Nanostructured materials with biomimetic recognition abilities for chemical sensing
© Bajwa et al.; licensee Springer. 2012
Received: 18 January 2012
Accepted: 26 April 2012
Published: 21 June 2012
Binding features found in biological systems can be implemented into man-made materials to design nanostructured artificial receptor matrices which are suitable, e.g., for chemical sensing applications. A range of different non-covalent interactions can be utilized based on the chemical properties of the respective analyte. One example is the formation of coordinative bonds between a polymerizable ligand (e.g., N-vinyl-2-pyrrolidone) and a metal ion (e.g., Cu(II)). Optimized molecularly imprinted sensor layers lead to selectivity factors of at least 2 compared to other bivalent ions. In the same way, H-bonds can be utilized for such sensing purposes, as shown in the case of Escherichia coli. The respective molecularly imprinted polymer leads to the selectivity factor of more than 5 between the W and B strains, respectively. Furthermore, nanoparticles with optimized Pearson hardness allow for designing sensors to detect organic thiols in air. The ‘harder’ MoS2 yields only about 40% of the signals towards octane thiol as compared to the ‘softer’ Cu2S. However, both materials strongly prefer molecules with -SH functionality over others, such as hydrocarbon chains. Finally, selectivity studies with wheat germ agglutinin (WGA) reveal that artificial receptors yield selectivities between WGA and bovine serum albumin that are only about a factor of 2 which is smaller than natural ligands.
KeywordsBivalent copper ions Organic vapors Wheat germ agglutinin lectin Escherichia coli Quartz crystal microbalance
Recent focus of material scientists and engineers is to design economically and functionally efficient receptors allowing for substrate binding characteristics similar to those of natural systems. Highly selective recognition is one of the fundamental features of life-governing biological functions, including immune reactions and catabolic and anabolic enzymatic processes to name the most important ones. Despite optimal selectivity, there are some inherent limitations of these natural systems, such as degradation in harsh environments and limited life time and stability. Furthermore, especially antibodies bind to their antigens very strongly, thus limiting reversibility of the recognition process. However, the non-covalent interaction networks governing biological systems can be mimicked to produce nanostructured artificial receptors with extended operation time and shelf life [1–4]. Various types of analyte-receptor interactions can be implemented in this way, such as affinity-based ones, hydrophobic interactions, hydrogen bonds, and polar interactions. In the case of ‘pure’ affinity interactions with the outer surface of the artificial receptor, nanostructuring the recognition layer should lead to substantially enhanced sensor responses due to the larger internal surface.
If both steric and geometric features are to be addressed, molecular imprinting  via covalent , non-covalent [7, 8] or semi-covalent approaches , respectively, can be implemented. Obviously, the interactions between the analyte and matrix play a key role in controlling the recognition ability of the material in any case. Thus, rationally functionalized materials, be these imprinted by the analyte of interest itself or possess affinity towards it, are able to distinguish the template from interfering species even when having related geometrical and chemical structures. Such (nano)materials constitute very promising artificial receptors for the detection of a variety of analytes from the subnano- to microlevel, such as ions , volatile organic compounds , cells, yeasts , viruses , and proteins  to name a few. The present work summarizes some aspects of interactions leading to the design of useful chemical sensors including affinity nanoparticles, generating the molecularly imprinted polymer (MIP) with the smallest possible templates and aspects of comparing artificial and natural receptors, respectively. The recognition abilities of the prepared materials are assessed by applying them onto quartz crystal microbalance (QCM) transducers and by tracing the subsequent frequency shifts following analyte exposure.
Materials and chemicals
All chemicals were purchased either from Merck (Vienna, Austria), Sigma-Aldrich (Vienna, Austria) or Alfa Aesar (Karlsruhe, Germany) as analytical grade or the highest available synthetic grade and were utilized without further purification. AT-cut quartz crystal sheets (10 MHz fundamental frequency) and the gold paste (for the screen printing of electrode over QCM sheets) were purchased from Great Microtama Electronics (Surabaya, Indonesia) and HERAEUS (Hanau, Germany), respectively.
Synthesis of cu(II)-imprinted polymer
Three milligrams of CuCl2·2H2O was dissolved in 300 mg of N-vinyl-2-pyrrolidone (NVP). Thirty milligrams of this Cu(II)-NVP complex was then mixed with 60 mg of ethylene glycol dimethylacrylate, 3 mg of 2,2′-azo-bis-isobutyronitrile, and 500 μl acetonitrile. This prepolymer mixture was kept under UV for 45 min to polymerize. Finally, 5 μl of this solution was drop-coated over one electrode pair of the QCM to achieve layer heights of about 400 nm that were verified by network analyzer measurements. A reference polymer was prepared and coated in exactly the same manner excluding the addition of copper ions. Distilled water was used to extract the metal from the imprinted polymer layer to obtain recognition sites.
Synthesis of molybdenum disulphide nanoparticles
Molybdenum disulphide (MoS2) nanoparticles (NPs) were prepared from Mo(CO)6 and elemental sulfur following an already published synthesis protocol [15, 16]. These papers also discuss the ways leading to the optimized sensor materials.
Synthesis of copper sulfide nanoparticles
Copper sulfide (CuxS) particles were synthesized via a photochemical method : 5 ml of CuSO4 (1 mol/l) was mixed drop wise with 15 ml Na2S2O3 (1 mol/l), resulting in a bright green solution. This was kept at ambient conditions for a week without stirring. Then, black green nanoparticles were collected from the solution by centrifugation and washed several times with distilled water to remove unwanted byproduct and impurities. Finally, particles were dried at 60°C overnight.
Synthesis of polymer for surface imprinting of WGA lectin
The procedure adopted for preparing optimized surface imprints of wheat germ agglutinin (WGA) lectin has been described earlier .
Synthesis of Escherichia coli surface MIP
Polyurethane (PU) matrix was prepared by first dissolving 50.4 mg of poly(4-vinylphenol) and 4.3 mg of phloroglucinol in tetrahydrofuran (THF) and then adding 56.38 mg of diphenylmethan-4,4′-diisocyanat. The reaction mixture was kept at room temperature for 20 min to complete the polymerization process until gel point was reached. One part of this stock prepolymer solution was diluted with 15 parts of THF and coated to obtain a polyurethane layer of 350 to 400 nm for the surface imprinting of E. coli. A glass stamp of E. coli was prepared and pressed against the PU oligomer on the QCM electrode. A 0.1% sodium dodecyl sulfate solution was used to wash out the E. coli and to obtain empty cavities.
Atomic force microscopic characterization
The Veeco Nanoscope IVa AFM/STM system (Plainview, NY, USA) was employed for characterizing Cu2S, MoS2 nanoparticles, and surface imprints of E. coli. To acquire scans, silicon nitride atomic force microscopy (AFM) probes (model NP-S10 from Veeco) having cantilever spring constants of 0.58 to 0.06 N/m were used. All scans were recorded at ambient temperature (24 ± 2°C) in air via contact mode. Three samples of each material were synthesized and imaged at three distinct areas using the same tip. Among these images, one representative image is displayed. Data analysis for obtaining further information on the systems was carried out with the Nanoscope AFM system software shipped together with the Veeco system, while E. coli-MIP cavities are depicted using the WSxM free software by Nanotec Electrónica (Madrid, Spain)
Results and discussion
Highly selective artificial recognition materials can be achieved by nanostructuring matrices and making use of a range of non-covalent intermolecular interactions, such as coordinative bonds, hydrogen bonds, and affinity interactions based on the Pearson hardness of both the analyte and the receptor layer. Both molecularly imprinted polymers and affinity material nanoparticles reach appreciable analyte-layer interactions, leading to measurable sensor signals in mass-sensitive detection by quartz crystal microbalances. This is true for both small and large species, as represented here by metal ions and bacteria, respectively. In the case of WGA lectin, the fully artificial imprinted system already yields selectivities of the same order of magnitude as can be achieved with immobilized ligand species of this protein.
SZB currently pursues her Ph.D. studies at the University of Vienna funded by a scholarship of the Pakistani Higher Education Commission. She has specialized on generating highly selective MIP materials for ionic analytes.
GM obtained his Ph.D. from the University of Vienna in July 2011, where he studied on a scholarship by the Pakistani Higher Education Commission. He has specialized on gas sensing applications of inorganic nanoparticles.
RS currently pursues her Ph.D. studies at the University of Vienna. She has specialized on bacteria MIP and their application in real-life environments.
TW pursues her Ph.D. studies via the Thai Royal Golden Jubilee Grant Program in a joint project between Kasetsart University, Bangkok and the University of Vienna. Her research interests are in elucidating glycoside-protein interactions in natural systems.
PAL holds a professorship in Analytical Chemistry at the University of Vienna. He is a chemist having received his Ph.D. from the University of Vienna in 1999 and his postdoctoral lecture qualification in 2007. He is especially interested in developing chemical sensors for real-life environments including complex mixtures and applies pattern recognition methods for sensor arrays. This work to date has resulted in about 65 publications in peer-reviewed journals and approximately 80 conference contributions. Furthermore, he is strongly engaged in projects within the European Research Framework Programs.
Part of this work has been funded by the European Commission in the Sixth Framework Program for Research, project number EU-FP6 NMP3-CT-2007-026549 ‘NANOSECURE’. SZB and GM gratefully acknowledge the Higher Education Commission (HEC) of Pakistan for support via Ph.D. scholarship. TW gratefully acknowledges funding by the Thai Royal Golden Jubilee Grant Foundation and the Asea Uninet Network.
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