Surface enhanced Raman spectroscopy (SERS) for the discrimination of Arthrobacter strains based on variations in cell surface composition

Hybrid Raman and Laser-Induced Breakdown Spectroscopy for Food Authentication Applications

The issue of food fraud has become a significant global concern as it affects both the quality and safety of food products, ultimately resulting in the loss of customer trust and brand loyalty. To address this problem, we have developed an innovative approach that can tackle various types of food fraud, including adulteration, substitution, and dilution. Our methodology utilizes an integrated system that combines laser-induced breakdown spectroscopy (LIBS) and Raman spectroscopy. Although both techniques emerged as valuable tools for food analysis, they have until now been used separately, and their combined potential in food fraud has not been thoroughly tested. The aim of our study was to demonstrate the potential benefits of integrating Raman and LIBS modalities in a portable system for improved product classification and subsequent authentication. In pursuit of this objective, we designed and tested a compact, hybrid Raman/LIBS system, which exhibited distinct advantages over the individual modalities. Our findings illustrate that the combination of these two modalities can achieve higher accuracy in product classification, leading to more effective and reliable product authentication. Overall, our research highlights the potential of hybrid systems for practical applications in a variety of industries. The integration and design were mainly focused on the detection and characterization of both elemental and molecular elements in various food products. Two different sets of solid food samples (sixteen Alpine-style cheeses and seven brands of Arabica coffee beans) were chosen for the authentication analysis. Class detection and classification were accomplished through the use of multivariate feature selection and machine-learning procedures. The accuracy of classification was observed to improve by approximately 10% when utilizing the hybrid Raman/LIBS spectra, as opposed to the analysis of spectra from the individual methods. This clearly demonstrates that the hybrid system can significantly improve food authentication accuracy while maintaining the portability of the combined system. Thus, the successful implementation of a hybrid Raman-LIBS technique is expected to contribute to the development of novel portable devices for food authentication in food as well as other various industries.

Application of lectin-based biosensor technology in the detection of foodborne pathogenic bacteria: a review

Foodborne diseases caused by pathogenic bacteria pose a serious threat to human health.

Ultrasensitive amyloid β-protein quantification with high dynamic range using a hybrid graphene-gold surface-enhanced Raman spectroscopy platform

Surface enhanced Raman spectroscopy (SERS) holds great promise in biosensing because of its single-molecule, label-free sensitivity. We describe here the use of a graphene-gold hybrid plasmonic platform that enables quantitative SERS measurement. Quantification is enabled by normalizing analyte peak intensities to that of the graphene G peak. We show that two complementary quantification modes are intrinsic features of the platform, and that through their combined use, the platform enables accurate determination of analyte concentration over a concentration range spanning seven orders of magnitude. We demonstrate, using a biologically relevant test analyte, the amyloid β-protein (Aβ), a seminal pathologic agent of Alzheimer's disease (AD), that linear relationships exist between (a) peak intensity and concentration at a single plasmonic hot spot smaller than 100 nm, and (b) frequency of hot spots with observable protein signals, i.e. the co-location of an Aβ protein and a hot spot. We demonstrate the detection of Aβ at a concentration as low as 10-18 M after a single 20 μl aliquot of the analyte onto the hybrid platform. This detection sensitivity can be improved further through multiple applications of analyte to the platform and by rastering the laser beam with smaller step sizes.

Effect of growth media and phase on Raman spectra and discrimination of mycobacteria

When developing a Raman spectral library to identify bacteria, differences between laboratory and real world conditions must be considered. For example, culturing bacteria in laboratory settings is performed under conditions for ideal bacteria growth. In contrast, culture conditions in the human body may differ and may not support optimized bacterial growth. To address these differences, researchers have studied the effect of conditions such as growth media and phase on Raman spectra. However, the majority of these studies focused on Gram-positive or Gram-negative bacteria. This article focuses on the influence of growth media and phase on Raman spectra and discrimination of mycobacteria, an acid-fast genus. Results showed that spectral differences from growth phase and media can be distinguished by spectral observation and multivariate analysis. Results were comparable to those found for other types of bacteria, such as Gram-positive and Gram-negative. In addition, the influence of growth phase and media had a significant impact on machine learning models and their resulting classification accuracy. This study highlights the need for machine learning models and their associated spectral libraries to account for various growth parameters and stages to further the transition of Raman spectral analysis of bacteria from laboratory to clinical settings.

Analysis of Biomolecules Based on the Surface Enhanced Raman Spectroscopy

Analyzing biomolecules is essential for disease diagnostics, food safety inspection, environmental monitoring and pharmaceutical development. Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for detecting biomolecules due to its high sensitivity, rapidness and specificity in identifying molecular structures. This review focuses on the SERS analysis of biomolecules originated from humans, animals, plants and microorganisms, combined with nanomaterials as SERS substrates and nanotags. Recent advances in SERS detection of target molecules were summarized with different detection strategies including label-free and label-mediated types. This comprehensive and critical summary of SERS analysis of biomolecules might help researchers from different scientific backgrounds spark new ideas and proposals.

A novel surface-enhanced Raman scattering (SERS) detection for natural gas exploration using methane-oxidizing bacteria

Methane-oxidizing bacteria (MOB), a unique group of Gram-negative bacteria utilizing methane as a sole source of carbon and energy, have been proved to be a biological indicator for gas prospecting. Field and cultivation-free detection of MOB is important but still challenging in current microbial prospecting of oil and gas (MPOG) system. Herein, SERS was used for the first time to our knowledge to investigate two species of methanotrophs and four closely relevant bacteria that universally coexisted in the upper soil of natural gas. A special but very simple approach was utilized to make silver nanoparticles (Ag NPs) sufficiently contact with every single bacterial cell, and highly strong and distinct Raman signals free from any native fluorescence have been obtained, and successfully utilized for distinguishing MOB from other species. A more convincing multi-Raman criterion based on single Raman bands, and further the entire Raman spectrum in combination with statistical analysis (e.g., principal component analysis (PCA)), which were found capable of classifying MOB related bacterial cells in soil with an accuracy of 100%. This study therefore demonstrated sensitive and rapid SERS measurement technique accompanied by complete Raman database of various gas reservoirs related bacteria could aid field exploration of natural gas reservoir.

Review on SERS of Bacteria

Surface enhanced Raman spectroscopy (SERS) has been widely used for chemical detection. Moreover, the inherent richness of the spectral data has made SERS attractive for use in detecting biological materials, including bacteria. This review discusses methods that have been used to obtain SERS spectra of bacteria. The kinds of SERS substrates employed to obtain SERS spectra are discussed as well as how bacteria interact with silver and gold nanoparticles. The roll of capping agents on Ag/Au NPs in obtaining SERS spectra is examined as well as the interpretation of the spectral data.

SERS substrates fabricated using ceramic filters for the detection of bacteria: Eliminating the citrate interference

It was found that spectra obtained for bacteria on SERS substrates fabricated by filtering citrate-generated Ag nanoparticles (NPs) onto rigid, ceramic filters exhibited peaks due to citrate as well as the bacteria. In many cases the citrate spectrum overwhelmed that of the bacteria. Given the simplicity of the method to prepare these substrates, means of eliminating this citrate interference were explored. It was found that allowing a mixture of bacteria suspension and citrate-generated Ag NPs to incubate prior to filtering onto the ceramic filter eliminated this interference.

Surface enhanced hyper Raman scattering (SEHRS) and its applications

Surface enhanced hyper Raman scattering (SEHRS) is the spontaneous, two-photon excited Raman scattering that occurs for molecules residing in high local optical fields of plasmonic nanostructures. Being regarded as a non-linear analogue of surface enhanced Raman scattering (SERS), SEHRS shares most of its properties, but also has additional characteristics. They include complementary spectroscopic information resulting from different selection rules and a stronger enhancement due to the non-linearity in excitation. In practical spectroscopy, this can translate to advantages, which include a high selectivity when probing molecule-surface interactions, the possibility of probing molecules at low concentrations due to the strong enhancement, and the advantages that come with excitation in the near-infrared. In this review, we give examples of the wealth of vibrational spectroscopic information that can be obtained by SEHRS and discuss work that has contributed to understanding the effect and that therefore provides directions for SEHRS spectroscopy. Future applications could range from biophotonics to materials research.

Multiplex in vitro detection using SERS

This review focuses on the recent advances in SERS and its potential to detect multiple biomolecules in clinical samples.

Analysis of Genomic DNAs from Nine Rosaceae Species Using Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) of genomic DNA was used to determine genetic relationships and species identification of nine plants from three subfamilies of Rosaceae. Genomic DNA was extracted, and the SERS spectra were obtained by using a nanosilver collosol at an excitation wavelength of 785 nm. Adenine and ribodesose were the active sites of genomic DNAs in the silver surface-enhanced Raman spectra. The strong peak at 714 cm(-1) was assigned to the stretching vibration of adenine, the strong peak at 1011cm(-1) contributed to the stretching vibration of the deoxyribose and the scissoring vibrations of cytosine, and the strong peak at 625 cm(-1) is the stretching vibration of glycosidic bond and the scissoring vibrations of guanine. The three-dimensional plot of the first, second, and third principal components showed that the nine species could be classified into three categories (three subfamilies), consistent with the traditional classification. The model of the hierarchical cluster combined with the principal component of the second derivative was more reasonable. The results of the cluster analysis showed that apricot (Prunus armeniaca L.) and cherry (Prunus seudocerasus Lindl.) were clustered into one category (Prunoideae); firethorn (Firethorn fortuneana Li.), loquat (Eriobotrya japonica Lindl.), apple (Malus pumila Mill.), and crabapple (Malus hallianna Koehne.) were clustered into a second category (Pomoideae); and potentilla (Potentilla fulgens Wall.), rose (Rosa chinensis Jacd.), and strawberry (Fragaria chiloensis Duchesne.) were clustered into a third category (Rosoideae). These classifications were in accordance with the traditional classification with a correction rate of clustering of 100%. The correct rate of species identification was 100%. These five main results indicate that the genetic relationship and species identification of nine Rosaceae species could be determined by using SERS spectra of their genomic DNAs.

Isolation and identification of bacteria by means of Raman spectroscopy

Bacterial detection is a highly topical research area, because various fields of application will benefit from the progress being made. Consequently, new and innovative strategies which enable the investigation of complex samples, like body fluids or food stuff, and improvements regarding the limit of detection are of general interest. Within this review the prospects of Raman spectroscopy as a reliable tool for identifying bacteria in complex samples are discussed. The main emphasis of this work is on important aspects of applying Raman spectroscopy for the detection of bacteria like sample preparation and the identification process. Several approaches for a Raman compatible isolation of bacterial cells have been developed and applied to different matrices. Here, an overview of the limitations and possibilities of these methods is provided. Furthermore, the utilization of Raman spectroscopy for diagnostic purposes, food safety and environmental issues is discussed under a critical view.

Rapid identification by surface-enhanced Raman spectroscopy of cancer cells at low concentrations flowing in a microfluidic channel

Reliable identification and collection of cells from bodily fluids is of growing interest for monitoring patient response to therapy and for early detection of disease or its recurrence. We describe a detection platform that combines microfluidics with surface-enhanced Raman spectroscopy (SERS) for the identification of individual mammalian cells continuously flowing in a microfluidics channel. A mixture of cancerous and noncancerous prostate cells was incubated with SERS biotags (SBTs) developed and synthesized by us, then injected into a flow-focused microfluidic channel, which forces the cells into a single file. The spectrally rich SBTs are based on a silver nanoparticle dimer core labeled with a Raman-active small reporter molecule paired with an affinity biomolecule, providing a unique barcode whose presence in a composite SERS spectrum can be deconvoluted. Individual cancer cells passing through the focused laser beam were correctly identified among a proportionally larger number of other cells by their Raman signatures. We examine two deconvolution strategies: principal component analysis and classical least-squares. The deconvolution strategies are used to unmix the overall spectrum to determine the relative contributions between two SBT barcodes, where one SBT barcode indicates neuropilin-1 overexpression, while a second SBT barcode is more universal and indicates unspecific binding to a cell's membrane. Highly reliable results were obtained for all of the cell mixture ratios tested, the lowest being 1 in 100 cells.

Differentiation and classification of bacteria using vancomycin functionalized silver nanorods array based surface-enhanced Raman spectroscopy and chemometric analysis

Twenty seven different bacteria isolates from 12 species were analyzed using intrinsic surface-enhanced Raman scattering (SERS) spectra with recently developed vancomycin coated silver nanorod (VAN AgNR) substrates. The VAN AgNR substrates could generate reproducible SERS spectra of the bacteria with little to no interference from the environment or bacterial by-products as compared to the pristine substrates. By taking advantage of the structural composition of the cellular wall which varies from species to species, the differentiation of bacterial species is demonstrated by using chemometric analyses on those spectra. A second chemometric analysis step within the species cluster is able to differentiate serotypes and strains. The spectral features used for serotype differentiation arises from the surface proteins, while Raman peaks from adenine dominate the differentiation of strains. In addition, due to the intrinsic structural differences in the cell walls, the SERS spectra can distinguish Gram-positive from Gram-negative bacteria with high sensitivity and specificity, as well as 100% accuracy on predicting test samples. Our results provide important insights for using SERS as a bacterial diagnostic tool and further guide the design of a SERS-based detection platform.

In situ fabrication of 3D Ag@ZnO nanostructures for microfluidic surface-enhanced Raman scattering systems

In this work, we develop an in situ method to grow highly controllable, sensitive, three-dimensional (3D) surface-enhanced Raman scattering (SERS) substrates via an optothermal effect within microfluidic devices. Implementing this approach, we fabricate SERS substrates composed of Ag@ZnO structures at prescribed locations inside microfluidic channels, sites within which current fabrication of SERS structures has been arduous. Conveniently, properties of the 3D Ag@ZnO nanostructures such as length, packing density, and coverage can also be adjusted by tuning laser irradiation parameters. After exploring the fabrication of the 3D nanostructures, we demonstrate a SERS enhancement factor of up to ∼2×10(6) and investigate the optical properties of the 3D Ag@ZnO structures through finite-difference time-domain simulations. To illustrate the potential value of our technique, low concentrations of biomolecules in the liquid state are detected. Moreover, an integrated cell-trapping function of the 3D Ag@ZnO structures records the surface chemical fingerprint of a living cell. Overall, our optothermal-effect-based fabrication technique offers an effective combination of microfluidics with SERS, resolving problems associated with the fabrication of SERS substrates in microfluidic channels. With its advantages in functionality, simplicity, and sensitivity, the microfluidic-SERS platform presented should be valuable in many biological, biochemical, and biomedical applications.

Effect of T-DNA insertions on mRNA transcript copy numbers upstream and downstream of the insertion site in Arabidopsis thaliana explored by surface enhanced Raman spectroscopy

We report the effect of a T-DNA insertion on the expression level of mRNA transcripts of the TWISTED DWARF 1 (TWD1) gene upstream and downstream of the T-DNA insertion site in Arabidopsis. A novel approach based on surface-enhanced Raman spectroscopy (SERS) was developed to detect and quantify the effect of a T-DNA insertion on mRNA transcript accumulation at 5'- and 3'-ends of the TWD1 gene. A T-DNA insertion mutant in the TWD1 gene (twd1-2) was chosen to test the sensitivity and the feasibility of the approach. The null mutant of the FK506-like immunophilin protein TWD1 in Arabidopsis shows severe dwarfism and strong disoriented growth of plant organs. A spontaneous arising suppressor allele of twd1-2 called twd-sup displayed an intermediate phenotype between wild type and the knockout phenotype of twd1-2. Both twd1 mutant alleles have identical DNA sequences at the TWD1 locus including the T-DNA insertion in the fourth intron of the TWD1 gene but they show clear variability in the mutant phenotype. We present here the development and application of SERS-based mRNA detection and quantification using the expression of the TWD1 gene in wild type and both mutant alleles. The hallmarks of our SERS approach are a robust and fast assay to detect up to 0.10 fm of target molecules including the ability to omit in vitro transcription and amplification steps after RNA isolation. Instead we perform direct quantification of RNA molecules. This enables us to detect and quantify rare RNA molecules at high levels of precision and sensitivity.

A hybrid FLIM-elastic net platform for label free profiling of breast cancer

We report a label-free fluorescence lifetime profiling strategy to classify breast cancer cells, MCF10CA1h (malignant), MCF10A (nonmalignant), and MCF10AneoT (premalignant) in different stages of malignancy. Fluorescence Lifetime Imaging Microscopy (FLIM) was used to record the lifetime of autofluorescence of endogenous flavin in MCF10 cells in different stages of malignancy. Predominant differences in lifetimes ascertained by multi-exponential fitting curves can be attributed to the different forms of flavin protein; flavin mononucleotide (FMN), free flavin adenine dinucleotide (FAD), semiquinone, and bound FAD. A lifetime map of the metabolite was derived from the contribution of the lifetime of each metabolite by iterative reconvolution fitting of the Time Correlated Single Photon Counting (TCSPC) decay curves. Lifetime maps were constructed by mapping the average lifetime values pixel by pixel using MATLAB. The FLIM image (150 × 150 pixels) of each cell was extracted, resized and centered into 100 × 100 pixels using the nearest neighbor algorithm. Principal Component Analysis (PCA) in conjunction with Elastic net Analysis (EnA) was then used to classify the different stages of MCF10 cell lines based on average lifetime values. The EnA model provided an excellent classification of the cells at different stages of tumorigenesis yielding 100% accuracy.

Reliable plasmonic substrates for bioanalytical SERS applications easily prepared by convective assembly of gold nanocolloids

The ability to easily prepare Surface Enhanced Raman Scattering (SERS) substrates by the assembly of chemically synthesized gold nanocolloids is of great interest for the advancement of SERS-based optical detection and identification of molecular species of biological or chemical interest, pollutants or warfare agents. In this work we employ three very simple strategies, which can be implemented in any laboratory without the need for specialized equipment, to prepare assemblies of citrate-stabilized spherical gold colloids: (i) drop-coating, which induces the assembly of colloids in so-called coffee rings; (ii) a simplified variant of convective self-assembly (CSA), based on water evaporation in a constrained geometry, which yields highly uniform strips of nanoparticles (NP); (iii) assembly onto chemically functionalized glass surfaces which yields randomly assembled colloids and colloidal clusters. The SERS properties of the resulting colloidal assemblies are comparatively evaluated under multiple excitation lines with p-aminothiophenol (pATP) as a model Raman scatterer. The NP strips obtained by CSA prove to be SERS-active both in the visible and NIR and possess a highly uniform SERS response as demonstrated by spectra at individually selected sites and by confocal SERS mapping. Further it is shown that these NP strips are effective for the detection of cytosine, a DNA component, and for multi-analyte SERS detection. These results, showing how an efficient SERS substrate can be obtained by a very simple assembly method from easy-to-synthesize colloidal gold NP, can have an impact on the development of analytical SERS applications.

Microfluidics and Raman microscopy: current applications and future challenges

Raman microscopy systems are becoming increasingly widespread and accessible for characterising chemical species. Microfluidic systems are also progressively finding their way into real world applications. Therefore, it is anticipated that the integration of Raman systems with microfluidics will become increasingly attractive and practical. This review aims to provide an overview of Raman microscopy-microfluidics integrated systems for researchers who are actively interested in utilising these tools. The fundamental principles and application strengths of Raman microscopy are discussed in the context of microfluidics. Various configurations of microfluidics that incorporate Raman microscopy methods are presented, with applications highlighted. Data analysis methods are discussed, with a focus on assisting the interpretation of Raman-microfluidics data from complex samples. Finally, possible future directions of Raman-microfluidic systems are presented.

Differentiation of cancer cells in two-dimensional and three-dimensional breast cancer models by Raman spectroscopy

We demonstrate the first application of Raman spectroscopy in diagnosing nonmalignant, premalignant, malignant, and metastatic stages of breast cancer in a three-dimensional (3-D) cell culture model that closely mimics an in vivo environment. Comprehensive study comparing classification in two-dimensional (2-D) and 3-D cell models was performed using statistical methods composed of principal component analysis for exploratory analysis and outlier removal, partial least squares discriminant analysis, and elastic net regularized regression for classification. Our results show that Raman spectroscopy with an appropriate classification tool has excellent resolution to discriminate the four stages of breast cancer progression, with a near 100% accuracy for both 2-D and 3-D cell models. The diversity in chemical groups related to nucleic acids, proteins, and lipids, among other chemicals, were identified by appropriate peaks in the Raman spectra that correspond to the correct classification of the different stages of tumorigenesis model comprising of MCF10A, MCF10AneoT, MCF10CA1h, and MCF10CA1a cell lines. An explicit relationship between wavenumber and the stages of cancer progression was identified by the elastic net variable selection.

Sub-femtomole detection of 16s rRNA from Legionella pneumophila using surface plasmon resonance imaging

Legionellosis has been and continues to be a life-threatening disease worldwide, even in developed countries. Given the severity and unpredictability of Legionellosis outbreaks, developing a rapid, highly specific, and sensitive detection method is thus of great pertinence. In this paper, we demonstrate that sub-femtomole levels of 16s rRNA from pathogenic Legionella pneumophila can be timely and effectively detected using an appropriate designed capture, detector probes, and a QD SPRi signal amplification strategy. To achieve specific and sensitive detection, optimal hybridization conditions and parameters were implemented. Among these parameters, fragmentation of the 16s rRNA and further signal amplification by QDs were found to be the main parameters contributing to signal enhancement. The appropriate design of the detector probes also increased the sensitivity of the detection system, mainly due to secondary structure of 16s rRNA. The use of 16s rRNA from L. pneumophila allowed for the detection of metabolically active pathogens with high sensitivity. Detection of 16s rRNA in solutions as diluted as 1 pM at 450 μL (0.45 femtomole) was achieved in less than 3h, making our approach suitable for the direct, timely, and effective detection of L. pneumophila within man-made water systems.