Pathogenic Bacteria

Biosensors & Bioelectronics 14 (1999) 599–624

Review

Biosensors for detection of pathogenic bacteria

Dmitri Ivnitski, Ihab Abdel-Hamid, Plamen Atanasov, Ebtisam Wilkins *Department of Chemical and Nuclear Engineering, Uni6ersity of New Mexico, Albuquerque, NM 87131, USA

Received 23 November 1998; received in revised form 1 June 1999; accepted 19 July 1999

Abstract

This paper presents an overview of different physicochemical instrumental techniques for direct and indirect identification ofbacteria such as: infrared and fluorescence spectroscopy, flow cytometry, chromatography and chemiluminescence techniques asa basis for biosensor construction. A discussion of publications dealing with emerging biosensors for bacterial detection ispresented. The review presents recent advances in the development of alternative enzyme- and immunosensors for detection ofpathogenic bacteria in a variety of fields (e.g. clinical diagnostics, food analysis and environmental monitoring). Depending on thebiological element employed: enzyme; nucleic acid and antibody based biosensors are discussed. Depending on the basictransducer principles, recent advances in biosensing technologies that use electrochemical, piezoelectric, optical, acoustic andthermal biosensors for detection of pathogenic bacteria are overviewed. Special attention is paid to methods for improving theanalytical parameters of biosensors including sensitivity and analysis time as well as automation of assay procedures. Recentdevelopments in immunofiltration, flow-injection and flow-through biosensors for bacterial detection are overviewed from thesystem’s engineering point of view. Future directions for biosensor development and problems related to the commercializationof bacterial biosensors are discussed in the final part of this review. © 1999 Elsevier Science S.A. All rights reserved.

Keywords: Bacteria; Biosensor; Optical; Electrochemical; Piezoelectric; Genosensors; Artificial nose

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1. Introduction

1.1. Bacteria and microbial diseases

Bacteria, viruses and other microorganisms are foundwidely throughout nature and the environment. Bacte-rial pathogens are distributed in soil, marine and estu-arine waters, the intestinal tract of animals, or watercontaminated with fecal matter. An average personcarries more than 150 kinds of bacteria which existboth inside and outside the body (Madigan et al.,1997). The majority of microorganisms carry out essen-tial activities in nature, and many are closely associatedwith plants or animals in beneficial relations. However,certain potentially harmful microorganisms can haveprofound effects on animals and humans and may be

the cause of different infectious diseases (Table 1).Bacteria can spread easily and rapidly requiring food,moisture and a favorable temperature. Worldwide, in-fectious diseases account for nearly 40% of the total 50million annual estimated deaths. Microbial diseasesconstitute the major cause of death in many developingcountries of the world. From a military point of view,there are a number of pathogenic bacteria which can beconsidered possible biological warfare agents, some ofwhich are listed in Table 1 (Compton, 1987; MalcolmDando, 1994). These microorganisms are resistant toenvironmental conditions, most of the human popula-tion is completely susceptible, and the diseases theycause are severe with a high fatality rate. A largequantity of these fatal organisms could easily be grownand preserved for several years.

A growing number of bacterial pathogens have beenidentified as important food- and waterborne pathogens(Swaminathan and Feng, 1994; McNamara, 1998;Slutsker et al., 1998). Estimates of the yearly incidence

* Corresponding author. Tel.: +1-505-2772928; fax: +1-505-2775433.

E-mail address: [email protected] (E. Wilkins)

0956-5663/99/$ - see front matter © 1999 Elsevier Science S.A. All rights reserved.

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D. I6nitski et al. / Biosensors & Bioelectronics 14 (1999) 599–624600

of foodborne illness vary widely from several millioncases to 81 million cases in the USA, with bacterialfoodborne outbreaks accounting for 91% of the totaloutbreaks (Beran et al., 1991; Potter et al., 1997). Infact, the incidence of human diseases caused by food-borne pathogens, such as Salmonella sp., Escherichiacoli, Staphylococcus aureus, Campylobacter jejuni,Campylobacter coli and Bacillus cereus has not de-creased (Swaminathan and Feng, 1994). For example,E. coli is a typical inhabitant of the human intestinaltract and can also be a causative agent of intestinal andextra-intestinal infections. E. coli O157:H7 is a rarestrain of E. coli that is considered to be one of the mostdangerous foodborne pathogens (Griffin and Tauxe,1991; Buchanan and Doly, 1997). This O157:H7 strainproduces large quantities of a potent toxin, in the liningof the intestine, and causes severe damage resulting inhemorrhagic colitis or hemolytic uremic syndromewhich may lead to death, especially in children (Roweet al., 1991). E. coli can easily contaminate ground beef,raw milk and chicken, therefore, careful control of thispathogen is extremely important especially in the fieldsof food production. Salmonella is another example of adangerous foodborne pathogen as all species andstrains of Salmonella may be presumed pathogenic forman (Jay, 1992). Salmonellosis is an infectious diseasethat continues to plague human populations in bothdeveloped and developing countries. Outbreak investi-gations have shown that between 1973 and 1987, 59%

of salmonellosis outbreaks could be traced to a specificfood vehicle (Tietjen and Fung, 1995). Current prac-tices for preventing microbial diseases rely upon carefulcontrol of various kinds of pathogenic bacteria in clini-cal medicine, food safety and environmental monitor-ing. Approximately 5 million analytical tests — forSalmonella only — are performed annually in theUnited States (Feng, 1992; Meng and Doyle, 1998).

The effective testing of bacteria requires methods ofanalysis that meet a number of challenging criteria.Time and sensitivity of analysis are the most importantlimitations related to the usefulness of microbiologicaltesting. Bacterial detection methods have to be rapidand very sensitive since the presence of even a singlepathogenic organism in the body or food may be aninfectious dose. Extremely selective detection methodol-ogy is required because low numbers of pathogenicbacteria are often present in a complex biological envi-ronment along with many other non-pathogenic organ-isms. For example, the infectious dosage of a pathogensuch as E. coli O157:H7 or Salmonella is as low as 10cells and the existing coliform standard for E. coli inwater is 4 cells/100 ml (Federal Register, 1990, 1991;Greenberg et al., 1992).

1.2. Con6entional methods for detection of bacteria

Conventional bacterial identification methods usuallyinclude a morphological evaluation of the microorgan-

Table 1Pathogenic bacteria, diseases they cause, toxins they secrete, infection sources and mortality rates for humans infected by microorganisms usedas biological warfare agent (BWA)a

DiseaseBacteria Infection sourcesToxin Mortality when used asBWA

Milk or meat, BWA FatalEdema factorAnthraxBacillus anthracisBrucellosis –Brucella melitensis Milk or meat, BWA LowDiarrhea dysentry –Campylobacter jejuni Dairy products, meats, mushrooms –

–FoodNeurotoxinClostridium botulinum BotulismBWA–Pneumonia LowCoxiella burnetti

Diphtheria Diphtheria toxinCorynebacterium diphtheriae BWA Low–Gastroenteritis Enterotoxin Meats, fish, milk, rice, vegetablesEscherichia coli

BWATularemia Low–Francisella (Pasteurella) tu-larensis

BWA– HighTuberculosisMycobacterium tuberculosis– BWA HighRickettsia rickettsi Rocky Mountain-spot-

ted fever–Salmonella paratyphi Paratyphoid Fecal contamination, eggs, milk,–

meatsTyphoid fever BWASalmonella typhi High–Bacillary dysentry –NeurotoxinShigella dysenteriae Fecal contaminationPneumonia EnterotoxinStaphylococcus aureus Human carriers –

Streptococcus pneumoniae Pneumococcal pneu- –Erythrogenic Human carrierstoxinmoni

–Infected exudate or blood–SyphilisTreponema pallidumCholera EnterotoxinVibro cholerae Fecal contamination HighBubonic plague Plague toxinYersinia pestis BWA Fatal

a BWA, biological warfare agent.

D. I6nitski et al. / Biosensors & Bioelectronics 14 (1999) 599–624 601

Fig. 1. Flow cytometry: automated single cell detection using opticsand fluorescent markers. Adapted with permission from Salzman etal. (1990).

1.3. Bacterial identification using instrumental methods

Common methods used for identification of bacteriaare: counting the cells by microscope or by flow cy-tometry; measuring physical parameters by piezocrys-tals, impedimetry, redox reactions, optical methods,calorimetry, ultrasound techniques and detecting cellu-lar compounds such as ATP (by bioluminescence),DNA, protein and lipid derivatives (by biochemicalmethods), radioactive isotopes (by radiometry) (Nelson,1985; Ramsay and Turner, 1988; Ding et al., 1993;Rodrigues and Kroll, 1990; Lloyd, 1993; Sharpe, 1994;Swaminathan and Feng, 1994; Hobson et al., 1996;Wang et al., 1997a,b,c; Zhai et al., 1997; Zhu andWang, 1997; Frat Amico et al., 1998). Among these theprimary physico-chemical methods of bacterial identifi-cation are those which involve the detection of somenaturally occurring component of the bacterium. Forexample, the Microbial Identification System (Newark,DE) uses gas chromatography to produce a fatty acidprofile for detection and identification of microorgan-isms (Swaminathan and Feng, 1994).

Another method for bacterial identification is basedon the use of infrared (IR) spectroscopy (Rossi andWarner, 1985). Bacteria are smeared onto an IR celland an IR absorbence spectra is acquired using conven-tional instrumentation. However, the main limitation ofIR spectroscopy is that it involves an evaluation of thechemical composition of bacteria which is especiallysimilar at the molecular level. Because of the inherentlimitations of this technique, reports of its applicationto bacterial detection became less frequent from 1960onwards.

In contrast to the IR identification methods, flowcytometry does not generate data from all the individ-ual molecular components of the microorganism. Flowcytometry may be considered as a form of automatedfluorescence microscopy in which, instead of a samplebeing fixed to a slide, it is injected into a fluid whichpasses through a sensing region of flow cell (Fig. 1). Inthe flow cytometer, cells are carried by laminar flow ofwater through a focus of light, the wavelength of whichmatches (as closely as possible) the absorption spectrumof the dye with which the cells have been stained. Onpassing through the focus, each cell emits a pulse offluorescence and the scattered light is collected by lensesand directed onto sensitive detectors (photomultipliertubes). These detectors transform the light pulses intoan equivalent electrical signal. The light scattering ofthe cells gives information on their size, shape andstructure, cell mass and bacterial growth (Salzman etal., 1990; Pinder et al., 1990; Lloyd, 1993). Flow cy-tometry is a highly effective means for rapid analysis ofindividual cells at rates of up to 1000 cells per second(Melamed et al., 1990; Lloyd, 1993; McClelland andPinder, 1994). By labeling the cells with specific

ism as well as tests for the organism’s ability to grow invarious media under a variety of conditions. Althoughstandard microbiological techniques allow the detectionof single bacteria, amplification of the signal is requiredthrough growth of a single cell into a colony. Thisprocess is relatively time-consuming. Traditional meth-ods for enumerating coliform bacteria (colony counts)are often slow (up to 72 h are required to obtainconfirmed results) and may vary in time since thedevelopment of a colony containing 106 organisms willtake between 18 and 24 h. Generally, no single testprovides a definitive identification of an unknown bac-terium. Traditional methods for the detection of bacte-ria involve following basic steps: preenrichment,selective enrichment, biochemical screening and sero-logical confirmation (Helrich, 1990; Kaspar andTartera, 1990; Tietjen and Fung, 1995; Hobson et al.,1996). Hence, a complex series of tests is often requiredbefore any identification can be confirmed. The resultsof such tests are often difficult to interpret and notavailable on the time scale desired in the clinical labora-tory. Some new technologies are very sensitive butanalysis time is lengthy. For example, the polymerasechain reaction (PCR) can be used to amplify smallquantities of genetic material to determine the presenceof bacteria. The PCR method is extremely sensitive, butrequires pure samples and hours of processing andexpertise in molecular biology (Meng et al., 1996; Sper-veslage et al., 1996). In response to this problem, con-siderable effort is now directed towards thedevelopment of methods that can rapidly detect lowconcentrations of pathogens in water, food and clinicalsamples. For this purpose, a number of instrumentshave been developed using various principles of detec-tion, e.g. chromatography, infrared or fluorescencespectroscopy, bioluminescence, flow cytometry, im-pedimetry and many others (Nelson, 1985; Bird et al.,1989; Lloyd, 1993; Fenselau, 1994; Van Emon et al.,1995; Wyatt, 1995; Hobson, et al., 1996; Basile et al.,1998; Perez et al., 1998).


fluorochromes or fluorescent conjugates that bind withhigh specificity to one particular cellular constituent, itis possible to measure a wide variety of cell con-stituents, such as proteins, carbohydrates, DNA, RNAand enzymes. Flow cytometry is conveniently used as abacterial counter in clinical, environmental, and indus-trial microbiology (Boye and Lobner-Olesen, 1991;Steen et al., 1990). The advantage of flow cytometry liesin its ability to make rapid, quantitative measurementsof multiple parameters of each cell within a largenumber of cells; this makes it possible to define theproperties of the overall population and of componentsubpopulations. However, flow cytometry has beenused almost exclusively for measurements of mam-malian, or at least eukaryotic cells, while they haveremained a rarity in microbiology, including bacteriol-ogy. The lack of progress in microbiological applica-tions of flow cytometry was the result of severalproblems encountered when analyzing bacteria. Thesmall size of bacteria and the low number of DNAmolecules present to be stained (typically three ordersof magnitude less than a mammalian cell) requiredinstruments with high sensitivity and sophistication.The main experimental difficulty in analyzing bacteriausing flow cytometry is that many of their biologicalcharacteristics (including size, shape and DNA content)vary depending upon the growth conditions used, orthe source from which the organism were obtained(Allman et al., 1993). Therefore, strict reproducibility ofconditions is required in order to produce consistentdata. Finally, the capital cost involved in flow cytome-try analyses is high which further restricts its use.

2. Biosensors for microorganisms

Currently most microbiological tests are centralizedin large stationary laboratories because complex instru-mentation and highly qualified technical staff are re-quired. In recent years, however, intensive research hasbeen undertaken to decentralize such tests so that theycan be performed virtually anywhere and under fieldconditions (Griffiths and Hall, 1993; Owen, 1994).Hence the development of portable, rapid and sensitivebiosensor technology with immediate ‘on-the-spot’ in-terpretation of results are well suited for this purpose.Areas for which biosensors show particular promise areclinical diagnostics, food analysis, bioprocess and envi-ronmental monitoring. The importance of biosensorsresults from their high specificity and sensitivity, whichallow the detection of a broad spectrum of analytes incomplex sample matrices (blood, serum, urine or food)with minimum sample pretreatment (Turner et al.,1986; Schmid and Scheller, 1989; Hall, 1990; Luong etal., 1991; Edelman and Wang, 1992; Feng, 1992; Al-varez-Icaza and Bilitewski, 1993; Deshpande and

Rocco, 1994; Rogers et al., 1995; Morgan et al., 1996;Blum, 1997; Kress-Rogers, 1997).

Biosensors for bacterial detection generally involve abiological recognition component such as receptors,nucleic acids, or antibodies in intimate contact with anappropriate transducer. Depending on the method ofsignal transduction, biosensors may be divided intofour basic groups: optical, mass, electrochemical, andthermal sensors (Goepel, 1991; Sethi, 1994; Goepel andHeiduschka, 1995). In addition, biosensors can beclassified into two broad categories: sensors for directdetection of the target analyte and sensors with indirect(labeled) detection. Direct detection biosensors are de-signed in such a way that the biospecific reaction isdirectly determined in real time by measuring the phys-ical changes induced by the complex formation. Indi-rect detection biosensors are those in which apreliminary biochemical reaction takes place and theproducts of that reaction are then detected by a sensor.Finally, biosensors for bacteria can also be divided intosensors operating in batch (intermittent) and continu-ous (monitoring) mode.

This part of the review has been divided into sixsections: biosensors based on direct (label-free) detec-tion of bacteria, biosensors based on monitoring bacte-rial metabolism, biosensors based on detection ofenzyme labels, flow-injection biosensors, genosensorsand the emerging artifical nose. A brief summary indi-cating some of the biosensors covered in this review ispresented in Table 2.

2.1. Direct (label-free) detection of bacteria

Several techniques have been described that allowdirect, label-free monitoring of cells at solid-liquid in-terfaces (Ebato et al., 1994; Morgan et al., 1996; Piehleret al., 1996; Medina, et al., 1997; Ghindilis et al., 1998;Frat Amico et al., 1998). These techniques are based ondirect measurement of a physical phenomena occurringduring the biochemical reactions on a transducer sur-face. Signal parameters such as changes in pH, oxygenconsumption, ion concentrations, potential difference,current, resistance, or optical properties can be mea-sured by electrochemical or optical transducers.

2.1.1. Optical biosensorsOptical transducers are particularly attractive for ap-

plication to direct (label-free) detection of bacteria.These sensors are able to detect minute changes in therefractive index or thickness which occur when cellsbind to receptors immobilized on the transducer sur-face. Several optical techniques have been reported fordetection of bacterial pathogens including: monomodedielectric waveguides (Sloper et al., 1990; Lukosz et al.,1991), surface plasmon resonance (Pollard-Knight etal., 1990; Karlsson et al., 1991; Bringham-Burke et al.,


Table 2Features of bacterial sensorsa

Biosensor typeBacteria type Assay format LOD (cells/ml) Reference

Optical biosensorsStaphylococcus aureus RM Direct 8×106 Watts et al., 1994

Direct 5×108 cfu/mlEWI Schneider et al., 1997Salmonella typhmuriumIndirect 105Escherichia coli O157:H7 Pyle et al., 1995FAIndirect 103IMAS Yu and Bruno, 1996Salmonella typhmurium

Piezoelectric biosensorsDirect 106QCM Muramatsu et al., 1986Candida albicansDirect 106Escherichia coli Plomer et al., 1992QCMDirect 106QCM Koenig and Gratzel, 1993a,bSalmonellaDirect 102 Bao et al., 1996Phylococcus epidermidis QCM

Electrical impedance biosensorsDirect 106Staphylococcus aureus Silley and Forsythe, 1996Direct 3×102BAWI Deng et al., 1996Proteus 6ulgaris

Potentiometric immunosensorsIndirect 103LAPS Libby and Wada, 1989Neisseria meningitidis

LAPSBrucella militensis 6×103 Lee et al., 1993a,bLAPSFrancisella tularensis 3×103 Thompson and Lee, 1992

Amperometric immunosensorsEscherichia coli Indirect 5×102 Nakamura et al., 1991

1–5 cfu/g Brooks et al., 1992Salmonella8×103 Brewster et al., 1996Salmonella50 Abdel-Hamid et al., 1999a,bEscherichia coli O157:H7

a RM, resonant mirror; EWI, evanescent wave interferometer; FA, flourescent labeled antibody method; IMAS, immuno-magnetic assay system;LAPS, light-addressable potentiometric sensor array; LOD, limit of detection; QCM, quartz crystal microbalance; BAWI, bulk acoustic waveimpedance sensor.

1992; Medina et al., 1997; Frat Amico et al., 1998),ellipsometry (Nakamura et al., 1991; Swenson, 1993),the resonant mirror (Watts et al., 1994) and the inter-ferometer (Schneider et al., 1997). Swenson (1993) uti-lized an ellipsometric technique for the development ofa label-free instrument (BDS-240) for detection of bac-teria. The main component of the BDS-240 system is anoptical unit that consists of an LED/filter excitationsource and a photodiode detection system. Metaboliz-ing bacteria would result in an increased CO2 concen-tration which in turn affects an emulsion of an aqueouscolorimetric pH indicator, thus modulating the fluores-cence detected at the photodiode. Selectivity of thissensor depends on the selectivity of the culture mediumbeing used to grow the bacteria. This system was usedfor positive/negative non-quantitative tests of both aer-obic and anaerobic bacteria.

The resonant mirror is another technique that maybeused for direct detection of bacteria (Cush et al., 1993).It is based on the use of a thin layer (�100 nm) of ahigh refractive index dielectric material and a thickerlayer (�1 mm) of low refractive index material. Atcertain angles of incidence, light maybe coupled intothe high refractive index layer where it undergoes multi-ple total internal reflections at the top interface, allow-ing an element of light, the evanescent wave, topenetrate to the sample overlayer. On reflection, the

light undergoes a phase change, and by monitoring theangle at which this occurs, it is possible to detectchanges within the evanescent field. Watts et al. (1994)used a resonant mirror biosensor for detecting S. aureusin the range of 8×106–8×107 cells/ml and a detectiontime of 5 min.

Schneider et al. (1997) described an evanescent waveinterferometer that uses a single planar wave of polar-ized light (Fig. 2). Light from a diode laser source iscoupled into the waveguiding film as a single broadbeam. The light then passes through multiple sensing

Fig. 2. Schematic view of the Hartman interferometer, showing topview (left) and side view (right). Adapted with permission fromSchneider et al. (1997).


regions on the surface of the chip. An array of inte-grated optical elements is used to combine light passingthrough adjacent regions which have been function-alised with specific or non-specific receptors. Using thistechnique it was possible to directly detect Salmonellatyphmurium in the range of 5×108 to 5×1010 CFU/mlwith a detection time of 5 min. The main advantage ofthe above techniques is their short detection time, how-ever this is compromised by their severe lack ofsensitivity.

Direct fluorescence techniques can also be used forbacterial identification. Direct methods are those inwhich the natural fluorescent components of the bac-terium are examined. All bacteria examined by directmethods must produce or contain some suitablefluorophore. An example of a direct fluorescencemethod is the identification of Bacteroides species bythe fluorescence of cells held under an ultraviolet lamp(Slots and Reynolds, 1982). Some species of Bacteroideswere found not to fluoresce, whereas others emittedfluorescence of characteristic colors. Generally a mix-ture of fluorescent metabolic products is detected. Inmany schemes used in the clinical environment, fluores-cence is detected visually while the sample is held undera UV lamp. This approach has the advantages ofsimplicity, low cost, and rapidity. However, there is atleast one major limitation to the utility of direct meth-ods. That is, only those bacteria which contain orproduce some fluorescent pigment may be examined.Therefore, the utility of this approach is very limited(Rossi and Warner, 1985). Glazier and Weetall (1994)described a method for direct detection of E. coli usingsilver membrane filters as the bacteria collecting filters.Using this method they were able to detect 1.7×105

cells/ml with an overall analysis time of 15 min.

2.1.2. Bioluminescence sensorsRecent advances in bioanalytical sensors have led to

the utilization of the ability of certain enzymes to emitphotons as a byproduct of their reactions. This phe-nomenon is known as bioluminescence and maybe usedto detect the presence and physiological condition ofcells. The potential applications of bioluminescence forbacterial detection were initiated by the development ofluciferase reporter phages by (Ulitzur and Kuhn, 1987).In their system (Ulitzur and Kuhn, 1987) introducedthe genes encoding luciferase into the genome of abacterial virus (bacteriophage). If this virus infects ahost bacteria, a bioluminescent phenotype can be con-ferred to a previously non-bioluminescent bacteria. Bio-luminescence systems have been used for detection of awide range of microorganisms (Prosser, 1994; Prosser etal., 1996; Ramanathan et al., 1998). Folley-Thomas etal. (1995) used the TM4 bacteriophage to detect My-cobacterium a6uim and Mycobacterium paratuberculosis,however, a concentration of 104 cells was required to

produce a detectable luciferase signal and the responsedeclined after 2 h. Sarkis et al. (1995) used the L5bacteriophage to detect Mycobacterium segmantis. Us-ing this bacteriophage it was possible to detect onehundred cells of M. segmantis in a few hours and 10cells in two days. Using the same approach, Salmonellaspp. and Listeria were also detected (Turpin et al., 1993;Chen and Griffiths, 1996). Recently, the use of theA511 bacteriophage led to the construction of a polyva-lent system for the detection of a wide range of Listeriastrains (Loessner et al., 1996). Using this bacteriophage,it was possible to detect one viable cell/gram of Listeriamonocytogenes within 24 h.

A sensitive and specific method has been developedfor the specific detection of Salmonella newport and E.coli (Blasco et al., 1998). In this method, bacteriophageswere used to provide specific lysis of the bacteria andcell content release was measured by ATP biolumines-cence. Increased sensitivity was obtained by focusing onthe bacteria’s adenylate kinase as the cell marker in-stead of ATP. Light emission was proportional to cellnumbers over three orders of magnitude, and 103 cellswere readily detectable in a 0.1 ml sample.

The bioluminescence approach is a new attractiveapproach due to its extremely high specificity and theinherent ability to distinguish viable from non viablecells. However, the main disadvantages is the relativelylong assay time as well as its lack of sensitivity thatbecomes apparent when low numbers of bacteria are tobe detected.

2.1.3. Piezoelectric biosensorsPiezoelectric (PZ) biosensor systems are very attrac-

tive systems which, in principle, may be used for directlabel-free detection of bacteria (He et al., 1994;Harteveld et al., 1997; Schmitt et al., 1997; Bunde et al.,1998). This technology offers a real-time output, sim-plicity of use and cost effectiveness. In the last decademany reports have been published using piezoelectricsensors for a wide range of applications in the foodindustry, environmental monitoring, clinical diagnosticsand biotechnology (Suleiman and Guilbault, 1994;Marco and Barcelo, 1996). The theoretical basis ofpiezoelectricity and the practical application of a PZsensors for the determination of various kinds of mi-croorganisms were illustrated in a series of reports(Plomer et al., 1992; Koenig and Gratzel, 1993a,b;Suleiman and Guilbault, 1994; Le et al., 1995; Bao etal., 1996; Hobson et al., 1996). The general idea isbased on coating the surface of the PZ sensor with aselectively binding substance, for example, antibodies tobacteria, and then placing it in a solution containingbacteria. The bacteria will bind to the antibodies andthe mass of the crystal will increase while the resonancefrequency of oscillation will decrease proportionally.PZ immunosensors were developed for Vibrio cholerae


(Carter et al., 1995), Candida albicans (Muramatsu etal., 1986), Salmonella typhimurium (Prusak-Sochaczewski et al., 1990), L. monocytogenes (Jacobs etal., 1995) and members of the Enterobacteriaceae family(Plomer et al., 1992). In the immunogravimetric micro-bial assay (Muramatsu et al., 1986), a PZ crystal coatedwith anti-C. albicans antibody was used for the detec-tion of C. albicans concentrations in the range of106–108 cells/ml. The sensor showed no response toother yeast species, and frequency shifts due to nonspe-cific adsorption were not significant.

A technique using a quartz crystal microbalance(QCM) sensor coated with a thin culture medium filmwas also developed and applied to determine Staphylo-coccus epidermidis in the range of 102–107 cells/ml (Baoet al., 1996). However, the PZ membrane was notstrong enough to hold out against several autoclavings.(Prusak-Sochaczewski et al., 1990) have developed abiosensor based on a QCM for the detection of S.typhimurium. The antibody was selective for the com-mon structural antigen present in a large number ofSalmonella species. An identical crystal without Ab wasused as a reference to correct for temperature fluctua-tions and other interferences. The sensor response to S.typhimurium in a microbial suspension was linear in theconcentration range 105–109 cells/ml. The time requiredto obtain a constant response depended on the cellconcentration. An assay time of 5 h was required fordetecting a concentration of 105 cells/ml of S. ty-phimurium. The coated crystal was stable for six toseven assays. For repeated use, the bound bacterianeeded was removed from the crystal by washing with8 M urea. (Koenig and Gratzel, 1993a,b) have used asimilar device to detect Salmonella, E. coli, Yersiniapestis and Shigella dysenteriae. The frequency shiftswere measured after incubating the sensor surface withthe bacterial sample for up to 45 min, washing withPBS and then air drying. The response of the sensor tobacteria was linear within the range of 106–108 cells.According to the authors, the sensor could be reused atleast 12 times. The best method for regenerating theantibody surface of the sensor is performed using com-petition with antigen-specific synthetic peptides. Re-cently, antigen monolayers assembled onto Au surfacesassociated with a quartz crystal were used for themicrogravimetric QCM detection of Chlamydia tra-chomatis in urine samples (Ben-Dov et al., 1997). Thesensing interfaces consist of a primary cystamine mono-layer assembled onto Au electrodes associated with thequartz crystal. The monolayer is further modified withgoat IgG-antimouse IgG Fc-specific Ab that act assublayers for the association of the sensor-active anti-C.trachomatis. A QCM (EG and G Model QCA 917)interfaced to a computer was used in the studies.

A PZ crystal immunosensor has been developed forthe detection of enterobacteria in drinking water using

antibodies against the enterobacterial common antigen(ECA) (Plomer, et al., 1992). Anti-ECA antibodycoated crystals were dipped for 40 min into a 25-mlsolution of the bacterial suspensions to be measured.Similarly, a reference crystal coated with antiatrazineantibody was incubated in the same solution. The crys-tals were then washed and dried and the resonantfrequency was measured and plotted vs the concentra-tion of E.coli K12. A response is observed for 106–109

cells/ml of E. coli K12. The reproducibility of themeasurements was 30% at a concentration of 106 cells/ml. Repeated usage of the coated crystal by removingthe bound bacteria with urea or glycine-HCl buffer wasnot possible. Not only was the bacteria removed, butpart of the antibody was removed, making reuseimpossible.

A flow-injection system, based on a PZ biosensor wasalso developed for detection of S. typhimurium (Ye etal., 1997). The anti-Salmonella sp. antibody was immo-bilized onto a gold coated quartz crystal surfacethrough a polyethylenimine-glutaraldehyde (PEG) tech-nique and dighiobis-succinimidylprpionate (DSP) cou-pling. The biosensor had responses of 23–47 Hz in 25min when the PEG immobilization technique was em-ployed, with R\0.94 for S. typhimurium concentra-tions of 5.3×105 to 1.2×109 CFU/ml.

A disadvantage of PZ sensors is the relatively longincubation time of the bacteria, the numerous washingand drying steps, and the problem of regeneration ofthe crystal surface. This last problem may not be im-portant if small crystals can be manufactured at lowcost so that disposable transducers are economicallyfeasible. Possible limitations of this technology includealso the lack of specificity, sensitivity and interferencesfrom the liquid media where the analysis takes place.

2.1.4. Electrical impedance biosensorsMicrobial metabolism usually results in an increase

in both conductance and capacitance, causing a de-crease in impedance. Therefore, the concepts ofimpedance, conductance, capacitance and resistance areonly different ways of monitoring the test system andare all inter-related (Silley and Forsythe, 1996; Milneret al., 1998). The relationship between impedance (Z),resistance (R), capacitance (C), and frequency ( f ) for aresistor and a capacitor in series is expressed as follows(Hadley and Yajko, 1985; Bataillard et al., 1988): Z2=R2+1/(2pfC)2. Impedance usually is measured by abridge circuit. Often a reference module is included tomeasure and exclude non specific changes in the testmodule. The reference module serves as a control fortemperature changes, evaporation, changes in amountsof dissolved gases, and degradation of culture mediumduring incubation.

The impedance method was accepted by the Associa-tion of Official Analytical Chemists, Intl. (AOAC) as a


first action method (Gibson et al., 1992). This methodis well suited for detection of bacteria in clinical speci-mens, to monitor quality and detect specific foodpathogens, also for industrial microbial process control,and for sanitation microbiology (Swaminathan andFeng, 1994; Silley and Forsythe, 1996). This techniquehas been used for estimating microbial biomass (Harrisand Kell, 1985), for detecting microbial metabolism(Dezenclos et al., 1994; Palmqvist et al., 1994) and fordetecting the concentration and physiological state ofbacteria (DeSilva et al., 1995; Dupont et al., 1996;Ehret et al., 1997). Current instruments usually detectactive metabolizing bacteria when 106–107 bacteria permilliliter are present in the culture media. Applied tobacterial detection in urine, concentrations of 105 cells/ml can be detected using the impedance technique witha detection time of 2.5 h. A very important parameterin cell culture is the number of viable cells. Viable cellsare commonly measured microscopically after suspend-ing the cells in a dye such as Trypan Blue. A newbiosensor for real-time monitoring of concentration,growth and physiological state of cells in culture mediawas proposed by (Ehret et al., 1997). This biosensor isbased on impedance measurement of adherently grow-ing cells on interdigitated electrode structures. Cell den-sity, growth and long-term behavior of cells on theelectrodes change the impedance of the biosensor. Themain effect of cells on the sensor signal is due to theinsulating property of the cell membrane. The presenceof intact cell membranes on the electrodes and theirdistance to the electrodes determine the current flowand thus the sensor signal. The biosensor providesinformation about spreading, attachment and morphol-ogy of cultured cells.

Several analytical devices based on the use ofimpedance technology have been proposed for detec-tion of bacteria, such as Bactometer and the MalthusM1000s (Swaminathan and Feng, 1994; Silley andForsythe, 1996). Most impedance analysis is completedin 20–25 h. Pless et al. (1994) investigated the detectionof Salmonella using the impedance method in 250 foodsamples. Food samples were pre-enriched 14–16 h at37°C in peptone water. A reusable Bulk Acoustic Wave(BAW)–Impedance Sensor has been developed forcontinuous detection of growth and numbers ofProteus 6ulgaris on the surface of a solid medium underordinary conditions (Deng et al., 1996, 1997). Theproposed sensor relies on the fact that bacteria cantransform uncharged or weakly charged substrates intohighly charged end products causing an alteration inthe conductance of the medium. The sensor is simpleand rapid and bacteria can be detected using the pro-posed method in the range of 3.4°102–6.7×106 cells/ml.

2.2. Indirect detection of bacteria

2.2.1. Fluorescence labeled biosensorsMicroorganisms are immunogenic due to the pres-

ence of proteins and polysaccharides in their outercoats. This permits the development of immunoassaytechniques for bacterial detection. In fluorescent im-munoassays (FIA), fluorochrome molecules are used tolabel immunoglobulins. The fluorochrome absorbsshort-wavelength light and then emits light at a higherwavelength which can be detected using fluorescentmicroscopy. Fluorescein isothiocyanate and rhodamineisothiocyanate-bovin serum albumin are the most com-mon fluorochromes used to tag antibodies. Direct andindirect detection methods are used to test bacteria-con-taining samples (Colwell et al., 1985; Donnelly andBaigent, 1986; Brayton et al., 1987; Kaspar andTartera, 1990). Food samples tested by FIA are typi-cally from enrichment cultures because the number ofbacteria in the original sample is insufficient to bedirectly detected and due to the interference caused byfood particulates producing background fluorescence.Water samples have been analyzed directly by concen-trating bacteria using membrane filtration. Polycarbon-ate filters are commonly used in this procedure (Hobbieet al., 1977; Kaspar and Tartera, 1990). Identificationof bacteria by fluorescent immunoassays (FIA) takesadvantage of the high degree of specificity inherent inthe immunological reaction. Recently (Cao et al., 1995)described a fluorescent immunoassay to detect a specificprotein-polysaccharide surface antigen (F1) of Y. pestis.The capture antibody was either a protein G-purifiedrabbit anti-plague Ab or a monoclonal Ab to the F1antigen. Samples containing 5 ng/ml F1 could be as-sayed within 30 min.

Using an antibody to the protective protein co-ex-pressed with the anthrax toxins (Wijesuriya et al., 1994)have shown that a device based on this approach couldbe used as a clinical diagnostic tool for the presence ofanthrax. In the same report, an approach simpler thanthe fluorescent-labeled antibody sandwich format wasdemonstrated. Cells in a sample were first treated witha dye (Nile Red) which fluoresces only when incorpo-rated into a lipid membrane. A specific monoclonalantibody to the cell surface antigens was used as thecapture antibody and 3×103 cells/ml of B. anthrax wasdetected.

Pyle et al. (1995) utilized the fluorescent antibodytechnique followed by incubation with cyanoditolyl te-trazolium chloride (CTC) to detect respiratory activity.After capture of the bacteria and incubation with CTCthe fluorescein conjugate was added and bacteria enu-merated. Using this technique it was possible to detectE. coli O157:H7 in the range of 105–109 CFU/ml withan assay time of 4 h. This technique was also used fordetecting S. typhimurium and Klebsiella pneumoniae.


Fig. 3. A diagram of the IMAS. Samples are initially processed by theIMAS, then analyzed by an ECL, a fluorimeter and a flow cytometer.Adapted with permission from Yu and Stopa (1995).

assay time was one hour. The sensitivity of the IMASfor Bacillus anthrax spores, E. coli O157:H7 and S.typhimurium detection is approximatly 100 cells/ml inPBS and 1000 cells/ml in biological samples. Decreasedsensitivity of the IMAS detection in biological sampleswas due to sample interference.

2.2.2. Microbial metabolism based biosensorsMicroorganisms are able to transduce their metabolic

redox reactions into quantifiable electrical signals byoxidoreductase reactions and an appropriate mediatoras illustrated in Fig. 4 (Takayama et al., 1993). Manypossible mediators have been used for characterizationof microbial respiratory chain components (Kalab andSkladal, 1994). Thus, the microbial content of a samplecan be determined by monitoring microbialmetabolism. To date, various combination of biosen-sors based on the monitoring of microbial metabolismhave been reported (Wilkins, 1978; Matsunaga et al.,1979; Holland et al., 1980; Turner et al., 1986; Libbyand Wada, 1989; Nakamura et al., 1991; Jouenne et al.,1991; Ding et al., 1993; Hitchens et al., 1993; Takayamaet al., 1993; Gehring et al., 1996; Perez et al., 1998). Thetransducer can either detect consumption of oxygen orthe appearance/disappearance of an electrochemicallyactive metabolite. Wilkins (1978) and Wilkins et al.(1978) described a method for monitoring the redoxpotential generated at a platinum electrode as a resultof the microbial oxidation of electroactive substances inthe supporting medium. This direction was continued inthe works of (Holland et al., 1980) and (Junter et al.,1980). They showed that direct potentiometric detectionmay be applicable to a wide range of bacteria. How-ever, the response times for the detection of 106 cells/mlvaried from 2 to 4 h and this simple system sufferedfrom low sensitivity due to the high background noise.Since the detection time relies upon microbial growth,this approach cannot provide a real-time analysis andpre-enrichment steps are required. Takayama et al.(1993) demonstrated mediated electrocatalysis based onthe bacterium Gluconobacter industrius. Bacteria wasimmobilized on the surface of carbon paste electrodecontaining p-benzoquinone (BQ) which worked as acatalyst to oxidize D-glucose in the presence of BQaccording to the scheme in Fig. 4. It was shown that thebioelectrocatalytic behavior of the G. industrius–BQ–electrode system is very similar to that observed with aglucose oxidase–BQ–electrode system. Glucose dehy-drogenase (GDH), an enzyme present in the bacterialcell membrane, was the catalyst for producing theBQ-mediated electrocatalytic current. A current magni-tude as high as 200 mA/cm2 was obtained with 2.4×106

cells in the presence of BQ and 10 mM glucose. Asteady-state current was attained in about 30 s.Takayama et al. (1993) demonstrated that mediatorssuch as K3Fe(CN)6 and dichlorophenol indophenol

Fig. 4. Schematic representation of bioelectrocatalysis based on anoxidoreductase in a cytoplasmic membrane of a microorganism. S,substrate; P, product; Mox and Mred oxidized and reduced forms of amediator respectively; DH, oxidoreductase. Adapted with permissionfrom Takayama et al. (1993).

Chowdhury et al. (1995) used a similar technique fordetecting Vibrio cholera O1 and O139. V. cholera cellswere incubated with a yeast extract in the presence ofnalidixic acid. This caused the substrate responsive,viable cells to elongate and enlarge and were readilydetectable using a fluorescent antibody. Using this tech-nique it was possible to detect 109 cells/ml of V. cholerawith an assay time of at least 6 h.

An immunomagnetic assay system (IMAS) has beendeveloped for detection of virulent bacteria in biologi-cal samples (Yu and Stopa, 1995; Yu and Bruno, 1996;Vernozy-Rozand et al., 1997). The IMAS includes amagnetic separator for capturing the antigen and anelectro-chemiluminescent detector. In addition, IMASwas coupled to a flow cytometer and to a continuousfluorimeter (Fig. 3). This approach, like other chemilu-minescence techniques, offers high signal-to-back-ground ratios and is comparable in sensitivity toradioisotopic methods but has the advantage over otherchemiluminescence techniques of being initiated by avoltage potential and thus providing better-controlledluminescence (Yu and Bruno, 1996). In the fluorescencesandwich immunoassay, biotinylated antibody plusstreptavidin-coated magnetic beads and fluorescein-con-jugated antibody were used for measurement. The total


were capable of accepting electrons from GDH or fromsome other part of the respiratory chain in the cellmembrane. Recently, bioelectrochemical instrumenta-tion has been developed (Ding et al., 1993) for rapiddetermination of E. coli using a flow-injection system.Electrochemical measurement of a mediator,K3Fe(CN)6, reduced by microbial metabolism allowedthe determination of fungi and bacteria in 20 min. E.coli was determined in the range of 4.7×106–2.4×109

CFU/ml when the microorganisms were not separatedfrom the cultivation medium. As the mechanism ofmicrobial mediator reduction is not yet fully under-stood, the application of this approach has to be inves-tigated further (Ding et al., 1993). Hitchens et al. (1993)describe a method for enumerating microorganismswhich combines electrochemical detection with flowinjection analysis. This method is based on the mea-surement of electrical currents generated by active mi-crobes in the presence of redox mediators (i.e. lowmolecular weight electron acceptors) that can diffusethrough the bacterial cell membrane. Analysis of sam-ples could be performed in 10 min at a lower detectionlimit of 105 cells/ml. The results also provided newinsights into factors that limit the lower limits of sensi-tivity of the mediated amperometric detection system.

Electrochemical biosensors based on the Clark-typeoxygen electrode have been introduced for the rapiddetermination of E. coli, S. aureus and Enterococcusserolicida in a biological sample (Endo et al., 1996). Thecell suspension was filtered through a cellulose nitratemembrane (pore size, 0.45 mm). The membrane alongwith the captured cells was set on the platinum workingcathode of a Clark oxygen electrode and covered with adialysis membrane. The microbial electrode was im-mersed in 0.05 M phosphate buffer until the outputcurrent became stable. The electrode was then takenout and placed in a solution containing sodium azide,which suppressed the growth of most microorganismsexcept E. serolicida.

A linear relationship was obtained in the range of1.4×107–7.2×107 cells/ml with an assay time of 2 h.However, the linear range of the oxygen electrode islimited because of low oxygen concentrations. Also, theresponse fluctuated as a result of variations in circulat-ing oxygen concentrations. The main drawbacks ofbiosensors based on the monitoring of microbialmetabolism are related to their poor selectivity andslow response times. This type of biosensor can only beused for well-defined samples because of the possiblepresence of enzymes from sources other than the bacte-ria of interest.

2.2.3. Electrochemical immunodetection of bacteriaElectrochemical sensors have some advantages over

optical-based systems in that they can operate in turbidmedia, offer comparable instrumental sensitivity, and

are more amenable to miniaturization. Modern electro-analytical techniques have very low detection limits(typically 10−9 M) that can be achieved using smallvolumes (1–20 ml) of samples (Jenkins et al., 1988).Furthermore, the continuous response of an electrodesystem allows for on-line control and the equipmentrequired for electrochemical analysis is simple andcheap compared to most other analytical techniques.The recently developed light addressable potentiometricsensor (LAPS) based on field effect transistor (FET)technology has proved to be highly successful for im-munoassay of bacteria (Libby and Wada, 1989;Thompson and Lee, 1992; Lee et al., 1993a,b; Menkingand Goode, 1993; Gehring et al., 1998). A LAPSconsists of n-type silicon doped with phosphorous andan insulating layer in contact with an aqueous solutionwhere the immunoreaction takes place. The differencebetween the charge distribution at the surface of theinsulating layer and a FET is used to detect changes inthe potential at the silicon-insulator interface. A LAPSmeasures an alternating photocurrent generated when alight source, such as a light emitting diode (LED)flashes rapidly (Fig. 5). The photocurrent can only bemeasured on these discrete zones where the sensor isilluminated. Thus LAPS may measure local changes bymultiplexing the LED and consequently measuring dif-ferent analytes simultaneously using a single sensor(Owicki et al., 1994). Based on this principle a devicecalled Threshold (TM) from Molecular Devices is onthe market. (Libby and Wada, 1989) used a LAPS in animmunofiltration procedure for the detection of thepathogenic bacteria, Neisseria meningitidis and Y.pestis. The bacteria were captured by filtration on eitherpolycarbonate or nitrocellulose membranes, throughwhich solutions containing the respective monoclonalantibodies labeled with peroxidase were then filtered.The enzyme activity was monitored in the LAPS read-ing chamber in the presence of peroxidase substrates. Inthe case of N. meningitidis 103 cells could detected in 20min, whereas a 2.5 h ELISA with the same reagentsdetected 6×104 cells. The LAPS has also been used todetect Brucella militensis (Lee et al., 1993a,b), Fran-cisella tularensis (Thompson and Lee, 1992), Coxiellaburnetti (Menking and Goode, 1993) and E. Coli(Gehring et al., 1998). For B. militensis the lowerdetection limit was 6×103 cells and 3.4×103 cells forF. tularensis during an incubation time of 1 h. AlthoughFET-based devices offer improvements to potentiomet-ric monitoring of bacteria, there are several problemsassociated with these devices such as light sensitivity ofthe materials used in their construction, poor repro-ducibility and selectivity.

Almost all microorganisms can now be sensed am-perometrically by their enzyme-catalyzed electrooxida-tion/electroreduction or their involvement in abioaffinity reaction. Because amperometric detection is


a heterogeneous process of electron transfer, electro-chemical measurements at electrode interfaces are easierto execute in very small volumes than optical measure-ments. Suitable electrode materials for amperometryare noble metals, graphite, modified forms of carbon(carbon paste, glassy carbon, pyrolytic graphite), andconducting polymers. Ag/AgCl is the most commonreference electrode. Interest in miniaturized electro-chemical biosensors and the development of inexpen-sive and disposable sensors has led to the application ofthick- and thin-film technology in the manufacturing ofbiosensors.

Amperometric biosensors have the advantage of be-ing highly sensitive, rapid, and inexpensive (Ghindilis etal., 1998). Amperometric systems have a linear concen-tration dependence compared to a logarithmic relation-ship in potentiometric systems. This makesamperometric immunosensors well suited for bacterialassay. Amperometric immunosensors aimed at micro-bial analysis have recently been reported (Mirhabibol-lahi et al., 1990; Nakamura et al., 1991; Brooks et al.,1992; Kim et al., 1995; Brewster et al., 1996; Rishponand Ivnitski, 1997). In the work of Nakamura et al.(1991), an electrode system consisting of a basal-planepyrolytic graphite (BPG) electrode and a porous nitro-cellulose membrane filter to trap bacteria was used forthe detection of bacteria in urine. The peak current ofa cyclic voltammogram increased with increasing initialcell concentration of E. coli in urine. Urine containing5×102–5×105 cells/ml was measured with this system.The susceptibility of bacteria to various antibiotics wasalso determined from the peak current. Mirhabibollahiet al. (1990), Brooks et al. (1990) and Brooks et al.(1992) utilized an enzyme-linked amperometric im-

munosensor for the detection of S. aureus andSalmonella in pure cultures and in foods. This im-munosensor could detect 104–105 CFU/ml of S. aureus.However, the electrochemical detection step was awk-ward to perform, and there were variations in thesignals produced by different strains of bacteria.

This approach was modified in a later work by thesame authors (Brooks et al., 1992) utilizing alkalinephosphatase as the enzyme-marker and phenyl phos-phate as the substrate followed by the amperometricdetection of phenol. They also proposed another systemwhich incorporated an enzyme amplification step andrelied on the amperometric detection of reduced media-tor (ferrocyanide). Both systems were able to detect lownumbers (1–5 CFU/g or per ml) of Salmonella in foodafter non-selective (18 h) and selective (22 h) enrich-ment steps. Kim et al. (1995) described a novel lipo-some-based amperometric biosensor for the detectionof haemolytic microorganisms. The potential of thisapproach was illustrated for detection of various strainsof L. monocytogenes, Listeria welshimeri and E. coli.Bacterial concentrations were determined in the rangeof 4.7×106–2.4×109 CFU/ml. Recently immunomag-netic beads have been applied in immunoelectrochemi-cal assays for the detection of S. typhimurium (Brewsteret al., 1996; Gehring et al., 1996). This technique com-bines the selectivity of antibody-coated superparamag-netic beads with the rapidity and sensitivity ofelectrochemical detection of bacteria in a format termedenzyme-linked immunomagnetic electrochemistry. Inthis case, heat-killed S. typhimurium were sandwichedbetween antibody-coated magnetic beads and an en-zyme-conjugated antibody (Fig. 6). With the aid of amagnet, the beads were localized onto the surface of

Fig. 5. Basic schematic of silicon field effect potentiometric sensors. (a) Configuration of a capacitor. The capacitance changes as a function ofthe potential applied. (b) Schematic representation of a light-addressable potentiometric sensor (LAPS). An alternating photocurrent is generatedwhen light emitting diodes flash rapidly. Adapted with permission from Marco and Barcelo (1996).


Fig. 6. Schematic representations of enzyme-linked immunomagneticcolorimetric (ELIMC) and electrochemical (ELIME) assays. AP,alkaline phosphatase; pNPP, p-nitrophenyl phosphate; pNP, p-nitro-phenol; pAPP, p-aminophenyl phosphate; pAP, p-aminophenol; andpQI, p-quinone imine. Adapted with permission from Gehring et al.(1996).

The biosensors presented so far are characterized bya lengthy analysis time and are greatly lacking sensitiv-ity. It has been demonstrated that diffusion to theinterface of the electrode surface is a rate-limiting stepduring heterogeneous electrochemical immunoassays(Gorovits, et al., 1993). Due to this diffusion control,the time required for achieving reaction equilibriumbetween the immobilized antibody and the antigen insolution is usually on the order of several tens ofminutes. The general approach to achieve significantlyshort immunoassay times is to reduce transport limita-tions, across the unstirred layer of solvent, to the solidsurface. The acceleration of the diffusion-controlledrate of immunological and enzymatic reactions on thesolid-solution interface has been accomplished by: in-tensive mixing of the solution (liquid phase); the utiliza-tion of highly dispersed carbon-based immunosorbentsas electrode materials (Krishnan et al., 1996); or byusing cascade schemes, where the enzyme label is linkedcatalytically to other enzymes (Litman et al., 1980;DiGleria et al. 1989; Duan and Meyerhoff, 1994; Mc-Neil et al., 1995; Ivnitski and Rishpon, 1996; Ivnitski etal., 1998). A ‘pseudo-homogeneous’ amperometricalimmunoassay (without a washing step) was also devel-oped for S. aureus (Rishpon and Ivnitski, 1996, 1997)and its configuration is presented in Fig. 7. The amplifi-cation of the analytical signal was achieved bycombining enzyme-channeling reactions, optimizing hy-drodynamic conditions, and electrochemical regenera-tion of mediators within the membrane layer of ananion-exchange polyethylenimine–glucose oxidase–an-tibody modified electrode. The immunosensor enablespreferential measurement of surface-bound conjugate

disposable graphite ink electrodes in a multi-well plateformat. After magnetic separation, the liquid was re-moved by aspiration and 200 ml of p-aminophenylphos-phate (2.7 mM in 0.2 M Tris, pH 9.6) was added to theelectrochemical cell and p-aminophenol, the product ofthe enzymatic reaction, was measured using squarewave voltammetry. Using this technique, a minimum of8×103 cells/ml of S. typhimurium in buffer was de-tected in :80 min. However, these immunoassays areboth labor intensive and time-consuming due to themany washing steps. Also, complex instrumentation isrequired for their automation.

Fig. 7. Separation-free enzyme channeling immunoassay for Staphylococcus aureus. Reaction scheme at the electrode surface includes (i) capturingof the target microorganism by an anti-protein A antibody immobilized on the electrode; (ii) sandwich formation by the peroxidase (HRP) labeledanti-protein A antibody; (iii) in situ generation of hydrogen peroxide by glucose oxidase (GOD) co-immobilised on the electrode to react withamino-salicyclic acid (catalysed by the peroxidase label) and to give a quinone-imine which is reduced at the electrode generating cathodic currentresponse.


relative to the excess enzyme-labeled reagent in the bulksample solution. S. aureus cells were detected in pureculture at concentrations as low as 1000 cells/ml in arelatively short assay time of 30 min.

A novel approach based on using partially immersedimmunoelectrodes has been demonstrated for fast andsensitive immunoassay of E. coli O157:H7 (Abdel-Hamid et al., 1998a). Immunoelectrodes were operatedwhile being partly immersed in the solution resulting inthe formation of a supermeniscus on the electrodesurface. This supermeniscus is characterized by a thick-ness of :0.4–0.8 mm and plays an important role inproviding optimal hydrodynamic conditions for thecurrent generation process. The sensitivity of the par-tially immersed electrode was six folds greater than thatof the fully immersed one. The partially immersedimmunoelectrode allows determination of E. coli cellconcentrations in the range of 150–7000 cells/ml. Sincethe magnitude of the diffusionally limited current isinversely proportional to the thickness of the diffusionlayer, the enhanced sensitivity effects observed with thepartially immersed electrodes may be explained by facil-itated diffusion of analyte, conjugate and substratemolecules to the electrode surface in the upper part ofthe meniscus and in the supermeniscus where the elec-trode, electrolyte and gas phase meet. This new im-munoassay approach can be easily extended to thedetection of other bacterial cells and may be a basis forcreating new, highly sensitive and rapidimmunosensors.

2.3. Flow immunosensors

Most microbial assays are currently based on solid-phase enzyme-linked immunoassays (ELISA) using mi-crotitration plates. This is a powerful analysis tool usedin biomedical research due to its high reproducibilityand possibility to simultaneously conduct a large num-ber of assays (Hock, 1996). However, disadvantages ofheterogeneous ELISA methods include the small sam-ple volume (200 ml) that the microtitration plate holdsand the long incubation time required for each ELISAstep. Also, the sensitivity of ELISA methods is insuffi-cient for direct measurement of bacteria and othermicroorganisms in the original samples. Because lownumbers of pathogenic bacteria are often present in abiological sample, an analytical standard often used forpathogenic bacteria is to detect cells in 25 g of food(Wyatt, 1995). Obviously, it is not possible to put a 25g sample directly in a microtitration plate. Therefore, inmany situations and in order to increase assay sensitiv-ity, it would be desirable to concentrate the bacteriainto a smaller volume prior to the assay or by growinga single cell into a colony. Several possible formats forconcentrating cells in analytical systems were describedby Wyatt (1995). The most attractive technique for the

concentration of bacteria is membrane filtration in con-junction with flow systems (Duverlie et al., 1992; Brak-stad and Maeland, 1993; Clark et al., 1993; Valcarceland DeCastro, 1993; Paffard et al., 1996; Abdel-Hamidet al., 1999a). This procedure, called the flow im-munofiltration assay, can be an excellent alternative fordetection of bacterial pathogens because it not onlyoverrides the effects of diffusional limitations, but alsoallows the concentration of bacteria on the membraneby filtering a large volume of the sample.

Heterogeneous flow immunofiltration assays offer ex-tremely accelerated binding kinetics (Ijsselmuiden et al.,1989; Morais et al., 1997). First of all, there is a highsurface area to volume ratio in the immunosorbent.Second, the flowing stream actively brings the sample incontact with the solid-phase antibody. This factor re-sults in a greatly enhanced antigen-antibody encounterrate and in nearly quantitative immunobinding duringthe short time of the immunoreaction. This approachhas also dramatically increased the potential for au-tomation of immunoassays. Clark et al. (1993) de-scribed an apparatus for use in an enzyme linkedimmunofiltration assay (ELIFA) which incorporated aperistaltic pumping system allowing continuous filtra-tion of reagents through a nitrocellulose membraneclamped between two 96-well plates. Upon completionof the immuno- and enzymatic reactions, the chro-mogenic reaction product from each well was collectedin a microtiter plate and quantitatively determined us-ing an ELISA reader. This method was further devel-oped for the detection of E. coli (Paffard et al., 1996).Quantitative bacterial detection was based on precipi-tated chromogen determined by scanning densitometryand the ELIFA method was capable of detecting 103

bacterial cells within 40 min.A very interesting flow injection immunosensor has

been developed for the determination of E. coli inartificially contaminated food samples (Bouvrette andLuong, 1995). This approach was based on direct non-competitive heterogeneous immunoassay of E. coli cellswith an antibody column and a fluorescence detector.The advantage of this method is that bacterial concen-trations can be determined without using any labeledcompounds. The technique is based on the direct detec-tion of the cell’s b-D-glucuronidase activity (GUD).Owing to the specificity of the antibody towards E. coli,the immunosensor was selective for detection of E. coliin the presence of Shigella boydii and another GUD-positive bacterium. However, the detection limit for E.coli was on the order of 5×107 CFU/ml which is lessthan the detection limit of the standard ELISA proce-dure for microbial cells (typically 106 CFU/ml).

Another promising format of immunoassay is basedon the use of flow injection systems and antibody-coated magnetic particles. This technique can be easilyautomated, the analyses performed quickly and contin-


uously and the renewal of the sensing surface of im-munosensor was easily accomplished. In order to regen-erate the immunoreagent, the magnet was removed andthe magnetic particles were washed down. At thatmoment, the immunosensor was ready for injection ofnew antibody modified magnetic particles for anotheranalytical cycle. The system has been applied to detectB. anthrax spores, E. coli O157 and S. typhimurium (Yuand Stopa, 1995; Brewster et al., 1996; Gehring et al.,1996; Yu and Bruno, 1996; Vernozy-Rozand et al.,1997; Brewster and Mazenko, 1998; Perez et al., 1998).This format offers several advantages for automaticimmunoassays: the many required washing steps areinherent and the immunoassays can be carried outrapidly and can be automated easier than formats usingtubes, microtiter plates or other similar reaction vessels.A continuous configuration of immunoassay used inconjunction with a biosensor has such important prop-erties as (Valcarcel and DeCastro, 1993): transferringthe injected or aspirated sample to the sensor; condi-tioning the sample (pH adjustment, mixing with otherreagents, masking) for optimal development of the re-action and detection that is to take place at the sensorsurface; regeneration of the sensor between samples;facilitating reliable calibration and increasing the sensorselectivity and sensitivity via a continuous separationmodule; boosting precision through reduced humanparticipation in biosensor-related operations. The typi-cal output of a flow-injection system is a peak thatresults from the dispersion of the injected sample. Flowimmunosensors have been applied in a different fieldsof medicine, biotechnology, environmental and biopro-cess monitoring (Schmid, 1991; Ding et al., 1993; Val-carcel and DeCastro, 1993; Bouvrette and Luong, 1995;Puchades and Maquieira, 1996; Lu et al., 1997; Abdel-Hamid et al., 1998b; Ghindilis et al., 1998).

Several semi-automated systems have been developedfor microorganism identification. A flow-injection im-munoanalysis system has recently been used to detectE. coli in artificially contaminated food samples (Bou-vrette and Luong, 1995). The flow-injection systemequipped with a 5 ml flow cell consisted of a peristalticpump, antibody column and fluorescence detector.Anti-E. coli antibodies were covalently immobilizedonto porous aminopropyl glass beads. The system suc-cessfully detected E. coli in 30 min and was reusable forat least 300 repeated assays and the detection limit wason the order of 5×107 CFU/ml. A disadvantage of thegenerally used regeneration methods is that they userelatively aggressive chemicals such as 8 M urea, 0.2 Mglycine-HCl (pH 2.8) or 0.2 M ethanolamine (pH 8).Treatment of the antibody modified surface of thebiosensor with harsh chemicals did not completely re-move the bound bacteria and partial desorption of theimmobilized antibody occurred during each regenera-tion cycle, resulting in a decrease in sensitivity. Perez et

al. (1998) proposed amperometric flow-injection systemfor measuring of viable E. coli O157. This system isbased on the selective immunological separation of abacterial strain and the generation of a signal by bacte-rial cells. For the immunological step, immunomagneticbeads were selected as the immunocapture reagent.Electrochemical detection was carried out using redoxmediators [potassium hexacyanoferrate (III) and 2,6-dichlorophenolondophenol]. The detection limit was105 CFU/ml, and the complete assay was performed in2 h. The basic advantages of this system and the systempresented by (Bouvrette and Luong, 1995) are the needfor only unlabeled antibodies and the ability of detect-ing viable cells.

Recently, a flow-injection amperometric im-munofiltration assay system has been developed forrapid detection of E. coli O157:H7 (Abdel-Hamid et al.,1999a). A schematic of the flow-through immunosensoris presented in Fig. 8. The immunosensor consists of adisposable antibody-modified filter Nylon membraneresting on top of a working carbon electrode. Thebuffer flows through the filter membrane and thenthrough the hollow channel in the working, counterand reference electrodes respectively. By combining theflow-injection amperometric system with an im-munofiltration technique, a high immunoassay sensitiv-ity and a substantial reduction in the time required todetect E. coli O157:H7 was achieved. The amperometricimmunosensor allows the detection of E. coli cells witha lower detection limit of 50 cells/ml and an overallanalysis time of 40 min. The immunosensor can beeasily adapted for assay of other microorganisms andwas further developed for detection of total E. coli andtotal Salmonella. A detection limit of 50 cells/ml withan analysis time of 35 min was achieved (Abdel-Hamidet al., 1999b). This approach offers a number of advan-tages over the ELISA, including greater antibody bind-ing capacity, higher sensitivity, easier discriminationbetween specific and non-specific signals, reduction ofassay time and simpler operation.

2.4. Genosensors

Gene probes are certain to play an increasingly im-portant role in health care, agriculture and environmen-tal monitoring (Mikkelsen, 1996; Wang et al.,1997a,b,c; Zhai et al., 1997; Zhu and Wang, 1997).Military applications of gene probes are associated withultrasensitive determination of microorganisms, viruses(biological warfare) and trace amounts of special chem-icals in various environments. Gene probes are alreadyfinding applications in detection of disease-causing mi-croorganisms in water supplies, food, or in plant, ani-mal or human tissues (Tenover, 1988; Highfield andDougan, 1992; Kapperud et al., 1993; Sharpe, 1994;Tietjen and Fung, 1995; Feng, 1996; Zhai et al., 1997).


Fig. 8. Scheme of the processes in a flow-through immunosensor forrapid detection of bacteria: (a) the immunofiltration membrane withantibodies and the flowing of the sample to be analysed; (b) immobi-lized antibodies capture bacterial cells and flowing of the conjugatesolution; (c) formation of the immuno-complex, flowing of the perox-idase substrates and amperometric signal generation.

for a nucleic acid duplex in comparison with an anti-body-protein complex and indicates that highly specificand sensitive detection systems can be developed usingnucleic acid probes (McGown et al., 1995; Skuridin etal., 1996). The specificity of nucleic acid probes relieson the ability of different nucleotides to form bondsonly with an appropriate counterpart. Since the nucleicacid recognition layers are very stable, an importantadvantage of nucleic acid ligands as immobilized sen-sors is that they can easily be denatured to reversebinding and then regenerated simply by controllingbuffer-ion concentrations (Graham et al., 1992). Thedetection of specific DNA sequences provides the basisfor detecting a wide variety of bacterial pathogens. Theoriginal DNA hybridization test for bacteria in foodsused a radioactively labeled probe (Feng, 1992). Themain disadvatages of radiolabelled probes are theshort-shelf life of 32 P-labelled probes, high cost, haz-ards, and disposal problems associated with radioactivewaste. The limitation of nucleic acid probes is also aproblem associated with cultivating bacteria to a de-tectable level. Hybridization requires the presence of atleast 105–106 bacteria in the sample to obtain a positivesignal. Therefore, without pre-enrichment of the targetorganism, DNA hybridization approach does notprovide the required sensitivity to detect bacteria atrequired level (Tietjen and Fung, 1995). However, pro-gress of a gene amplification method (the polymerasechain reaction) extremely enhances the sensitivity ofDNA probes, at least three orders of magnitude (Sailkiet al., 1985). This technique uses the heat-stable DNApolymerase of Thermus aquaticus, and allows shortlengths of a double-stranded target DNA (template) tobe copied in vitro thousands or millions of times, veryquickly. According to Jones et al. (1993) a PCR-geneprobe based assay has high potential for improvingmonitoring of foodborn bacteria. To date only methodsinvolving the PCR have been employed to detect food-borne pathogens. The PCR method is an extremlyspecific and sensitive method. Bacteria can be detecteddirectly, without cultivation, by extraction and isolationof nucleic acids from real samples, followed by hy-bridization with specific probes. Without any enrich-ment steps, the PCR method detects less than 40cells/gram of a given food sample (Tietjen and Fung,1995).Since sensitivity is not a limiting factor, a promis-ing alternative way to conduct nucleic acid based assaysis by using non-radioactive labelled probes, which isassociated with the development of biosensor technolo-gies (Wang et al., 1997a,b,c; Zhai et al., 1997; Zhu andWang, 1997). Two aims of biosensor assay developmentshould be emphasized: (i) an improvement over conven-tional nucleic acid assay (gene probe) performance and(ii) the design of special gene probe techniques forspecial applications under special conditions. Based onthe nature of the physical detection principle used in

Clinical applications of gene probes are another primearea of intensive development (Zhai et al., 1997). Theterm nucleic acid (gene) probe describes a segment ofnucleic acid which specifically recognizes, and binds to,a nucleic acid target. The recognition is dependentupon the formation of stable hydrogen bonds betweenthe two nucleic acid strands. This contrasts with inter-actions of antibody-antigen complex formation wherehydrophobic, ionic and hydrogen bonds play a role.The bonding between nucleic acids takes place at regu-lar (nucleotide) intervals along the length of the nucleicacid duplex, whereas antibody-protein bonds occuronly at a few specific sites (epitopes). The frequency ofbonding is reflected in the higher association constant


the transducer, genosensing systems can be classified asoptical, gravimetric and electrochemical. The principlesand applications of the electrochemical DNA biosen-sors were described and discussed in a number ofreviews (Mikkelsen, 1996; Wang et al., 1997a,b,c).Pathogens responsible for disease states, bacteria andviruses, are detectable via their unique nucleic acidsequences. Recently DNA hybridization electrochemi-cal biosensor for the detection of DNA fragments tothe waterborne pathogen Cryptosporidium have beendeveloped (Wang et al., 1997a,b,c). The sensor relies onthe immobilization of an oligonucleotide unique to theCryptosporidium DNA onto the carbon-paste trans-ducer, and employs a highly sensitive chronopotentio-metric transduction mode for monitoring thehybridization event. Very short (3 min) hybridizationperiods give rise to well defined hibridization signals atmg/ml concentrations of the Cryptosporidium target,while longer (20–30 min) ones permit ng/ml detectionlimit. Similar hybridization/chronopotentiometricschemes are currently being developed for other patho-gens, such as E. coli, Giardia and Mycobacterium tuber-culosis (Wang et al., 1997a,b,c). The ultimate goal ofthis research is to design an array of microelectrodes ona chip for the simultaneous field monitoring of multiplepathogens in water supplies. Evanescent wave methodsof total internal reflection fluorescence (TIRF) (Gra-ham et al., 1992) and LAPS (Hafeman et al., 1988)were described as labeling methods for DNA assay.

Direct (labelless) monitoring of hybridization reac-tions has been demonstrated with surface plasmon reso-nance (SPR) (Pollard-Knight et al., 1990; Schwarz etal., 1991) and PZ acoustic wave devices (Wu et al.,1990; Andle et al., 1992). Two commercially availableoptical sensors, both based on evanescent wave technol-ogy, have been used for detection of DNA–DNAinteractions. The Biacore system (Pharmacia, Sweden)uses SPR which arises in thin metal films under condi-tions of total internal reflection. In the sensing elementof this instrument, a gold transducer surface is modifiedwith a dextran matrix on which the biological probe isimmobilized (often via avidin–biotin links). Oligonucle-otides are introduced within a fluid flow system. Hy-bridization is carried out at room temperature andpositive signals are obtained within several minutes. Asimilar optical sensor, the IAsys system (Affinity Sen-sor, UK), has been introduced where the gold film isreplaced by titania or hafnia, acting as a dielectricresonant layer of high refractive index (resonant mir-ror). The sensing surface is modified with either aderivatized dextrin matrix or an aminosilane. The reso-nant mirror method has been used to detect DNAhybridization with an estimated limit of detection in thefemtomolar range. Regeneration of the surface-immobi-lized probe was possible, allowing reuse without asignificant loss of hybridization activity (Titball andSquirrell, 1997).

Two types of hybridization are currently used: (i)pseudo-homogeneous hybridization, which can beachieved in systems with high surface-to-volume ratio,such as porous membranes and highly dispersed immo-bilization carriers; (ii) solid-phase hybridization, whichis preceded by transfer to a membrane. The maindisadvantage of solid-phase relative to pseudo-homoge-neous hybridization is the longer time required and theneed for several manipulations (Aubert et al., 1997;Yang et al., 1997). In this case engineering approachesfor conducting the hybridization process in pseudo-ho-mogeneous conditions can be applied. Conducting thehybridization reaction in a constant flow mode (inflow-through sensor systems as a variant of flow-injec-tion assay) facilitates elimination of transport restric-tions. The development of enzyme-linkedimmunofiltration assay technique for rapid detection ofToxoplasma gondii DNA in real samples was described(Aubert et al., 1997). Hybridization technqiues are be-ing currently formatted for a relatively fast (ca. 24–48h) identification of bacteria (Avanissaghajani et al.,1996; Goh et al., 1997; Guschin et al., 1997). However,the DNA hybridization method has a number of prob-lems. This method is not straightforward, complicated(multistep assay) and time-consuming. There is also aproblem of false amplifications.

2.5. The electronic nose

‘Electronic nose’ systems have advanced rapidly dur-ing the past 10 years, the majority of applications beingwithin the food and drink industry (Gardner andBartlett, 1992; DiNatale et al., 1997; Kress-Rogers,1997; Haugen and Kvaal, 1998; Schaller et al., 1998).Electronic nose systems comprise sophisticated hard-ware, with sensors, electronics, pumps, flow controllers,software, data pre-processing, statistical analysis(Schaller et al., 1998). The sensor array of an electronicnose has a very large information potential and re-sponds to both odorous and odourless volatile com-pounds. In the electronic nose the signal pattern from asensor array, comprised usually of individual sensingelements with limited specificity, is collected by a com-puter, where a first pre-treatment of the data is carriedout. These data are then further processed by suitablesoftware based on artificial neural networks approachfor training and learning (Winquist et al., 1993). Amajor effort is required to define the mathematicalrelationship that describes the application, and to vali-date the model obtained (Blixt and Borch, 1999). Aseries of electronic noses have been produced commer-cially during the last few years (Gardner and Bartlett,1994; Haugen and Kvaal, 1998). The theoretical basisand the practical application of the electronic noseshave been illustrated in a number of reports (Gardnerand Bartlett, 1992, 1994; Gibson et al., 1997; Kress-


Rogers, 1997; Haugen and Kvaal, 1998; Wit and Buss-cher, 1998).

At present, different detection principles (heat gener-ation, conductivity, electrochemical, optical, dielectricand magnetic properties) are used in the basic sensingelements of the electronic. The ideal sensors to beintegrated in an electronic nose should fulfil the follow-ing criteria (Schaller et al., 1998): high sensitivity (downto 10−12 g/ml), they must respond to different com-pounds present in the headspace of the sample; highstability and reproducibility; short recovery time; easycalibration; they must also be robust and portable.

Artificial electronic noses have been used for mea-surement of beer quality (Pearce et al., 1993), meat-taint (Bourrounet et al., 1995), ground meat (Winquistet al., 1993; Haugen and Kvaal, 1998) and the freshnessof fish (Schweizer-Berberich et al., 1994). One of thefirst attempts to identify microorganisms with an elec-tronic nose was made by Craven et al. (1994). An arrayof four different commercial metal oxide gas sensorswas used to sample the head space of six pathogenicbacteria (Clostridia perfringens, Proteus, Haemophilusinfluenzae, Bacteroides fragilis, Oxford staphylococcusand Pseudomonas aeruginosa) grown in blood agar. Inthis test the four-element electronic nose was able toclassify correctly 62% of the pathogens. Gibson et al.(1997) reported on the use of an array of 16 conduct-ing-polymer resistive gas sensors to detect 12 differentbacteria from cultures grown on agar plates. Morerecently, an investigation into the use of an electronicnose to predict the class and growth phase of twopathogenic bacteria, E. coli and S. aureus, has beenperformed by Gardner et al. (1998). The sample fromthe head space was passed into a sensor chamber whichcontained six commercial metal oxide odour sensors.The sensors were chosen based on the knowledge thatsecondary metabolites of growing microorganisms arehydrocarbons, alcohols, aldehydes, acids, ammonia andso on. The performance of 36 different pre-processingalgorithms has been studied in the basis of nine differ-ent sensor parameters and four different normalizationtechniques. Authors demonstrated that the type of bac-terium can be correctly predicted for 96% of all samplestaken during a 12 h incubation period. The growthphase of the bacteria was correctly predicted for 81% ofall unknown samples. In other work, Rossi et al. (1995)were able to discriminate between seven species of thebacteria Micrococaoceae that can be found in fer-mented meat products. The species investigated in cul-ture were respectively four aromatic (Micrococcus andStaphylococcus) and three pathogenic bacteria strains.One hundred percent of the bacteria samples wereclassified correctly into their respective groups based onfactorial discriminant analysis. Recently (Gibson et al.,1997; Haugen and Kvaal, 1998; Holmberg et al., 1998;Namdev et al., 1998) described the feasibility of using

electronic noses for the following applications: monitor-ing lot-to-lot variation in bioprocess medium ingredi-ents, detection and simultaneous identification ofmicroorganisms, bacteria classification; and evaluatingbioprocess performance during cultivation of microor-ganisms at inoculum and production stages.

Data evaluation and classification have been madeon measurements by an electronic nose on theheadspace of samples of different types of bacteriagrowing on petri dishes (Holmberg et al., 1998). E. coli,Enterococcus sp., Proteus mirabilis, P. aeruginosa, andStaphylococcus saprophytica were selected for thisstudy. An approximation of the response curve by timewas made and the parameters in the curve fit weretaken as important features of the data set. A classifica-tion tree was used to extract the most important fea-tures. These features were then used in an artificialneural network for classification. Using the ‘leave-one-out’ method for validating the model, a classificationrate of 76% was obtained. The detection and simulta-neous identification of a range of microorganisms bymeasuring the volatile compounds produced from platecultures has been carried out using a neural networkclassifier (Gibson et al., 1997). Headspace samples weretaken from static atmospheres formed from inoculatedagar plates after a suitable growth period at 37°C andanalysed using a standard 16 sensor array. The sensorarray was made up of 16 different electroconductivepolymer materials and was operated in a transient flowmode. Electropolymerisation of a variety of monomericsubstrates selected from different heterocyclic com-pounds, such as substituted pyrroles, thiophenes andanilines was the basic method of sensor production.The response curves produced were processed usingstandard back propagation neural network techniquesto provide identification. The overall classification ratefor 12 different bacteria and one pathogenic yeast was93.4%. Data for a sub-set of seven bacteria gave 100%classification using the same methods. Thus, an array of‘conductive polymer’ sensors with different chemicalsensitivities produces a set of different responses to thesame odor. The responses are analyzed mathematically,using pattern recognition techniques, to differentiatebetween different odors with a high level of sensitivity.

In microbiology the smell of a culture of bacteriaoften provides a clue to the identification of the organ-ism present and it is usual for trained microbiologists tobe able to identify microorganisms by smell alone (Gib-son et al., 1997). A deterioration in food freshness isoften associated with microbial spoilage. A largeamount of different gaseous components are releasedfrom substrates contaminated with spoilage organisms.The traditional approach to characterize volatile com-pounds has been sample extraction followed by GC-MSanalysis. This approach is very tedious and requiressome knowledge of the molecules involved. Frequently,


several variables such as pH value, acidity, carbohy-drate, temperature, protein may all need to be keptwithin narrow target bands (Kress-Rogers, 1997). Inthis plane, an electronic nose can be applied either inmonitoring factors influencing spoilage or in monitor-ing factors indicating spoilage. Blixt and Borch (1999)described the use of an electronic nose in the quantita-tive determination of the degree of spoilage of vacuum-packaged beef. Beef from four different slaughterhouseswas sliced, vacuum-packaged and stored at 4°C for 8weeks. Samples were withdrawn for bacterial analyses(aerobic bacteria, lactic acid bacteria, Brochothrix ther-mosphacta, Pseudomonas and Enterobacteriaceae) andanalysis of the volatile compounds during the storageperiod. A trained panel was used for the sensorialevaluations. The volatile compounds were analysed us-ing an electronic nose containing a sensory array com-posed of 10 metal oxide semiconductor field-effecttransistors, four Taguchi type sensors and one CO2-sen-sitive sensor. Partial least-squares regression was usedto define the mathematical relationships between thedegree of spoilage of vacuum-packaged beef, as deter-mined by the sensory panel, and the signal magnitudesof the sensors of the electronic nose. The mathematicalmodels were validated after 6 months using a new set ofsamples. The stability of the sensors during this periodwas examined and it was shown that the sensitivity offive of the 11 sensors used had changed. Using the sixremaining sensors, the signal patterns obtained fromthe meat from the different slaughterhouses did notchange over a period of 6 months. It was shown thatthe degree of spoilage as calculated using a model basedon two Tagushi sensors, correlated well with the degreeof spoilage determined by the sensory panel. Thespoilage of raw meat caused by microbiological pro-

cesses taking place during storage represents a greatproblem in the meat industry (Haugen and Kvaal,1998). The method currently used for determining thestatus of meat, with respect to spoilage, is analysis ofthe total bacterial count. A drawback with the bacterio-logical method is the incubation period of 1–2 daysthat is required for colony formation. Instead, thegrowth of specific spoilage bacteria can be analysed.Chemical compounds such as acetate, ethanol, lacticacid, CO2 may be used as spoilage indicators in meatproducts (Dainty and Mackey, 1992; Dalgaard, 1995;Borch et al., 1996). Winquist et al. (1993) used an arrayof 10 MOSFET, five Taguchi (MOS) and one IR-basedCO2-sensor, respectively, for measuring ground porkand ground beef during storage up to 8 days at 4°C.The storage time could be well predicted even with areduced number of sensors by using artificial neuralnetwork.

2.6. Commercial instrumental systems

A series of automated and semi-automated systemsfor microbiological analysis have been extensively de-scribed in a number of monographs, reviews and arti-cles (Eden and Eden, 1984; Nelson, 1985; Turner et al.,1987; Nakata and Yoshikawa, 1990; Feng, 1992; Stagerand Davis, 1992; Flint and Hartley, 1993; Fenselau,1994; Sharpe, 1994; Tietjen and Fung, 1995; Hobson etal., 1996; Wang et al., 1997a,b,c; Zhai et al., 1997; Zhuand Wang, 1997). A list of commercial devices availablefor identifying bacteria is shown in Table 3. Cobra 2024(Biocom, France) is one of the completely automatedmicroscopic counting systems. It features three comput-ers, attending to the sample preparation, staining, filtra-tion, drying and image analysis. This system is capable

Table 3Manufactures and/or developers of the commercial instruments for detection of bacteriaa

Commercial instrument Detection technique Detection limit Analysis time(min, h)(cells/ml)

Midas Pro (Biosensori SpA., Milan, Italy) Amperometry 106 20 minPiezoelectric 106 40 minThe PZ 106 Immuno-biosensor System (Universal Sensors, New Orleans,

USA)ImpedimetryBactometer (Bactomatic, Princeton, NJ, USA) 105 3–8 h

1 cell/g 2 daysDNA probe for SalmonellaIntegrated Genetics, MA, USADNA probe for the bac- – –Enzo Biochem, NY, USAterium ChlamydiaDNA probe for bacteriaHybritech, CA, USA – –ConductanceMalthus 2000 (Malthus Instruments, Stoke-on-Trent, England, UK) 105 8–24 hBioluminescenceUnilite (Biotrace, Bridgend, UK) 103 15 min

Lumac Biocounter (Lumac B.V., Schesberg, Netherlands) Bioluminescence 103 20 minCoulter counter 5×104 30 minCoulter counter (Coulter Electronics, Canada)Microcalorimetry 105 3 hThermal activity monitor (Thermometric, Northwich, Cheshire, UK)

1 h105BIA-core (Pharmacia, Uppsala, Sweden) Surface plasmon resonanceVitek AutoMicrobic System (BioMerieux Vitek, Hazelwood, MO) Optical 104 4 h

a Nelson, 1985; Feng, 1992; Tietjen and Fung, 1995; Hobson et al., 1996.


of detecting bacteria with a lower detection limit of2×104 CFU/ml with a throughput rate of 150 samples/h (Sharpe, 1994). The AutoMicrobic System with thegram-negative identification card (GNI), the gram-posi-tive identification card (GPI) and the Yeast Biochemi-cal test kit (Vitek Systems, Hazelwood, MO) consists ofa filling-sealer unit, a computer, an optical reader dataterminal, and a multicopy printer. The GNI systemcorrectly detected Salmonella, E. coli and other Enter-obacteriaceae isolated from food samples (Knight et al.,1990; Stager and Davis, 1992) and confirmed identifica-tion by the GNI is reported in 4–18 h. In the review ofStager and Davis (1992), the analytical characteristicsof the Vitek Systems were discussed in detail.

Two commercial devices are currently available forpreparing PZ immunosensors. The PZ 106 Immuno-biosensor System (Universal Sensors, New Orleans, LA70148, USA) contains a liquid flow cell and a computerprogram to make real time assays of biospecific interac-tions. The second is model QCA 917 (EG & G, Prince-ton Applied Research, Princeton, NJ, USA) designedfor simultaneous electrochemical and weight measure-ments using a dip or a well holder.

The impedance principle is applied to microorganismmonitoring in commercial analytical systems such asthe ‘Bactometer’ of BioMerieux Vitek, and ‘Bacto-bridge’ (Nelson, 1985; Swaminathan and Feng, 1994;Hobson et al., 1996). Bactometer and its modificationsis the registered trademark for a series of automatedsystems for microbiological analysis that are made byBactomatic (Princeton, NJ). These devices have beenused for detection of microbial growth in blood, cere-brospinal fluid, and urine. The Bactometer incorporatesan electronic analyzer-incubator, a microcomputer withspecialized software, display and test card reports. Theinstrument can measure bacteria (after a preenrichmentstep) in 24–48 h when the bacterial concentrationreaches 106–107 cells/ml. The Bactobridge (TEM, Cen-tronic Sales, King Henry’s Drive, New Addington, UK)uses a pair of special conductivity cells, which havewell-matched capacitance and thermal properties. Eachcell has a 100 ml volume containing gold-plated elec-trodes. The bridge is activated by a 10 KHz alternatingcurrent. Results are recorded on a computer and 103

CFU/ml can be detected within 3 h of incubation.Unlike the devices mentioned above, the Malthus

Microbiological Analyzer (Malthus Instruments, Craw-ley, West Sussex, UK) and the Malthus M1000S fromRadiometer America use conductance technology toestimate microbial populations including coliforms, lac-tic acid bacteria, fungi and yeasts (Feng, 1992; Gibsonet al., 1992; Tietjen and Fung, 1995; Hobson et al.,1996). This analyzer detects changes in the electricalconductance of media caused by the growth andmetabolism of microorganism. Salmonella positive sam-ples can be detected in 24 h (which includes the preen-

richment step) while negative tests require 40–46 h. Themain problems of the impedimetric and conductimetricdevices are their high cost of instrumentation andlengthy incubation times.

The Lumac Biocounter, Netherlands and the‘Unilite’, UK are developed for the estimation of mi-crobial biomass based upon the bioluminescence princi-ple. This approach is based on the fact that allmicroorganisms, except for viruses, contain ATP. Thereaction is so specific for ATP that using a relativelycrude preparation of luciferase, luciferin, and magne-sium ion, a very specific and sensitive assay for mi-croorganisms can be developed. Both analyzers candetect microorganisms in the range of 103 cells/ml in 10min (Neufeld et al., 1985; Hobson et al., 1996). How-ever, in the assay of milk and other biological samples,it is necessary to remove non-bacterial ATP present insomatic cells. More detailed information regarding au-tomated system for microorganisms including compari-son of features of automated identification systems canbe found in reviews (Feng, 1992; Stager and Davis,1992; Sharpe, 1994; Tietjen and Fung, 1995; Hobson etal., 1996).

3. Conclusions and future avenues

Analysis of published literature has shown that de-spite the great R&D effort spent on developing biosen-sors in the last years, only a few biosensors for bacterialdetection are commercially available or are approach-ing commercialization. The main reasons for this areboth technology and market related. It is a challenge tocreate biosensors with the necessary properties for reli-able and effective use in routine applications. Thebiosensor system must have the specificity to distinguishthe target bacteria in a multi-organism matrix, theadaptability to detect different analytes, the sensitivityto detect bacteria directly, on-line without preenrich-ment and the rapidity to give real-time results. At thesame time, the biosensor must have relatively simpleand inexpensive configurations. Another obstacle is thetendency to focus only on the scientific basis of thetechnology while excluding the other equally importantaspects. Research usually proceeds without a definedspecification that is adhered to. There are a number ofpractical and technical issues which must be overcomein the development of bacterial biosensors for theircommercialization. Table 4 illustrates the typical fea-tures of the ‘ideal’ biosensor. There is no biosensorsystem-to date-that has a bacterial specificty as that ofthe plate culture method, which is one of the crucialrequirements of todays market. Obviously, enhancingthe specificty of biosensor systems and incorporation ofall the features in Table 4 within one bacterial biosen-sor device is a very complicated task. This is the main


Table 4A summary of the requirements for a bacterial biosensor

Low detection Ability to detect a single bacterial cell in alimit reasonably small sample volume (from 1 to

100 ml)Ability to distinguish an individual bacterialSpecies selectivityspecies in the presence of other microorgan-isms or cellsAbility to distinguish an individual bacterialStrain selectivitystrain from other strains of the same species5–10 min for a single testAssay time1%PrecisionNo reagent addition neededAssay protocolDirect, without pre-enrichmentMeasurement

Format Highly automated format (‘single buttondevice’)

Operator No skill needed to use the assayViable cell count Should discriminate between live and dead

cellsCompact, portable, hand-held, design for fieldSizeuse

formulations, they still represent the first generation ofdevices used to identify bacteria. It is our understand-ing that in the near future the second generation ofbiosensors will be fully automated analytical systems(Total Analytical Systems) based on combining of amulti-sensor technology with artificial neural network(as in the case of the electronic nose) or with otheranalytical and discriminative mathematical methods.The potential of the electronic nose approach withinthe food and drink industry, medical diagnostics andenvironmental control lies in the speed and simplicity ofthe method and also in the non-destructive determina-tion of the sample. Artificial neural networks do notrequire any expert knowledge once programmed, andthe only task of the operator is to indicate the objectsto be recognized after which the network functions onits own.

There are several markets which could support stand-alone biosensors. Highly sensitive and accurate biosen-sor systems could have great application in the medicaldiagnostics, food quality control, environmental moni-toring, defense and other industries, particularly ifbiosensors could be designed such that multiple ana-lytes could be detected simultaneously. The medicaldiagnostics field offers real opportunities for the ex-ploitation of biosensors for bacterial detection. In fact,the opportunities for biosensors to enter into the clini-cal diagnostic market are wide open since few productshave been commercialized. The most viable openings inthe food industry will arise where a biosensor canrapidly detect total microbial contamination. Thelargest area of application for the environment lies inthe development of biosensors for monitoring bacteriain drinking and waste water, rivers, reservoirs andsupplies.

Acknowledgements

The financial support of the DoE/Waste Manage-ment Education and Research Consortium of NewMexico is gratefully acknowledged. Dr. D. Ivnitskiwould like to thank the University of New MexicoSchool of Engineering for financial support.

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