Investigation of the Affinity of Aptamers for Bacteria by Surface Plasmon Resonance Imaging Using Nanosomes.

The cell-SELEX method enables efficient selection of aptamers that bind whole bacterial cells. However, after selection, it is difficult to determine their binding affinities using common screening methods because of the large size of the bacteria. Here we propose a simple surface plasmon resonance imaging method (SPRi) for aptamer characterization using bacterial membrane vesicles, called nanosomes, instead of whole cells. Nanosomes were obtained from membrane fragments after mechanical cell disruption in order to preserve the external surface epitopes of the bacterium used for their production. The study was conducted on Bacillus cereus (B. cereus), a Gram-positive bacterium commonly found in soil, rice, vegetables, and dairy products. Four aptamers and one negative control were initially grafted onto a biochip. The binding of B. cereus cells and nanosomes to immobilized aptamers was then compared. The use of nanosomes instead of cells provided a 30-fold amplification of the SPRi signal, thus allowing the selection of aptamers with higher affinities. Aptamer SP15 was found to be the most sensitive and selective for B. cereus ATCC14579 nanosomes. It was then truncated into three new sequences (SP15M, SP15S1, and SP15S2) to reduce its size while preserving the binding site. Fitting the results of the SPRi signal for B. cereus nanosomes showed a similar trend for SP15 and SP15M, and a slightly higher apparent association rate constant kon for SP15S2, which is the truncation with a high probability of a G-quadruplex structure. These observations were confirmed on nanosomes from B. cereus ATCC14579 grown in milk and from the clinical strain B. cereus J066. The developed method was validated using fluorescence microscopy on whole B. cereus cells and the SP15M aptamer labeled with a rhodamine. This study showed that nanosomes can successfully mimic the bacterial membrane with great potential for facilitating the screening of specific ligands for bacteria.

Recent Advances on Peptide-Based Biosensors and Electronic Noses for Foodborne Pathogen Detection.

Foodborne pathogens present a serious issue around the world due to the remarkably high number of illnesses they cause every year. In an effort to narrow the gap between monitoring needs and currently implemented classical detection methodologies, the last decades have seen an increased development of highly accurate and reliable biosensors. Peptides as recognition biomolecules have been explored to develop biosensors that combine simple sample preparation and enhanced detection of bacterial pathogens in food. This review first focuses on the selection strategies for the design and screening of sensitive peptide bioreceptors, such as the isolation of natural antimicrobial peptides (AMPs) from living organisms, the screening of peptides by phage display and the use of in silico tools. Subsequently, an overview on the state-of-the-art techniques in the development of peptide-based biosensors for foodborne pathogen detection based on various transduction systems was given. Additionally, limitations in classical detection strategies have led to the development of innovative approaches for food monitoring, such as electronic noses, as promising alternatives. The use of peptide receptors in electronic noses is a growing field and the recent advances of such systems for foodborne pathogen detection are presented. All these biosensors and electronic noses are promising alternatives for the pathogen detection with high sensitivity, low cost and rapid response, and some of them are potential portable devices for on-site analyses.

Silicon photonic olfactory sensor based on an array of 64 biofunctionalized Mach-Zehnder interferometers.

Silicon photonics can address a variety of applications, from datacom and biosensing to lidars. Recently, this technology has been explored for gas sensing. Detection and identification of odors remains a critical challenge in diverse areas such as air quality, food spoilage, or personal well-being. In this work, we present an olfactory sensor based on an array of 64 biofunctionalized Mach-Zehnder interferometers integrated on a silicon nitride platform. The ability to analyze odors at ppm level is demonstrated for several volatile organic compounds.

Surfactant-like Peptide Self-Assembled into Hybrid Nanostructures for Electronic Nose Applications.

An electronic nose (e-nose) utilizes a multisensor array, which relies on the vector contrast of combinatorial responses, to effectively discriminate between volatile organic compounds (VOCs). In recent years, hierarchical structures made of nonbiological materials have been used to achieve the required sensor diversity. With the advent of self-assembling peptides, the ability to tune nanostructuration, surprisingly, has not been exploited for sensor array diversification. In this work, a designer surfactant-like peptide sequence, CG7-NH2, is used to fabricate morphologically and physicochemically heterogeneous "biohybrid" surfaces on Au-covered chips. These multistructural sensing surfaces, containing immobilized hierarchical nanostructures surrounded by self-assembled monolayers, are used for the detection and discrimination of VOCs. Through a simple and judicious design process, involving changes in pH and water content of peptide solutions, a five-element biohybrid sensor array coupled with a gas-phase surface plasmon resonance imaging system is shown to achieve sufficient discriminatory capabilities for four VOCs. Moreover, the limit of detection of the multiarray system is bench-marked at <1 and 6 ppbv for hexanoic acid and phenol (esophago-gastric biomarkers), respectively. Finally, the humidity effects are characterized, identifying the dissociation rate constant as a robust descriptor for classification, further exemplifying their efficacy as biomaterials in the field of artificial olfaction.

Interaction between Nanoparticles, Membranes and Proteins: A Surface Plasmon Resonance Study.

Regardless of the promising use of nanoparticles (NPs) in biomedical applications, several toxic effects have increased the concerns about the safety of these nanomaterials. Although the pathways for NPs toxicity are diverse and dependent upon many parameters such as the nature of the nanoparticle and the biochemical environment, numerous studies have provided evidence that direct contact between NPs and biomolecules or cell membranes leads to cell inactivation or damage and may be a primary mechanism for cytotoxicity. In such a context, this work focused on developing a fast and accurate method to characterize the interaction between NPs, proteins and lipidic membranes by surface plasmon resonance imaging (SPRi) technique. The interaction of gold NPs with mimetic membranes was evaluated by monitoring the variation of reflectivity after several consecutive gold NPs injections on the lipidic membranes prepared on the SPRi biochip. The interaction on the membranes with varied lipidic composition was compared regarding the total surface concentration density of gold NPs adsorbed on them. Then, the interaction of gold and silver NPs with blood proteins was analyzed regarding their kinetic profile of the association/dissociation and dissociation constants (koff). The surface concentration density on the membrane composed of 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine and cholesterol (POPC/cholesterol) was 2.5 times higher than the value found after the injections of gold NPs on POPC only or with dimethyldioctadecylammonium (POPC/DDAB). Regarding the proteins, gold NPs showed preferential binding to fibrinogen resulting in a value of the variation of reflectivity that was 8 times higher than the value found for the other proteins. Differently, silver NPs showed similar interaction on all the tested proteins but with a variation of reflectivity on immunoglobulin G (IgG) 2 times higher than the value found for the other tested proteins.

An Overview of Artificial Olfaction Systems with a Focus on Surface Plasmon Resonance for the Analysis of Volatile Organic Compounds.

The last three decades have witnessed an increasing demand for novel analytical tools for the analysis of gases including odorants and volatile organic compounds (VOCs) in various domains. Traditional techniques such as gas chromatography coupled with mass spectrometry, although very efficient, present several drawbacks. Such a context has incited the research and industrial communities to work on the development of alternative technologies such as artificial olfaction systems, including gas sensors, olfactory biosensors and electronic noses (eNs). A wide variety of these systems have been designed using chemiresistive, electrochemical, acoustic or optical transducers. Among optical transduction systems, surface plasmon resonance (SPR) has been extensively studied thanks to its attractive features (high sensitivity, label free, real-time measurements). In this paper, we present an overview of the advances in the development of artificial olfaction systems with a focus on their development based on propagating SPR with different coupling configurations, including prism coupler, wave guide, and grating.

Improvement of sensitivity of surface plasmon resonance imaging for the gas-phase detection of volatile organic compounds.

The analysis of volatile organic compounds (VOCs) is an important issue in various domains. For this, electronic noses (eN) are very promising as novel analytical tools that are portable, inexpensive, and efficient for reliable and rapid analyses. Recently, we have demonstrated that surface plasmon resonance imaging (SPRI) is especially interesting for the development of eNs dedicated for gas-phase analysis of VOCs. To further improve the performance of the eN based on SPRI, in this study, we investigated the influence of the LED wavelength on the sensitivity of the system. For this, a complete theoretical study together with a related experimental investigation for the validation were carried out. We have shown that the wavelength of the light source has an impact on the surface sensitivity of SPRI for the detection of VOCs. Indeed, in the studied wavelength range from 530 nm to 740 nm, both bulk sensitivity and surface sensitivity increase as the wavelength increases with good coherence between theoretical and experimental results. With the optimal LED wavelength, the detection limits of our eN reach low ppb range for VOC such as 1-butanol.

Antimicrobial peptide arrays for wide spectrum sensing of pathogenic bacteria.

Fast detection of bacteria in samples presumed to be un-contaminated, such as blood, is of great importance. Indeed, rapid diagnosis allows the set-up of appropriate antibiotic treatment. Besides clinical issues, there are many other domains, such as food processing or drug manufacturing, where the strict absence of any bacteria has to be assessed. Because the bacterial load found in most contaminated samples is often below the limit of detection for currently validated assays, a preliminary enrichment step is required to allow bacterial multiplication before proceeding to the analysis step, whatever it might be - cultural, immunological or molecular methods. In this study, we describe the use of a biosensor for single-step bacteria detection. The whole analysis is performed in less than 20 h, during the growth phase of the micro-organisms, using an array of antimicrobial peptides (AMPs) coupled with a surface plasmon resonance imager (SPRI). A wide range of bacterial strains are assayed, showing differentiated affinity patterns with the immobilized peptides, which are confirmed by multivariate analysis. This work establishes the evidence that antimicrobial peptides, mostly used so far in the antibiotic drug industry, are suited for the wide-spectrum detection of unknown bacteria in samples, even at very low initial loads. Moreover, the small set of AMPs that were assayed provided a specific affinity profile for each pathogen, as confirmed by multivariate analyses. Furthermore, this work opens up the possibility of applying this method in more complex and relevant samples such as foodstuff, urine or blood.

Direct identification of clinically relevant bacterial and yeast microcolonies and macrocolonies on solid culture media by Raman spectroscopy.

Decreasing turnaround time is a paramount objective in clinical diagnosis. We evaluated the discrimination power of Raman spectroscopy when analyzing colonies from 80 strains belonging to nine bacterial and one yeast species directly on solid culture medium after 24-h (macrocolonies) and 6-h (microcolonies) incubation. This approach, that minimizes sample preparation and culture time, would allow resuming culture after identification to perform downstream antibiotic susceptibility testing. Correct identification rates measured for macrocolonies and microcolonies reached 94.1% and 91.5%, respectively, in a leave-one-strain-out cross-validation mode without any correction for possible medium interference. Large spectral differences were observed between macrocolonies and microcolonies, that were attributed to true biological differences. Our results, conducted on a very diversified panel of species and strains, were obtained by using simple and robust sample preparation and preprocessing procedures, while still confirming published results obtained by using more complex elaborated protocols. Instrumentation is simplified by the use of 532-nm laser excitation yielding a Raman signal in the visible range. It is, to our knowledge, the first side-by-side full classification study of microorganisms in the exponential and stationary phases confirming the excellent performance of Raman spectroscopy for early species-level identification of microorganisms directly from an agar culture.