- Email: [email protected]
Love wave biosensor for real-time detection of okadaic acid as DSP phycotoxin
Sensors and Actuators B 170 (2012) 122–128
Contents lists available at ScienceDirect
Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb
Love wave biosensor for real-time detection of okadaic acid as DSP phycotoxin F. Fournel a,∗ , E. Baco b , M. Mamani-Matsuda c , M. Degueil b , B. Bennetau b , D. Moynet c , D. Mossalayi c , L. Vellutini b , J.-P. Pillot b , C. Dejous a , D. Rebière a a b c
Université de Bordeaux, IMS, ENSEIRB, CNRS UMR 5218, Talence 33405, France Université de Bordeaux, ISM, CNRS UMR 5255, Talence 33405, France Université de Bordeaux, Laboratoire d’Immunologie/Parasitologie, UFR Sciences Pharmaceutiques, Bordeaux 33076, France
a r t i c l e
i n f o
Article history: Received 29 September 2010 Received in revised form 21 February 2011 Accepted 23 February 2011 Available online 30 March 2012 Keywords: Acoustic wave Phycotoxin Microfluidic Biodetection
a b s t r a c t This paper reports the detection of okadaic acid (OA) as a Diarrheic Shellfish Poisoning (DSP) toxin with an acoustic wave platform in real-time. According to the FDA, the threshold for safe consumption of shellfish is 20 g of OA for 100 g of shellfish tissue. The high gravimetric sensitivity of Love wave acoustic devices allow, in liquid media, immuno-detection thanks to immobilized specific antibodies. The biosensor is composed of two lines, one for the test and one used as a reference. Sensitive films were deposited through a PolyDiMethylSiloxane (PDMS) microfluidic chip. On both lines, anti-okadaic acid antibodies (OA-Ab) and saturating agents were successively injected under continuous flow with controlled flow rate. On the test line, okadaic acid (OA) was injected while an unspecific peptide (6×Histidine, 6×His) was used on the control line. On both lines, polyclonal OA-Ab were re-injected a second time to reveal previously fixed OA on the test line. Measured frequency shifts were three times higher on test lines than on control lines. In these conditions, for only 2 g of OA used for detection, the acoustic wave platform could detect DSP toxins with only 10 g of shellfish tissue. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Food poisoning caused by bacteria, fungi or viruses represent a major public health problem with significant economic consequences [1]. It has been estimated that 40% of the total annual deaths world-wide were due to infectious diseases caused by these harmful micro-organisms and, each year, 200 million people suffer from non-lethal infections [2,3]. Although not infectious, shellfish
Abbreviations: OA, okadaic acid; DSP, diarrheic shellfish poisoning; FDA, food and drug administration; Ab, antibody/antibodies; OA-Ab, anti-okadaic acid antibody, antibody specific to okadaic acid; 6×His, 6histidines coupled together; OD, optical density; SAW, surface acoustic wave; IDT, interdigital transducer; PECVD, plasma-enhanced chemical vapor deposition; PDMS, polydimethylsiloxane; GPTS, (3-glycidoxypropyl)-trimethoxysilane; SBBB, starting blockTM blocking buffer; TBS, tris buffer saline; ELISA, enzyme-linked immunosorbent assay. ∗ Corresponding author. Tel.: +33 540006581; fax: +33 556371545. E-mail addresses: [email protected] (F. Fournel), [email protected] (E. Baco), [email protected] (M. Mamani-Matsuda), [email protected] (M. Degueil), [email protected] (B. Bennetau), [email protected] (D. Moynet), [email protected] (D. Mossalayi), [email protected] (L. Vellutini), [email protected] (J.-P. Pillot), [email protected] (C. Dejous), [email protected] (D. Rebière). 0925-4005/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2011.02.056
poisoning represent a serious threat [4,5]. Toxins are produced by harmful algae species but their potential poisoning is not directly correlated with the cell concentration. Temperature, salinity of water, macronutrients and other environmental factors have to be considered [6]. Thus, direct measurement of phycotoxins, contained in phytoplanktons, is needed in addition to phytoplankton detection to meet FDA health requirements, as stated by Doucette et al. [7]. Investigations on more rapid, sensitive, selective, portable, power-efficient and low-cost methods have to be carried out as noticed by Rocha-Gaso et al. [8]. Some improvements in the development of systems capable of generating real- or near real-time data for certain harmful algal species have already been published [9–11]. These new developments mainly regarded molecular probe-based methods with antibody recognition coupled with embedded systems allowing spectrometric measurements and remote data transmission [7]. Over the last decades, surface acoustic wave devices have been successfully used for real-time biosensing of cells, bacteria and molecules [8]. In particular, Love wave platforms offer high potentialities in terms of mass loading sensitivity in liquid media and have proven their ability for bacteria detection [12]. The aim of this paper is to demonstrate the feasibility of phycotoxin detection in real-time by using a Love wave platform with a microfluidic feature and an ELISA-like protocol.
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
123
2. Materials and methods 2.1. Love wave sensors The Love wave sensor platform is composed of a Quartz substrate, Interdigital Transducers (IDTs) as input and output ports of the delay-line, a SiO2 guiding layer and an immuno-sensitive coating. IDTs consisted of 44 pairs of split-fingers ( = 8 m × 5 m) whose geometrical parameters are defined in Fig. 1. They were composed of Gold–Titanium as adhesion layer (total thickness about 200 nm), and deposited through a lift-off technique on the Quartz piezoelectric crystal (AT-cut, Euler angles: 0◦ , 121.5◦ , 90◦ ). A 4.5 m thick SiO2 guiding layer was deposited all over the substrate by using a PECVD technique, and then etched to access the electrical contacts. Thanks to the shear horizontal polarization of the waves, Love wave devices can be used as sensors in liquid media. The controlled thickness of the guiding layer enables to trap the acoustic wave energy near the sensing surface, improving the sensitivity to surface variations. The resulting synchronous frequency of the Love wave platform was near 117 MHz. Placed in an oscillator configuration, the short-term stability of the device in steady-state was lower than 1 Hz s−1 . 2.2. PDMS microfluidic chip In order to improve detection resolution and save biological material, a continuous micro-flow was applied at the sensor surface with a polymeric chip maintained by pressure onto the sensor (Fig. 2). The microfluidic chip was designed by using COMSOL® software in order to control liquid flow over the sensor without vortex and favouring a homogeneous species distribution (Fig. 3). The microchamber volume was limited by the chip cavity and the sensor acoustic path surface. The resulting micro-chamber dimensions (Fig. 2a) were 31.3 mm2 by 100 m in height, corresponding to 3.1 l. This weak volume allowed biological product saving. Additional air cavities have been designed above the IDTs to protect them from liquid polarity perturbation due to ionized water, while not being in contact with the polymeric chip, which is an acoustic absorbent [13]. One hundred microns thick walls ensured the sealing of the micro-chamber without causing excessive attenuation of the wave. The chip was 10 mm high, calibrated to ensure constant pressure and to enhance the reproducibility. This microfluidic chip was made of Polydimethylsiloxane (PDMS, Dow Corning, Sylgard 184 Silicone Elastomer Kit) by using soft lithography [12,13] and molding techniques developed by Hakim Tarbague [14]. As a first step, a SU-8 photoresist (Microchem, SU-8 2075) spin-coated on a 4 silicon wafer was insulated through
Fig. 2. (a) Conceptual design of the microfluidic chip drawn with Google Sketchup® , micro-chamber surface: 31.3 mm2 . (b) Final PDMS microfluidic chip.
a negative mask (Fig. 4a). The resulting pattern was used to create the bottom part of the microfluidic chip, in contact with the sensor surface. A mixture of PDMS and its cross-linker (ratio 10:1, respectively) was poured on the micro-pattern for molding (thickness about 3 mm) (Fig. 4b). After cross-linking, this PDMS part,
Fig. 1. Dual Love wave delay-line geometry. (a) Electrode pads for electrical input or output. (b) Acoustic wave path, centre-to-centre length (Lcc ) is 8.4 mm. (c) IDT wavelength is 40 m. Effective aperture w is 1.6 mm.
124
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
Fig. 3. Flow simulation in the PDMS chip with COMSOL software: (left) velocity flow lines. For typical flow rate of 10 l/min, velocity on the central flow line is 0.5 mm/s and average renewal time for 75% of the microchannel is 16 s. (Right) antibody distribution on the sensor surface was homogeneous along the acoustic wave path for flow rate under 10 l/min (simulation with diffusion/convection module).
Fig. 4. PDMS microchip molding protocol.
containing the microfluidic shape, was cut off and placed into an aluminum mold (Fig. 4c). The PDMS mixture was poured again and a cover was used to calibrate the microchip height to 10 mm. The final chip was unmolded and pipe holes were drilled through as inputs and outputs of liquid (Fig. 4d).
solubilised in H2 O at 100 g/ml (Fig. 6a). OA has a molar mass about 805 g mol−1 for 44 carbon atoms. The peptide 6×Histidine (6×His, from Genecust), with a molar mass about 930.9 g mol−1 for 36 carbon atoms and a similar geometry, has been used for control purposes (Fig. 6b).
2.3. Instrumentation description The sensors were inserted on the detection platform with the PDMS microfluidic chip after the chemical functionalization process; the Self Assembled Monolayer (SAM) made of (3-glycidoxypropyl)-trimethoxysilane (GPTS) ensures covalent binding with the SiO2 guiding layer and with antibodies [12]. Entry cones were used to inject species and tubes were connected to a syringe pump (BioSeb, ref: BS-9000-8) pulling the liquid with glass syringes (Hamilton, 10 ml, ref: GASTIGHT #1010) (Fig. 5). Tris buffer saline (Sigma, ref: T6664-10PAK) was used as a reference medium, ensuring flow continuity during the whole protocol. 2.4. Okadaic acid and 6×Histidine Detection tests were made with a commercial okadaic acid (OA, from LC Laboratories, Cat O-2220, or from Sigma–Aldrich, O8010),
Fig. 5. Instrumentation bench: composed of a dual Love wave delay-line, a PDMS microfluidic chip, a cell test (not represented), and a cone/hose/syringe for each line (only one is represented).
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
125
Fig. 6. Chemical formulas. (a) Okadaic acid. (b) 6×Histidine (synthesized molecule).
As shown in Fig. 7 and taking into account standard deviations, the dilution of 1/400 provided significant results about complex formation between OA and OA-Ab. For the Love wave biosensor protocol, antibody solutions were diluted by 3.5 in the entry cone before reaching the microfluidic chamber. Thus, the 1/100 diluted antibody solution was chosen for injection in entry cones. More concentrated solutions gave similar results.
2.6. Okadaic acid detection protocol
Fig. 7. Direct ELISA test of the polyclonal rabbit anti-OA antibodies for different dilutions. The blank corresponds to PBS alone (no antibody). Significant responses are those with an optical density (OD) superior to three times the blank optic OD (red line). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
2.5. Anti-okadaic acid antibodies In order to ensure a specific detection of the OA, commercial specific anti-OA antibodies (OA-Ab, polyclonal rabbit anti-OA, Abcam, ref: ab-2897) have been used. An ELISA test was performed for antibody titration; OA was coated on each well at 10 g/ml, then were injected different dilutions of the OA-Ab original solution, from 1/100 to 1/6400 (Fig. 7). All the dilutions were made in phosphate buffer saline (PBS).
The immuno-sensitive layer was prepared with 20 l of OA-Ab (at 1/100 from original solution) for grafting onto GPTS modified sensor surface (Fig. 8a). To prevent non specific binding on the surface, a solution of 20 l of StartingBlock Blocking Buffer (SBBB, Thermo Scientific, ref: 37542), a saturating agent composed of molecules with different sizes, was then injected (Fig. 8b). Species injections were always made when 50 l of TBS were left in cones. Flow rate was fixed at 10 l/min. This allowed both coating effect (with mass-loading) and cleaning of molecules that were not covalently bonded on the surface. After the immuno-sensitive layer preparation, a solution of 20 l OA (2 g, concentration at 28 g/ml in the cone) was injected on the test delay-line (Fig. 8c), while 2 g of 6×Histidine (same concentration) were injected on the control line. Before injections, the flow rate had been reduced at 1 l/min in order to let these small molecules to reach the sensor surface. After 10 min, the flow rate was raised again to 10 l/min to clean the surface from nonimmobilized molecules.
Fig. 8. Protocol step representation, focus on the sensor surface. (a) OA-Ab coating. (b) Surface saturation. (c) OA complex formation. (d) Second injection of polyclonal OA-Ab.
126
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
Fig. 9. Frequency shift responses to mass-loading effect on the sensor surface (a) antibody covalent grafting trends. The 1/100 dilution of OA-Ab was used for all of them (concentration unknown). (b) and (c) Saturating agent coating trends with a flow rate of 1 l/min for (b) and 10 l/min for (c). (d) Mean frequency shifts and standard deviations for antibodies, saturating agent and assessment of the antibody surface covering rate.
Nor OA neither 6×His molecules were directly detected with significant frequency shifts. This was partially due to their low molecular weight. However, the sensitivity towards OA has been enhanced by a second injection of polyclonal OA-Ab, as different epitopes can be recognized like in a sandwich ELISA test (Fig. 8d) as presented in Section 3.2. The second injection of OA-Ab was done on both the test and the control lines. 3. Results 3.1. Immuno-sensitive layer frequency shifts Synchronous frequencies were acquired as species were covalently grafted onto the GPTS surface. Average frequency shifting for antibodies and saturating agent were, respectively, fA = −7.4 kHz (±23%) and fS = −1.8 kHz (±24%) (Fig. 9). Frequency shifts have been normalized to fit in one plot. Fig. 9a represents the sensor responses when antibodies were grafted onto the GPTS layer surface (flow rate set at 10 l/min), while Fig. 9b and c shows surface saturation by SBBB (flow rate of 1 or 10 l/min, respectively). It takes about 15 min at 1 l/min and 5 min at 10 l/min to clean unbonded molecules. Mean frequency shifts with standard deviations for antibodies, saturating agent and assessment of the covering rate of antibodies have been reported on Fig. 9d. To estimate the covering rate of antibodies on the sensor, the ratio (fR ) between antibodies and saturating agent frequency shifts was calculated for each experiment, according to the equation: fR = fA /(fA + fS ). This method indicated a covering rate of 80 ± 5% and was used to discriminate faulty
sensors. Including stabilization time, immuno-sensitive layer coating takes about 20 min. 3.2. Okadaic acid detection frequency shifts Fig. 10 presents typical frequency responses associated with the last step of the protocol (Fig. 8d), during the second injections of polyclonal OA-Ab. Frequency shifts on test lines are significant (average about 2 kHz) compared to previous injections of OA (not shown). Moreover, it can be seen that frequency shifts on test lines were 3 times (±9%) higher than on control lines (less than 800 Hz), whatever the flow rate was. Frequency needs 10 min to reach a steady-state with a flow rate of 1 l/min. At this speed, the stabilization trend is similar to those under static conditions [15]. The microfluidic device improves response trend quality. At 10 l/min, stabilization takes 5 min, thus, increasing the flow rate increases the mass convection on the sensor surface without changing the relative difference between test and control lines. 4. Discussion Controls prove that the frequency shifts on the test lines during the second antibody injection must be related to a specific antibody/antigen complex formation with okadaic acid. This demonstrates phycotoxin detection feasibility by acoustic wave sensors using a sandwich ELISA-like protocol. Including immunosensitive layer coating, phycotoxin and antibody injections, with steady-state periods between each protocol stage, the experiment duration time lasted less than 3 h.
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
127
The authors also want to thank Angélique Tetelin (IMS-Bordeaux) for English assistance. References
Fig. 10. Frequency shifts during second injection of polyclonal antibody. Dark curves indicate test line responses while gray curves indicate control line responses. (a) Flow rate of 1 l/min. (b) Flow rate of 10 l/min.
Food & Drug Administration have set the maximal concentration to avoid DSP poisoning at 0.2 ppm, e.g. 20 g of okadaic acid for 100 g of shellfish. Under the reported conditions, this method can significantly detect 2 g of okadaic acid, thus, only a small mixture of 10 g of shellfish food would be needed. Investigations to lower minimum toxin concentration for detection have yet to be taken. This quantity seems to be the detection limit of the Love wave platform. Although the frequency shift difference is significant, a smaller one could be confusing, leading to false positives or, worse, false negatives. Moreover, it is more than likely that all OA molecules do not reach the sensor surface so that the quantity and concentration should be high enough to ensure sufficient bindings onto immobilized antibodies. Future work will aim at further improve the design of the platform. Integrating a microfluidic network would promote the efficient capture of target toxins on the bio-functional surface, and lower the OA concentration needed for detection. Acknowledgements This work received financial support from the Conseil Régional d’Aquitaine and the European Union. We would like to warmly thank Véronique Conedera and Monique Benoît from LAAS-CNRS Laboratory (UMR CNRS 8001) in Toulouse for the fabrication of the Love wave devices in the frame of the National Technology Network (RTB), as well as Mathieu Guirardel from Rhodia-LOF (Pessac, UMR CNRS 5258) and Hakim Tarbague (IMS-Bordeaux) for valuable scientific discussions and technical help for the PDMS cell design.
[1] P. Leonard, S. Hearty, J. Brennan, L. Dunne, J. Quinn, T. Chakraborty, R. O’Kennedy, Advances in biosensors for detection of pathogens in food and water, Enzyme Microbial Technology 32 (2003) 3–13. [2] D. Ivnitski, I. Abdel-Hamid, P. Atanasov, E. Wilkins, Biosensors for the detection of pathogenic bacteria, Biosensors & Bioelectronics 14 (1999) 599–624. [3] Anon, Waterborne pathogens kill 10 M–20 M people/year, World Water and Environmental Engineering (June (6)) (1996). [4] G.A. Codd, J. Lindsay, F.M. Young, L.F. Morrison, J.F. Metcalf, Harmful cyanobacteria: from mass mortalities to management measures, in: J. Huisman, H.C.P. Matthijs, P.M. Visser (Eds.), Harmful Cyanobacteria. Aquatic Ecology Series, vol. 3, Springer, Berlin, Heidelberg, New York, 2005, pp. 1–24. [5] J. Landsberg, F. Van Dolah, G. Doucette, Marine and estuarine harmful algal blooms: impacts on human and animal health, in: S. Belkin, R.R. Colwell (Eds.), Oceans and Health: Pathogens in the Marine Environment, Springer, New York, 2005, pp. 165–215. [6] E. Granéli, K. Flynn, Chemical and physical factors influencing toxin content, in: E. Granéli, J.T. Turner (Eds.), Ecology of Harmful Algae. Ecological Studies, vol. 189, Springer-Verlag, Berlin, Heidelberg, 2006, pp. 229–241. [7] G.J. Doucette, C.M. Mikulski, K.L. Jones, K.L. King, D.I. Greenfield, R. Marin III, S. Jensen, B. Roman, C.T. Elliott, C.A. Scholin, Remote, subsurface detection of the algal toxin domoic onboard the environmental sample processor: assay development and field trials, Harmful Algae 8 (2009) 880–888. [8] M.-I Rocha-Gaso, C. March-Iborra, Á. Montoya-Baides, A. Arnau-Vives, Surface generated acoustic wave biosensors for the detection of pathogens: a review, Sensors 9 (7) (2009) 5740–5769. [9] M. Babin, J.J. Cullen, C.S. Roesler, P.L. Donaghay, G.J. Doucette, M. Kahru, M.R. Lewis, C.A. Scholin, M.E. Sieracki, H.M. Sosik, New approaches and technologies for observing harmful algal blooms, Oceanography 18 (2005) 210–227. [10] R.J. Olson, H.M. Sosik, A submersible imaging-in-flow instrument to analyze nano- and microplankton: imaging flowCytobot, Limnology and Oceanography: Methods 5 (2007) 195–203. [11] J. Paul, C. Scholin, G. Van Den Engh, M.J. Perry, In situ instrumentation, Oceanography 20 (2007) 58–66. [12] N. Moll, E. Pascal, D.H. Dinh, J.-P. Pillot, B. Bennetau, D. Rebière, D. Moynet, Y. Mas, D. Mossalayi, J. Pistré, C. Dejous, A love wave immunosensor for whole E. coli bacteria detection using an innovative two steps immobilisation approach, Biosensors & Bioelectronics 22 (9–10) (2007) 2145–2150. [13] V. Raimbault, D. Rebière, C. Dejous, M. Guirardel, J. Pistré, J.L. Lachaud, High frequency microrheological measurements of PDMS fluids using saw microfluidic system, Sensors and Actuators B 144 (2010) 467–471. [14] H. Tarbague, J.L. Lachaud, S. Destor, L. Vellutini, J.-P. Pillot, B. Bennetau, D. Moynet, D. Rebière, J. Pistre, C. Dejous, PDMS (polydimethylsiloxane) microfluidic chip molding for love wave biosensor, ECS Transactions 23 (1) (2009) 319–325. [15] I. Gammoudi, H. Tarbague, A. Othmane, D. Moynet, D. Rebiere, R. Kalfat, C. Dejous, Love-wave bacteria-based sensor for the detection of heavy metal toxicity in liquid medium, Biosensors & Bioelectronics, BIOS-3999 (2010), doi:10.1016/j.bios.2010.07.118.
Biographies Fabien Fournel is a PhD-Student in the IMS-Bordeaux laboratory since 2007 under the supervision of Professor Dominique Rebière and Professor Corinne Dejous, Université de Bordeaux. He has been working on Love sensors and application to toxin detections. His thesis was financed by the Région d’Aquitaine. He has studied electronics for which he graduated the Baccalaureate (secondary-school diploma). Etienne Baco obtained his Msc Chemistry in 2007 from Hull (UK) and his Master Degree from Amiens, France and is presently PhD student at the University of Bordeaux. His researches were funded by Conseil Régional d’Aquitaine and were focused on toxins analogue hapten synthesis. Maria Mamani-Matsuda works as an assistant professor at the Université de Bordeaux. Since her PhD obtention in 2001, she has worked on different sides of the immune response, including macrophages and inflammation as well as B lymphocytes and immune memory. She now focuses on T cell response in human diseases. Marie Degueil obtained her PhD thesis in 1983, dealing with organometallic chemistry under high pressure, especially trialkyltin hydrides addition on unsaturated systems. She received a CNRS position at the Université de Bordeaux 1 (Chargée de Recherche) and developed free radical chemistry and particularly peroxide chemistry applied to the synthesis of functionalized polyolefins. Her current research interests mainly include the design and synthesis of haptens for production of antibody against small biologically active molecules (phycotoxins) to develop biosensors for real time detection. Bernard Bennetau studied at the Université de Bordeaux 1 where he has got his PhD in 1982. His PhD thesis dealt with the synthesis of natural compounds mostly using organosilicon chemistry. In 1982, he received a CNRS position and became Directeur
128
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
de Recherche CNRS in 2001. His current research interests mainly include chemical modifications of surfaces for applications in biotechnology (biosensors). For this purpose, new multifunctional coupling agents to change the chemical nature of the surface were developed. Design and synthesis of haptens for production of antibody against small biologically active molecules are also investigated (phytoestrogens and phycotoxins). Daniel Moynet received his PhD from Université Paul Sabatier (Toulouse) in 1984. He is an assistant professor of microbiology in Université de Bordeaux since 1981. His research activity is focused on human inflammatory pathologies (auto immunes or viro induced), comprehension of the inflammatory response and drug discovery. Djavad Mossalayi passed PhD in Molecular Hematology from Poitiers, France, in 1987. He joined Cellular Immunology Research Unit at Pitiés-Salpêtrière Hospital in Paris as Permanent Research Fellow. He studied early human T cell development (1991) and the role of CD23 as functional IgE-receptor on the surface of epithelial cells, eosinophils and macrophages (1995), together with the ability of CD23 to induce iNOS activation and nitric oxide production in above cells. He joined the faculty of Pharmacy at Université de Bordeaux-2 in 1998 as full professor and chief of “Anti-inflammatory and Anti-parasitic drug discovery” research team with 3 new patented immunosuppressing molecules. Luc Vellutini received his PhD degree in the field of synthesis and characterization of hybrid silica materials from the University of Montpellier (France) in 2002. He was
a postdoctoral fellow in the Institut des Matériaux Jean Rouxel de Nantes between 2003 and 2005. Currently, he is an assistant professor in chemistry at the University of Bordeaux (France). His research interests are in the field of the functionalization and biofunctionalization of surfaces for biosensors and application of the sol gel process to design new materials. Jean-Paul Pillot received his PhD (science) from University of Bordeaux in 1979. He is a research engineer at CNRS. His main research interests are organometallic chemistry, organosilicon chemistry and silicon-based materials. Currently, he is working in the field of the functionalization of surfaces for biosensing applications. Corinne Dejous received an electronics engineer degree (ENSEIRB) in 1991, and a PhD in 1994 (Université de Bordeaux, France). She is now professor at Institut Polytechnique de Bordeaux, where she teaches basic electronics and instrumentation, chemical sensors and microsystems. Since 1991, she has been involved in acoustic wave sensors at IMS laboratory. She is more particularly in charge of the development of these microsystems for biological applications. Dominique Rebière received the Maîtrise d’Électronique – Électrotechnique Automatique, the Diplôme d’Études Approfondies in electronics and a PhD from Université de Bordeaux, France, in 1987, 1988 and 1992, respectively. He is now professor at Université de Bordeaux in electronics engineering. Most of his research work has focused on surface acoustic wave sensors for chemical and biochemical applications at IMS laboratory, where he is in charge of the team “Acoustic Wave based Microsystems” since 2007.
Contents lists available at ScienceDirect
Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb
Love wave biosensor for real-time detection of okadaic acid as DSP phycotoxin F. Fournel a,∗ , E. Baco b , M. Mamani-Matsuda c , M. Degueil b , B. Bennetau b , D. Moynet c , D. Mossalayi c , L. Vellutini b , J.-P. Pillot b , C. Dejous a , D. Rebière a a b c
Université de Bordeaux, IMS, ENSEIRB, CNRS UMR 5218, Talence 33405, France Université de Bordeaux, ISM, CNRS UMR 5255, Talence 33405, France Université de Bordeaux, Laboratoire d’Immunologie/Parasitologie, UFR Sciences Pharmaceutiques, Bordeaux 33076, France
a r t i c l e
i n f o
Article history: Received 29 September 2010 Received in revised form 21 February 2011 Accepted 23 February 2011 Available online 30 March 2012 Keywords: Acoustic wave Phycotoxin Microfluidic Biodetection
a b s t r a c t This paper reports the detection of okadaic acid (OA) as a Diarrheic Shellfish Poisoning (DSP) toxin with an acoustic wave platform in real-time. According to the FDA, the threshold for safe consumption of shellfish is 20 g of OA for 100 g of shellfish tissue. The high gravimetric sensitivity of Love wave acoustic devices allow, in liquid media, immuno-detection thanks to immobilized specific antibodies. The biosensor is composed of two lines, one for the test and one used as a reference. Sensitive films were deposited through a PolyDiMethylSiloxane (PDMS) microfluidic chip. On both lines, anti-okadaic acid antibodies (OA-Ab) and saturating agents were successively injected under continuous flow with controlled flow rate. On the test line, okadaic acid (OA) was injected while an unspecific peptide (6×Histidine, 6×His) was used on the control line. On both lines, polyclonal OA-Ab were re-injected a second time to reveal previously fixed OA on the test line. Measured frequency shifts were three times higher on test lines than on control lines. In these conditions, for only 2 g of OA used for detection, the acoustic wave platform could detect DSP toxins with only 10 g of shellfish tissue. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Food poisoning caused by bacteria, fungi or viruses represent a major public health problem with significant economic consequences [1]. It has been estimated that 40% of the total annual deaths world-wide were due to infectious diseases caused by these harmful micro-organisms and, each year, 200 million people suffer from non-lethal infections [2,3]. Although not infectious, shellfish
Abbreviations: OA, okadaic acid; DSP, diarrheic shellfish poisoning; FDA, food and drug administration; Ab, antibody/antibodies; OA-Ab, anti-okadaic acid antibody, antibody specific to okadaic acid; 6×His, 6histidines coupled together; OD, optical density; SAW, surface acoustic wave; IDT, interdigital transducer; PECVD, plasma-enhanced chemical vapor deposition; PDMS, polydimethylsiloxane; GPTS, (3-glycidoxypropyl)-trimethoxysilane; SBBB, starting blockTM blocking buffer; TBS, tris buffer saline; ELISA, enzyme-linked immunosorbent assay. ∗ Corresponding author. Tel.: +33 540006581; fax: +33 556371545. E-mail addresses: [email protected] (F. Fournel), [email protected] (E. Baco), [email protected] (M. Mamani-Matsuda), [email protected] (M. Degueil), [email protected] (B. Bennetau), [email protected] (D. Moynet), [email protected] (D. Mossalayi), [email protected] (L. Vellutini), [email protected] (J.-P. Pillot), [email protected] (C. Dejous), [email protected] (D. Rebière). 0925-4005/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.snb.2011.02.056
poisoning represent a serious threat [4,5]. Toxins are produced by harmful algae species but their potential poisoning is not directly correlated with the cell concentration. Temperature, salinity of water, macronutrients and other environmental factors have to be considered [6]. Thus, direct measurement of phycotoxins, contained in phytoplanktons, is needed in addition to phytoplankton detection to meet FDA health requirements, as stated by Doucette et al. [7]. Investigations on more rapid, sensitive, selective, portable, power-efficient and low-cost methods have to be carried out as noticed by Rocha-Gaso et al. [8]. Some improvements in the development of systems capable of generating real- or near real-time data for certain harmful algal species have already been published [9–11]. These new developments mainly regarded molecular probe-based methods with antibody recognition coupled with embedded systems allowing spectrometric measurements and remote data transmission [7]. Over the last decades, surface acoustic wave devices have been successfully used for real-time biosensing of cells, bacteria and molecules [8]. In particular, Love wave platforms offer high potentialities in terms of mass loading sensitivity in liquid media and have proven their ability for bacteria detection [12]. The aim of this paper is to demonstrate the feasibility of phycotoxin detection in real-time by using a Love wave platform with a microfluidic feature and an ELISA-like protocol.
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
123
2. Materials and methods 2.1. Love wave sensors The Love wave sensor platform is composed of a Quartz substrate, Interdigital Transducers (IDTs) as input and output ports of the delay-line, a SiO2 guiding layer and an immuno-sensitive coating. IDTs consisted of 44 pairs of split-fingers ( = 8 m × 5 m) whose geometrical parameters are defined in Fig. 1. They were composed of Gold–Titanium as adhesion layer (total thickness about 200 nm), and deposited through a lift-off technique on the Quartz piezoelectric crystal (AT-cut, Euler angles: 0◦ , 121.5◦ , 90◦ ). A 4.5 m thick SiO2 guiding layer was deposited all over the substrate by using a PECVD technique, and then etched to access the electrical contacts. Thanks to the shear horizontal polarization of the waves, Love wave devices can be used as sensors in liquid media. The controlled thickness of the guiding layer enables to trap the acoustic wave energy near the sensing surface, improving the sensitivity to surface variations. The resulting synchronous frequency of the Love wave platform was near 117 MHz. Placed in an oscillator configuration, the short-term stability of the device in steady-state was lower than 1 Hz s−1 . 2.2. PDMS microfluidic chip In order to improve detection resolution and save biological material, a continuous micro-flow was applied at the sensor surface with a polymeric chip maintained by pressure onto the sensor (Fig. 2). The microfluidic chip was designed by using COMSOL® software in order to control liquid flow over the sensor without vortex and favouring a homogeneous species distribution (Fig. 3). The microchamber volume was limited by the chip cavity and the sensor acoustic path surface. The resulting micro-chamber dimensions (Fig. 2a) were 31.3 mm2 by 100 m in height, corresponding to 3.1 l. This weak volume allowed biological product saving. Additional air cavities have been designed above the IDTs to protect them from liquid polarity perturbation due to ionized water, while not being in contact with the polymeric chip, which is an acoustic absorbent [13]. One hundred microns thick walls ensured the sealing of the micro-chamber without causing excessive attenuation of the wave. The chip was 10 mm high, calibrated to ensure constant pressure and to enhance the reproducibility. This microfluidic chip was made of Polydimethylsiloxane (PDMS, Dow Corning, Sylgard 184 Silicone Elastomer Kit) by using soft lithography [12,13] and molding techniques developed by Hakim Tarbague [14]. As a first step, a SU-8 photoresist (Microchem, SU-8 2075) spin-coated on a 4 silicon wafer was insulated through
Fig. 2. (a) Conceptual design of the microfluidic chip drawn with Google Sketchup® , micro-chamber surface: 31.3 mm2 . (b) Final PDMS microfluidic chip.
a negative mask (Fig. 4a). The resulting pattern was used to create the bottom part of the microfluidic chip, in contact with the sensor surface. A mixture of PDMS and its cross-linker (ratio 10:1, respectively) was poured on the micro-pattern for molding (thickness about 3 mm) (Fig. 4b). After cross-linking, this PDMS part,
Fig. 1. Dual Love wave delay-line geometry. (a) Electrode pads for electrical input or output. (b) Acoustic wave path, centre-to-centre length (Lcc ) is 8.4 mm. (c) IDT wavelength is 40 m. Effective aperture w is 1.6 mm.
124
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
Fig. 3. Flow simulation in the PDMS chip with COMSOL software: (left) velocity flow lines. For typical flow rate of 10 l/min, velocity on the central flow line is 0.5 mm/s and average renewal time for 75% of the microchannel is 16 s. (Right) antibody distribution on the sensor surface was homogeneous along the acoustic wave path for flow rate under 10 l/min (simulation with diffusion/convection module).
Fig. 4. PDMS microchip molding protocol.
containing the microfluidic shape, was cut off and placed into an aluminum mold (Fig. 4c). The PDMS mixture was poured again and a cover was used to calibrate the microchip height to 10 mm. The final chip was unmolded and pipe holes were drilled through as inputs and outputs of liquid (Fig. 4d).
solubilised in H2 O at 100 g/ml (Fig. 6a). OA has a molar mass about 805 g mol−1 for 44 carbon atoms. The peptide 6×Histidine (6×His, from Genecust), with a molar mass about 930.9 g mol−1 for 36 carbon atoms and a similar geometry, has been used for control purposes (Fig. 6b).
2.3. Instrumentation description The sensors were inserted on the detection platform with the PDMS microfluidic chip after the chemical functionalization process; the Self Assembled Monolayer (SAM) made of (3-glycidoxypropyl)-trimethoxysilane (GPTS) ensures covalent binding with the SiO2 guiding layer and with antibodies [12]. Entry cones were used to inject species and tubes were connected to a syringe pump (BioSeb, ref: BS-9000-8) pulling the liquid with glass syringes (Hamilton, 10 ml, ref: GASTIGHT #1010) (Fig. 5). Tris buffer saline (Sigma, ref: T6664-10PAK) was used as a reference medium, ensuring flow continuity during the whole protocol. 2.4. Okadaic acid and 6×Histidine Detection tests were made with a commercial okadaic acid (OA, from LC Laboratories, Cat O-2220, or from Sigma–Aldrich, O8010),
Fig. 5. Instrumentation bench: composed of a dual Love wave delay-line, a PDMS microfluidic chip, a cell test (not represented), and a cone/hose/syringe for each line (only one is represented).
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
125
Fig. 6. Chemical formulas. (a) Okadaic acid. (b) 6×Histidine (synthesized molecule).
As shown in Fig. 7 and taking into account standard deviations, the dilution of 1/400 provided significant results about complex formation between OA and OA-Ab. For the Love wave biosensor protocol, antibody solutions were diluted by 3.5 in the entry cone before reaching the microfluidic chamber. Thus, the 1/100 diluted antibody solution was chosen for injection in entry cones. More concentrated solutions gave similar results.
2.6. Okadaic acid detection protocol
Fig. 7. Direct ELISA test of the polyclonal rabbit anti-OA antibodies for different dilutions. The blank corresponds to PBS alone (no antibody). Significant responses are those with an optical density (OD) superior to three times the blank optic OD (red line). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)
2.5. Anti-okadaic acid antibodies In order to ensure a specific detection of the OA, commercial specific anti-OA antibodies (OA-Ab, polyclonal rabbit anti-OA, Abcam, ref: ab-2897) have been used. An ELISA test was performed for antibody titration; OA was coated on each well at 10 g/ml, then were injected different dilutions of the OA-Ab original solution, from 1/100 to 1/6400 (Fig. 7). All the dilutions were made in phosphate buffer saline (PBS).
The immuno-sensitive layer was prepared with 20 l of OA-Ab (at 1/100 from original solution) for grafting onto GPTS modified sensor surface (Fig. 8a). To prevent non specific binding on the surface, a solution of 20 l of StartingBlock Blocking Buffer (SBBB, Thermo Scientific, ref: 37542), a saturating agent composed of molecules with different sizes, was then injected (Fig. 8b). Species injections were always made when 50 l of TBS were left in cones. Flow rate was fixed at 10 l/min. This allowed both coating effect (with mass-loading) and cleaning of molecules that were not covalently bonded on the surface. After the immuno-sensitive layer preparation, a solution of 20 l OA (2 g, concentration at 28 g/ml in the cone) was injected on the test delay-line (Fig. 8c), while 2 g of 6×Histidine (same concentration) were injected on the control line. Before injections, the flow rate had been reduced at 1 l/min in order to let these small molecules to reach the sensor surface. After 10 min, the flow rate was raised again to 10 l/min to clean the surface from nonimmobilized molecules.
Fig. 8. Protocol step representation, focus on the sensor surface. (a) OA-Ab coating. (b) Surface saturation. (c) OA complex formation. (d) Second injection of polyclonal OA-Ab.
126
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
Fig. 9. Frequency shift responses to mass-loading effect on the sensor surface (a) antibody covalent grafting trends. The 1/100 dilution of OA-Ab was used for all of them (concentration unknown). (b) and (c) Saturating agent coating trends with a flow rate of 1 l/min for (b) and 10 l/min for (c). (d) Mean frequency shifts and standard deviations for antibodies, saturating agent and assessment of the antibody surface covering rate.
Nor OA neither 6×His molecules were directly detected with significant frequency shifts. This was partially due to their low molecular weight. However, the sensitivity towards OA has been enhanced by a second injection of polyclonal OA-Ab, as different epitopes can be recognized like in a sandwich ELISA test (Fig. 8d) as presented in Section 3.2. The second injection of OA-Ab was done on both the test and the control lines. 3. Results 3.1. Immuno-sensitive layer frequency shifts Synchronous frequencies were acquired as species were covalently grafted onto the GPTS surface. Average frequency shifting for antibodies and saturating agent were, respectively, fA = −7.4 kHz (±23%) and fS = −1.8 kHz (±24%) (Fig. 9). Frequency shifts have been normalized to fit in one plot. Fig. 9a represents the sensor responses when antibodies were grafted onto the GPTS layer surface (flow rate set at 10 l/min), while Fig. 9b and c shows surface saturation by SBBB (flow rate of 1 or 10 l/min, respectively). It takes about 15 min at 1 l/min and 5 min at 10 l/min to clean unbonded molecules. Mean frequency shifts with standard deviations for antibodies, saturating agent and assessment of the covering rate of antibodies have been reported on Fig. 9d. To estimate the covering rate of antibodies on the sensor, the ratio (fR ) between antibodies and saturating agent frequency shifts was calculated for each experiment, according to the equation: fR = fA /(fA + fS ). This method indicated a covering rate of 80 ± 5% and was used to discriminate faulty
sensors. Including stabilization time, immuno-sensitive layer coating takes about 20 min. 3.2. Okadaic acid detection frequency shifts Fig. 10 presents typical frequency responses associated with the last step of the protocol (Fig. 8d), during the second injections of polyclonal OA-Ab. Frequency shifts on test lines are significant (average about 2 kHz) compared to previous injections of OA (not shown). Moreover, it can be seen that frequency shifts on test lines were 3 times (±9%) higher than on control lines (less than 800 Hz), whatever the flow rate was. Frequency needs 10 min to reach a steady-state with a flow rate of 1 l/min. At this speed, the stabilization trend is similar to those under static conditions [15]. The microfluidic device improves response trend quality. At 10 l/min, stabilization takes 5 min, thus, increasing the flow rate increases the mass convection on the sensor surface without changing the relative difference between test and control lines. 4. Discussion Controls prove that the frequency shifts on the test lines during the second antibody injection must be related to a specific antibody/antigen complex formation with okadaic acid. This demonstrates phycotoxin detection feasibility by acoustic wave sensors using a sandwich ELISA-like protocol. Including immunosensitive layer coating, phycotoxin and antibody injections, with steady-state periods between each protocol stage, the experiment duration time lasted less than 3 h.
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
127
The authors also want to thank Angélique Tetelin (IMS-Bordeaux) for English assistance. References
Fig. 10. Frequency shifts during second injection of polyclonal antibody. Dark curves indicate test line responses while gray curves indicate control line responses. (a) Flow rate of 1 l/min. (b) Flow rate of 10 l/min.
Food & Drug Administration have set the maximal concentration to avoid DSP poisoning at 0.2 ppm, e.g. 20 g of okadaic acid for 100 g of shellfish. Under the reported conditions, this method can significantly detect 2 g of okadaic acid, thus, only a small mixture of 10 g of shellfish food would be needed. Investigations to lower minimum toxin concentration for detection have yet to be taken. This quantity seems to be the detection limit of the Love wave platform. Although the frequency shift difference is significant, a smaller one could be confusing, leading to false positives or, worse, false negatives. Moreover, it is more than likely that all OA molecules do not reach the sensor surface so that the quantity and concentration should be high enough to ensure sufficient bindings onto immobilized antibodies. Future work will aim at further improve the design of the platform. Integrating a microfluidic network would promote the efficient capture of target toxins on the bio-functional surface, and lower the OA concentration needed for detection. Acknowledgements This work received financial support from the Conseil Régional d’Aquitaine and the European Union. We would like to warmly thank Véronique Conedera and Monique Benoît from LAAS-CNRS Laboratory (UMR CNRS 8001) in Toulouse for the fabrication of the Love wave devices in the frame of the National Technology Network (RTB), as well as Mathieu Guirardel from Rhodia-LOF (Pessac, UMR CNRS 5258) and Hakim Tarbague (IMS-Bordeaux) for valuable scientific discussions and technical help for the PDMS cell design.
[1] P. Leonard, S. Hearty, J. Brennan, L. Dunne, J. Quinn, T. Chakraborty, R. O’Kennedy, Advances in biosensors for detection of pathogens in food and water, Enzyme Microbial Technology 32 (2003) 3–13. [2] D. Ivnitski, I. Abdel-Hamid, P. Atanasov, E. Wilkins, Biosensors for the detection of pathogenic bacteria, Biosensors & Bioelectronics 14 (1999) 599–624. [3] Anon, Waterborne pathogens kill 10 M–20 M people/year, World Water and Environmental Engineering (June (6)) (1996). [4] G.A. Codd, J. Lindsay, F.M. Young, L.F. Morrison, J.F. Metcalf, Harmful cyanobacteria: from mass mortalities to management measures, in: J. Huisman, H.C.P. Matthijs, P.M. Visser (Eds.), Harmful Cyanobacteria. Aquatic Ecology Series, vol. 3, Springer, Berlin, Heidelberg, New York, 2005, pp. 1–24. [5] J. Landsberg, F. Van Dolah, G. Doucette, Marine and estuarine harmful algal blooms: impacts on human and animal health, in: S. Belkin, R.R. Colwell (Eds.), Oceans and Health: Pathogens in the Marine Environment, Springer, New York, 2005, pp. 165–215. [6] E. Granéli, K. Flynn, Chemical and physical factors influencing toxin content, in: E. Granéli, J.T. Turner (Eds.), Ecology of Harmful Algae. Ecological Studies, vol. 189, Springer-Verlag, Berlin, Heidelberg, 2006, pp. 229–241. [7] G.J. Doucette, C.M. Mikulski, K.L. Jones, K.L. King, D.I. Greenfield, R. Marin III, S. Jensen, B. Roman, C.T. Elliott, C.A. Scholin, Remote, subsurface detection of the algal toxin domoic onboard the environmental sample processor: assay development and field trials, Harmful Algae 8 (2009) 880–888. [8] M.-I Rocha-Gaso, C. March-Iborra, Á. Montoya-Baides, A. Arnau-Vives, Surface generated acoustic wave biosensors for the detection of pathogens: a review, Sensors 9 (7) (2009) 5740–5769. [9] M. Babin, J.J. Cullen, C.S. Roesler, P.L. Donaghay, G.J. Doucette, M. Kahru, M.R. Lewis, C.A. Scholin, M.E. Sieracki, H.M. Sosik, New approaches and technologies for observing harmful algal blooms, Oceanography 18 (2005) 210–227. [10] R.J. Olson, H.M. Sosik, A submersible imaging-in-flow instrument to analyze nano- and microplankton: imaging flowCytobot, Limnology and Oceanography: Methods 5 (2007) 195–203. [11] J. Paul, C. Scholin, G. Van Den Engh, M.J. Perry, In situ instrumentation, Oceanography 20 (2007) 58–66. [12] N. Moll, E. Pascal, D.H. Dinh, J.-P. Pillot, B. Bennetau, D. Rebière, D. Moynet, Y. Mas, D. Mossalayi, J. Pistré, C. Dejous, A love wave immunosensor for whole E. coli bacteria detection using an innovative two steps immobilisation approach, Biosensors & Bioelectronics 22 (9–10) (2007) 2145–2150. [13] V. Raimbault, D. Rebière, C. Dejous, M. Guirardel, J. Pistré, J.L. Lachaud, High frequency microrheological measurements of PDMS fluids using saw microfluidic system, Sensors and Actuators B 144 (2010) 467–471. [14] H. Tarbague, J.L. Lachaud, S. Destor, L. Vellutini, J.-P. Pillot, B. Bennetau, D. Moynet, D. Rebière, J. Pistre, C. Dejous, PDMS (polydimethylsiloxane) microfluidic chip molding for love wave biosensor, ECS Transactions 23 (1) (2009) 319–325. [15] I. Gammoudi, H. Tarbague, A. Othmane, D. Moynet, D. Rebiere, R. Kalfat, C. Dejous, Love-wave bacteria-based sensor for the detection of heavy metal toxicity in liquid medium, Biosensors & Bioelectronics, BIOS-3999 (2010), doi:10.1016/j.bios.2010.07.118.
Biographies Fabien Fournel is a PhD-Student in the IMS-Bordeaux laboratory since 2007 under the supervision of Professor Dominique Rebière and Professor Corinne Dejous, Université de Bordeaux. He has been working on Love sensors and application to toxin detections. His thesis was financed by the Région d’Aquitaine. He has studied electronics for which he graduated the Baccalaureate (secondary-school diploma). Etienne Baco obtained his Msc Chemistry in 2007 from Hull (UK) and his Master Degree from Amiens, France and is presently PhD student at the University of Bordeaux. His researches were funded by Conseil Régional d’Aquitaine and were focused on toxins analogue hapten synthesis. Maria Mamani-Matsuda works as an assistant professor at the Université de Bordeaux. Since her PhD obtention in 2001, she has worked on different sides of the immune response, including macrophages and inflammation as well as B lymphocytes and immune memory. She now focuses on T cell response in human diseases. Marie Degueil obtained her PhD thesis in 1983, dealing with organometallic chemistry under high pressure, especially trialkyltin hydrides addition on unsaturated systems. She received a CNRS position at the Université de Bordeaux 1 (Chargée de Recherche) and developed free radical chemistry and particularly peroxide chemistry applied to the synthesis of functionalized polyolefins. Her current research interests mainly include the design and synthesis of haptens for production of antibody against small biologically active molecules (phycotoxins) to develop biosensors for real time detection. Bernard Bennetau studied at the Université de Bordeaux 1 where he has got his PhD in 1982. His PhD thesis dealt with the synthesis of natural compounds mostly using organosilicon chemistry. In 1982, he received a CNRS position and became Directeur
128
F. Fournel et al. / Sensors and Actuators B 170 (2012) 122–128
de Recherche CNRS in 2001. His current research interests mainly include chemical modifications of surfaces for applications in biotechnology (biosensors). For this purpose, new multifunctional coupling agents to change the chemical nature of the surface were developed. Design and synthesis of haptens for production of antibody against small biologically active molecules are also investigated (phytoestrogens and phycotoxins). Daniel Moynet received his PhD from Université Paul Sabatier (Toulouse) in 1984. He is an assistant professor of microbiology in Université de Bordeaux since 1981. His research activity is focused on human inflammatory pathologies (auto immunes or viro induced), comprehension of the inflammatory response and drug discovery. Djavad Mossalayi passed PhD in Molecular Hematology from Poitiers, France, in 1987. He joined Cellular Immunology Research Unit at Pitiés-Salpêtrière Hospital in Paris as Permanent Research Fellow. He studied early human T cell development (1991) and the role of CD23 as functional IgE-receptor on the surface of epithelial cells, eosinophils and macrophages (1995), together with the ability of CD23 to induce iNOS activation and nitric oxide production in above cells. He joined the faculty of Pharmacy at Université de Bordeaux-2 in 1998 as full professor and chief of “Anti-inflammatory and Anti-parasitic drug discovery” research team with 3 new patented immunosuppressing molecules. Luc Vellutini received his PhD degree in the field of synthesis and characterization of hybrid silica materials from the University of Montpellier (France) in 2002. He was
a postdoctoral fellow in the Institut des Matériaux Jean Rouxel de Nantes between 2003 and 2005. Currently, he is an assistant professor in chemistry at the University of Bordeaux (France). His research interests are in the field of the functionalization and biofunctionalization of surfaces for biosensors and application of the sol gel process to design new materials. Jean-Paul Pillot received his PhD (science) from University of Bordeaux in 1979. He is a research engineer at CNRS. His main research interests are organometallic chemistry, organosilicon chemistry and silicon-based materials. Currently, he is working in the field of the functionalization of surfaces for biosensing applications. Corinne Dejous received an electronics engineer degree (ENSEIRB) in 1991, and a PhD in 1994 (Université de Bordeaux, France). She is now professor at Institut Polytechnique de Bordeaux, where she teaches basic electronics and instrumentation, chemical sensors and microsystems. Since 1991, she has been involved in acoustic wave sensors at IMS laboratory. She is more particularly in charge of the development of these microsystems for biological applications. Dominique Rebière received the Maîtrise d’Électronique – Électrotechnique Automatique, the Diplôme d’Études Approfondies in electronics and a PhD from Université de Bordeaux, France, in 1987, 1988 and 1992, respectively. He is now professor at Université de Bordeaux in electronics engineering. Most of his research work has focused on surface acoustic wave sensors for chemical and biochemical applications at IMS laboratory, where he is in charge of the team “Acoustic Wave based Microsystems” since 2007.