris cell biosensors basedon alginate and polypyrrole-alginate gels, Electroanalysis, 2006, 18 (11), 1041-1046.

[57]

Perullini, M; Jobbágy, M; Bermúdez Moretti, M; Correa García, S;Bilmes, SA. Optimizing Silica Encapsulation of Living Cells: In SituEvaluation of Cellular Stress, Chem. Mater., 2008 , 20, 3015-3021.

[58]

Perullini, M ; Amoura, M ; Jobbágy, M ; Roux, C ; Livage, J ; Coradin, T ; Bilmes, SA. Improving bacteria viability in metal oxide hosts via an

alginate-based hybrid approach, J. Mater. Chem., 2011, 21(22), 8026-

8031.

[59]

Perullini, M; Jobbágy, M; Bilmes, SA; Torriani, IL; Candal, R. Effect ofsynthesis conditions on the microstructure of TEOS derived silicahydrogels synthesized by the alcohol-free sol-gel route, J. Sol-Gel Sci.

Technol ., 2011, 59 (1), 174-180.

[60]

Perullini, M; Jobbágy, M; Japas, ML; Bilmes, SA. New method for thesimultaneous determination of diffusion and adsorption of dyes in silicahydrogels, J. Coll. Interf. Sci., 2014, 425, 91-95.

[61]

Perullini, M; Ferro, Y; Durrieu, C; Jobbágy, M; Bilmes, SA. Sol–gelsilica platforms for microalgae-based optical biosensors, J. Biotechnol.,2014, 179, 65-70.

[62] Sicard, C; Perullini, M; Spedalieri, C; Coradin, T; Brayner, R; Livage, J;Jobbagy, M; Bilmes, SA. CeO2 Nanoparticles for the Protection of

Photosynthetic Organisms Immobilized in Silica Gels. Chem. Mater.,2011, 23, 1374–1378.





[63]

Perullini, M; Durrieu, C; Jobbágy, M; Bilmes, SA. Rhodamine B dopedsilica encapsulation matrices for the protection of photosyntheticorganisms, J. Biotechnol ., 2014, 184, 20, 94–99.

[64]

Pandard, P; Vasseur, P. Biocapteurs pour le contrôle de la toxicité deseaux: application des bioélectrodes algales , Rev. Sci. Eau/J. Water Sci.,1992, 5, 445–461.

[65]

Giardi, MT; Pace, E. Trends Biotech, 2005, 25, 253–267.[66]

Carrilho, EN; Nobrega, JA; Gilbert, TR. Talanta, 2003, 60, 1131–1140.[67]

Moreno-Garrido, I. Bioresour Technol , 2008, 99, 3949–3964.[68]

Oettmeier, W. Cell Mol Life Sci, 1999, 10, 1255–1277.[69]

Shigeoka, T; Sato, Y; Takeda, Y; Yoshida, K; Yamauchi, F. Environ.

Toxicol. Chem., 1988, 847.[70] Ma, J; Xu, L; Wang, S; Zheng, R; Jin, S; Huang, S; Huang, Y.

Ecotoxicol Environ Safe, 2002, 51, 128.[71]

Brayner, R; Couté, A; Livage, J; Perrette, C; Sicard, C. Micro-algal biosensors, Anal. Bioanal. Chem., 2011, 401, 581-597.





Chapter 4

BIOSENSORS FOR ATRAZINEDETERMINATION: A R EVIEW

M. T. Beleño 1 , M . Stoytcheva

1 , R. Zlatev

1 , G. Montero

1 ,

R. Torres 1 and B. Jaramil lo

2

1Autonomous University of Baja California,

Engineering Institute, Mexicali, Mexico2University of Cartagena,Faculty of Exact and Natural Sciences, Cartagena, Colombia

ABSTRACT

Atrazine is one of the most widely used herbicides for weeds

treatment in crops. Nevertheless, its toxicity, high persistence and low biodegradation rate provoke serious environmental and health problems.Having in mind that atrazine use is not restricted in USA and LatinAmerica, the analytical determination of atrazine residues in food,drinking water, and environmental samples is of primary importance.Thus, in this report different methods currently applied for atrazineanalysis are reviewed, emphasizing those that use biosensor technology.The principle of functioning of the electrochemical, optical and piezoelectric biosensors is detailed, considering these devices as a reliabletool for atrazine quantification.

Address correspondence to this author at the Autonomous University of Baja California,Engineering Institute, Mexicali, Mexico. Tel: 52 686 5664150; Fax: 52 686 5664150; E-mail: [email protected].




M. T. Beleño, M. Stoytcheva, R. Zlatev et al.76

Keywords: Biosensors, atrazine, polyphenol oxidase

INTRODUCTION

Herbicides are widely used in modern agriculture with the purpose ofmaintaining and reaching high crop production. However, their indiscriminateuse causes adverse effects of environmental and public concern [1].

Atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine, CAS1912-24-9) belongs to the group of triazinic herbicides. It is selective, of lowcost, and extensively used for weeds control, mainly in sugarcane, maize,

sorghum and wheat crops. This herbicide was first introduced in 1958 andnowadays it is one of the most popular worldwide [2]. It is effective to stop pre- and post-emergency broadleaf and grassy weeds in crops. Atrazine binding to the plastoquinone-binding protein in photosystem II causeschlorophyll destruction and photosynthesis breakdown [3, 4]. Atrazine and itsmetabolites are persistent in the environment, relatively high soluble in water,and toxic for human beings and animals [5]. Atrazine can cause interruptionsin the normal hormonal function, reproductive tumors, birth defects, and

mother and fetus weight loss [6]. Likewise, exposure to atrazine has beenrelated to an increase in incidence of stomach cancer [7]. Therefore,continuous control and monitoring of its residues is important. EuropeanCommunity (EU) established a maximum permissible limit for atrazine of 0.1μg L-1 in water for human consumption [8], while in USA this limit was set at3 μg L-1 [9]. Meanwhile, the World Health Organization proposed a limit of 2μg L-1 for atrazine and 100 μg L-1 for atrazine plus its metabolites [10].

Various instrumental methods are currently available for atrazine

determination: chromatographic techniques such as gas chromatography [11-13], high-performance liquid chromatography [14], gas chromatography-massspectrometry [15], liquid chromatography-mass spectrometry [16-18], andthin-layer chromatography [13, 19, 20], as well as some electrochemicalmethods [21] and immunoassays [13, 22-25]. Chromatography is the mostused for the determination of traces of atrazine, thanks to its selectivity andsensitivity. It is a well-established method and offers countless advantages, butit is complicated and requires expensive instruments and reagents. It is worth

mentioning that this technique cannot be performed outside the laboratory, andrequires long lasting procedures for sample pretreatment. On the other hand,early warning, sensitive, simple, and easy to use tools with powerful analyticaldetection capabilities like the biosensors are needed nowadays [26]. The




Biosensors for Atrazine Determination 77

objective of this review is to provide recent information on the achievementsand the emerging biosensors based strategies for atrazine determination.

BIOSENSORS BASED METHODS FOR

ATRAZINE DETERMINATION

The IUPAC defines the biosensor as “a self-contained integrated devicewhich is capable of providing specific quantitative or semi-quantitativeanalytical information using a biological recognition element (biochemicalreceptor) which is in direct contact with a transducer element” [27]. Thetransducer must be able to transform the biological reaction rate into ameasurable electric signal that can be related to the analytes concentration.Therefore, the transducer determines the efficacy in the processing of the biosensor’s signal, while its selectivity is mainly defined by the interaction ofthe biological component with the analyte [28]. Taking into consideration thenature of the biological process, biosensors can be classified as biocatalytic or bioaffinity biosensors. The firsts use mostly enzymes, microorganisms,complete cells or tissues, and are based on the catalytic reactions that are

carried out involving the analyte and generating a measurable product.Affinity biosensors use bioligands such as nucleic acids, antibodies, lecithinand peptides. They are designed to monitor a reaction of affinity between theanalyte and its ligand [29]. Other classification is performed in accordancewith the transducer type: electrochemical, optical or piezoelectric.Electrochemical biosensors, in turn, are subdivided in amperometric, potentiometric and conductometric, if some change in electric current,electrode’s potential or in conductivity is respectively detected [30]. To

determine atrazine, different biosensors were proposed. Their function and performances are commented below.

Electrochemical Biosensors for Atrazine Determination

Electrochemical biosensors are the most widely applied for atrazinedetermination. The typical ones are the enzymatic sensors with amperometric

detection, i.e. the analytical signal is the resulting faradaic current recorded atan appropriate constant potential [31].





The enzymatic amperometric sensors [32-40] involve the enzymetyrosinase, which catalyzes the o-hydroxylation of the monophenols to o-diphenols (monophenolase or cresolase activity) and the oxidation of the o-

diphenols to the corresponding o-quinones (diphenolase or cathecolaseactivity). Since atrazine is a tyrosinase inhibitor, it is quantified by measuringthe decrease of the current of o-quinones reduction registered usually at a potential of -0.2 V/SCE (Figure 1).

Figure 1. Functioning principle of a tyrosinase based sensor for atrazinedetermination.

Nevertheless quinones can spontaneously react to produce oligomers orcan be attacked by nucleophiles [41, 42], which fallouts in insulating polymerfilm formation and electrode passivation. Therefore, in an attempt to improvethe analytical characteristics of atrazine determination, some tyrosinase basedamperometric sensors make use of mediators [43]. Another approach relies inmonitoring the consumption of the oxygen cofactor, applying Clark typeelectrode [44].

Additionally, tyrosinase could be inactivated by quinone polymers. As the

process is water sensitive [45, 46], inactivation could be avoided performingthe analysis in anhydrous organic media. Thus, atrazine determination issuccessfully carried out in chloroform [38, 39].

Another disadvantage of the tyrosinase based sensors is associated withthe low stability and the limited enzyme binding to solid surfaces [47]. Hence,a great variety of tyrosinase immobilization protocols were assayed to ensurehigh operational and storage stability of the biosensors, using amphiphilic poly(pyrrole) [32, 33], polythiophene [35], sol-gel [37], carrageenan [40], etc.

as enzyme immobilization supports.Better biosensors performances in terms of tyrosinase stability and

sensitivity improving were reached applying nanomaterials as enzyme

OH

R

R O

O

R OH

OH

R O

O

R OH

OH

cresolase activity catecholase activity

+ 2H+ + 2e-





immobilization matrix, namely tyrosinase was retained on the surface ofvertical growth TiO2-nanotubes [36]. The remarkable characteristics of thefabricated biosensor for atrazine quantification were attributed to the

appropriate bioelectrochemical interface of tyrosinase/TiO2-nanotubes,resulting from the preponderant tubular structure, excellent biocompatibility,and hydrophilicity of TiO2-nanotubes [36].

Tyrosinase inhibition by atrazine was also exploited for the developmentof conductimetric sensors [13, 48]. The detection principle is based on theregistration of the conductivity change of the enzyme membrane whentyrosinase either interacts with its substrate or is inhibited by atrazine.Detection limit for atrazine was approximately 1 ppb. However, one of the

limitations of this kind of biosensors is clearly their lack of selectivity.Some of the disadvantages of the tyrosinase based amperometric sensors

for atrazine determination could be avoided applying electrochemicalimmunosensors. It has been demonstrated that the enzyme-linked immunosorbent assays (ELISA) are very suitable for atrazine determination, becauseof the high specificity of the analysis and the achieved low detection limit [13,23-25]. Thus, the electrochemical immunosensors which combine thesimplicity and the sensitivity of the electrochemical methods, and the low cost

of the electrochemical equipment with the specificity of the immunoassays areconsidered as very advantageous analytical tools [49]. The steps to followapplying electrochemical immunosensors currently include the immobilizationof the recognition element (antigen or antibody) on the electrode surface, theinjection of a secondary enzyme-labelled antibody, the addition of anappropriate enzymatic substrate which produces electroactive species, andtheir electrochemical detection [50].

Most of the electrochemical immunosensors make use of the

amperometric detection using as transducers glassy carbon electrodes orvarious screen printed electrodes, and monoclonal antibodies (with alkaline phosphatase label, HPR label, glucose oxidase label with HRP for enzymechannelling and catalase for substrate scavenging, and signals amplified withatrazine-tagged liposomes), biotinylated monoclonal antibodies (HRP label), polyclonal antibodies (HRP label) in concert with a “molecularly-wired’osmium polymer system, and recombinant scAb fragments (HRP label), as biological recognition elements [51-58].

Another strategy for atrazine detection using electrochemicalimmunosensors is this, associated with the application of electrochemicalimpedance spectroscopy (EIS).

The technique makes it possible the label-free,





direct detection of the antibody-pesticide binding by measuring the change ofimpedance.

The impedimetric immunosensors are constructed applying a variety of

approaches, targeting the stable and reproducible immobilization of the biological macromolecules on the electrode surface with complete retention oftheir biological activity. As known, the analytical performances of theimmunosensors, such as sensitivity and reproducibility are strongly dependenton the amount of immobilized antibodies and their remaining antigen binding properties. Therefore, Helali [59] reports a procedure for the formation of amixed self-assembled on gold electrode monolayer, composed of 1,2dipalmitoyl-sn-glycero-3-phosphoethanolamine N-(biotinyl) (biotinyl-PE) and

16-mercaptohexadecanoic acid (MHDA). Then, neutravidin was bound on the biotinyl-PE. In the following step, biotinyl-Fab fragment K47 antibody wasanchored onto neutravidin to allow the specific affinity immobilization ofatrazine. In another biosensor format, Helali et al. [59, 60] immobilized theantibody biotinyl–Fab fragment K47 onto a magnetic monolayer of magnetic particles coated with streptavidin, through the high binding affinity ofstreptavidin/biotin. After the antibody layer formation the antigen atrazine wasinjected to react with the antibody. The change of electron transfer resistance

was correlated to atrazine concentration. Ionescu et al. [61] suggest animpedimetric immunosesnor based on the immobilization of anti-atrazineantibody by affinity onto a polypyrrole film N-substituted by nitrilotriaceticacid (NTA) electrogenerated on a gold electrode. The poly- NTA film was previously modified by the coordination of Cu2+ ions by the chelating NTAcenters.

The anti-atrazine antibody Fab fragment K47 modified with histidine-tagwas then anchored by affinity interactions between the histidine-tag and the

coordinated Cu2+

. The immunoreaction of atrazine on the attached anti-atrazine antibody directly triggers an increase in the charge transfer resistance proportional to the atrazine concentration, allowing the detection of extremelylow atrazine concentration, namely 10 pg mL-1. The ultrasensitive detection ofatrazine in the dynamic range of 10 fg mL-1 to 1 ng mL-1 (0.01 ppt to 1 ppm)was achieved using a combination of EIS and nanomaterials: the nanoporousimpedimetric sensor was constructed by immobilizing the biorecognitionelement in size matched nanoscale confined spaces [62]. Sensitivity

enhancement could be also reached using interdigitated microelectrodesmeasuring impedance [63, 64], or conductivity changes [63, 65, 66].The analytical characteristics of the electrochemical biosensors applied for

atrazine quantification are listed in Table 1.





Table 1. Main analytical characteristics of the electrochemical biosensors

applied for atrazine quantification

Biosensor LOD Linear range Ref.Amperometric enzymatic 4 M - 32Amperometric enzymatic 1 mg L-1 - 34Amperometric enzymatic 0.1 ppt 0.2 ppt-2 ppb 36Amperometric enzymatic 5.5 M 1x10-5-1x10-4 M 37Amperometric enzymatic 0.5 mg L-1 1-7 mg L-1 38Amperometric enzymatic 0.5x10-6 mM 2x10-6 – 2x10-1 mM 39Amperometric enzymatic 10 M 20-130 M 44Conductometric enzymatic 1 ppb 2.15-2150 ppb 48

Amperometric immuno 0.1 g L-1

- 51Amperometric immuno 5x10-11 M 1x10-10-2.8x10-5 M 52Impedimetric immuno - 10-600 ng mL-1 60Impedimetric immuno 10 pg mL-1 - 61Impedimetric immuno - 0.01 ppt-1 ppm 62Impedimetric immuno 0.04 g L-1 - 64

Optical Biosensors for Atrazine Determination

According to the IUPAC definition, the optical biosensor is a device thatuses specific biochemical reactions mediated by isolated enzymes,immunosystems, tissues, organelles or whole cells to detect chemicalcompounds by optical signals [67]. It is based on the measure of the variations produced in the properties of the electromagnetic radiation, as a consequenceof the physical or chemical interaction between the analyte and the biosensor’srecognition element.

The optical biosensors for atrazine determination reported in the literaturecould be classified as enzyme and whole cells optical biosensors [78-70], andimmunoassay optical biosensors [71-77]. For instance, an enzyme-based fiberoptic biosensor was successfully applied by Andreou and Clonis for thedetermination of atrazine in real water samples using glutathione S-transferaseI, expressed in E. coli (GST-I) [68]. The sensing bioactive material was athree-layer mini-sandwich. The enzyme was immobilized on the outerhydrophilic polyvinylidenefluoride membrane. This membrane was supported

on an inner glass disk by means of an intermediate binder sol-gel layer withincorporated bromcresol green. The signal transduction was a result of theGST-catalyzed nucleophilic attack of glutathione on atrazine with subsequentrelease of H+; this resulted in local pH alterations with concomitant sol-gel





entrapped indicator color change. The sensor detection limit was0.84 mol L-1. Another example of enzyme fiber optic sensor is reported byDas and Reardon [769]. The sensor was fabricated by immobilizing cells

containing atrazine chlorohydrolase to the surface of a pH-sensitive optrode.The enzyme catalyzes the dechlorination of atrazine with a release of HCl,thus creating a sensor response from the optrode, proportional to atrazineconcentration. Sensor’s response to atrazine could also result fromfluorescence intensity change, like demonstrated by Vedrine et al. [70]. Thesuggested fiber optic whole cell biosensor measured Chlorella vulgaris chlorophyll fluorescence. The presence of anti PSII herbicides (diuron,atrazine, simazine and isoproturon) increased the fluorescence emission.

Immunoassay optical biosensors usually require the immobilization of a primary antibody to the surface of a substrate and the use of an optical label.Such a fiber optic biosensor for atrazine determination was developed byOroszlan et al. [71]. In the competitive assay format chosen, fluorescein-labeled and non-labeled atrazine in solution compete for the binding sites ofanti-atrazine antibodies immobilized on the surface of the optical fiber.

Nevertheless, in terms of simplicity of the analysis, undoubtedly moresuitable are the direct label-free optical immunosensors, in contrast to the

indirect immunosensors which use enzyme or fluorescent labels to achievehigh sensitivity. The label-free optical immunosensors are based on theoccurrence of a specific interaction at the sensitive area of the physicaltransducer. The detection of this event for atrazine determination is performedusing: surface plasmon resonance (SPR) [72], grating coupling [73],reflectometric interference spectroscopy [74], waveguide-based SPR [75],infrared spectroscopy [76], and resonant mirror based techniques [77].

The main analytical characteristics of the optical biosensors applied for

atrazine quantification are listed in Table 2.

Table 2. Main analytical characteristics of the optical biosensors applied

for atrazine quantification

Biosensor Principle LOD Ref.

Optical enzymatic pH change detection 0.84 M 68

Optical whole cell Fluorescence change detection 0.25 g L-1 70

Optical immuno Surface Plasmon Resonance 0.05 ppb 72

Optical immuno IR detection 1.5 nM 76

Optical immuno IR detection 13 nM 76

Optical immuno Resonant mirro 1 g L-1 77





Piezoelectric Biosensors for Atrazine Determination

The piezoelectric biosensor measures the mass deposited on the surface of

a piezoelectric crystal, detecting variations in the characteristic resonancefrequency of the crystal. The survey of the literature demonstrated that the piezoelectric sensors for atrazine quantification are based mainly onimmunoassays: the surface of the piezoelectric crystal is covered with anantibody or an antigen, and the mass variation induced by the antigen-antibody binding is correlated to the antigen concentration [78-81].

The first piezoelectric immunosensor for atrazine determination [79] wasdeveloped by immobilizing atrazine antibodies (polyclonal from sheep) onto

the gold electrode of 10 MHz piezoelectric crystals. Piezoelectricimmunosensor response was monitored after dying the sensor surface [79].Determinations from 0.3-100 μg L−1 of atrazine were made with a RSD ofabout ± 8%.

Highly sensitive immunosensors for atrazine determination under wetconditions, based on direct and competitive assay procedures were developed by J. Př ibyl et al. [80], and Steegborn et al. [81]. The competitiveimmunoassay [80] was performed using anti-atrazine monoclonal antibody

(MAb, clone D6F3), and atrazine covalently attached onto the functionalizedsurface of the gold electrode of the piezoelectric crystal. The limit of detectionreached was 0.025 ng mL-1, and the total time of analysis was 25 min. Thedirect immunosensor for atrazine [80] was fabricated by orientedimmobilization of anti-atrazine MAb to Protein A covalently attached to theactivated gold surface of the electrode. The sensor provided a limit ofdetection of 1.5 ng mL-1, and one assay was completed within 10 min. Theresults obtained demonstrate that the piezoelectric immunosensors are suitable

for the determination of atrazine in drinking water. In addition they are moreeconomically effective compared with the optical biosensors.

CONCLUSION

In contrast to the established techniques for atrazine determination such aschromatography and immunoassays, the biosensors based methods offer

several advantages: low costs, almost immediate measurements without orwith a limited sample pretreatment, low reagent consumption, and smallsample volume. Hence, biosensors technology assumes a great promise for thecontrol and vigilance of pesticide residues.





R EFERENCES

[1]

Nwani, C.; Lakra, D.W.S.; Nagpure, N.S.; Kumar, R.; Kushwaha, B.;Srivastava S.K. Int. J. Environ. Res. Public Health 2010, 7, 3298-3312.

[2]

Golla, V.; Nelms, J.; Taylor, R.; Mishra S. J. Environm. Sci. Engi. 2011,5, 955-961.

[3] Nascimento, C.R.; Souza, M.M.; Martinez, C.B. Comp. Biochem. Physiol. C Toxico.l Pharmacol . 2012, 155, 456-61.

[4]

Appleby, A.P.; Müller, F.; Carpy, S. In Ullmann's Encyclopedia ofIndustrial Chemistry; Wiley, 2001.

[5]

Hansen, A.M.; Treviño-Quintanilla, L.G.; Márquez-Pacheco, H.;

Villada-Canela, M.; González-Márquez, L.C.; Guillén-Garcés, R.A.;Hernández-Antonio, A. Rev. Int. Contam. Ambient . 2013, 29, 65-84.

[6]

Savitz, D.A.; Arbuckle, T.; Kaczor, D.; Curtis, K.M. Am. J. Epidemiol. 1997, 146, 1025-1036.

[7] Van Leeuwen, J.A.; Waltner-Toews, D.; Abernathy, T.; Smit, B.;Shoukri, M. Int. J. Epidemiol . 1999, 28, 836-840.

[8]

European Parliament. Council Directive 98/83/EC of 3 November 1998on the quality of water intended for human consumption. Official

Journal of the European Communities, 1998, L 330/32.[9]

USEPA. Interim Reregistration Eligibility Decision for Atrazine. UnitedStates Environmental Protection Agency. Washington, D.C. 2003, 285

[10] WHO Guidelines for drinking-water quality. 4a ed. World HealthOrganization. Ginebra, Suiza, 2011.

[11] Tomkins, B.A.; Ilgner, R.H. J. Chromatogr. A 2002, 972, 183-194.[12]

García, M.Á.; Santaeufemia, M.; Melgar. M.J. Food Chem. Toxicol. 2012, 50, 503–510.

[13]

Barchańska, H.; Baranowska, I. In Reviews of EnvironmentalContamination and Toxicology; Whitacre, D.M.; Ed.; SpringerScience+Business Media, 2009; 200, 53-84.

[14]

Pinto, G.M.F.; Jardim I.C.S.F. J. Chromatogr. A 2000, 869, 463-469.[15]

Bruzzoniti, M.C.; Sarzanini, C.; Costantino, G.; Hongos M. Anal. Chim. Acta. 2006, 578, 241-249.

[16]

Ross, M.K.; Filipov N.M. Anal. Biochem. 2006, 351, 161-173.[17]

Kuklenyik, Z.; Panuwet, P.; Jayatilaka, N.K.; Pirkle, J.L.; Calafat A.M.

J. Chromatogr . B. 2012, 901, 1-8.[18] Mou, R.X.; Chen, M.X.; Cao, Z.Y.; Zhu, Z.W. Anal. Chim. Acta 2011,706, 149-156.





[19]

Rezic, I.; Horvat, A.J.M.; Babić, S.; Kaštelan-Macan, M. Ultrason.

Sonochem. 2005, 12, 477-481.[20] Huss, M.; Adamović, V.M. J. Chromatogr. A. 1973, 80, 137-139.

[21]

Maleki, N.; Absalan, G.; Safavi, A.; Farjami, E. Anal. Chim. Acta. 2007,581, 37-41.

[22]

Kima, J.Y.; Mulchandani,A.; Chen, W. Anal. Biochem 2003, 322, 251– 256.

[23]

Amistadi, M.K.; Hall, J.K., Bogus, E.R., Mumma, R.O. J. Environ. Sci.

Health, B 1997, 32, 845-860.[24]

Lima, D.L.D.; Silva, C.P.; Schneider, R.J.; Esteves, W.I. Talanta 2011,85, 1494-1499.

[25]

Franek, M.; Kolar, V.; Eremin, S.A. Anal. Chim. Acta 1995, 311, 349-356.

[26] Van Dyk, S.J.; Pletschke, B. Chemosphere 2011, 82, 3, 291–307.[27]

Thévenot, D.R.; Toth, K.; Durst, R.A.; Wilson, G.S. Pure and Applied Chemistry 1999, 71, 2333-2348.

[28]

Carrazón, J.M.P.; Batanero, P.S Química electroanalítica, fundamentos yaplicaciones; Síntesis. Madrid, España, 1999.

[29]

Gooding, J.J. Anal. Chim. Acta. 2006, 559, 137-151.

[30]

Thévenot, D.R.; Toth, K.; Durst, R.A.; Wilson, G.S. Biosens. Bioelectron. 2001, 16, 121-131.

[31] Reviejo, A.J.; Pingarron, J.M. Anales de la Real Sociedad Española deQuimica 2000, 2, 5-15.

[32]

Besombes, J-L.; Cosnier, S.; Labbé, P.; Reverdy, G. Anal. Chim. Acta 1995, 311, 255-263.

[33] McArdie, F.A.; Persaud, K.C. Analyst 1993, 118, 419-423.[34] Wang, J.; Nascimento, V.B.; Kane, S.A.; Rogers, K.; Smith, M.R.;

Angnes, L. Talanta 1996, 43, 1903-1907.[35]

Védrine, C.; Fabiano, S.; Tran-Minh, C. Talanta 2003, 59, 535-544.[36]

Yu, Z.; Zhao, G.; Liu, M.; Lei, Y.; Li, M. Environ. Sci. Technol . 2010,44, 7878–7883.

[37]

Majidi, M.R.; Asadpour-Zeynali, K.; Gholizadeh, S. J. Chin. Chem. Soc. 2008, 55, 522-528.

[38]

Hipólito-Moreno, A.; León-González, M.E.; Pérez-Arribas, L.V.; Polo-Díez, L.M. Anal. Chim. Acta 1998, 362 187-192.

[39]

Campanella, L.; Bonanni, A.; Martini, E.; Todini, N.; Tomassetti, M.Sensors and Actuators B 2005, 111–112, 505–514.[40] Campanella, L.; Dragone, R.; Lelo, D.; Martini, E.; Tomassetti, M. Anal.

Bioanal. Chem. 2006, 384, 915–921.





[41]

Nourmohammadi, F.; Gloabi, S.M.; Saadnia, A. J. Electroanal. Chem. 2002, 529, 12– 19.

[42] Nematollahi, D.; Tammari, E.; Sharifi, S.; Kazemi, M. Electrochim. Acta

2004, 49, 591– 595.[43] Vidal, J.C.; Bonel, L.; Castillo, J.R. Electroanalysis 2008, 20, 865 – 873.[44]

Mazzei, F.; Botrè, F.; Lorenti, G.; Simonetti, G.; Porcelli, F.; Scibona,G.; Botrè, C. Anal. Chim. Acta 1995, 316 79-82.

[45]

Estrada, P.; Sánchez-Muñiz, R.; Acebal, C.; Arche, R.; Castillón, M.P. Biotechnol. Appl. Biochem. 1991, 14, 12-20.

[46]

Estrada, P.; Baroto, W.; Castillón, M.P.; Acebal, C.; Arche, R.J. Chem. Tech. Biotechnol . 1993, 56 59-65.

[47]

Ricci, R.; Palleschi, G. Biosens. Bioelectron. 2005, 21, 389-407.[48] Anh, T.M.; Dzyadevychc, S.V.; Van, M.C.; Jaffrezic Renault, N.; Duc,

C.N.; Chovelon, J.M. Talanta 2004, 63, 365–370.[49]

Zacco, E.; Galve, R.; Marco, M.P.; Alegret, S.; Pividori, M.I. Biosens.

Bioelectron. 2007, 22, 1707-1715.[50]

Ricci, F.; Adornetto, G.; Palleschi, G. 2010. Electrochim. Acta 2012, 84,74-83.

[51]

Grennan, K.; Strachan, G.; Porter, A.J.; Killard, A.J.; Smyth, M.R. Anal.

Chim. Acta 2003, 500, 287–298.[52] Campanella, L.; Eremin, S.; Lela, D.; Martini, E.; Tomassetti, M.

Sensors and Actuators B 2011, 156, 50–62.[53]

Keay, R.W.; McNeil, C.J. Biosens. Bioelect . 1998, 13, 963-970.[54]

Vianello, F.; Signor, L.; Pizzariello, A.; Di Paolo, M.L.; Scarpa, M.;Hock, B.; Giersch, T.; Rigo, A. Biosens. Bioelect . 1998, 13, 45-53.

[55] Fernández Romero, J.M.; Stiene, M.; Kast, R.; Luque de Castro, M.D.;Bilitewski, U. Biosens. Bioelect . 1998, 13, 1107-1115.

[56]

Parellada, J.; Narváez, A.; López, M.A.; Dominguez, E.; Fernández, J.J.;Pavlov, V.; Katakis, I. Anal. Chim. Acta 1998, 362, 47-57.[57]

Bäumner, A.J.; Schmid, R.D. Biosens. Bioelect . 1998, 13, 519-529.[58]

López, M.A.; Ortega, F.; Domínguez, E.; Katakis, I. J. Mol. Recog. 1998, 11, 178-181.

[59]

Helali, S. In State of the Art in Biosensors - Environmental and MedicalApplications; Rinken, T.; Ed.; InTech: Croatia, 2013, 121-147.

[60]

Helali, S.; Martelet, C., Abdelghani, A.; Maaref, M.A.; Jaffrezic-

Renault, N. Electrochim. Acta 2006, 51, 5182-5186.[61] Ionescu, R.; Gondran, C.; Bouffier, L.; Jaffrezic-Renault, N.; Martelet,C.; Cosnier, S. Electrochim. Acta 2010, 55, 6228-6232.





[62]

Pichetsurnthorn, P.; Vattipalli, K., Prasad, S. Biosens. Bioelectron. 2012,32, 155-162.

[63] Valera, E.; Rodríguez, A. In Herbicides - Mechanisms and Mode of

Action; Hasaneen, M.N.A.E.G; Ed.; InTech: Croatia, 2011; 25-48.[64] Ramón-Azcón, J.; Valera, E.; Rodríguez, A.; Barranco, A.; Alfaro, B.;

Sánchez-Baeza, F.; Marco, M.P. Biosens. Bioelectron. 2008, 23, 1367– 1373.

[65]

Valera, E.; Ramón-Azcón, J.; Sánchez, F.-J.; Marco, M.P.; Rodríguez,A. Sensors and Actuators B 2008, 134, 95–103.

[66]

Valera, E.; Muñiz, D.; Rodríguez, A. Microelectronic Engineering2010,87, 167–173.

[67]

Nagel, B.; Dellweg, Gierasch, L.M. Pure and Applied Chemistry 1992,64, 143–168.

[68] Andreou, V.G.; Clonis, Y.D. Anal. Chim. Acta 2002, 460, 151–161.[69]

Das, N.; Reardon, K. Anal. Letters 2012, 45, 251-261.[70]

Védrine C., Leclerc, J.C.; Durrieu, C.; Tran-Minh, C. Biosens.

Bioelectron. 2003, 18, 457–463.[71]

Oroszlan, P.; Duveneck, G.L.; Ehrat, M.; Widmer, H.M. Sensors and

Actuators, B 1993, 11, 301-305.

[72]

Minunni, M.; Mascini, M.; Anal. Lett. 1993, 26, 1441-1460.[73] Bier, F.F.; Schmid, R.D. Biosens. Bioelectron. 1994, 9, 125-130.[74] Brecht, A.; Piehler, J.; Lang, G.; Gauglitz, G. Anal. Chim. Acta 1995,

311, 289-299.[75]

Mouvet, C.; Harris, R.D.; Maciag, C.; Luff, B.J.; Wilkinson, J.S.;Piehler, J.; Brecht, A.; Gauglitz, G.; Abuknesha, R.; Ismail, G. Anal.

Chim. Acta 1997, 338, 109-117.[76] Salmain, M.; Fischer-Durand, N.; Pradier, C.M. Anal. Biochem. 2008,

373, 61-70.[77]

Skládal, P.; Deng, A.; Kolář , V. Anal. Chim. Acta1999, 399, 29–36.[78]

Ju, H.; Kandimalla, V.B. In Electrochemical Sensors, Biosensors andtheir Biomedical Applications; Zhang, X.; Ju, H.; Wang, J.; Eds.;Academic Press: USA, 2008, 31-56.

[79]

Guilbault, G.G.; Hock, B.; Schmid, R.D. Biosens. Bioelectron. 1992, 7,411-419.

[80]

Př ibyl, J.; Hepel, M.; Halamek, J.; Skladal, P. Sensors and Actuators B

2003, 91, 333-341.[81] Steegborn, C.; Skládal, P. Biosens. Bioelectron. 1997, 12, 19–27.





Chapter 5

MICROBIAL BIOSENSORS FOR METHYL PARATHION: FROM SINGLE

TO MULTIPLE SAMPLES ANALYSIS

Ji tendra Kumar

and Jose Savio Melo †

Nuclear Agriculture and Biotechnology Division, Bhabha Atomic

Research Centre Trombay, Mumbai, Maharashtra, India

ABSTRACT

Methyl parathion (MP) is an organophosphate (OP) compound whichis being used as non-systemic insecticide in agriculture to protect thecrops. However MP can cause many health problems in humans related to

acetylcholinesterase inhibition such as impaired memory andconcentration, disorientation, severe depression etc. Also, when inhaledits immediate adverse effects are a bloody or runny nose, coughing, chestdiscomfort and difficulty in breathing. It is thus classified by the WorldHealth Organization (WHO) as Category Ia (extremely toxic) and by theUnited States Environmental Protection Agency (US EPA) as ToxicityCategory I (most toxic) insecticide. Although banned in developedcountries like US and Japan it is still being used in developing countrieslike India as a restricted insecticide. Presence of this insecticide is thusexpected in the soil samples, water resources and even in food materials

Jitendra Kumar, e-mail: [email protected].† Jose Savio Melo, tel.: +91 22 25592760; fax: +91 22 25505151; e-mail address: jsmelo@

barc.gov.in.




Jitendra Kumar and Jose Savio Melo90

across countries still using this pesticide. Therefore, economicallyfeasible, rapid, sensitive, selective and reliable methods for detection ofMP are necessary. Also required are methods to monitor a large number

of samples in a short period of time. Thus there has been an intense effortto develop biosensors for the detection of methyl parathion. Microbial biosensors are a good alternative to enzyme biosensors because they provide the benefits of low cost and improved stability to the enzymes.This chapter thus aims to review the status of research in this field besides the work that is being carried out in our laboratory on microbial based biosensors for the detection of single to multiple samples of MP.

1. INTRODUCTION

Organophosphates (OP) pesticides are a group of compounds that have been used to control the pests in agricultural crops. This group includes pesticides such as malathion, diazinon, chlorpyrifos, azamethiphos, dichlorvos, phorate, parathion and methyl parathion [1]. As per statistical report fromDirectorate of Plant Protection Quarantine and Storage (PPQS), India, methyl parathion (MP) ranks 2nd among the most consumed OP pesticides and 5th

among all the other pesticides consumed in India, during the period between2005 to 2010 as seen in table 1 [2]. Same trend has also been reported by Indiafor Safe Food [3].

Methyl parathion (MP) is not known to occur as a natural substance. MPwas first produced commercially in the United States in 1952 and wasregistered as an organophosphate insecticide in 1954 [4].

Table 1. Five most consumed pesticides in India

(during 2005 to 2010) [2, 3]

Sl. No. Pesticide (Technical Grade) Quantity consumed(metric tons)

1 Sulphur (fungicide) 164242 Endosulfan (insecticide) 155373 Mancozeb (fungicide) 110674 Phorate (insecticide) 107635 Methyl Parathion (insecticide) 08408

The IUPAC chemical name of MP is O,O-dimethyl O-4-nitrophenyl phosphorothioate. Its chemical structure is shown below:




Microbial Biosensors for Methyl Parathion 91

MP is produced by the reaction of O,O-dimethyl

phosphorochloridothionate and the sodium salt of 4-nitrophenol in acetone

solvent [4, 5]. Physico-chemical properties of MP are enlisted in Table 2 [6].

1.2. Manufacturers and Production

Bayer has developed this pesticide and has long been the ‘parent’

company for MP, with its well-known brand ‘Folidol’. However there have

also been a number of other manufacturers globally. The main manufacturers

of MP are All India Medical Co (India), Bayer India, Bayer Mexico,

Cheminova (Denmark), Rallis India, Sundat (Singapore) and Velpol Company

(Mexico) [7].

Table 2. Physicochemical properties of MP [6]

Chemical and Physical Properties

1. Identity

The pure active ingredient is a white crystalline odourless

material; the technical grade material (approx 80% purity)

is a yellowish - brown liquid with characteristic odour

2.

Formula C8H10 NO5PS

Chemical NameO-(4-nitrophenyl) phosphorothioate (CAS.)

O,O-dimethyl O-4-nitrophenylphosphorothioate (IUPAC)

Chemical Type Organophosphate

3.Solubility

Solubility in water 55 - 60 mg/L(20 °C); soluble in most

organic solvents, slightly soluble in petroleum and

mineral oils

IogPow 3 - 3.43

4. Vapour Pressure Vapour pressure 0.41 mPa (25 °C)

5. Melting Point 35 - 36 °C

6. Reactivity Rapidly hydrolyzed in alkaline conditions

In one report, India produced an estimated 2,200 tons of technical grade

MP in the year 1995-96 [8].





1.3. Application and Consumption

MP is a non-systemic insecticide, nematicide, acaricide/miticide, which

controls numerous insects by contact poison through stomach, and respiratoryaction [4]. It kills pests by acting as a stomach poison and act as potentirreversible acetylcholinesterase inhibitor that have a profound effect on thenervous system of exposed organisms. It is used for the control of chewing andsucking insects and mites, including thrips, weevils, aphids and leafhoppers, ina very wide range of crops including cereals, fruit, nuts, vines, vegetables,ornamentals, cotton, and field crops [4, 9]. It is also reported that most methyl parathion is used for protecting cotton fields. It is available as a wettable

powder (WP), emulsifiable concentrate (EC), dustable powder (DP) andmicroencapsulated product [2, 6, 9, 10]. It is applied aerially, by ground boomand airblast sprayers [9]. It is also applied by handheld or backpack sprayerscontrary to the advice of the WHO [11]. Although banned in developedcountries, it is still being used in developing countries like India as a restrictedinsecticide. In India, Central Insecticide Board and Registration Committee(CIBRC) has recommended MP in two different concentrations either in 2%DP or 50% EC for controlling the pests from the cotton, paddy, wheat, pulses

such as green gram and black gram and oilseeds such as ground nut andmustard crops. As per statistical reports by Directorate of PPQS, India [2] andCentre of Science and Environment (CSE) [12], consumption of MP in Indiaduring 2005 - 2010 was 8408 metric tons. It was also reported that during2009-10, consumption of MP was 2739 tons.

1.4. Mode of Action, Toxicity and Regulatory Mechanism

Like other OP pesticides, MP also binds into the acyl pocket at the activesite of AChE. The binding of a phosphate group to the serine amino acid at theactive site of AChE changes the configuration of the enzyme molecule,stabilizing it and preventing it from functioning and inactivating permanently[13]. When inhaled by human being, the first adverse effects are a bloody orrunny nose, coughing, chest discomfort and difficulty in breathing. Skincontact may cause localized sweating and involuntary muscle contractions.

Following exposure by any route, other systemic effects may begin withina few minutes, or be delayed for up to 12 hours. These may include pallor,nausea, vomiting, diarrhea, abdominal cramps, headache, dizziness, eye pain,





blurred vision, constriction or dilation of the pupils, tears, salivation, sweatingand confusion [4, 6].

In severe cases, poisoning will affect the central nervous system,

producing in-coordination, slurred speech, loss of reflexes, weakness, fatigue,and eventual paralysis of the body extremities and respiratory muscles. Deathmay be caused by respiratory failure or cardiac arrest [4, 6, 15].

MP was initially registered in 1954 in the United States for application asinsecticide [14] but its uses was restricted in 1978 as a result of detrimentaleffects to humans [15]. Environmental Protection Agency (EPA) has nowclassified MP as a restricted-use pesticide and has given approval for outdooruse only [9]. It was classified by the World Health Organization (WHO) as a

Category Ia (extremely toxic) and by the United States EPA (US EPA) as aToxicity Category I (most toxic) insecticide [9].

As per CIBRC in India, formulations of MP, 50% EC and 2% DP are banned for use on fruits and vegetables (S.O.680 (E) dated 17th July, 2001),and its use is restricted to only those crops where honeybees are not acting as pollinators. (S.O.658 (E) dated 04th Sep., 1992) [16].

1.5. Recommended ADI and MRL Values

The Joint FAO/WHO Meeting on Pesticide Residues (JMPR) evaluatedMP in 1968, 1972, 1975, 1979, 1980, and 1984 [17, 18]. The acceptable dailyintake (ADI) for humans was estimated at 0-0.02 mg/kg body weight in 1984.This was based on the levels causing no toxicological effects: 2 mg/kg diet,equivalent to 0.1 mg/kg body weight in the rat; and 0.3 mg/kg body weight perday in man.

The FAO/WHO Codex Alimentarius Commission [19] recommendedMaximum Residue Limits (MRLs) in several food commodities, ranging from0.05 to 0.2 mg/kg. As per CSE report [12], in India, MP was registered for

seven crops by CIBRC, but, Food Safety and Standards Authority of India(FSSAI) did not set MRLs for these crops.

However, they have set MRLs for fruits (0.2 mg/kg) and vegetables (1mg/kg) for which using of MP formulations are not registered.





1.6. Environmental Fate

Once MP is introduced into the environment by spraying on crops,

droplets will fall on soil and plants. While most of the MP will stay in the areawhere it is applied, some can move to areas away from where it was appliedthrough rain, fog and wind. MP residue remains in the environment for a fewdays to several months. It has a half-life in aqueous solution of 175 days, and10 days to two months in soil [21, 22]. It is degraded to other chemicalcompounds by sunlight, and bacteria found in soil and water. The rate ofdegradation increases with temperature and with exposure to sunlight. Whenlarge concentrations of MP reach the soil as in the case of an accidental spill,

degradation will occur only after many years [7, 21].The concentrated amounts of MP that occur in soil, such as landfills and

hazardous waste sites do not degrade fast. Also large volume of wastewatercontaminated with MP, generated at both the producer and consumer level,require treatment before being released to the environment. Presence of this pesticide is thus expected in the soils, water resources and even in foodmaterials across India and developing countries where MP has been used for pest control. Therefore, economically feasible, rapid, sensitive, selective and

reliable methods for detection of MP are necessary. It is also required tomonitor a large number of samples in a short period of time.

1.7. Monitoring

Micro-quantities of MP are being measured using traditional analyticalmethods such as spectrophotometer, gas–liquid chromatography, thin-layer

chromatography high-performance liquid chromatography, capillaryelectrophoresis and mass spectrometry [23-27]. These analytical methods areeffective for the analysis of MP and are very sensitive and reliable but havesome limitations such as matrix complexity, time required for sample preparation, requirement of expensive apparatus and trained personnel tooperate the instrument, it cannot be carried to the field or site and it is difficultto monitor a large number of samples in a short period of time. Recently, therehas been an intense effort to develop biosensor devices for the determination

of methyl parathion pesticide. A biosensor is a self-contained integrated devicewhich is capable of providing specific quantitative or semi-quantitativeanalytical information using a biological recognition element (biochemicalreceptor) which is in direct spatial contact with a transducer element.





2. BIOSENSORS FOR THE DETECTION

OF METHYL PARATHION

Among the various biosensors for MP determination and quantification,systems based on acetylcholinesterase (AChE), organophosphorus hydrolase(OPH) and methyl parathion hydrolase (MPH) contribute a major share [28].

The basic principle of operation of the AChE based biosensor is the abilityof pesticide to inhibit cholinesterases, acetylcholinesterase, or butyrylcholinesterase and the ability to hydrolyze acetylcholine or butyrylcholine, respectively. On the other hand, OPH and MPH are used ascatalytic-based biosensors where OP pesticides and nerve gases are used assubstrate and hydrolyzed to generate an acid and alcohol.

Various biosensors for MP pesticide based on the AChE irreversibleinhibition test, using different transducers have been reported. Table 3 lists afew such biosensors which have been reported recently [28-35].

The concept of these biosensors is the quantitative measurement ofenzyme activity before and after incubation with the MP pesticide. Almost allof the systems mentioned, either differs in the technique used for enzymeimmobilization or the transducer for response measurement. Although the

above systems are very sensitive these systems however, face limitations withrespect to single use, poor specificity, longer incubation time and interferencefrom other substances including heavy metals and carbamates. Also thesesystems are unable to handle many samples in short period of time. Toovercome these drawbacks of the inhibition-based system, focus has beenshifted towards catalytic based systems, based on OPH.

OPH is also known as phosphotriesterase, parathion hydrolase, paraoxonase, DFPase, somanase, sarinase, phosphorothiolase and parathion

aryl esterase. It was first found in Pseudomonas diminuta, and then in Flavobacterium sp., both are soil microbes. It catalyzes the hydrolysis of OPcompounds and generates two protons as a result of the cleavage of the P-O,P-F, P-S or P-CN bonds and an alcohol, which in many cases is chromophoricand/or electroactive [36-42]. OPH is a 72kDa homodimeric metalloenzymecapable of degrading a large variety of OP-containing compounds byhydrolyzing the phosphoester bonds between the phosphorus center and anelectrophilic leaving group. OPH hydrolyzes the MP into detectable product p-

nitrophenol (PNP) as shown below.





MPH also a member of OPH family acts specifically on MP in a similar

way. This makes OPH and MPH a suitable recognition element for the

detection of MP pesticide.

Table 3. Acetylcholiesterase based biosensor for detection of MP

Immobilization Matrix Transducer Linear Detectionranges

Stability References

AChE entrapped using

silica sol-gel onto the

carbon paste electrode

Cyclic Voltammetry 0.1 - 1.0 ppbOne

month[29]

Labeled as AChE-Au-

PPy/GCECyclic Voltammetry

Two ranges

0.005 –

0.12 µg mL−1

and 0.5 –

4.5 µg mL

−1

.

10 days

storage[30]

Graphene- Fe3O4

nanocomposite film

modified glassy carbon

electrode

Cyclic Voltammetry

and Differential

Pulse Voltammetry

2. 5×10-9

∼

2×5×10-6

g mL-1

Not

reported[31]

Layered double

hydroxides (LDHs) as

the immobilization

matrix of AChE

Amperometric

Two ranges

0.005 - 0.3 µg mL-1

and

0.3 to 4.0 µg mL-1

Not

reported[32]

Polyaniline deposited on

vertically assembled

carbon nanotubes

wrapped with ssDNA

Voltammetric1.0 × 10-11 –

1.0 × 10-6

M5 days [33]

SnO2 nanoparticles-

carboxylic graphene-

nafion modified

electrode

Amperometric

Two ranges

10-13

- 10-10

M and

10-10

- 10-8

M

30 days [34]

AChE-GNs-QDs hybrid Electroluminescence

Two ranges

from 0.2 –

10 ng mL−1

and 20 –

150 ng mL−1

30 days [35]





Table 4. OPH and MPH based biosensors for detection of MP

Matrices Transducer

Linear

Detectionranges Stability Reusability References

OPH enzyme

MPDE–CdTe/Cys/Aunano/MWCNTs/GCE

Electrochemicalimpedance spectraLinearVoltammetry

Two ranges5.0 - 200ng/mL and200 - 1000ng/mL

30 days 8 replicates [43]

pH electrode modifiedwith an immobilized OPH

by glutaraldehydePotentiometric 0.1 – 0.43 mM One month

NotReported

[44]

Activated aminopropylcontrolled pore glass

beads and anelectrochemical flow-through detectorcontaining carbon pasteworking electrode

Amperometric Up to 140 μM One month 35 reactions [45]

Thin-film gold detectorthrough a cystamine/glutaraldehyde coupling

Amperometric 1 – 10 μM 4 weeks Not reported [46]

OPH/Nafion layerimmobilized onto thethick-film screen printedelectrode

Amperometric Up to 40 µM Notreported

Not reported [47]

CNT/OPH biosensorAmperometricCyclicvoltammetry

Up to 2µM Notreported

Not reported [48]

OPH/nafion on carbon paste electrode

Chronoamperometric

4.6 x10-6 –46 x 10-6 M

Notreported

Not reported [49]

MPH enzyme4-carboxylphenyl species

introduced to AuNPsurface followed bycovalent attachment ofMPH to achieve surface 6

CyclicvoltammetrySquare Wavevoltammetry

0.2 – 100 ppb 10 weeks 11 reactions [50]

MPH on agarose by metal-chelate affinity

Opticalabsorbance

0 – 1 × 10−4 M Notreported

Not reported [51]

MPH/Fe3O4@Au/SPE

Square waveVoltammetryElectrochemicalimpedance spectra

0.5 –1000 ng mL-1

30 days 6 reactions [52]

MPH/SP@AuNPs/MWC NTs/GCE

CyclicvoltammetryElectrochemicalimpedance spectra

0.001-5.0 μgmL−1

30 days NotReported

[53]





Various biosensors for MP pesticides based on the OPH and MPHenzymes have been reported (Table 4) [43-53].

Although purified enzymes have very high specificity for their substrates

or inhibitors, their application in biosensor construction may be limited by thetedious, time-consuming and costly enzyme purification steps and requirementof cofactor/coenzyme to generate the measurable product. Microorganisms provide an ideal alternative to these bottle-necks [54-56]. The many enzymesand co-factors that co-exist in the cells give the cells the ability to consumeand hence detect large number of analytes. Microbial cells can be easilymanipulated and adapted to consume and degrade new substrates under certaincultivating condition. Additionally, the progress in molecular biology/

recombinant DNA technology has opened endless possibilities of tailoring themicroorganisms to improve the activity of an existing enzyme or expressforeign enzyme/protein in host cell. All of the above makes microbial cells anexcellent biosensing element for developing biosensors.

3. MICROBIAL BIOSENSORS FOR METHYL PARATHION

The use of microbial cells has been demonstrated as an alternative biological catalyst without compromising on cost of purifying enzymes [54-56]. Thus, using microorganisms as biorecognition element provides an idealalternative to purified enzyme. Microbial cells having catalytic capability tohydrolyze MP into a detectable product can be utilized for biosensor detection.

In this direction many biosensors (as mentioned in table 5) [57-66] have been reported, where various microbial cells having OPH were immobilizedon different supports and associated with either electrochemical or optical

transducers for MP detection. In this context we review in detail the variousmicrobial biosensors that have been reported.

3.1. Electrochemical Microbial Biosensors

Electrochemical approaches are widely used in the development ofmicrobial biosensors. According to the detection principle, electrochemical

techniques can be divided into potentiometry, amperometry, conductometryand voltammetry.




Table 5. Microbial biosensors for detection of MP

MicroorganismImmobilizing

matrices

TransducersDetection

Limit

Linear Detection

ranges

Reusability

Electrochemical Microbial Biosensors

Recombinant Escherichia

coli cells OPHintracellularly

Entrapment behind amicroporus

polycarbonatemembrane onhydrogen ion sensingglass membrane of

pH electrode

Potentiometric 3μM Not reported Not reported

Escherichia coli cells

expressing OPH on cellsurface

Modifying a pHelectrode Potentiometric 2μM 0.06 - 0.91 mM 20 times

Genetically engineered Moraxella sp. expressINPNC-OPH on the cellsurface

Carbon pasteelectrode

Amperometric 1μM Upto 175 μM Not reported

Pseudomonas putida JS444, geneticallyengineered to expressOPH on the cell surface

Carbon pasteelectrode

Amperometric0.26 ppb(1 nM)

Upto 2 μM Not reported

Genetically engineered Pseudomonas putida JS444 expressing OPH onthe cell surface

Nucleopore polycarbonatemembrane

Dissolve oxygenelectrode

53 ppb(0.2 μM)

0.2 – 50 μM Not repotted




Table 5. (Continued)

Microorganism

Immobilizing

matrices Transducers

Detection

Limit

Linear

Detectionranges Reusability

Electrochemical Microbial Biosensors

Genetically engineered Escherichia coli strainsurface displayed mutantOPH (S5)

Glass carbonelectrode (GCE)modified withordered mesoporecarbons (OMCs)

Amperometric 15 nM 0.08-30 μM Not Reported

Recombinant E. coli was

having high periplasmicexpression of OPH

Screen printedcarbon electrode

(SPCE) usingglutaraldehyde

Cyclic

voltammetric 0.5 μM 2 - 80 μM 32 reactions

Optical Microbial Biosensors

Flavobacterium sp.Trapping in glassfiber filter.

Optical 0.3 μM 4 - 80 μMOne(disposable)

Sphingomonas sp.

Surface of the wellsof polystyrenemicroplates (96wells)

Optical NotReported

4 - 80 μM 75 reactions

Sphingomonas sp.Inner epidermis ofonion bulb scale Optical

NotReported 4 - 80 μM 52 reactions





Potentiometry involves the measurement of the potential difference between the working electrode and the reference electrode and the potentialsignal will be proportional to the concentration of analyte.

In one report, a potentiometric microbial biosensor was developedwherein the biological sensing element was recombinant Escherichia coli cellscontaining the plasmid pJK33 that expressed OPH intracellularly. The cellswere immobilized by entrapment behind a microporus polycarbonatemembrane on top of the hydrogen ion sensing glass membrane pH electrode.Microbial OPH catalyzes the hydrolysis of MP to release protons, theconcentration of which is proportional to the amount of hydrolyzed substrate.The sensor had a detection limit of 3 µM MP and could establish a storage

stability for 1 month [57]. In another report, a potentiometric microbial biosensor was developed by modifying a pH electrode with an immobilizedlayer of Escherichia coli cells expressing OPH on the cell surface. In this casealso, mechanism was same as above but sensitivity of biosensor was as low as2 μM and it showed a linear detection range between 0.06 - 0.91 mM MP. This biosensor also reported good storage stability for 60 days and proved thereusibility of immobilized biocomponent for 20 reactions [58].

Amperometry is conducted at a given applied potential between the

working electrode and the reference electrode and the current signal isrecorded and correlated to the concentration of MP. An amperometricmicrobial biosensor was described where sensor was based on a carbon pasteelectrode containing genetically engineered Moraxella sp. expressing INPNC-OPH on the cell surface under tac promoter. OPH catalyzes the hydrolysis ofMP pesticides to p-nitrophenol (PNP). PNP is detected anodically at thecarbon transducer with the oxidation current being proportional to MP. In thiscase, a potential of +0.9 V was applied to the working electrode vs. the Ag/

AgCl reference electrode. Authors have reported the sensitivity of the biosensor for MP in term of detection limit of 1µM and in term of detectionlevels up to 175 µM. Also immobilized biocomponent was stable for 45 days[59]. In another report, Lie et al., 2005 have reported a whole cell-basedamperometric biosensor where PNP degrader, Pseudomonas putida JS444cells, genetically engineered to express OPH on the cell surface wereimmobilized on the carbon paste electrode. Using the same catalyticmechanism mentioned above, surface-expressed OPH catalyzed MP to release

PNP, which was subsequently degraded by the enzymatic machinery of P. putida JS444. The electro oxidization current of the intermediates wasmeasured and correlated to the concentration of MP. The best sensitivity interm of detection limit of 0.26 ppb MP and detection range up to 2 μM were




Jitendra Kumar and ose Savio Melo102

reported at applied potential of 600 mV (vs Ag/AgCl reference). Storagestability of the microbial amperometric biosensor was however only 5 days[60]. Recently, Tang et al., 2014 have reported novel electrochemical

microbial biosensor based on glass carbon electrode (GCE) modified with bothordered mesopore carbons (OMCs) and cell surface-expressed OPH (OPH- bacteria/OMCs/GCE). In this report the genetically engineered Escherichia

coli strain mutant displayed OPH (S5) on surface with improved enzymeactivity and favorable stability and was constructed using a newly identified N-terminal of ice nucleation protein as an anchoring motif, which can be useddirectly without further time-consuming enzyme-extraction and purification.Using OPH-bacteria/OMCs/GCE, the current response at 0.84 V (vs. SCE)

was linear between 0.08–30 μM and showed a detection limit of 15 nM MP.Storage stability of the biosensors was 1 month [62].

Cyclic voltammetry is a very versatile electrochemical technique whichallows probing the mechanism of redox and transport properties of a system insolution. This is accomplished with a three electrode arrangement whereby the potential relative to some reference electrode is scanned at a working electrodewhile the resulting current flowing through a counter (or auxiliary) electrodeis monitored in a quiescent solution. The technique is ideally suited for a quick

search of redox couples present in a system; once located, it may becharacterized by more careful analysis of the cyclic voltammogram.

In one of our study, a cyclic voltammetry based microbial biosensor forMP was described. In this study, recombinant E. coli cells with high periplasmic expression of OPH was immobilized on screen printed carbonelectrode (SPCE), associated with cyclic voltammetry system and cyclicvoltammograms were recorded before and after hydrolysis of MP. Detectionwas calibrated based on the relationship between the changes in the current

observed at +0.1 V potential. As the concentration of MP was increased theoxidation current also increased. Detection range of biosensor was reported between 2 - 80 µM of MP. A single SPCE with immobilized cells could bereused for 32 reactions and showed storage stability for 22 days [63].

3.2. Optical Microbial Biosensors

Optical transducer is another commonly used system in microbial biosensors. Optical detection is usually based on the measurement ofabsorbance, color, luminescence, fluorescence, or other optical signal produced by the interaction of microorganism with the analyte and correlates





the observed optical signal with the concentration of target compound. Opticalsensing techniques are especially attractive in high throughput screening sincethey enable biosensors to monitor multiple analytes simultaneously. The

colorimetric sensing technique in microbial biosensors involves the conversionof a chromogen substrate into a colored compound by the metabolic activity ofthe microbial sensing element. The colored product can be distinguished bythe naked eye or a spectrophotometer. Because of its simple and inexpensivemeasurement setup, colorimetric technique has been widely applied in thefabrication of cost-effective microbial biosensors.

Colorimetric microbial biosensors involve the generation of coloredcompound which can be measured and correlated with the concentration of

analyte. In our first study, an optical microbial biosensor was described for thedetection of MP. In this study, whole cells of Flavobacterium sp. having OPHenzyme, were immobilized by trapping in glass fiber filters and were used as biocomponent along with optical fiber system.

Detection was based on the relationship between the amount MPhydrolyzed and the amount of chromophoric product PNP formed which wasquantified by measuring the absorbance at the λmax of 410 nm. A lowerdetection limit of 0.3 μM and linear detection range of 4 - 80 μM of MP was

established. The immobilized microbial biocomponent was disposable, cost-effective and showed high reproducibility and uniformity. Applicability of biosensor was also demonstrated with synthetic MP spiked samples [64].

In another study of ours, a microplate-based biosensor was describedwhere isolated Sphingomonas sp., were immobilized directly onto the surfaceof the wells of a polystyrene make 96 wells microplate using glutaraldehyde asthe cross-linker. MP was hydrolyzed to a chromophoric product PNP.

Microplate with immobilized bacteria was directly associated with the

optical transducer of microplate reader and PNP was quantified by measuringthe absorbance at a λmax of 410 nm. In this case linear detection range of the biosensor was also between 4 - 80 μM MP but the cells-immobilizedmicroplate showed a reusability up to 75 reactions and storage stability of 18days [65].

In another study, inner epidermis of onion bulb scale was used as a naturalsupport for immobilization of microbial cells of Sphingomonas sp. In thisstudy, cells immobilized on onion membrane were placed inside the wells of

the microplate and same mechanism as mentioned above was used fordetection. Detection range was similar because microbial cells and transducerwere same but there was a difference in reusability and storage stability whichwas 52 reaction and 32 days respectively [66].





4. TREND OF MICROBIAL BIOSENSORS FROM

SINGLE TO MULTIPLE SAMPLES ANALYSIS

In our study, the first biosensor for MP was an optical microbial biosensordeveloped based on immobilization of whole cells of Flavobacterium sp.

containing OPH on glass fibre filters by adsorption method and was used as adisposable biocomponent in association with optical fibre transducer fordetection of methyl parathion pesticide. The biosensor required only 75 µL ofsamples and its biocomponent was disposable in nature and could be used forfield samples analysis [64]. In this the biocomponent was not reusable like inAChE based biosensors which can be used for single sample analysis only. Inthe second biosensor, an electrochemical microbial biosensor was developedfor detection of MP. In this study, recombinant E.coli was immobilized onSPCE and associated with cyclic voltammetry. It could be reused upto 32times with biosensor requiring only 20 µL sample for analysis and thus itcould be used when very low sample amount is available [63]. In our third biosensor, a microplate based optical biosensor was developed for detectingmultiple numbers of samples (96) in a single platform and in a very short period of time (5 min). In this study, Sphingomonas sp. JK1 was immobilized

directly onto the surface of the 96 wells microplate and on onion membranefixed inside the wells of microplate [65, 66]. Cells immobilized directly onmicroplate and on onion membrane have shown a reusability of 75 and 52reactions respectively. Biocomponents were associated with optical transducerof multi detection microplate reader (MDMR) for online optical detection interm of absorbance. Microplate technique provides a simpler alternative forthe typical two-dimensional micropositioning, enabling to acquire the wholearray simultaneously and making the measurement time independent of the

number of wells in the plate. Thus microplate-based biosensor provides aninnovative concept where multiple samples of MP could be detected in veryshort period of time as well as biocomponent are reusable for analysis of morethan one samples.

5. FUTURE PROSPECTS

The microbial biosensors herein have thus proved to be effective for thedetection and analysis of single to multiple numbers of MP samples. Howeverthese systems are not as sensitive as AChE based biosensors.





Future prospects would involve devising ways to increase the sensitivityof the multiple samples microbial biosensors by integrating the biocomponentwith nano based materials as well as through advances in the transducer

element.

R EFERENCES

[1]

International Programme in Chemical Safety (IPCS). Organophosphorus pesticides. Available from: http://www.inchem.org/documents/pims/chemical/pimg001.htm.

[2]

Directorate of Plant Protection, Quarantine and Storage (PPQS), India.Statistics of pesticides. Avaialble from: http://ppqs.gov.in/IpmPesticides _Cont.htm.

[3]

India for Safe Food. Pesticide Use in India. Available from: http://www.indiaforsafefood.in/farminginindia.html.

[4]

ATSDR 1999 Toxicological profile for methyl parathion. Draft for

public comment . Atlanta, GA, US Department of Health and HumanServices, Public Health Service, Agency for Toxic Substances and

Disease Registry.[5] EPA. 1974b. Production, distribution, use, and environmental impact

potential of selected pesticides [final report]. Washington, DC: USEnvironmental Protection Agency, Office of Pesticide Programs. EPA540/1-74-001, 181-188.

[6]

IPCS. 1993. Environmental Health Criteria 145, Methyl Parathion. International Programme on Chemical Safety. http://www.inchem.org/documents/ehc/ehc145.htm.

[7]

Methyl Parathion, Prior Informed Decision Guidance Document , (FAO/UNEP, Joint Database, IRPTC, Geneva), Update 17, September 1996.(PAN International Website, Methyl Parathion Fact Sheet).

[8]

Mulchandani, A., Chen, W., Mulchandani, P., Wang, J., Rogers, K. R.,2001. Biosensors for direct determination of organophosphate pesticides. Biosensors Bioelectronics. 16, 225-230.

[9] US EPA. 2003. Interim Reregistration Eligibility Decision for Methyl

Parathion. Case No. 0153. United States Environmental Protection

Agency. http://www.epa.gov/oppsrrd/REDs/methylparathion.pdf. Signed05/2003. Accessed 20/11/04.[10]

FAO 1997. Methyl Parathion. Food and Agriculture Organisation, http://www.fao.org/docrep/W5715E/w5715e03.htm. Accessed 19/10/04.





[11]

FAO/UNEP. 1996. Decision Guidance Document . Methyl Parathion(emulsifiable concentrates at or above 19.5% active ingredient and dustsat or above 1.5% active ingredient). Joint FAO/UNEP Programme for

the Operation of Prior Informed Consent. http://www.pic.int/en/DGDs/MetparaEN. doc. Accessed 19/10/04.

[12]

CSE 2011. Centre of Science and Environment (CSE). State of Pesticide

Regulations in India. Available from: http://www.cseindia.org/userfiles/ paper_pesticide.pdf.

[13]

Sultatos, L. G. 1994: Mammalian toxicology of organophosphorus pesticides. J. Toxicol. Environ. Health, 43(3): 271-289.

[14]

US EPA. 1999. United States Environmental Protection Agency. Methyl

Parathion Risk Management Decision. Available from http://www.epa.gov/pesticides/factsheets/chemicals/mpfactsheet.htm. Accessed 5/12/06.

[15]

Garcia, S. J., Abu-Qare, A. W., Meeker-O’Connel, W. A., Borton, A. J.,Abou-Donia, M. B. 2003. Methyl parathion: A review of health effects.Journal of Toxicology and Environmental Health, Part B. 6, 285-210.

[16] CIBRC 2007. Pesticides Restricted for Use in India. Central InsecticidesBoard and Registration Committee. Directorate of Plant Protection,Quarantine and Storage, Department of Agriculture and Cooperation,

India. Available from http://cibrc.nic.in/list_pest_bann.htm. Accessed08/02/07.

[17]

IPCS 1993. International Programme on Chemical Safety. Methyl

parathion Health and Safety Guide No. 75. Available from http://www.inchem.org/documents/hsg/hsg/hsg75_e.htm.

[18] Hertel, R. 1993. Environmental health criteria 145, methyl parathion.United Nations Environment Programme, International LabourOrganisation and the World Health Organization. Available at http://

www.inchem.org/documents/ehc/ehc/ehc145.htm. Accessed on 19 Aug.1991.[19]

FAO/WHO 1986. Codex Maximum Limits for pesticide residues. Codex

Alimentarius Commission CAC/Vol. XIII. 3rd ed. Rome, Food andAgriculture Organization of the United Nations.

[20] PPQS 2012. Directorate of Plant Protection, Quarantine and Storage(PPQS), Central Insecticides Board and Registration Committee. Major

uses of pesticides (Registered under the Insecticides Act, 1968).

Available from: http://cibrc.nic.in/mupi2012.doc.[21] Pesticide News. 1995. Methyl parathion. Pesticide News. 36(20-21).Available from: http://www.pan-uk.org/pestnews/actives/methylpa.htm.





[22]

Horward, P. H., Handbook of Environmental Fate and Exposure Data

for Organic Chemicals, Vol. 3, (Pesticides, Lewis), 1989.[23] Beck, J. and Sherman, M. 1968. Detection by TLC of organophosphorus

insecticides in acutely poisoned rats and chickens. Acta Pharmacol.

Toxicol., 26: 35-40.[24]

Camoni, I., Gandolfo, N., Ramelli, G. C., Sampaolo, A., and Binetti, L.1968. Analytical procedure for the detection and determination of parathion and methyl-parathion in food products. Bollettino dei

Laboratori Chimica Provinciali. 19: 615-629.[25]

Suzuki, K., Goto, S. and Kashiwa, T. 1968. Residue analysis ofagricultural chemicals. I. Determination of parathion-methyl in rice

grains by gas chromatography with electron-capture detection. Japan Analyst , 17: 187-191 (in Japanese).

[26] Kawahara, F. K., Lichtenberg, J. J., Eichelberger, J. W. 1967. Thin layerand gas chromatographic analysis of parathion and methyl parathion inthe presence of chlorinated hdrocarbons. J. Water Pollut. Control Fed., 39: 446-457.

[27]

Nielsen, P. G. 1985 Quantitative analysis of parathion and parathion-methyl by combined capillary column gas chromatography negative ion

chemical ionization mass spectrometry. Biomed. Mass Spectrom., 12:695498.

[28]

Pundir, C. S., Chauhan, N. 2012. Acetylcholinesterase inhibition-based

biosensors for pesticide determination: a review. Analytical

Biochemistry. 429, 19-31.[29] Mulchandani, A., Mulchandani, P., Chen, W. 1998. Enzyme biosensor

for determination of organophosphates. Field Analytical Chemistry and

Technology. 2, 363-369.

[30]

Raghu, P., Madhusudana Reddy, T., Kumara Swamy, B. E.,Chandrashekar, B. N., Reddaiah, K., Sreedhar, M. 2012. Developmentof AChE biosensor for the determination of methyl parathion andmonocrotophos in water and fruit samples: A cyclic voltammetric study. Journal of Electroanalytical Chemistry, 665, pp. 76-82.

[31]

Gong, J., Wang, L., Zhang, L. 2009. Electrochemical biosensing ofmethyl parathion pesticide based on acetylcholinesterase immobilizedonto Au-polypyrrole interlaced network-like nanocomposite. Biosensors

and Bioelectronics, 24 (7), pp. 2285-2288.[32]

Liu, Z.-M., Jing, Y.-F.a, Wang, Z.-L., Zhan, H.-J., Shen, Q. 2013.Highly sensitive electrochemical biosensing of methyl parathion





pesticide based on acetylcholinesterase immobilized onto graphene-Fe3O 4 Nanocomposite. Sensor Letters, 11 (3), pp. 531-538.

[33] Gong, J., Guan, Z., Song, D. 2013. Biosensor based on

acetylcholinesterase immobilized onto layered double hydroxides forflow injection/amperometric detection of organophosphate pesticides Biosensors and Bioelectronics, 39 (1), pp. 320-323.

[34]

Viswanathan, S., Radecka, H., Radecki, J. 2009. Electrochemical biosensor for pesticides based on acetylcholinesterase immobilized on polyaniline deposited on vertically assembled carbon nanotubes wrappedwith ssDNA. Biosensors and Bioelectronics, 24 (9), pp. 2772-2777.

[35]

Yang, L., Zhou, Q., Wang, G., Yang, Y. 2013. Acetylcholinesterase

biosensor based on SnO2 nanoparticles-carboxylic graphene-nafionmodified electrode for detection of pesticides. Biosensors and

Bioelectronics, 49, pp. 25-31.[36]

Liang, H., Song, D., Gong, J. 2014. Signal-on electrochemiluminescenceof biofunctional CdTe quantum dots for biosensing of organophosphate pesticides. Biosensors and Bioelectronics, 53, pp. 363-369.

[37]

Lai, K., Dave, K. I. and Wild, J. R. 1994. Bimetallic binding motifs inorganophosphorus hydrolase are important for catalysis and structural

organization. Journal of Biological Chemistry, 269(24), 16579-16584.[38] Lai, K., Stolowich, N. J. and Wild, J. R. 1995. Characterization of P-S

bond hydrolysis in organophosphorothioate pesticides byorganophosphorus hydrolase. Archives of Biochemistry and Biophysics,

318(1), 59-64.[39]

Singh, B. K. 2009. Organophosphorus-degrading bacteria: Ecology andindustrial applications. Nature Reviews Microbiology, 7(2), 156-164.

[40] Singh, B. K. and Walker, A. 2006. Microbial degradation of

organophosphorus compounds. FEMS Microbiology Reviews, 30(3),428-471.[41]

Dumas, D. P. and Raushel, F. M. 1990. Chemical and kinetic evidencefor an essential histidine in the phosphotriesterase from Pseudomonas

diminuta. Journal of Biological Chemistry, 265(35), 21498-21503.[42]

Dumas, D. P., Caldwell, S. R., Wild, J. R., and Raushel, F. M. 1989.Purification and properties of the phosphotriesterase from Pseudomonas

diminuta. Journal of Biological Chemistry, 264(33), 19659-19665.

[43]

Dumas, D. P., Durst, H. D., Landis, W. G., Raushel, F. M., and Wild, J.R. 1990. Inactivation of organophosphorus nerve agents by the phosphotriesterase from Pseudomonas diminuta. Archives of

Biochemistry and Biophysics, 277(1), 155-159.





[44]

Du, D., Chen, W., Zhang, W., Liu, D., Li, H., Lin, Y. 2010. Covalentcoupling of organophosphorus hydrolase loaded quantum dots to carbonnanotube/Au nanocomposite for enhanced detection of methyl parathion.

Biosensors and Bioelectronics, 25 (6), pp. 1370-1375.[45] Mulchandani, P., Mulchandani, A., Kaneva, I., Chen, W. 1999.

Biosensor for direct determination of organophosphate nerve agents. 1.Potentiometric enzyme electrode. Biosensors and Bioelectronics, 14 (1), pp. 77-85.

[46]

Mulchandani, P., Chen, W., Mulchandani, A. 2001. Flow injectionamperometric enzyme biosensor for direct determination oforganophosphate nerve agents. Environmental Science and Technology,

35 (12), pp. 2562-2565.[47] Wang, J., Krause, R., Block, K., Musameh, M., Mulchandani, A.,

Schöning, M. J. 2003. Flow injection amperometric detection of OPnerve agents based on an organophosphorus-hydrolase biosensordetector. Biosensors and Bioelectronics, 18 (2-3), pp. 255-260.

[48]

Mulchandani, A. 1999. Amperometric thick-film strip electrodes formonitoring organophosphate nerve agents based on immobilizedorganophosphorus hydrolase. Analytical Chemistry, 71 (11), pp. 2246-

2249.[49] Deo, R. P., Wang, J., Block, I., Mulchandani, A., Joshi, K. A.,

Trojanowicz, M., Scholz, F., Chen, W., Lin, Y. 2005. Determination oforganophosphate pesticides at a carbon nanotube/organophosphorushydrolase electrochemical biosensor. Analytica Chimica Acta, 530 (2), pp. 185-189.

[50] Wang, J., Chen, L., Mulchandani, A., Mulchandani, P., Chen, W. 1999.Remote biosensor for in-situ monitoring of organophosphate nerve

agents. Electroanalysis, 11 (12), pp. 866-869. MPH.[51]

Liu, G., Guo, W., Yin, Z. 2014. Covalent fabrication of methyl parathionhydrolase on gold nanoparticles modified carbon substrates fordesigning a methyl parathion biosensor. Biosensors and Bioelectronics,53, pp. 440-446.

[52]

Lan, W., Chen, G., Cui, F., Tan, F., Liu, R., Yushupujiang, M. 2012.Development of a novel optical biosensor for detection oforganophoshorus pesticides based on methyl parathion hydrolase

immobilized by metal-chelate affinity. Sensors (Switzerland), 12 (7), pp.8477-8490.[53]

Zhao, Y., Zhang, W., Lin, Y., Du, D. 2013. The vital function ofFe3O4@Au nanocomposites for hydrolase biosensor design and its





application in detection of methyl parathion. Nanoscale, 5 (3), pp. 1121-1126.

[54] Chen, S., Huang, J., Du, D., Li, J., Tu, H., Liu, D., Zhang, A. 2011.

Methyl parathion hydrolase based nanocomposite biosensors for highlysensitive and selective determination of methyl parathion. Biosensors

and Bioelectronics, 26 (11), pp. 4320-4325.[55]

D'Souza, S. F. 2001. Microbial biosensors. Biosensors and

Bioelectronics, 16(6), 337-353.[56]

Lei, Y., Chen, W. and Mulchandani, A. 2006. Microbial biosensors. Analytica Chimica Acta, 568(1-2), 200-210.

[57]

Su, L., Jia, W., Hou, C., Lei, Y. 2011. Microbial biosensors: A review.

Biosensors and Bioelectronics, 26 (5), pp. 1788-1799.[58] Mulchandani, A., Mulchandani, P., Chauhan, S., Kaneva, I., Chen, W.,

1998. A potentiometric microbial biosensor for direct determination oforganophosphate nerve agents. Electroanalysis 10 (11), 733-737.

[59]

Mulchandani, A., Mulchandani, P., Kaneva, I., Chen, W., 1998c.Biosensor for direct determination of organophosphate nerve agentsusing recombinant Escherichia coli with surface-expressedorganophophorus hydrolase. 1. Potentiometric microbial electrode. Anal.

Chem. 70, 4140-4145.[60] Mulchandani, P., Chen, W., Mulchandani, A., Wang, J., Chen, L. 2001.

Amperometric microbial biosensor for direct determination oforganophosphate pesticides using recombinant microorganism withsurface expressed organophosphorus hydrolase. Biosensors and

Bioelectronics, 16 (7-8), pp. 433-437.[61] Lei, Y., Mulchandani, P., Wang, J., Chen, W., Mulchandani, A. 2005.

Highly sensitive and selective amperometric microbial biosensor for

direct determination of p-nitrophenyl-substituted organophosphate nerveagents. Environmental Science and Technology, 39 (22), pp. 8853-8857.[62]

Lei, Y., Mulchandani, P., Chen, W., Mulchandani, A. 2005. Directdetermination of p-nitrophenyl substituent organophosphorus nerveagents using a recombinant Pseudomonas putida js444-modified clarkoxygen electrode. Journal of Agricultural and Food Chemistry, 53 (3), pp. 524-527.

[63] Tang, X., Zhang, T., Liang, B., Han, D., Zeng, L., Zheng, C., Li, T.,

Wei, M., Liu, A. 2014. Sensitive electrochemical microbial biosensor for p-nitrophenylorganophosphates based on electrode modified with cellsurface-displayed organophosphorus hydrolase and ordered mesoporecarbons. Biosensors and Bioelectronics, 60, pp. 137-142.





[64]

Kumar, J., D'Souza, S. F. 2011. Microbial biosensor for detection ofmethyl parathion using screen printed carbon electrode and cyclicvoltammetry. Biosensors and Bioelectronics, 26 (11), pp. 4289-4293.

[65]

Kumar, J., Jha, S. K., D'Souza, S. F. 2006. Optical microbial biosensorfor detection of methyl parathion pesticide using Flavobacterium sp.whole cells adsorbed on glass fiber filters as disposable biocomponent. Biosensors and Bioelectronics, 21 (11), pp. 2100-2105.

[66]

Kumar, J., D'Souza, S. F. 2010. An optical microbial biosensor fordetection of methyl parathion using Sphingomonas sp. immobilized onmicroplate as a reusable biocomponent. Biosensors and Bioelectronics,26 (4), pp. 1292-1296.

[67]

Kumar, J., D'Souza, S. F. 2011. Immobilization of microbial cells oninner epidermis of onion bulb scale for biosensor application. Biosensors

and Bioelectronics, 26 (11), pp. 4399-4404.




INDEX

A

acetone, 91acetonitrile, 7acetylcholine, 95acetylcholinesterase, ix, 89, 92, 95, 107, 108acetylcholinesterase inhibitor, 92

acid, 11, 16, 17, 28, 61, 80, 95acidic, 66active site, 36, 92additives, 67adenine, 16, 27denosine triphosphate, 26adenovirus, 19adsorption, 10, 35, 67, 73, 104adverse effects, ix, 8, 76, 89, 92aerogels, 63

affinity receptor design, vii, 1aflatoxin, 8agar, 66aggregation, 13agriculture, ix, 13, 76, 89algae, 47, 58, 61aluminium, vii, 1, 3amiloride, 22amino acid, 21, 26, 92

ammonia, 47amylase, 19anchoring, 102angiogenesis, 23

aniline, 17anthrax, 25antibody, 11, 15, 21, 24, 67, 79, 80, 82, 83antigen, 11, 15, 25, 79, 80, 83aptamers, vii, 1, 10, 11, 23, 24aqueous solutions, 61Argentina, 57, 69artificial affinity ligands, vii, 1

artificial intelligence, 41Artificial Neural Networks, 41ascorbic acid, 18aspartic acid, 16asymmetry, 29ATP, 16, 18Atrazine, v, ix, 75, 76, 77, 81, 83, 84atrazine residues, ix, 75

B

bacteria, 12, 13, 14, 17, 20, 59, 66, 68, 72,94, 102, 103, 108

beer, 35, 43 benefits, ix, 90 beverages, 37, 43 binding affinities, vii, 2 binding energy, 5, 6

biocompatibility, 58, 61, 63, 66, 79 biodegradability, 65 biodegradation, viii, ix, 57, 65, 75 biologic functions, viii, 57




Index114

biological activity, 80 biological processes, 43 biological responses, 58

biological samples, 18 biological systems, 69 biomarker discovery, vii, 1, 3 biomarker-based diagnosis, vii, 1 biomarkers, 3, 13, 19, 20, 28, 46 biomolecules, 12, 13, 46, 67 biopolymer(s), viii, 57, 60, 61, 63, 66 biosafety, 65 biosensors, vii, viii, ix, 1, 3, 10, 11, 13, 14,

15, 19, 20, 21, 23, 24, 25, 26, 41, 46, 47,

57, 58, 59, 67, 72, 73, 75, 76, 77, 78, 79,80, 81, 82, 83, 90, 95, 97, 98, 99, 102,103, 104, 105, 107, 110

biosensors research, vii biotechnology, 23, 24 biotin, 80 bleeding, 7, 8 blood, 10, 46 blood plasma, 10

bloodstream, 24 body fluid, 35 body weight, 93 bonding, 3, 10, 11 bonds, 3, 64, 95 bone cancer, 46 brain, 27, 32, 41 brain functions, 41Brazil, 31, 47, 50, 53

breakdown, 76

breathing, ix, 89, 92 by-products, 60

C

Ca2+, 61, 63, 64cadmium, vii, 1caffeine, 26, 44calibration, 40

caloric intake, 27calorimetry, 6cancer, vii, 1, 19, 20, 25, 28, 76capillary, 8, 24, 94, 107

carbamazepine, 22carbohydrates, 17carbon, 18, 28, 29, 47, 49, 79, 96, 97, 100,

101, 102, 108, 109, 111carbon nanotubes, 29, 49, 96, 108carcinoembryonic antigen, 19, 25carcinoma, 64cardiac arrest, 93cardiovascular disease, 46cardiovascular system, 15catalysis, 20, 108catalyst, 98cation, 61

cell division, 59cell invasion, 23cell line(s), 19, 59cell surface, 99, 101, 110central nervous system (CNS), 93ceramic, 58challenges, 20, 21, 48, 69, 72chemical(s), viii, 2, 3, 5, 6, 11, 12, 14, 17,

21, 26, 32, 33, 34, 35, 41, 42, 44, 45, 46,

48, 49, 53, 57, 58, 59, 68, 81, 90, 91, 94,105, 106, 107chemical interaction, 58, 81chemical properties, 17, 33, 91chemical stability, viii, 5, 57, 59chemical structures, 49chitosan, 18, 28, 29, 49chloroform, 7, 9, 78chlorophyll, 76, 82cholera, 47

cholesterol, 29chromatographic technique, 76chromatography, 25, 29, 76, 83, 94, 107classes, 11, 47classification, viii, 31, 40, 42, 43, 44, 45, 48,

77cleavage, 95clinical diagnosis, viii, 32, 41, 50clone, 83

clusters, 39coenzyme, 98coffee, 44collagen, 61, 66




Index 115

Colombia, 75colon cancer, 19colorectal cancer, 23

complexity, 42, 44, 94composites, 18, 28composition, viii, 31, 32, 34, 42, 44, 58compounds, 2, 3, 5, 13, 35, 42, 45, 49, 58,

81, 90, 94, 95, 108condensation, 63, 64, 65conductivity, 38, 49, 77, 79, 80configuration, 19, 92confinement, 63construction, 2, 15, 17, 98

consumption, 36, 45, 76, 78, 83, 84, 92contamination, 7, 8, 43copolymerisation, 2copolymers, 61copper, 3correlation(s), 38, 44, 45corticosteroids, 24cost, ix, 2, 3, 12, 13, 20, 33, 36, 47, 61, 67,

76, 79, 90, 98, 103

cotton, 92coughing, ix, 89, 92covalent bond, 3, 9creatinine, 46Croatia, 86, 87crop production, 76crop(s), ix, 75, 76, 89, 90, 92, 93, 94crystalline, 91crystals, 17culture, viii, 19, 58, 60, 62, 68

culture conditions, viii, 58culture medium, 19, 60, 62cycles, 17cytotoxicity, 58

D

data analysis, viii, 31, 41, 42, 49data gathering, 48

data set, 39decomposition, 40, 47defects, 76degradation, 94, 108

Denmark, 91Department of Agriculture, 106dependent variable, 40

depolarization, 37deposition, 17depression, ix, 89derivatives, 27, 49destruction, 76detectable, 95, 98developed countries, ix, 89, 92developing countries, ix, 89, 92, 94diabetes, vii, 1dialysis, 46

diarrhea, 92dielectric constant, 38diet, 93diffusion, 38, 60, 63, 65, 73dilation, 93dimensionality, 39, 40dimethacrylate, 6, 10dipoles, 37discomfort, ix, 89, 92

discriminant analysis, 43, 45discrimination, 33, 36, 39, 47disease diagnostics, vii, 1diseases, vii, 1, 15, 33, 46displacement, 23dissociation, 3, 11, 19distilled water, 49distribution, 3, 7, 61, 63, 105diversification, 60dizziness, 92

DNA, vii, 1, 3, 10, 15, 23, 25, 46, 67dopamine, 17, 18, 27drinking water, ix, 75, 83drug addict, 18drug addiction, 18drug delivery, 20, 21, 64drugs, 14dusts, 106dyes, 12, 73

E

E.coli, 104




Index116

early warning, 76ecosystem, viii, 58, 69effluent, 47

EIS, 79, 80electric current, 77electrical properties, 37electrical response, viii, 31, 32, 49electricity, 17electrochemical impedance, 79electrochemical methods, viii, 31, 76, 79electrode surface, 79, 80electrodes, 26, 27, 34, 35, 36, 37, 38, 43, 44,

47, 79, 109

electromagnetic, 81electron(s), 36, 37, 80, 107Electronic Tongue, v, viii, 31, 32electrophoresis, 24, 94ELISA, 79emergency, 76emission, 82emulsions, 45encapsulation, viii, 57, 58, 59, 60, 61, 65,

66, 67, 68, 73endocrine, 2, 5endotoxins, 47energy, 5, 12, 35England, 1entrapment(s), 58, 59, 101environment, 34, 58, 60, 65, 76, 94environmental change, 50environmental impact, 105Environmental Protection Agency (EPA),

ix, 84, 89, 93, 105, 106enzyme(s), ix, 2, 3, 11, 13, 14, 23, 46, 67,

78, 77, 79, 81, 82, 90, 92, 95, 97, 98,102, 103, 109

enzyme immobilization, 78, 79, 95epidermis, 100, 103, 111epitopes, 13equipment, 33, 79ester, 17

ethylene, 10E-tongue, viii, 31, 32, 33, 34, 35, 36, 37, 38,39, 41, 42, 43, 44, 45, 46, 47, 48, 49

eukaryotic, 66

eukaryotic cell, 66European Community, 76European Parliament, 84

experimental condition, 41expert systems, 41exposure, 76, 92, 94extraction, 2, 8, 21, 22, 23, 25, 102extracts, 48

F

fabrication, viii, 32, 103, 109

fat, 43fermentation, 45ferritin, 16fetus, 76fiber(s), 14, 63, 64, 81, 82, 100, 103, 111fibrin, 61field crops, 92film formation, 78films, viii, 17, 24, 25, 31, 34, 38, 48filters, 103, 104, 111

financial support, 50fingerprint(s), viii, 31, 32fish, 45flavour, 32, 45flex, 47flexibility, 58fluid, 28fluorescence, 14, 82, 102folic acid, 27

food, viii, ix, 32, 33, 43, 45, 50, 75, 89, 93,94, 107food products, 107formation, 2, 7, 12, 61, 65, 80fragility, 20fragments, 11, 29, 67, 79France, 48fruits, 93functionalization, 22fungi, 59, 70




Index 117

G

GCE, 28, 96, 97, 100, 102

gel, viii, 24, 57, 58, 59, 64, 66, 67, 69, 72,73, 81

gelation, 60, 61, 63, 66genetic immunization, 24genetic marker, 19geographical origin, 36, 44, 47glasses, 34, 35, 72glucose, 47, 67, 79glucose oxidase, 47, 67, 79

glutamic acid, 10, 16glutathione, 81glycol, 6glycoproteins, 26gold nanoparticles, 17, 27, 28, 109graphite, 26, 44, 49growth, 60, 62, 64, 66, 70, 79

H

half-life, 94hazardous waste, 94headache, 92health, vii, ix, 1, 75, 89, 106health care, vii, 1health care diagnostics, viii, 2health effects, 106health problems, ix, 75, 89heavy metals, 46, 48, 49, 65, 95

hemoglobin, 28hepatitis, 21herbicide(s), ix, 75, 76, 82hexane, 63histamine, 27histidine, 16, 80, 108HIV, 24host, viii, 57, 58, 59, 65, 66, 67, 68, 70, 98human body, vii, 1, 3

hybrid, 17, 28, 58, 63, 72, 96hydrogels, viii, 57, 59, 61, 65, 66, 70, 72, 73hydrogen, 3, 7, 10, 11, 49, 99, 101hydrogen bonds, 11

hydrolysis, 63, 64, 65, 95, 101, 102, 108hydrophilicity, 79hydrophobicity, 12

hydroquinone, 49hydroxide, 65hydroxyethyl methacrylate, 10hysteresis, 39

I

immobilization, viii, 57, 59, 63, 66, 67, 72,78, 79, 80, 82, 83, 96, 103, 104

immunoglobulin(s), 11, 20, 29imprinting, vii, 2, 3, 4, 5, 6, 7, 8, 10, 12, 13,19, 20, 21, 23, 25, 28

improvements, vii, 1, 5, 20, 21in vivo, 46incidence, 76income, 59incubation time, 95India, ix, 89, 90, 91, 92, 93, 94, 105, 106industries, 45, 48

industry, viii, 32, 42, 43, 47infectious diseases, vii, 1infrared spectroscopy, 6, 45, 82inhibition, ix, 23, 45, 79, 89, 95, 107inhibitor, 78insecticide, ix, 89, 90, 92, 93insects, 92insertion, 42insulin, 63

integration, 18, 49integrity, 5interface, 14, 35, 37, 38, 79interference, 33, 34, 82, 95International Labour Organisation, 106ionization, 107ions, 10, 35, 37, 47, 61, 63, 64, 80IR spectroscopy, 42iron, vii, 1, 3, 28isolation, 8, 11

Italy, 54




Index118

J

Japan, ix, 48, 89, 107

K

K +, 63kinetics, 61

L

landfills, 94Latin America, ix, 75layered double hydroxides, 108lead, 2, 5, 7, 8, 14, 33, 34, 46leakage, 59learning, 41lecithin, 77leukemia, 26ligand, 5, 14, 15, 17, 77light, 11, 67

lipids, 45liposomes, 79liquid chromatography, 21, 76, 94liquid phase, 7, 46liquids, 39liver, 64luminescence, 102lung cancer, 23, 25lysine, 64

M

machinery, 59, 101macromolecules, 18, 20, 21, 22, 80macropores, 63magnetic particles, 80manual procedures, 42manufacturing, 13, 43

mapping, 29, 41masking, 45mass, 8, 9, 16, 18, 76, 83, 94, 107mass spectrometry, 76, 94, 107

materials, vii, viii, ix, 1, 10, 19, 26, 27, 34,37, 47, 57, 58, 59, 65, 67, 69, 72, 89, 94,105

matrix, viii, 6, 20, 40, 43, 57, 58, 59, 60, 62,63, 65, 66, 67, 68, 79, 94, 96measurement(s), 34, 36, 38, 39, 41, 43, 46,

47, 83, 95, 101, 102, 104meat, 45mechanical properties, 59, 60media, 2, 59, 61, 78medical, 21, 42, 46, 50medicine, vii, 1, 13, 46membranes, 21, 28, 34, 35, 63

memory, ix, 2, 89mercury, vii, 1metabolism, 18, 66metabolites, 76metal ion(s0, 5, 10, 15metal oxides, 66metals, 35, 46, 47methodology, 9, 20Methyl parathion, ix, 89, 90, 106, 110

Mexico, 75, 91mice, 24microbial cells, 98, 103, 111microelectronics, 3microorganism(s), vii, viii, 1, 58, 59, 65, 68,

72, 77, 98, 102, 110microspheres, 22, 23microstructure, 72mineral water, 35mineralization, 66

MIP, 4, 5, 6, 7, 8, 9, 12, 13, 14, 15, 17, 18,20, 21, 24, 25, 27

modelling, 5, 6, 17, 21, 22models, 41, 42, 48modifications, 21molar ratios, 6mold, 60, 62molecular biology, 98molecular imprinting technology, viii, 2, 19

molecular recognition, vii, 2, 3, 6, 20, 21,23, 27, 46, 50molecular weight, 17, 61, 65, 69




Index 119

molecules, 2, 4, 5, 6, 9, 10, 11, 12, 13, 14,15, 19, 25, 48, 63

monoclonal antibody, 83

monolayer, 15, 80monomers, 2, 3, 4, 5, 6, 7, 9, 22morphology, 6, 22multicellular organisms, viii, 58, 59multidimensional, 39, 41multivariate analysis, 32multivariate data analysis, 39muscle contraction, 92muscles, 93mutant, 100, 102

mutation, 25

N

Na+, 63nafion, 96, 97, 108nanocomposites, 28, 109nanomaterials, 14, 15, 78, 80nanoparticles, 9, 13, 23, 24, 25, 28, 29, 49,

64, 67, 96, 108nanostructured materials, 49nanotechnology, vii, 1, 3, 21, 27, 33nanotube, 18, 28, 109

National Academy of Sciences, 24nausea, 92nerve, 14, 18, 95, 108, 109, 110nervous system, 92neural network, 43

neurodegenerative disorders, vii, 1neurotransmitters, 28neutral, 5, 63, 64

NHS, 15nitrogen, 7nitrogen gas, 7noble metals, 34nuclear magnetic resonance, 6nucleation, 102nucleic acid, 10, 11, 17, 23, 46, 77

nucleophiles, 78nutrients, 65

O

oil, 45

oligomers, 65, 78olive oil, 45operations, 13optical fiber, 82, 103optical properties, 66optimization, 41, 45, 66organ, 108organelles, 81organic compounds, 65

organic solvents, 7, 91organism, 66, 68organophosphate, ix, 89, 90, 105, 108, 109,

110organs, 63osmium, 79oxidation, 36, 78, 101, 102oxidative stress, 67oxygen, 7, 14, 44, 65, 78, 99, 110

P

pain, 92 pairing, 61 pallor, 92PAN, 105

pancreas, 64 parallel, 41 paralysis, 93

Partial Least Squares (PLS), 39, 40, 44 partial least squares regression, 44 passivation, 78 pathogens, 24 pathways, 59 pattern recognition, viii, 31, 43PCA, 39, 40, 43, 44, 45PCR, 19, 39

peptides, 2, 3, 5, 20, 24, 77

permeability, 8 pesticide, ix, 46, 80, 83, 90, 91, 93, 94, 95,96, 104, 106, 107, 108, 111

pests, 90, 92




Index120

petroleum, 47, 49, 91 pH, 13, 14, 58, 60, 63, 64, 66, 81, 82, 97,

99, 101

pharmaceutical(s), viii, 2, 5, 32, 33, 42, 45,50 phenolic compounds, 44 phenylalanine, 16 phosphate, 47, 66, 92 phosphorus, 95 photosynthesis, 76 physics, 27 piezoelectric crystal, 14, 83 plants, 46, 47, 94

plasmid, 101 platform, 26, 68, 104 platinum, 28, 37 point-of-care tests, vii, 1 poison, 92 polar, 7 polarity, 7 polarization, 37 pollinators, 93

pollutants, 68 pollution, viii, 46, 58, 69 polycarbonate, 99, 101 polymer, vii, viii, 2, 3, 4, 6, 7, 8, 9, 10, 12,

17, 18, 19, 22, 24, 25, 26, 27, 28, 29, 44,49, 57, 59, 60, 61, 65, 78, 79

polymer chain(s), 24, 61 polymer films, 27, 49 polymer matrix, vii, 2, 6, 9 polymer structure, 8

polymerase, 19 polymerase chain reaction, 19 polymeric membranes, 35 polymerisation conditions, 4 polymerization, 6, 8, 12, 22 polymers, 2, 3, 4, 5, 6, 7, 10, 12, 13, 17, 18,

21, 22, 24, 26, 27, 28, 59, 61, 78 polyphenols, 44 polysaccharides, 61, 66

polystyrene, 100, 103 polyurethanes, 66 porosity, viii, 6, 57, 63, 65 portability, 33, 36

precipitation, 9, 22 preparation, 13, 17, 24, 33, 36, 94 principal component analysis, 38, 40, 43

principles, viii, 3, 31, 49 prior knowledge, 41 probiotic, 43 proliferation, 64, 70 promoter, 101 propagation, 14, 61 propane, 6 protection, viii, 58, 60, 66, 67, 73 proteins, 5, 8, 9, 12, 13, 14, 15, 17, 18, 20,

21, 25, 27, 32, 48, 61, 66

protons, 95, 101 prototypes, 32 psychology, 41 public concern, 76 purification, 21, 98, 102 purity, 91PVC, 35, 45

Q

qualifications, 15quality control, 43quantification, ix, 5, 10, 42, 75, 79, 80, 81,

82, 83, 95quantum dots, 108, 109quartz, 16, 17, 24, 25, 27quinones, 78

R

radial distribution, 63radiation, 81reaction rate, 77reactions, 12, 36, 63, 77, 81, 97, 100, 101,

102, 103, 104reactivity, 19reagents, 76

receptors, vii, 2, 3, 5, 13, 14, 15, 21, 22recognition, vii, 1, 2, 3, 4, 5, 6, 10, 11, 13,14, 16, 17, 19, 20, 21, 22, 23, 24, 27, 28,46, 50, 67, 77, 79, 81, 94, 96




Index 121

recombinant DNA, 98recombination, 38recovery, 10, 18

red wine, 44reflectivity, 14reflexes, 93refractive index, 14registry, 105regression, 36, 40regression model, 36reinforcement learning, 28reliability, 21, 59remediation, 70

repulsion, 63requirements, viii, 13, 33, 57, 59, 60, 61residues, ix, 61, 75, 76, 83, 106resistance, 17, 64, 80resonator, 16, 27respiratory failure, 93response, viii, 19, 25, 31, 32, 33, 34, 35, 39,

41, 42, 47, 49, 57, 82, 83, 95, 102reusability, 17, 19, 103, 104

rheology, 61risk, 8, 65RNA, vii, 1, 3, 10robotics, 49room temperature, 37runny nose, ix, 89, 92

S

SAB, 69saliva, 46salmonella, 23salts, 63SAXS, 61schizophrenia, 18security, 41selectivity, 5, 8, 12, 14, 21, 24, 25, 33, 34,

49, 76, 77, 79sensing, viii, 2, 5, 14, 16, 19, 20, 27, 31, 32,

33, 34, 35, 38, 41, 46, 47, 48, 49, 50, 65,67, 69, 81, 99, 101, 103

sensitivity, 8, 19, 26, 33, 34, 35, 44, 49, 76,78, 79, 80, 82, 101, 105

sensors, viii, 2, 11, 14, 15, 18, 20, 21, 25,26, 28, 31, 32, 33, 34, 35, 38, 39, 41, 42,43, 44, 45, 46, 48, 53, 77, 78, 79, 83

sequencing, 19serine, 92serum, 17, 18, 29, 67serum albumin, 29shape, vii, 2, 6, 11shear, 26sheep, 83showing, 47, 68signal transduction, 81signals, 32, 37, 45, 59, 79, 81

silane, 63silica, viii, 8, 9, 12, 24, 57, 59, 60, 62, 63,

64, 66, 67, 70, 72, 73, 96silicon, 44, 65silk, 64silver, 49simulation, 5Singapore, 91siRNA, 23

skin, 46sodium, 64, 91software, 32, 33, 38sol-gel, viii, 57, 58, 60, 62, 63, 68, 70, 72,

78, 81, 96solid phase, 8, 9, 21, 25solid surfaces, 78solution, 7, 8, 9, 10, 13, 32, 33, 34, 35, 37,

41, 42, 58, 59, 61, 62, 63, 64, 82, 94, 102solvents, 7, 12

soy bean, 44species, 33, 36, 37, 47, 60, 79, 97specific adsorption, 14, 19spectrophotometric method, 36spectroscopy, viii, 16, 19, 31, 34, 37, 38, 41,

45, 52, 79, 82speech, 93Spring, 55stability, viii, ix, 3, 6, 8, 13, 17, 21, 34, 57,

65, 78, 90, 101, 102, 103stable complexes, 6state, 35, 36stimulus, 59




Index122

stomach, 76, 92storage, 43, 78, 96, 101, 102, 103stress, 58, 60, 62, 63, 66

structure, 6, 11, 12, 20, 24, 61, 79, 90substrate(s), 2, 11, 13, 68, 79, 82, 95, 98,101, 103, 109

sugarcane, 76Sun, 22, 23surface area, 6surface chemistry, 15, 25surface tension, 65sweat, 46swelling, viii, 57, 63, 65

Switzerland, 70, 109synthesis, viii, 4, 5, 6, 9, 12, 17, 20, 21, 22,

57, 58, 60, 62, 65, 66, 67, 68, 72synthetic polymers, 66

T

target, vii, 2, 3, 4, 5, 6, 10, 11, 12, 15, 18,24, 34, 61, 63, 103

targets detection, vii, 1techniques, 3, 5, 7, 11, 14, 19, 20, 25, 33,

37, 39, 40, 41, 42, 49, 72, 82, 83, 98, 103technologies, vii, 1, 32, 48, 58technology, vii, viii, ix, 1, 2, 3, 11, 13, 18,

19, 21, 34, 49, 57, 58, 75, 83, 98temperature, 8, 13, 34, 35, 58, 61, 94template molecules, 2, 20TEOS, 64, 72

testing, 48tetraethoxysilane, 66texture, 63therapeutic agents, 11therapeutics, vii, 1, 23therapy, 23thermodynamic equilibrium, 3thrombin, 23tobacco, 59toluene, 7

toxic materials, vii, 1toxic substances, 46toxicity, ix, 58, 68, 75toxicology, 106

toxin, 47TP53, 25transducer, 14, 33, 34, 67, 77, 82, 94, 95,

101, 102, 103, 104, 105transduction, 36, 65transistor, 44transition metal, 61transparency, 65transport, 8, 60, 62, 65, 66, 69, 102treatment, ix, 9, 47, 75, 94triggers, 80tumor(s), 23, 76tumor growth, 23

tyramine, 18, 28

U

UK, 1, 55United Nations, 106United States (USA), ix, 24, 53, 75, 76, 84,

87, 89, 90, 93, 105, 106universal gas constant, 35

urea, 46uric acid, 18urine, 22, 46US Department of Health and Human

Services, 105UV, 8, 33, 42, 67UV-irradiation, 67

V

variables, 36, 39, 40variations, 4, 12, 81, 83varieties, 44, 47vector, 45vegetables, 92, 93viruses, 3, 5, 8, 9, 12, 13, 14, 17, 18, 19, 20,

28viscosity, 34, 61

vision, 93visualization, 39, 41volatility, 49vomiting, 92




Index 123

W

Washington, 84, 105

wastewater, 47, 94water, viii, ix, 9, 17, 21, 32, 39, 45, 46, 47,

49, 63, 64, 68, 70, 76, 78, 81, 84, 89, 91,94, 107

water quality, viii, 32, 47, 84water resources, ix, 89, 94weakness, 93weight loss, 76wells, 100, 103, 104

World Health Organization (WHO), ix, 76,84, 89, 92, 93, 106

Y

yeast, 59, 63yield, 41

Z

zirconium, 66

2015 nova advances in biosensors ch 3.pdf

Documents