New biochip technology for label-free detection of pathogens and their toxins

Advancing Mycotoxin Detection in Food and Feed: Novel Insights from Surface-Enhanced Raman Spectroscopy (SERS)

The implementation of low-cost and rapid technologies for the on-site detection of mycotoxin-contaminated crops is a promising solution to address the growing concerns of the agri-food industry. Recently, there have been significant developments in surface-enhanced Raman spectroscopy (SERS) for the direct detection of mycotoxins in food and feed. This review provides an overview of the most recent advancements in the utilization of SERS through the successful fabrication of novel nanostructured materials. Various bottom-up and top-down approaches have demonstrated their potential in improving sensitivity, while many applications exploit the immobilization of recognition elements and molecular imprinted polymers (MIPs) to enhance specificity and reproducibility in complex matrices. Therefore, the design and fabrication of nanomaterials is of utmost importance and are presented herein. This paper uncovers that limited studies establish detection limits or conduct validation using naturally contaminated samples. One decade on, SERS is still lacking significant progress and there is a disconnect between the technology, the European regulatory limits, and the intended end-user. Ongoing challenges and potential solutions are discussed including nanofabrication, molecular binders, and data analytics. Recommendations to assay design, portability, and substrate stability are made to help improve the potential and feasibility of SERS for future on-site agri-food applications.

Biosensors as early warning detection systems for waterborne Cryptosporidium

Waterborne disease is a global health threat contributing to a high burden of diarrhoeal disease, and growing evidence indicates a prospective increase in incidence coinciding with the profound effects of climate change. A major causative agent of gastrointestinal disease is Cryptosporidium, a protozoan waterborne parasite identified in over 70 countries. Cryptosporidium is a cause of high disease morbidity in children and the immunocompromised with limited treatment options for patients at risk of severe illness. The hardy nature of the organism leads to its persistence in various water sources, with certain water treatment procedures proving inefficient for its complete removal. While diagnostic methods for Cryptosporidium are well-defined in the clinical sphere, detection of Cryptosporidium in water sources remains suboptimal due to low dispersion of organisms in large sample volumes, lengthy processing times and high costs of equipment and reagents. A need for improvement exists to identify the organism as an emerging threat in domestic water systems, and the technological advantages that biosensors offer over current analytical methods may provide a preventative approach to outbreaks of Cryptosporidium. Biosensors are innovative, versatile and adaptable analytical tools that could provide highly sensitive, rapid, on-site analysis needed for Cryptosporidium detection in low-resource settings.

Thermally generated Au-Ag nanostructures with tunable localized surface plasmon resonance as SERS activity substrates

Various Au-Ag bimetallic alloy nanostructures were obtained as sensitive surface-enhanced Raman scattering (SERS) substrates by changing the thermal annealing sequence. The atomic force microscopy (AFM) and scanning electron microscopy (SEM) results confirm that Au/Ag bimetallic clusters and Ag-Au core-shell like structures can be designed by thermal annealing. The absorption spectra showed that the localized surface plasmon resonance (LSPR) frequency of the annealed Au/Ag bimetallic alloy structure could effectively shift from the near ultraviolet to the visible region. At the same time, the Au/Ag bimetallic alloy films modified by thermal annealing have shown satisfactory performance as SERS substrates. Raman enhancement mechanism of Au-Ag bimetallic alloy films is verified by finite-difference time-domain (FDTD) simulation results.

Machine learning-augmented surface-enhanced spectroscopy toward next-generation molecular diagnostics

The world today is witnessing the significant role and huge demand for molecular detection and screening in healthcare and medical diagnosis, especially during the outbreak of COVID-19. Surface-enhanced spectroscopy techniques, including Surface-Enhanced Raman Scattering (SERS) and Infrared Absorption (SEIRA), provide lattice and molecular vibrational fingerprint information which is directly linked to the molecular constituents, chemical bonds, and configuration. These properties make them an unambiguous, nondestructive, and label-free toolkit for molecular diagnostics and screening. However, new issues in molecular diagnostics, such as increasing molecular species, faster spread of viruses, and higher requirements for detection accuracy and sensitivity, have brought great challenges to detection technology. Advancements in artificial intelligence and machine learning (ML) techniques show promising potential in empowering SERS and SEIRA with rapid analysis and automatic data processing to jointly tackle the challenge. This review introduces the combination of ML and SERS/SEIRA by investigating how ML algorithms can be beneficial to SERS/SEIRA, discussing the general process of combining ML and SEIRA/SERS, highlighting the molecular diagnostics and screening applications based on ML-combined SEIRA/SERS, and providing perspectives on the future development of ML-integrated SEIRA/SERS. In general, this review offers comprehensive knowledge about the recent advances and the future outlook regarding ML-integrated SEIRA/SERS for molecular diagnostics and screening.

SERS-based antibiotic susceptibility testing: Towards point-of-care clinical diagnosis

Emerging antibiotic resistant bacteria constitute one of the biggest threats to public health. Surface-enhanced Raman scattering (SERS) is highly promising for detecting such bacteria and for antibiotic susceptibility testing (AST). SERS is fast, non-destructive (can probe living cells) and it is technologically flexible (readily integrated with robotics and machine learning algorithms). However, in order to integrate into efficient point-of-care (PoC) devices and to effectively replace the current culture-based methods, it needs to overcome the challenges of reliability, cost and complexity. Recently, significant progress has been made with the emergence of both new questions and new promising directions of research and technological development. This article brings together insights from several representative SERS-based AST studies and approaches oriented towards clinical PoC biosensing. It aims to serve as a reference source that can guide progress towards PoC routines for identifying antibiotic resistant pathogens. In turn, such identification would help to trace the origin of sporadic infections, in order to prevent outbreaks and to design effective medical treatment and preventive procedures.

Comprehensive review of conventional and state-of-the-art detection methods of Cryptosporidium

Cryptosporidium is a critical waterborne protozoan pathogen found in water resources that have been a major cause of death and serious illnesses worldwide, costing millions of dollars annually for its detection and treatment. Over the past several decades, substantial efforts have been made towards developing techniques for the detection of Cryptosporidium. Early diagnostic techniques were established based on the existing tools in laboratories, such as microscopes. Advancements in fluorescence microscopy, immunological, and molecular techniques have led to the development of several kits for the detection of Cryptosporidium spp. However, these methods have several limitations, such as long processing times, large sample volumes, the requirement for bulky and expensive laboratory tools, and the high cost of reagents. There is an urgent need to improve these existing techniques and develop low-cost, portable and rapid detection tools for applications in the water quality industry. In this review, we compare recent advances in nanotechnology, biosensing and microfluidics that have facilitated the development of sophisticated tools for the detection of Cryptosporidium spp.Finally, we highlight the advantages and disadvantages, of these state-of-the-art detection methods compared to current analytical methodologies and discuss the need for future developments to improve such methods for detecting Cryptosporidium in the water supply chain to enable real-time and on-site monitoring in water resources and remote areas.

Rapid and sensitive identification of uropathogenic Escherichia coli using a surface-enhanced-Raman-scattering-based biochip

Rapid, selective and sensitive sensing of bacteria remains challenging. We report on a highly sensitive and reproducible surface-enhanced Raman spectroscopy (SERS)-based sensing approach for the detection of uropathogenic Escherichia coli (E. coli) bacteria in urine. The assay is based on the specific capture of the bacteria followed by interaction with cetyltrimethylammonium bromide (CTAB)-stabilised gold nanorods (Au NRS) as SERS markers. High sensitivity up to 10 CFU mL^-1 is achieved by optimizing the capture interface based on hydrogenated amorphous silicon a-Si:H thin films. The integration of CH₃O-PEG750 onto a-Si:H gives the sensing interface an efficient anti-fouling character, while covalent linkage of antibodies directed against the major type-1 fimbrial pilin FimA of the human pathogen E. coli results in the specific trapping of fimbriated E. coli onto the SERS substrate and their spectral fingerprint identification.

An intracellular silver deposition method for targeted detection and chemical analysis of uncultured microorganisms

The vast majority of environmental bacteria remain uncultured, despite two centuries of effort in cultivating microorganisms. Our knowledge of their physiology and metabolic activity depends to a large extent on methods capable of analyzing single cells. Bacterial identification is a key step required by all currently used single-cell imaging techniques and is typically performed by means of fluorescent labeling. However, fluorescent cells cannot be visualized by ion- and electron microscopy and thus only correlative, indirect, cell identification is possible. Here we present a new method of bacterial identification by in situ hybridization coupled to the deposition of elemental silver nanoparticles (silver-DISH). We show that hybridized cells containing silver can be directly visualized by light microscopy, scanning electron microscopy, energy dispersive X-ray spectroscopy, secondary ion mass spectrometry (nanoSIMS), and confocal Raman micro-spectroscopy. Silver-DISH did not alter the isotopic (¹³C) and elemental composition of stable-isotope probed cells more than other available hybridization methods, making silver-DISH suitable for broad applications in stable-isotope labeling studies. Additionally, we demonstrate that silver-DISH can induce a surface-enhanced Raman scattering (SERS) effect, amplifying the Raman signal of biomolecules inside bacterial cells. This makes silver-DISH the only currently available method that is capable of delivering a SERS-active substrate inside specifically targeted microbial cells.

Whole-Organism Analysis by Vibrational Spectroscopy

Vibrational spectroscopy has contributed to the understanding of biological materials for many years. As the technology has advanced, the technique has been brought to bear on the analysis of whole organisms. Here, we discuss advanced and recently developed infrared and Raman spectroscopic instrumentation to whole-organism analysis. We highlight many of the recent contributions made in this relatively new area of spectroscopy, particularly addressing organisms associated with disease with emphasis on diagnosis and treatment. The application of vibrational spectroscopic techniques to entire organisms is still in its infancy, but new developments in imaging and chemometric processing will likely expand in the field in the near future.

Microscale and Nanoscale Electrophotonic Diagnostic Devices

Detecting and identifying infectious agents and potential pathogens in complex environments and characterizing their mode of action is a critical need. Traditional diagnostics have targeted a single characteristic (e.g., spectral response, surface receptor, mass, intrinsic conductivity, etc.). However, advances in detection technologies have identified emerging approaches in which multiple modes of action are combined to obtain enhanced performance characteristics. Particularly appealing in this regard, electrophotonic devices capable of coupling light to electron translocation have experienced rapid recent growth and offer significant advantages for diagnostics. In this review, we explore three specific promising approaches that combine electronics and photonics: (1) assays based on closed bipolar electrochemistry coupling electron transfer to color or fluorescence, (2) sensors based on localized surface plasmon resonances, and (3) emerging nanophotonics approaches, such as those based on zero-mode waveguides and metamaterials.

Characterization and Discrimination of Gram-Positive Bacteria Using Raman Spectroscopy with the Aid of Principal Component Analysis

Raman scattering and its particular effect, surface-enhanced Raman scattering (SERS), are whole-organism fingerprinting spectroscopic techniques that gain more and more popularity in bacterial detection. In this work, two relevant Gram-positive bacteria species, Lactobacillus casei (L. casei) and Listeria monocytogenes (L. monocytogenes) were characterized based on their Raman and SERS spectral fingerprints. The SERS spectra were used to identify the biochemical structures of the bacterial cell wall. Two synthesis methods of the SERS-active nanomaterials were used and the recorded spectra were analyzed. L. casei and L. monocytogenes were successfully discriminated by applying Principal Component Analysis (PCA) to their specific spectral data.

Surface-enhanced Raman spectroscopy introduced into the International Standard Organization (ISO) regulations as an alternative method for detection and identification of pathogens in the food industry

We show that surface-enhanced Raman spectroscopy (SERS) coupled with principal component analysis (PCA) can serve as a fast, reliable, and easy method for detection and identification of food-borne bacteria, namely Salmonella spp., Listeria monocytogenes, and Cronobacter spp., in different types of food matrices (salmon, eggs, powdered infant formula milk, mixed herbs, respectively). The main aim of this work was to introduce the SERS technique into three ISO (6579:2002; 11290-1:1996/A1:2004; 22964:2006) standard procedures required for detection of these bacteria in food. Our study demonstrates that the SERS technique is effective in distinguishing very closely related bacteria within a genus grown on solid and liquid media. The advantages of the proposed ISO-SERS method for bacteria identification include simplicity and reduced time of analysis, from almost 144 h required by standard methods to 48 h for the SERS-based approach. Additionally, PCA allows one to perform statistical classification of studied bacteria and to identify the spectrum of an unknown sample. Calculated first and second principal components (PC-1, PC-2) account for 96, 98, and 90% of total variance in the spectra and enable one to identify the Salmonella spp., L. monocytogenes, and Cronobacter spp., respectively. Moreover, the presented study demonstrates the excellent possibility for simultaneous detection of analyzed food-borne bacteria in one sample test (98% of PC-1 and PC-2) with a goal of splitting the data set into three separated clusters corresponding to the three studied bacteria species. The studies described in this paper suggest that SERS represents an alternative to standard microorganism diagnostic procedures. Graphical Abstract New approach of the SERS strategy for detection and identification of food-borne bacteria, namely S. enterica, L. monocytogenes, and C. sakazakii in selected food matrices.

Challenges in the analysis of multiple mycotoxins

The problems associated with different groups or ‘families’ of mycotoxins have been known for some time, and for many years certain groups of mycotoxins have been known to co-occur in commodities and foods. Until fairly recently commodities and foods were analysed for individual toxins or groups of related toxins and attempts to measure multiple groups of toxins required significant investments in terms of time, effort, and expense. Analytical technologies using both the instrument-intensive techniques, such as mass spectrometry, and screening techniques, such as immunoassays, have progressed significantly in recent years. This has led to the proliferation of techniques capable of detecting multiple groups of mycotoxins using a variety of approaches. Despite considerable progress, the challenges for routine monitoring of multiple toxins continue. Certain of these challenges, such as the need for co-extraction of multiple analytes with widely different polarities and the potential for carry-over of matrix components that can influence the results, are independent of the analytical technique (MS or immunoassay) used. Because of the wide variety of analytical platforms used for multi-toxin analysis, there are also specific challenges that arise amongst the analytical platforms. We showed that chromatographic methods with optical detection for aflatoxins maintain stable response factors over rather long periods. This offers the potential to reduce the analytical burden, provided the use of a single signal receives general acceptance once shown in practise as working approach. This must however be verified by a larger community of laboratories. For immunosensors the arising challenges include the reusability of sensors and, for chromatography-based assays they include the selection of appropriate calibration systems. In this article we seek to further describe the challenges associated with multi-toxin analysis and articulate how such challenges have recently been addressed.

Single-cell level methods for studying the effect of antibiotics on bacteria during infection

Considerable evidence about phenotypic heterogeneity among bacteria during infection has accumulated during recent years. This heterogeneity has to be considered if the mechanisms of infection and antibiotic action are to be understood, so we need to implement existing and find novel methods to monitor the effects of antibiotics on bacteria at the single-cell level. This review provides an overview of methods by which this aim can be achieved. Fluorescence label-based methods and Raman scattering as a label-free approach are discussed in particular detail. Other label-free methods that can provide single-cell level information, such as impedance spectroscopy and surface plasmon resonance, are briefly summarized. The advantages and disadvantages of these different methods are discussed in light of a challenging in vivo environment.

Raman-based microarray readout: a review

For a quarter of a century, microarrays have been part of the routine analytical toolbox. Label-based fluorescence detection is still the commonest optical readout strategy. Since the 1990s, a continuously increasing number of label-based as well as label-free experiments on Raman-based microarray readout concepts have been reported. This review summarizes the possible concepts and methods and their advantages and challenges. A common label-based strategy is based on the binding of selective receptors as well as Raman reporter molecules to plasmonic nanoparticles in a sandwich immunoassay, which results in surface-enhanced Raman scattering signals of the reporter molecule. Alternatively, capture of the analytes can be performed by receptors on a microarray surface. Addition of plasmonic nanoparticles again leads to a surface-enhanced Raman scattering signal, not of a label but directly of the analyte. This approach is mostly proposed for bacteria and cell detection. However, although many promising readout strategies have been discussed in numerous publications, rarely have any of them made the step from proof of concept to a practical application, let alone routine use. Graphical Abstract Possible realization of a SERS (Surface-Enhanced Raman Scattering) system for microarray readout.

Detection of Listeria innocua on roll-to-roll produced SERS substrates with gold nanoparticles

The rapid and accurate detection of food pathogens plays a critical role in the early prevention of foodborne epidemics. Combination of low cost sensing platforms and SERS detection can offer a solution for the pathogen detection.

Exploitation of Nanotechnology for the Monitoring of Waterborne Pathogens: State-of-the-Art and Future Research Priorities

Contaminated drinking water is one of the most important environmental contributors to the human disease burden. Monitoring of water for the presence of pathogens is an essential part of ensuring drinking water safety. In order to assess water quality it is essential to have methods available to sample and detect the type, level and viability of pathogens in water which are effective, cheap, quick, sensitive, and where possible high throughput. Nanotechnology has the potential to drastically improve the monitoring of waterborne pathogens when compared to conventional approaches. To date, there have been no reviews that outline the applications of nanotechnology in this area despite increasing exploitation of nanotechnology for this purpose. This review is therefore the first overview of the state-of-the-art in the application of nanotechnology to waterborne pathogen sampling and detection schemes. Research in this field has been centered on the use of engineered nanomaterials. The effectiveness and limitations of nanomaterial-based approaches is outlined. A future outlook of the advances that are likely to emerge in this area, as well as recommendations for areas of further research are provided.

Label-Free in Situ Discrimination of Live and Dead Bacteria by Surface-Enhanced Raman Scattering

Techniques to distinguish between live and dead bacteria in a quantitative manner are in high demand in numerous fields including medical care, food safety, and public security as well as basic science research. This work demonstrates new nanostructures (silver nanoparticles coating bacteria structure, Bacteria@AgNPs) and their utility for rapid counting of live and dead bacteria by surface-enhanced Raman scattering (SERS). We found that suspensions containing Gram-negative organisms as well as AgNPs give strong SERS signals of live bacteria when generated selectively on the particle surface. However, almost no SERS signals can be detected from Bacteria@AgNPs suspensions containing dead bacteria. We demonstrate successful quantification of different percentages of dead bacteria both in bulk liquid and on glass surfaces by using SERS mapping on a single cell basis. Furthermore, different chemicals have been used to elucidate the mechanism involved in this observation. Finally, we used the Bacteria@AgNPs method to detect antibiotic resistance of E. coli strains against several antibiotics used in human medicine.

Surfaces for competitive selective bacterial capture from protein solutions

Active surfaces that form the basis for bacterial sensors for threat detection, food safety, or certain diagnostic applications rely on bacterial adhesion. However, bacteria capture from complex fluids on the active surfaces can be reduced by the competing adsorption of proteins and other large molecules. Such adsorption can also interfere with device performance. As a result, multiple upstream processing steps are frequently employed to separate macromolecules from any cells, which remain in the buffer. Here, we present an economical approach to capture bacteria, without competitive adsorption by proteins, on engineered surfaces that do not employ biomolecular recognition, antibodies, or other molecules with engineered sequences. The surfaces are based on polyethylene glycol (PEG) brushes that, on their own, repel both proteins and bacteria. These PEG brushes backfill the surface around sparsely adsorbed cationic polymer coils (here, poly-L-lysine (PLL)). The PLL coils are effectively embedded within the brush and produce locally cationic nanoscale regions that attract negatively charged regions of proteins or cells against the steric background repulsion from the PEG brush. By carefully designing the surfaces to include just enough PLL to capture bacteria, but not enough to capture proteins, we achieve sharp selectivity where S. aureus is captured from albumin- or fibrinogen-containing solutions, but free albumin or fibrinogen molecules are rejected from the surface. Bacterial adhesion on these surfaces is not reduced by competitive protein adsorption, in contrast to performance of more uniformly cationic surfaces. Also, protein adsorption to the bacteria does not interfere with capture, at least for the case of S. aureus, to which fibrinogen binds through a specific receptor.

Integration of a nanostructured dielectrophoretic device and a surface-enhanced Raman probe for highly sensitive rapid bacteria detection

This work reports a synergistic approach to the concentration, detection and kinetic monitoring of pathogens through the integration of nanostructured dielectrophoresis (DEP) with nanotag-labelled Surface Enhanced Raman Spectroscopy (SERS). A nanoelectrode array made of embedded Vertically Aligned Carbon Nanofibers (VACNFs) at the bottom of a microfluidic chip was used to effectively capture and concentrate nanotag-labelled E. coli DHα5 cells into a 200 μm × 200 μm area on which a Raman laser probe was focused. The SERS nanotags were based on iron oxide-gold (IO-Au) core-shell nanoovals (NOVs) of ∼50 nm size, which were coated with a QSY21 Raman reporter and attached to E. coli through specific immunochemistry. The combination of the greatly enhanced Raman signal by the SERS nanotags and the effective DEP concentration significantly improved the detection limit and speed. The SERS signal was measured with both a confocal Raman microscope and a portable Raman probe during DEP capture, and was fully validated with fluorescence microscopy measurements under all DEP conditions. The SERS measurements were sensitive enough to detect a single bacterium. A concentration detection limit as low as 210 cfu ml(-1) using a portable Raman system was obtained with a DEP capture time of only ∼50 s. These results demonstrate the potential to develop a compact portable system for rapid and highly sensitive detection of specific pathogens. This system is reusable, requires minimum sample preparation, and is amenable to field applications.

An empirical evaluation of three vibrational spectroscopic methods for detection of aflatoxins in maize

Three commercially available vibrational spectroscopic techniques, including Raman, Fourier transform near infrared reflectance (FT-NIR), and Fourier transform infrared (FTIR) were evaluated to help users determine the spectroscopic method best suitable for aflatoxin analysis in maize (Zea mays L.) grain based on their relative efficiency and predictive ability. Spectral differences of Raman and FTIR spectra were more marked and pronounced among aflatoxin contamination groups than those of FT-NIR spectra. From the observations and findings in our current and previous studies, Raman and FTIR spectroscopic methods are superior to FT-NIR method in terms of predictive power and model performance for aflatoxin analysis and they are equally effective and accurate in predicting aflatoxin concentration in maize. The present study is considered as the first attempt to assess how spectroscopic techniques with different physical processes can influence and improve accuracy and reliability for rapid screening of aflatoxin contaminated maize samples.

Evaluation of antibiotic effects on Pseudomonas aeruginosa biofilm using Raman spectroscopy and multivariate analysis

We investigate the mode of action and classification of antibiotic agents (ceftazidime, patulin, and epigallocatechin gallate; EGCG) on Pseudomonas aeruginosa (P. aeruginosa) biofilm using Raman spectroscopy with multivariate analysis, including support vector machine (SVM) and principal component analysis (PCA). This method allows for quantitative, label-free, non-invasive and rapid monitoring of biochemical changes in complex biofilm matrices with high sensitivity and specificity. In this study, the biofilms were grown and treated with various agents in the microfluidic device, and then transferred onto gold-coated substrates for Raman measurement. Here, we show changes in biochemical properties, and this technology can be used to distinguish between changes induced in P. aeruginosa biofilms using three antibiotic agents. The Raman band intensities associated with DNA and proteins were decreased, compared to control biofilms, when the biofilms were treated with antibiotics. Unlike with exposure to ceftazidime and patulin, the Raman spectrum of biofilms exposed to EGCG showed a shift in the spectral position of the CH deformation stretch band from 1313 cm(-1) to 1333 cm(-1), and there was no difference in the band intensity at 1530 cm(-1) (C = C stretching, carotenoids). The PCA-SVM analysis results show that antibiotic-treated biofilms can be detected with high sensitivity of 93.33%, a specificity of 100% and an accuracy of 98.33%. This method also discriminated the three antibiotic agents based on the cellular biochemical and structural changes induced by antibiotics with high sensitivity and specificity of 100%. This study suggests that Raman spectroscopy with PCA-SVM is potentially useful for the rapid identification and classification of clinically-relevant antibiotics of bacteria biofilm. Furthermore, this method could be a powerful approach for the development and screening of new antibiotics.

Cellphone camera imaging of a periodically patterned chip as a potential method for point-of-care diagnostics

In this study, we demonstrate that a disposable chip periodically patterned with suitable ligands, an ordinary cellphone camera, and a simple pattern recognition software, can potentially be used for quantitative diagnostics. A key factor in this demonstration is the design of a calibration grid around the chip that, through a contrast transfer process, enables reliable analysis of the images collected under variable ambient lighting conditions. After exposure to a dispersion of amine terminated silica beads used as analyte mimicking pathogens, an epoxy-terminated glass substrate microcontact printed with octadecyltrichlorosilane (250 μm periodicity) developed a characteristic pattern of beads which could be easily imaged with a cellphone camera of 3.2 MP pixels. A simple pattern recognition algorithm using fast Fourier transform produced a quantitative estimate of the analyte concentration present in the test solution. In this method importantly, neither the chip fabrication process nor the fill-factor of the periodic pattern need be perfect to arrive at a conclusive diagnosis. The method suggests a viable platform that may potentially find use in fault-tolerant and robust point-of-care diagnostic applications.

Detection of the mycotoxin citrinin using silver substrates and Raman spectroscopy

We detected a trace amount of the mycotoxin citrinin using surface-enhanced Raman scattering (SERS) on silver nanoparticle (Ag NP) surfaces. The SERS substrate on hydrophobic Teflon films was also introduced to observe the citrinin peaks. A broad band at ∼1382cm(-1), which was ascribed to the symmetric carboxylate stretching mode, was observed in addition to an antisymmetric carboxylate stretching mode at ∼1568cm(-1) in the Raman spectra. The spectral feature indicated that citrinin would adsorb on Ag NPs via its carboxylate form. Based on density functional theory (DFT) calculations, vibrational mode analysis was performed to compare the Raman spectra of citrinin. DFT calculations also predicted that a bidentate bridge configuration through O15 and O16 atoms in citrinin would be the most stable on three Ag atoms. After treating with Ag NPs, observation of citrinin peaks was attempted in fungal cells of Penicillium citrinum. This work may provide useful insights into the direct observation of the hazardous citrinin mycotoxin using SERS by understanding its adsorption behaviors on Ag surfaces.

Next revolution in the molecular theranostics of infectious diseases: microfabricated systems for personalized medicine

The molecular diagnosis of infectious diseases is currently going through a revolution sustained by the regulatory approval of amplification tests that have been shown to be equivalent or superior to existing gold standard methods. The recent approval of a microarray system for the pharmacogenomic profiling of cytochrome P450-mediated drug metabolism is paving the way to novel, rapid, sensitive, robust and economical microfabricated systems for point-of-care diagnostics, which are utilized closer and closer to the patient's bedside. These systems will enable the multiparametric genetic evaluation of several medical conditions, including infectious diseases. This forecoming revolution will position molecular theranostics in a broader integrated view of personalized medicine, which exploits genetic information from microbes and human hosts to optimize patient management and disease treatment.

Silver nanoaggregates on chitosan functionalized graphene oxide for high-performance surface-enhanced Raman scattering

Herein we describe a self-assembly synthesis of graphene oxide/Ag nanoparticles nano-composites (GO/CS/AgNPs) by non-covalent attachment of AgNPs to chitosan (CS) functionalized graphene oxide (GO) sheets. The negatively charged AgNPs are prone to form aggregates on GO/CS via electrostatic interaction, which is extremely beneficial to the surface-enhanced Raman scattering (SERS) detection of aromatic molecules. Taking advantage of the enrichment of target molecules on GO, the obtained hybrids exhibit strong SERS activity to aromatic molecules (trypan blue and methylene blue). Furthermore, SERS signals of a negatively charged molecule (trypan blue) are stronger than signals of a positively charged molecule (methylene blue) due to the different adsorption capacity of GO/CS/AgNPs for the two opposite charged molecules through electrostatic interaction. Moreover, GO/CS/AgNPs remarkably enhance the main peaks of l-phenylalanine, in comparison with the silver nanoparticles, showing great potential for biomedical applications.

Surface enhanced Raman scattering substrate with metallic nanogap array fabricated by etching the assembled polystyrene spheres array

A sensitive surface enhanced Raman scattering (SERS) substrate with metallic nanogap array (MNGA) is fabricated by etching of an assembled polystyrene (PS) spheres array, followed by the coating of a metal film. The substrate is reproducible in fabrication and sensitive due to the nanogap coupling resonance (NGCR) enhancement. The NGCR is analyzed with the finite difference time domain (FDTD) method, and the relationship between the gap parameter and the field enhancement is obtained. Experimental measurements of R6G on demonstrate that the enhancement factor (EF) of the MNGA SERS substrate is increased by more than two fold compared with the control sample.

Surface-Enhanced Raman Scattering: A Technique of Choice for Molecular Detection

Although surface-enhanced Raman scattering (SERS) has crossed its infancy long ago, it is yet to persuade different challenges to make it available in day-to-day applications. SERS is being criticized mainly due to the quality of the SERS analyses that uses substrates to get the giant enhancement for respective Raman signal of the target molecule. Hence, understanding the phenomena behind substrates, cost-effective development and optimization of such substrates for routine analytical purposes and utilization of modern modalities to get the insights out has become a very wide-spreading and interesting area of research. In this piece of work, several key terminologies related to SERS have been presented in brief. Since SERS is a localized surface plasmon resonance (LSPR) mediated signal-enhancing phenomena, it is indispensable to understand the correlation between LSPR excitations originated from substrate and SERS signal originated from molecules. A wide range of SERS-active substrates including scattered nanoaggregates, anisotropic assembly, two-dimensional nanostructure, multi-layered nanostructure of gold nanoparticles and colloidal approach have been used to interpret such correlation between LSPR excitations and SERS characteristics. Few exemplary applications of SERS have been also mentioned followed by typical simulative work how nanoobject behaves at different excitations and polarizations.

Quantitative Detection with Surface Enhanced Raman Scattering (SERS) Using Self-Assembled Gold Nanoparticle Cluster Arrays

We analysed sensitivity of high-density arrays of self-assembled gold nanoparticle clusters towards trace analyte detection and quantitative determination by surface enhanced Raman spectroscopy (SERS) employing an aromatic thiol as probe molecule. Periodic nanoscale arrays of gold nanoparticle clusters consisting of an average of 18 nanoparticles per cluster, and exhibiting mean inter-particle and inter-cluster separations below 10 nm were prepared using electrostatic self-assembly on block copolymer templates. The concentration dependent scaling of SERS intensities and the lowest detection limits on the cluster arrays on silicon substrate was probed using 1-naphthalenethiol (NT) as test molecule. The substrates show a detection limit of 10 nM along with high sensitivity to changes in NT concentration, which we attribute to high density of hot-spots uniformly organised across the surface. The capability for facile realisation of such arrays without a clean room environment or expensive tools makes the approach suitable for adoption for economic and high-performing SERS sensors.

Detection of Cryptosporidium in miniaturised fluidic devices

Contamination of drinking water with the protozoan pathogen, Cryptosporidium, represents a serious risk to human health due to the low infectious dose and the resistance of this parasite to chlorine disinfection. Therefore, several countries have legislated for the frequent monitoring of drinking water for Cryptosporidium presence. Existing approved monitoring protocols are however time-consuming and do not provide essential information on the species, virulence or viability of detected oocysts. Rapid, more information-rich and automatable systems for Cryptosporidium detection are highly sought-after, and numerous miniaturised devices have been developed to address this need. This review article aims to summarise the state-of-the-art and compare the performance of these systems in terms of detection limit, ability to determine species, viability and performance in the presence of interferents. Finally, conclusions are drawn with regard to the most promising methods and directions of future research.

Nanoparticle cluster arrays for high-performance SERS through directed self-assembly on flat substrates and on optical fibers

We demonstrate template-guided self-assembly of gold nanoparticles into ordered arrays of uniform clusters suitable for high-performance SERS on both flat (silicon or glass) chips and an optical fiber faucet. Cluster formation is driven by electrostatic self-assembly of anionic citrate-stabilized gold nanoparticles (~11.6 nm diameter) onto two-dimensionally ordered polyelectrolyte templates realized by self-assembly of polystyrene-block-poly(2-vinylpyridine). A systematic variation is demonstrated for the number of particles (N ≈ 5, 8, 13, or 18) per cluster as well as intercluster separations (S(c) ≈ 37-10 nm). Minimum interparticle separations of <5 nm, intercluster separations of ~10 nm, and nanoparticle densities on surfaces as high as ~7 × 10(11)/in.(2) are demonstrated. Geometric modeling is used to support experimental data toward estimation of interparticle and intercluster separations in cluster arrays. Optical modeling and simulations using the finite difference time domain method are used to establish the influence of cluster size, shape, and intercluster separations on the optical properties of the cluster arrays in relation to their SERS performance. Excellent SERS performance, as evidenced by a high enhancement factor, >10(8) on flat chips and >10(7) for remote sensing, using SERS-enabled optical fibers is demonstrated. The best performing cluster arrays in both cases are achievable without the use of any expensive equipment or clean room processing. The demonstrated approach paves the way to significantly low-cost and high-throughput production of sensor chips or 3D-configured surfaces for remote sensing applications.

A Novel Method for Bacterial UTI Diagnosis Using Raman Spectroscopy

The current state of the art on bacterial classification using Raman and Surface Enhanced Raman Spectroscopy (SERS) for the purpose of developing a rapid and more accurate method for urinary tract infection (UTI) diagnosis is presented. SERS, an enhanced version of Raman offering much increased sensitivity, provides complex biochemical information which, in conjunction with advanced analysis and classification techniques, can become a valuable diagnostic tool. The variety of metal substrates used for SERS, including silver and gold colloids, as well as nanostructured metal surfaces, is reviewed. The challenges in preprocessing noisy and complicated spectra and the various methods used for feature creation as well as a novel method using spectral band ratios are described. The various unsupervised and supervised classification methods commonly used for SERS spectra of bacteria are evaluated. Current research on transforming SERS into a valuable clinical tool for the diagnosis of UTIs is presented. Specifically, the classification of bacterial spectra (a) as positive or negative for an infection, (b) as belonging to a particular species of bacteria, and (c) as sensitive or resistant to an antibiotic are described. This work can lead to the development of novel technology with extremely important benefits for public health.

Methods used for the detection and subtyping of Listeria monocytogenes

Listeria monocytogenes is an important foodborne pathogen responsible for non-invasive and invasive diseases in the elderly, pregnant women, neonates and immunocompromised populations. This bacterium has many similarities with other non-pathogenic Listeria species which makes its detection from food and environmental samples challenging. Subtyping of L. monocytogenes strains can prove to be crucial in epidemiological investigations, source tracking contamination from food processing plants and determining evolutionary relationships between different strains. In recent years there has been a shift towards the use of molecular subtyping. This has led to the development of new subtyping techniques such as multi-locus variable number tandem repeat analysis (MLVA) and multi-locus sequence based typing (MLST). This review focuses on the available methods for Listeria detection including immuno-based techniques and the more recently developed molecular methods and analytical techniques such as matrix-assisted laser desorption/ionisation time-of-flight based mass spectrometry (MALDI-TOF MS). It also includes a comparison and critical analysis of the available phenotypic and genotypic subtyping techniques that have been investigated for L. monocytogenes.