Parallel acoustic detection of biological warfare agents surrogates by means of piezoelectric immunochips

Parallel acoustic detection of biological warfare agents surrogates by means of piezoelectric immunochips

Sensors and Actuators B 138 (2009) 532–538 Contents lists available at ScienceDirect Sensors and Actuators B: Chemical journal homepage: www.elsevie...

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Sensors and Actuators B 138 (2009) 532–538

Contents lists available at ScienceDirect

Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb

Parallel acoustic detection of biological warfare agents surrogates by means of piezoelectric immunochips Thomas Alava a , Nathalie Berthet-Duroure a , Cédric Ayela a , Emmanuelle Trévisiol a , Martine Pugnière b , Yannick Morel c , Pascal Rameil c , Liviu Nicu a,∗ a b c

LAAS-CNRS, 7 avenue du Colonel Roche, 31077 Toulouse, France CPBS-CNRS, Faculté de Pharmacie, 15 avenue Charles Flahault, 34093 Montpellier, France Centre d’Etudes du Bouchet, DGA/DET/CEB, 5 rue Lavoisier, 91710 Vert le Petit, France

a r t i c l e

i n f o

Article history: Received 15 December 2008 Received in revised form 9 February 2009 Accepted 20 February 2009 Available online 17 March 2009 Keywords: Biosensors Bioassays Quartz crystal microbalance Biological warfare agents

a b s t r a c t This paper focuses on flow functionalization of piezoelectric immunochips with antibodies against four different biological warfare agents (BWA) surrogates. To perform parallel detection of all BWA surrogates at once, the E4 Quartz Crystal Microbalance with Dissipation monitoring system (QCM-D) is used. Assessment of antibodies immobilization, parallel detection of related BWA surrogates diluted in buffer solutions and regeneration of the complex antibodies/BWA surrogates are first discussed. Minimal detection thresholds for Escherichia coli MRE 162, Bacillus atrophaeus, Cydia pomonella granulosis virus (CpGV) and ovalbumin are respectively equal to 2.4 × 107 CFU/mL, 1.4 × 106 spores/mL, 1.1 × 108 granules/mL and 1 ␮g/mL. Detection experiments for three of the four BWA surrogates (E. coli MRE 162, B. atrophaeus and ovalbumin) immersed in real liquid matrices from air sampler are successfully performed. © 2009 Elsevier B.V. All rights reserved.

1. Introduction Intelligence sources have systematically warned of the risk of terrorist organizations attack using biological weapons such as anthrax, ricin, botulinum toxin, smallpox, plague or Ebola. To efficiently face this contemporary threat (namely for biodefense and risk evaluation), an early and definite identification of bacteria, viruses and toxins is of enormous importance. Real-time biosensors that can quickly, cheaply, and accurately detect airborne biological warfare agents (BWA) might be one of the solutions. Actually, these biosensors may be roughly divided into two classes: the first class relies on sort of “physical profiling” of the BWA of interest by means of mass spectrometry [1,2], modern infra-red [3,4] and Raman spectroscopy [4,5], while the second class uses a specific biological recognition step that is provided by an appropriate ligand-receptor binding, such as antibody/antigen binding [6,7] or complementary binding of specific oligonucleotides to target DNAs [8]. In order to provide real-time detection and identification of BWA, the physical profiling methods target “marker” molecules specific only to the agent(s) to be detected through complete biological sample

Abbreviations: BWA, biological warfare agents; QCM, quartz crystal microbalance; SAM, self-assembled monolayer; MUA, mercaptoundecanoic acid; PBS, phosphate-buffered saline. ∗ Corresponding author. Tel.: +33 5 61 33 78 38; fax: +33 5 61 55 35 77. E-mail address: [email protected] (L. Nicu). 0925-4005/$ – see front matter © 2009 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2009.02.060

preparation/analysis (including collection, concentration, lysis, and analysis of the sample [9]). In case of biological recognition-based systems, the event of recognition/identification is revealed and reported in a certain measurable way. Antibody/antigen binding recognition-based systems (also called “immunosensors”) generally rely on highly sensitive devices (or transducers) to translate the biological recognition event into a physical signal variation. More precisely, antibodies are “grafted” onto the active surface of the transducer so that the event of antigen binding triggers changes of the transducer’s physical surface state (thus inducing readout signal variation) such as refractive indices of the layer in Surface Plasmonic Resonance case [10–12], orientation of molecules within the layer in “liquid-crystal” transducers [13] or the layer’s weight/thickness in Quartz Crystal Microbalance (QCM) transducer [14,15]. Compared to the other antibody/antigen binding recognition techniques that often suffer from either long analysis time, complicated procedures, non-portability or high costs [16], acoustic-based sensors (such as QCM) have attracted considerable interest for the development of BWA sensors. The QCM exploits the piezoelectric properties of a quartz crystal disc such as when an electric field is applied across electrodes placed on both sides of the crystal, it leads to a physical deformation of the disc (due to the so-called inverse piezoelectric effect) [17]. Perturbation of the resonant frequencies of the crystal is attributed to a change of mass on the modified electrode surface. The frequency and mass change on a QCM crystal surface is expressed by the well-known Sauerbrey equation

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[18]: f = −nCf f02

 m  A

where f is the frequency change, n the harmonic order, Cf the Sauerbrey constant, f0 the fundamental resonant frequency of the crystal, m the change in mass, and A is the sensing area of the crystal. Moreover, the measurement of the crystal’s dissipation energy (D) (as does the Q-Sense AB’s commercially available instrument QCM-D [19]) allows to interestingly getting information on the grafted layer’s viscoelasticity or conformational changes [6]. The sensitivity of the quartz crystal (that can be in the ng/cm2 range) prevents from tagging the analyte with a fluorescent or radioactive label thus making the QCM sensors an attractive analytical tool. Piezoelectric sensors (QCM-based) for viruses, bacterial spores and toxins have widely been reported during the last decade [20]. Su and Li [21] compared a SAM-based QCM immunosensor and a Protein A-based QCM sensor for the detection of E. coli O157:H7, one of the most dangerous foodborne pathogens. They demonstrated that the immunosensor could detect the target bacteria in a range of 103 –108 CFU/mL (where CFU stands for Colony Forming Units) within 30–50 min. Liu et al. [22] recently described that a minimal detection threshold of 102 CFU/mL could be achieved on a SAM-based immunosensor with nanoparticle amplification. A comparable response was obtained by Mao et al. [23] by using DNA-based QCM biosensors leading to a minimal detection threshold of 2.67 × 102 CFU/mL. Shen et al. [24] developed a functional mannose self-assembled monolayer in combination with lectin concanavalin A (Con A) for the detection of E. coli W1485 using a QCM as transducer. The multivalent binding of Con A to the E. coli surface O-antigen favours the strong adhesion of the bacteria to the mannose-modified QCM surface. The minimal detection threshold is 7.5 × 102 CFU/mL. Bacillus atrophaeus (historically referred Bacillus globigii or BG) is a Gram-positive, aerobic, endospore-forming, rod-shaped bacterium whose description is virtually identical to that of Bacillus subtilis except for the production of a pigment on media containing an organic nitrogen source [25]. Several of the strains of this Bacillus are used in industry as sterilization control organisms. Lee et al. [26] estimated that their “home-made QCM system” allows the detection of 450 spores of Bacillus subtilis on an immunosensorbased surface. BG is the most common surrogate used in biodefense studies. Some results suggest that the detection of viruses by QCM can give a comparable sensitivity that of an ELISA but not the one obtained by PCR or RT-PCR. Eun et al. [27] developed a QCM immunosensor for the detection of two orchid viruses by precoating the quartz with virus-specific antibodies. The minimal detection threshold was about 1 ng which is comparable to an ELISA. Dickert et al. [28] demonstrated that surface imprinting techniques on polymer-coated QCM could be used to detect tobacco mosaic viruses (TMV). Molecularly imprinted polymers (MIP), tailor-made by self-organization of monomers around the TMV were generated directly on the gold electrodes. The sensors are applicable to TMV detection ranging from 100 ng/mL to 1 mg/mL. Owen et al. [29] reported the development and characterization of a QCM sensor for the direct detection of aerosolized influenza A virions. Self-assembled monolayers of Mercaptol Undecanoïc acid (MUA) are formed on QCM gold electrodes to allow the immobilization of anti-influenza A antibodies using NHS/EDC chemistry. The limit of detection for this system is 104 particles/mL or 29.6 ng/mL. In the toxins detection field, Alfonta et al. [30] developed a method for detection of cholera toxin by coupling a piezoelectric immunoassay (monoclonal antibodies/protein G) to oxidation of 4-chloronaphthol with HRP in the presence of H2 O2 . This amplifi-

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cation resulted in very low detection limits for the toxin in the order of 10−13 M. Spangler et al. [31] evaluated a SPR and a QCM device for the detection of E. coli enterotoxin. They obtained a detection limit of 35 pmol (3 ␮g/mL) for the QCM device. The gold electrode was coated with ganglioside GM1. In this article, QCM-D multiplexed detection of Escherichia coli, B. atrophaeus, Cydia pomonella granulosis virus and ovalbumin (which are respectively BWA surrogates for plague bacteria, anthrax spores, smallpox virus and protein toxin) is presented for model as well as for real biological samples provided by a conventional air biocollector. Polyclonal antibodies for each agent are used as capture molecules. To build the sensing interface, a self-assembled monolayer of 11-mercaptoundecanoic acid (MUA) is generically formed on the gold electrode of quartz crystals and NHS/EDC coupling chemistry is used for covalent grafting of the anti-agent antibodies to the SAM surface. Aqueous solutions of BWA surrogates are flowed in parallel over four immunochips located in separate fluidic chambers in a first attempt to determine the detection levels as well as the specificity of each agent binding to the immobilized antibodies. In addition, series of supplementary experiments performed using dilutions of BWA surrogates in real biological samples provided by a conventional air biocollector confirmed the detection levels and the specificity of the recognition interactions between the agents and their specific antibodies. 2. Materials and methods 2.1. Material N-hydroxy-succinimide (NHS) and N-Ethyl-N -(3-Dimethylaminopropyl)carbodiimide were purchased from Fluka. Ethanol, sulphuric acid (H2 SO4 ) and hydrogen peroxide (H2 O2 ) were from Rockwood, Ethanolamine-HCl was from Biacore AB and 11-mercaptoundecanoic acid (MUA) was from Sigma–Aldrich. Phosphate buffer saline (PBS, 0.05 M, pH 7.4) and HEPES buffer (10 mM HEPES, 150 mM NaCl, pH 7.4) were used in the experiments. Air samples, BWA surrogates and their corresponding antibodies were prepared in the “Centre d’Etudes du Bouchet” (Délégation Générale pour l’Armement–France). Air was collected using a “cyclone” sampler (Biotrace International, UK) and concentrated in collecting buffer PBS Tween (0.01% v/v). Solutions containing decreasing amounts of BWA surrogates were prepared by dilution in PBS 1× from stock solutions respectively containing: 2.4 × 109 CFU/mL E. coli MRE 162, 1.4 × 109 spores/mL B. atrophaeus, 1.1 × 109 granules/mL C. pomonella granulosis virus (CpGV) and 1 mg/mL ovalbumin. Antibodies against these four BWA surrogates were produced in rabbits, purified and quantified. Solutions containing 50 ␮g/mL antibodies were prepared by dilution in PBS 1×. Detection was performed using the Q-Sense E4 system (Qsense), which enables to monitor resonance frequency and dissipation shifts on 4 sensor crystals at once. 2.2. Antibodies immobilization Antibodies were covalently immobilized on gold-coated quartz via a self-assembled monolayer of MUA. Each quartz sensor was immersed overnight, in the dark, in a solution of MUA (5 mM MUA in absolute ethanol). It was then washed in absolute ethanol, next in water, dried under a stream of nitrogen, and assembled into QCMD flow chamber. HEPES buffer was injected at a flow of 10 ␮L/min until signal stabilization was obtained. This flow value was used for the whole experiment. To activate carboxyl groups of surface-coated MUA, a solution containing 50 mM NHS and 200 mM EDC in HEPES buffer was injected for 20 min. Immediately afterwards, pure HEPES was

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injected for 5 min, and PBS 1× for another 5 min. Anti-agent antibodies diluted in PBS 1× were then flowed on sensor crystal until surface saturation was observed (60–120 min). PBS 1× was then injected to wash out any unbound antibody. At the end, unreacted binding sites were saturated with ethanolamine (1 M, pH 8.5, 30 min). PBS 1× was then injected until signal stabilization before detection test started. 2.3. BWA surrogates detection For each experiment, 4 quartz crystals were used simultaneously. Two of them were used for detecting specific BWA surrogates, while the other two quartz crystals were used as negative controls. For example, ovalbumin was simultaneously injected on two crystals, one coated with anti-ovalbumin antibody (detecting crystal), and the other coated with another antibody, for example, antiCpGV (negative control). In the same time, CpGV was injected on anti-CpGV antibody (detecting sensors), and on anti-ovalbumin antibody (negative control). This experimental set-up enabled to ascertain the specificity of each interaction. To determine detection levels, solutions containing increasing amounts of BWA surrogates were successively flowed over sensor crystals. For each concentration, signal stabilization was awaited before injection of the next solution. All the experiments were performed using the temperature control option of the QCM-D apparatus so that the temperature was maintained at 25 ◦ C. 2.4. Detection of BWA extracted from air samples In a second set of experiments, BWA surrogates were diluted in liquid matrices collected from air samples instead of PBS. The experimental set-up was the same, but collection buffer, and next pure air sample, were injected before detection tests started. Thus, signals corresponding to media viscosity changes were separated from signals corresponding to BWA surrogates fixation on antibodies. For some experiments, air samples were diluted 10 to 100 times in collecting buffer before being added to BWA surrogates solutions. 2.5. Sensor crystals washing and cleaning At the end of each experiment, crystal sensors were waterwashed and dried under a stream of nitrogen. The cleaning procedure consisted in dipping the crystal sensors in a “piranha” solution (H2 SO4 , H2 O2 , 50% v/v) for 10 min, then washing them as previously described.

Table 1 Relative variation of resonant frequency consecutive to the injection of three solutions with three different concentrations of antibodies on three different resonant crystals sensors in the QCM-D system. Concentrations of antibodies Variation of quartz resonance frequency (Hz)

25 ␮g/mL −19 Hz

50 ␮g/mL −40 Hz

100 ␮g/mL −42 Hz

results for the anti-B. atrophaeus antibody are shown; the procedure and the obtained results were similar for the other cases. The values of the resonance frequency shifts (calculated as the frequency values difference before antibodies injection and at the immobilization plateau) are indicated in Table 1. Moreover, Fig. 1 represents the evolution of the frequency signal in real time (during the immobilization phase) for the three concentration values. No release of antibodies was observed during the consecutive rinse step with a PBS 1× solution. Therefore, the relative decreases in the crystals’ resonant frequency indicate the effective grafting of the (BWA surrogates) antibodies onto the SAMs. The 50 ␮g/mL solution has been chosen as the optimum for the antibodies grafting. Indeed, although the immobilization process is steeper in the most concentrated solution case, the saturation level may be reached with less biological material when using less concentrated solutions. 3.1.2. Minimal detection threshold evaluation For each detection experiment, two crystals were mounted in the QCM-D system. Each time, one sensor was functionalized with antibodies against the concerned BWA surrogates while the other was functionalized with a different antibody. The BWA surrogate of interest was then injected on the two crystals at once. Therefore, the specificity of the resulting interaction (if any) has been evaluated. Four concentrations have been injected consecutively, each one corresponding to 10 times-fold dilution of the mother solution. The minimal detection threshold evaluation with the QCM-D apparatus has been performed for the four BWA surrogates. A typical series of frequency shifts corresponding to the consecutive recognition of BWA surrogates at different concentrations is shown in Fig. 2. Table 2 groups the values of resonance frequency shift obtained during the experiments. For each concentration, the resonant frequency level is calculated with respect to its initial level, before the first BWA surrogates solution injection. Specific detection is reported for ovalbumin with a minimal detection threshold of 1 ␮g/mL. In case of CpGV viruses,

3. Results and discussion The work is split into two parts: first, results related to BWA surrogates detection in buffer solutions (model samples) is reported, then detection of the same biological agents diluted in liquid samples obtained using a conventional air sampler is discussed. The latter solution is referred as “real samples” as they are getting closer to real biological recognition operations. 3.1. Detection in model samples 3.1.1. Optimization of antibodies immobilization protocol After forming the SAMs onto the gold-coated surfaces of the sensors (as indicated in Section 2), we determined the optimal concentration for antibodies solutions to be flown into the QCMD fluidic cells so that maximum immobilization levels could be obtained. Three different concentrations solutions (25, 50 and 100 ␮g/mL) of each antibody were injected onto separate sensors until stabilization of the frequency signal. In the following, only

Fig. 1. Curves for the resonance frequency shift observed for three QCM-D resonating crystals. The three different curves correspond to the injection and consecutive immobilization of antibodies from three differently concentrated solutions.

0 [0] 0 [0] −1.1 [0] 1.1 11 110 1.4 14 140 −1.4 [0] −6.3 [−1.7] −11.5 [−4] 1 10 100

−1 [0] −7.5 [0] −10.7 [−1.2]

2.4 24 240

0 [0] −2.8 [0] −12.6 [−1.2]

Specific frequency shift (Hz) [non-specific signal (Hz)] CpGV viruses

Concentration (×106 granules/mL) Specific frequency shift (Hz) [non-specific signal (Hz)]

E. coli

Concentration (×106 CFU/mL) Concentration (×106 spores/mL) Concentration (␮g/mL)

Specific frequency shift (Hz) [non-specific signal (Hz)] Bacillus atropheus

Specific frequency shift (Hz) [non-specific signal (Hz)] Ovalbumin

Table 2 Frequency shifts obtained during the minimal detection threshold determination experiments. The values shown are the shifts of resonance frequency for the quartz hosting the specific antigen/antibody reaction. If any, the shifts of resonant frequency for the quartz allowing the monitoring of non-specific interaction (negative control) are shown between parentheses.

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Fig. 2. Graph for variations of resonant frequency of two crystals during the B. atrophaeus (BA) detection experiment. One quartz sensor is functionalized with antiB. atrophaeus antibodies while the other bears anti-ovalbumin antibodies (negative control).

the minimal detection threshold of 1.1 × 108 granules/mL is to be compared with state of art results recently reported by Lee et al. [32] where the minimal detection threshold for similar biological species (Vaccinia viruses) was estimated at about 1.93 × 109 viruses/mL. Finally the minimal detection threshold s in case of B. atrophaeus and E. coli detection were respectively of 1.4 × 106 spores/mL and 1.4 × 107 CFU/mL. Non-specific fixation was observed for higher concentrations. Nonetheless, the phenomenon remains non-significant as the concerned concentrations imply rapid sedimentation of the biological species. One can be tempted to evaluate the performance of the concerned QCM-based detection protocol if included in an aerosolized BWA detection set-up. For instance, Campbell et al. [33] have presented a complete detection set-up for detection of airborne Bacillus anthracis spores and a mean to compute the minimum detectable airborne concentration of the concerned BWA directly from the minimum detectable concentration of BWA in liquid. The QCMbased immunosensing principle presented here is considered to be placed in a similar air sampling and detection set-up. The main changing parameter is the liquid flow in the tubing and sensor fluidic cell. Indeed, in our experimental protocols, the liquid flow rate value through the fluidic cells was fixed at 10 ␮L/min to allow the sample liquid enough time for temperature stabilization in the flow module before reaching the sensor surface. Consequently, the time of detection is about 40 min at least as the total volume of the tubing and fluidic cell equals 400 ␮L. As noted from Table 2, we reached a minimal detection threshold level for the B. atrophaeus of 1.1 × 106 spores/mL of liquid solution. If we came down to an estimation of Bacillus concentration per liter of air (using the transfer formulas as given in [32]), the minimal detection threshold of the QCM-D would be equal to 11771 spores/L of air. This value is extracted considering that the immunosensor (self-excited PZT-glass microcantilever) studied by Campbell et al. [33] is replaced by our QCM-based set-up. In case of Bacillus anthracis detection, the minimal detection threshold of the selfexcited piezoelectric microcantilever is estimated at 38 spores/L of air. The difference between the QCM-D and piezoelectric microcantilever minimal detection threshold can be explained by computing the ratio between the modal mass of the sensors and their corresponding quality factors. Indeed, such a ratio has been shown proportional to the minimum detectable mass of a mechanical biosensor by Wagonner and Craighead [34]. The mass of the piezoelectric microcantilever is evaluated to approximately 10−9 kg and its quality factor is 12. On the other hand, the mass of typical QCM-D quartz sensors can be estimated to 5 × 10−4 kg and its quality factor close to 2700. Therefore the ratio between the mass and the quality factor is approximated to 10−10 kg for the piezoelectric microcantilevers whereas it is of 10−7 kg in case of the

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Table 3 Frequency shifts for the detection threshold determination experiments for BWA surrogates diluted in air samples. The values shown are the shifts of resonance frequency for the quartz hosting the specific antigen/antibody reaction. If any, the shifts of resonant frequency for the quartz allowing the monitoring of non-specific interaction (negative control) are shown between parentheses. In the ovalbumin case, specific detection has been performed in air samples diluted ten times explaining the higher frequency shifts. Ovalbumin

Bacillus atropheus

E. coli

Concentration (␮g/mL)

Specific frequency shift (Hz) [non-specific signal (Hz)]

Concentration (×106 spores/mL)

Specific frequency shift (Hz) [non-specific signal (Hz)]

Concentration (×106 CFU/mL)

Specific frequency shift (Hz) [non-specific signal (Hz)]

1 10 100

−2.5 [0] −4 [−0.5] −10.5 [−6.5]

1.4 14 140

−0.5 [0] −2.5 [0] −3 [−0.2]

2.4 24 240

0 [0] −1.7 [0] −7 [−4]

Concentrated air sample

−1 Hz

Collector buffer

−2 Hz

QCM-D sensor. The same three orders of magnitudes are separating the QCM-D’s and piezoelectric microcantilever’s minimal detection threshold. 3.1.3. Regeneration Regeneration of sensors’ active surfaces has been successfully performed by mean of high-flow injection of small volume of sodium hydroxide inside the QCM-D microfluidic cells. Fig. 3 shows the typical resonant frequency graph obtained during the regeneration phase of the linkage between B. atrophaeus and its related antibody. This step was performed using 200 ␮L of 100 mM NaOH solution flowing through the fluidic cell at 100 ␮L/min. The characteristic increase of the resonant frequency is to be associated to the decrease of the dissipation signal. Both signals confirm the release of biological species. No decrease in resonant frequency has been observed for the negative control during this step. An attempt for a second consecutive detection has been successfully realized. The specific fixation of B. atrophaeus spores on anti-BA antibodies finally confirms that spores were actually released from the quartz without damaging the antibodies property of specific recognition. As shown in Fig. 3, the level of resonant frequency after the regeneration is slightly higher than the level before the first detection of BA spores (initial level for specific signal—0.2 Hz). A possible reason to this may be the formation of antibodies clusters in the neighborhood of binding sites during the functionalization step. The clusters, constituted close to covalently fixed antibodies on top of MUA molecules, may jeopardize further detection of BWA surrogates. Thus, as the injection of NaOH induces a drastic change in pH conditions, it also favors the washing of unbound antibodies. Therefore the second detection of BA spores induces higher decrease in resonant frequency as the available binding sites are more accessible.

Fig. 4. Resonant frequency variations for two quartz sensors functionalized respectively with anti-BA antibodies and anti-E. Coli antibodies (negative control) during the attempt of determination of detection threshold for B. atrophaeus in air samples.

3.2. Detection in real samples. Minimal detection threshold evaluation The same protocol as previously described has been used to perform antigen detection experiments in representative environmental air samples. For this to be done, BWA surrogates solutions were mixed with liquid samples from collected air with “cyclone” sampler. Specific detection has been obtained in air sample for E. coli, B. atrophaeus and ovalbumin. Fig. 4 shows a typical graph of resonant frequency variation during the detection experiment of B. atrophaeus in air sample. Table 3 resumes significant resonant frequency shift values obtained from quartz sensors where specific biological recognition took place. It has to be pointed out that instabilities were observed on both resonance frequency and dissipation signals when compared to detection experiments using model solutions. Such instabilities tend to reduce the actual minimum detection threshold of the quartz sensors, as the discrimination of the specific biological recognition from the negative control is harder to achieve. In many cases, monitoring of the dissipation signal was mandatory for validating the specific detection. Generally, the decreases of resonant frequency corresponding to BWA surrogates trapping from environmental air samples exhibited smaller values than for detection in model solutions. Meanwhile, the same signals related to nonspecific detections were more important. Starting conditions of minimal detection threshold determination experiments for ovalbumin in model solutions and in environmental samples (quality, aging of the gold quartzs) might explain the difference from the trends for the lowest concentration (1 ␮g/mL). 4. Conclusion

Fig. 3. Resonant frequency variation of two quartz sensors functionalized respectively with anti-BA antibodies and anti-ovalbumin antibodies (negative control) during the validation of the regeneration procedure.

In conclusion, the work presented in this paper has lead to the assessment of SAM-based functionalization gold surfaces with anti-

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bodies against BWA surrogates. Detection of E. coli, C. pomonella granulosis virus, ovalbumin and B. atrophaeus has been achieved. The resolution obtained for C. pomonella granulosis viruses is better than currently claimed resolutions in the state of art for QCM-based immunosensing. The regeneration of the immobilized antibodies has been realized and provens efficient with successive specific detection of BWA surrogates with the same antibodies. Detection of BWA surrogates has also been realized successfully in samples from natural aerosol biocollection. The minimal detection threshold of QCM-based immunosensor presented in this work represents an upper limit below which will stand the future generation of MEMS-based immunosensors. Micro-mechanical biosensors, developed with small effective mass and high quality factor, are expected to offer significantly lower minimal detection threshold when placed in an aerosolized biowarfare agents detection set-up. Acknowledgment This work was supported by the Mission for Research and Scientific Innovation of French Delegation for Armament and Weaponry (DGA/MRIS) under Contract no. 06.34.025. References [1] B.L.M. Van Baar, Materials of the Second International Symposium on Detection Technologies, Knowledge Foundation, Arlington, VA, 2002. [2] C.A. Noble, K.A. Prather, Real-time single particle mass spectrometry: a historical review of a quarter century of the chemical analysis of aerosols, Mass. Spectrom. Rev. 19 (2000) 248–274. [3] K.C. Schuster, F. Mertens, J.R. Gapes, FTIR spectroscopy applied to bacterial cells as a novel method for monitoring complex biotechnological processes, Vib. Spectrosc. 19 (1999) 467–477. [4] W. Petrich, Mid-infrared Raman spectroscopy for medical diagnostics, Appl. Spectrosc. Rev. 36 (2001) 181–237. [5] M.O. Scully, G.W. Kattawar, R.P. Lucht, T. Opatrny, H. Pilloff, A. Rebane, A.V. Sokolov, M.S. Zubairy, FAST CARS: engineering a laser spectroscopic technique for rapid identification of bacterial spores, Proc. Natl. Acad. Sci. 99 (2002) 10994–11001. [6] C. Ayela, F. Roquet, L. Valera, C. Granier, L. Nicu, M. Pugniere, Real time interaction studies monitored by SPR and QCM: antibody detection with antigenic peptides immobilized on gold surfaces; suitable model for detecting autoantibody in human serum, Biosens. Bioelectron. 22 (2007) 3113–3119. [7] P.A. Emanuel, J. Dang, J.S. Gebhardt, J. Aldrich, E.A.E. Garber, H. Kulaga, P. Stopa, J.J. Valdes, A. Dion-Schultz, Recombinant antibodies: a new reagent for biological agent detection, Biosens. Bioelectron. 14 (2000) 751–759. [8] J.M. Walker, R. Rapley, Molecular Biology and Biotechnology, RSC, Cambridge, 2000. [9] J.C. Stachowiak, E.E. Shugard, B.P. Mosier, R.F. Renzi, P.F. Caton, S.M. Ferko, J.L.V. de Vreugde, D.D. Yee, B.L. Haroldsen, V.A. VanderNoot, Autonomous microfluidic sample preparation system for protein profile-based detection of aerosolized bacterial cells and spores, Anal. Chem. 79 (2007) 5763–5770. [10] J. Homola, S.S. Yee, G. Gauglitz, Surface plasmon resonance sensors: a review, Sens. Actuators B Chem. 54 (1999) 3–15. [11] X.D. Hoa, A.G. Kirk, M. Tabrizian, Towards integrated and sensitive surface plasmon resonance biosensors: a review of recent progress, Biosens. Bioelectron. 23 (2007) 151–160. [12] A.K. Sharma, R. Jha, B.D. Gupta, Fiber-optic sensors based on surface plasmon resonance: a comprehensive review, IEEE Sens. J. 7 (2007) 1118–1129. [13] V.K. Gupta, J.J. Skaife, T.B. Dubrovsky, N.L. Abbott, Optical amplification of ligand-receptor binding using liquid crystals, Science 279 (1998) 2077–2080. [14] C.K. O’Sullivan, G.G. Guibault, Commercial quartz crystal microbalance, Biosens. Bioelectron. 14 (1999) 663–670. [15] E. Uttenthaler, M. Schräml, J. Mandel, S. Drost, Ultrasensitive quartz crystal microbalance sensors for detection of M13-phages in liquids, Biosens. Bioelectron. 16 (2001) 735–743. [16] Y. Amano, Q. Cheng, Detection of influenza virus: traditional approaches and development of biosensors, Anal. Bioanal. Chem. 381 (2005) 156–164. [17] A.J. Bard, L.R. Faulkner, Electrochemical Methods, Fundamentals and Applications, John Willey & Sons, New York, 2001. [18] G. Sauerbrey, The use of quartz crystal oscillators for weighing thin layers and for micro-weighing, Zeitschrift für Physik 155 (1959) 206–222. [19] M. Rodahl, F. Hook, A. Krozer, P. Brzezinski, B. Kasemo, Quartz crystal microbalance set up for frequency and Q-factor measurements in gaseous and liquids environments, Rev. Sci. Instrum. 66 (1995) 3924–3930. [20] M.A. Cooper, V.T. Singleton, A survey of the 2001 to 2005 quartz crystal microbalance biosensor literature: applications of acoustic physics to the analysis of biomolecular interactions, J. Mol. Recognit. 20 (2007) 154–184.

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Biographies Thomas Alava was born in 1983 in Pau (France). After 3 years of attending lectures at Politecnico of Turin (Italy), at Ecole polytechnique fédérale of Lausanne (Switzerland) and at Institut National Polytechnique of Grenoble (France), he achieved his master of micro and nanotechnologies for integrated systems, delivered jointly by the three universities. He is currently, and since 2006, PhD student in the NanoBioSystems group at the LAAS (Laboratory for Analysis and Architecture of Systems) of Toulouse (France). He is working on the conception, fabrication and characterization of a platform, based on piezoelectric/piezoresistive resonant silicon micromembranes, for biosensing applications. Nathalie Duroure was born in 1983 in Figeac (France). After completing her master of biotechnologies at the Institut National des Sciences Appliquées (Toulouse, France) in 2005, she joined the Biochips platform were she prepared her PhD, in strong interaction with the NanoBiosystems Group at the LAAS (Laboratory for Analysis and Architecture of Systems). Indeed, her interest is focused on developing interdisciplinary approaches to answer biotechnological issues. More precisely, her research topics included high density biochips, single cell analysis or molecular endoscopy. She is now working for the French start-up MicroBioChips, where she develops the Bioplume technology. Cédric Ayela was born in Tarbes (France) in 1981. He received the engineer degree in electronics from the National Institute of Applied Sciences in Toulouse and a PhD degree on label-free real-time techniques for the quantitative measurement of biological interactions in 2007. More specifically, he developed matrices of piezoelectric micromembranes for the integrated detection of biological molecules at the Laboratory for Analysis and Architecture of Systems (LAAS-CNRS) in Toulouse. He recently integrated the French National Center for Scientific Research (CNRS) as a full-time researcher at IMS laboratory in Bordeaux (France). He is focusing his researches on developing polymers-based MEMS. Emmanuelle Trevisiol was born in 1970 in Brianc¸on (France). She received the master of science degree in biochemistry at the J. Fourier University (Grenoble, France) in 1996 and the PhD degree in bioorganic chemistry (LEDSS, Grenoble, France) in 1999. She joined the Biochip platform group (LISBP-Toulouse) in 2002 as full time researcher (CNRS). Her activities include synthesis of modified triphosphates, the post-labelling of DNA for diagnostic purpose, resequencing on DNAchip and, more recently, the functionalization of glass and silicon slides for biochip applications (DNA, protein or carbohydrate chips).

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Martine Pugniere was born in 1957 in Khouribga (Maroc). After two PhD (1983 and 1991) in chemistry and biotechnology at the University of Sciences of Montpellier in an INSERM group directed by Dr. CRASTES DE PAULET and then Dr. DESCOMPS, she joined the INSERM institute as a research scientist in 1987. Since 1998 her area of expertise has included the study of biospecific interactions by Surface Plasmon Resonance in the fields of immunoanalysis and pharmacology, CNRS-UMR 5160 (directed Prof. B. PAU and Dr. P. PETIT) and since 2005 she is currently in charge of research on the topic “Kinetic study of interactions” in the group of “Prokaryotic Transcription, kinetic and pharmacology of the interactions” in CNRS-UMR 5236 (directed Dr. C. DEVAUX) Montpellier, France. For 8 years she was at the head of protein interaction (Biacore) facility. Yannick Morel was born in 1971 in Montpellier (France). After graduating from Ecole Polytechnique in 1995, he completed a master and a PhD in molecular biology at INSERM (National Institute for Medical Research) in the U490 Unit (gene regulation of xenobiotic-metabolizing enzyme especially cytochromes P450) and followed research management (HDR habilitation) on paraoxonase. Since 2000 he joined the CEB (Centre d’Etudes du Bouchet - DGA, French MoD, which is the national reference establishment for biological and chemical defence, technologies both for the armed and national security), first as engineer in biological risk assessment then as group leader for biodetection technologies. He currently manages the biological activities of CEB. He published 15 articles as first or last author. Pascal Rameil was born in 1974 in Toulouse (France). After completing his master of immunology at the Luminy University of Marseille (France) in 1996, he

joined the Transcription Group at the Cancer Research Center (INSERM, National Instute for Medical Research) of Marseille where he got his PhD in 2000 into the transcription CD25/Il-2R␣ gene control field. Between 2000 and 2001, he did one’s military service at CRSSA (Health Service Research Center for Armed Forces), La Tronche (France). Since 2001 he joined, as a full time research engineer, the Detection Biotechnology Department at CEB (Centre d’Etudes du Bouchet - DGA, French Armament procurement Agency–French Defence Minister) which is the national reference establishment in the area of biological and chemical defence, working for the armed forces as well as for the benefit of national security. Liviu Nicu was born in 1973 in Bucharest (Romania). After completing his master of electrical engineering at the Paul Sabatier University of Toulouse (France) in 1997, he joined the Integrated Microsystems Group at the LAAS (Laboratory for Analysis and Architecture of Systems) of Toulouse where he got his PhD in 2000 into the micromechanical structures field. Between 2000 and 2003, he was R&D Engineer at Thales Avionics, Valence (France). His activities focused onto the development of micromechanical sensors for the civil and military navigation applications. Since 2003 he joined the Nanoadressing and Nanobiotechnology Group at LAAS as a full time CNRS (National Center of Scientific Research) researcher where he currently works in two main research fields: the development of (1) new resonant bio(chemical)sensors using M(N)EMS technologies and of (2) cantilever-based microsystems for contact deposition of small amounts of biological samples for biochip applications.