SERS characterization of biochemical changes associated with biodesulfurization of dibenzothiophene using Gordonia sp. HS126-4N

In this study, Gordonia sp. HS126-4N was employed for dibenzothiophene (DBT) biodesulfurization, tracked over 9 days using SERS. During the initial lag phase, no significant spectral changes were observed, but after 48 h, elevated metabolic activity was evident. At 72 h, maximal bacterial population correlated with peak spectrum variance, followed by stable spectral patterns. Despite 2-hydroxybiphenyl (2-HBP) induced enzyme suppression, DBT biodesulfurization persisted. PCA and PLS-DA analysis of the SERS spectra revealed distinctive features linked to both bacteria and DBT, showcasing successful desulfurization and bacterial growth stimulation. PLS-DA achieved a specificity of 95.5 %, sensitivity of 94.3 %, and AUC of 74 %, indicating excellent classification of bacteria exposed to DBT. SERS effectively tracked DBT biodesulfurization and bacterial metabolic changes, offering insights into biodesulfurization mechanisms and bacterial development phases. This study highlights SERS' utility in biodesulfurization research, including its use in promising advancements in the field.

Unraveling RNA contribution to the molecular origins of bacterial surface-enhanced Raman spectroscopy (SERS) signals

Surface-enhanced Raman spectroscopy (SERS) is widely utilized in bacterial analyses, with the dominant SERS peaks attributed to purine metabolites released during sample preparation. Although adenosine triphosphate (ATP) and nucleic acids are potential molecular origins of these metabolites, research on their exact contributions remains limited. This study explored purine metabolite release from E. coli and RNA integrity following various sample preparation methods. Standard water washing generated dominant SERS signals within 10 s, a duration shorter than the anticipated RNA half-lives under starvation. Evaluating RNA integrity indicated that the most abundant ribosomal RNA species remained intact for hours post-washing, whereas messenger RNA and transfer RNA species degraded gradually. This suggests that bacterial SERS signatures observed after the typical washing step could originate from only a small fraction of endogenous purine-containing molecules. In contrast, acid depurination led to degradation of most RNA species, releasing about 40 times more purine derivatives than water washing. Mild heating also instigated the RNA degradation and released more purine derivatives than water washing. Notably, differences were also evident in the dominant SERS signals following these treatments. This work provides insights into SERS-based studies of purine metabolites released by bacteria and future development of methodologies.

Characterization of vaginal Lactobacillus in biologically relevant fluid using surface-enhanced Raman spectroscopy

The native vaginal microbiome plays a crucial role in maintaining vaginal health and disruption can have significant consequences for women during their lifetime. While the composition of the vaginal microbiome is important, current methods for monitoring this community are lacking. Clinically used techniques routinely rely on subjective analysis of vaginal fluid characteristics or time-consuming microorganism culturing. Surface-enhanced Raman spectroscopy (SERS) can aid in filling this gap in timely detection of alterations in the vaginal microbiome as it can discriminate between bacterial species in complex solutions including bacterial mixtures and biofluids. SERS has not previously been applied to study variations in vaginal Lactobacillus, the most common species found in the vaginal microbiome, in complex solutions. Herein, the SERS spectra of Lactobacillus crispatus (L. crispatus) and Lactobacillus iners (L. iners), two of the most common vaginal bacteria, was characterized at physiologically relevant concentrations. Subsequently, the ability of SERS to detect L. crispatus and L. iners in both pure mixtures and when mixed with a synthetic vaginal fluid mimicking solution was determined. In both pure and complex solutions, SERS coupled with partial least squares regression predicted the ratiometric bacterial content with less than 10% error and strong goodness of prediction (Q2 > 0.9). This developed method highlights the applicability of SERS to predict the dominant Lactobacillus in the vaginal micro-environment toward the monitoring of this community.

Raman-Activated, Interactive Sorting of Isotope-Labeled Bacteria

Due to its high spatial resolution, Raman microspectroscopy allows for the analysis of single microbial cells. Since Raman spectroscopy analyzes the whole cell content, this method is phenotypic and can therefore be used to evaluate cellular changes. In particular, labeling with stable isotopes (SIPs) enables the versatile use and observation of different metabolic states in microbes. Nevertheless, static measurements can only analyze the present situation and do not allow for further downstream evaluations. Therefore, a combination of Raman analysis and cell sorting is necessary to provide the possibility for further research on selected bacteria in a sample. Here, a new microfluidic approach for Raman-activated continuous-flow sorting of bacteria using an optical setup for image-based particle sorting with synchronous acquisition and analysis of Raman spectra for making the sorting decision is demonstrated, showing that active cells can be successfully sorted by means of this microfluidic chip.

Accurate age-grading of field-aged mosquitoes reared under ambient conditions using surface-enhanced Raman spectroscopy and artificial neural networks

Age-grading mosquitoes are significant because only older mosquitoes are competent to transmit pathogens to humans. However, we lack effective tools to do so, especially at the critical point where mosquitoes become a risk to humans. In this study, we demonstrated the capability of using surface-enhanced Raman spectroscopy and artificial neural networks to accurately age-grade field-aged low-generation (F2) female Aedes aegypti mosquitoes held under ambient conditions (error was 1.9 chronological days, in the range 0-22 days). When degree days were used for model calibration, the accuracy was further improved to 20.8 degree days (approximately equal to 1.4 chronological days), which indicates the impact of temperature fluctuation on prediction accuracy. This performance is a significant advancement over binary classification. The great accuracy of this method outperforms traditional age-grading methods and will facilitate effective epidemiological studies, risk assessment, vector intervention monitoring, and evaluation.

Rapid discrimination of Shigella spp. and Escherichia coli via label-free surface enhanced Raman spectroscopy coupled with machine learning algorithms

Shigella and enterotoxigenic Escherichia coli (ETEC) are major bacterial pathogens of diarrheal disease that is the second leading cause of childhood mortality globally. Currently, it is well known that Shigella spp., and E. coli are very closely related with many common characteristics. Evolutionarily speaking, Shigella spp., are positioned within the phylogenetic tree of E. coli. Therefore, discrimination of Shigella spp., from E. coli is very difficult. Many methods have been developed with the aim of differentiating the two species, which include but not limited to biochemical tests, nucleic acids amplification, and mass spectrometry, etc. However, these methods suffer from high false positive rates and complicated operation procedures, which requires the development of novel methods for accurate and rapid identification of Shigella spp., and E. coli. As a low-cost and non-invasive method, surface enhanced Raman spectroscopy (SERS) is currently under intensive study for its diagnostic potential in bacterial pathogens, which is worthy of further investigation for its application in bacterial discrimination. In this study, we focused on clinically isolated E. coli strains and Shigella species (spp.), that is, S. dysenteriae, S. boydii, S. flexneri, and S. sonnei, based on which SERS spectra were generated and characteristic peaks for Shigella spp., and E. coli were identified, revealing unique molecular components in the two bacterial groups. Further comparative analysis of machine learning algorithms showed that, the Convolutional Neural Network (CNN) achieved the best performance and robustness in bacterial discrimination capacity when compared with Random Forest (RF) and Support Vector Machine (SVM) algorithms. Taken together, this study confirmed that SERS paired with machine learning could achieve high accuracy in discriminating Shigella spp., from E. coli, which facilitated its application potential for diarrheal prevention and control in clinical settings.

Traceability of bilberries (Vaccinium myrtillus L.) of the Baltic-Nordic region using surface-enhanced Raman spectroscopy (SERS): DFT simulation-based DNA analysis

Food traceability is a major issue in the industry. We investigated whether bilberries (Vaccinium myrtillus L.) from 4 different locations within the Baltic-Nordic region could be effectively differentiated using surface-enhanced Raman scattering (SERS) based spectral data and chemometric analyses. Furthermore, we aimed to determine if nucleobase (adenine and cytosine) methylation could be responsible for any observed variation. Our experiment was successful in that both principal component (PCA) and discriminant function analyses (DFA) showed differentiation between bilberry DNA from all 4 geographical regions. Density functional theory (DFT) based simulations allowed us to analyze whether DNA's spectral data dissimilarities may be due to nucleobase methylation. Although results were inconclusive on this, our investigation provides valuable data on simulated versus experimental DNA and DNA component spectra. Further research will be directed towards understanding what other epigenetic changes could be responsible for the observed DNA variation as well as determining the optimal parameters for using DFT simulations in upcoming projects.

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.

Surface-enhanced Raman spectroscopy combined with stable isotope probing to assess the metabolic activity of Escherichia coli cells in chicken carcass wash water

Rapid evaluation of the metabolic activity of microorganisms is crucial in the assessment of the disinfection ability of various antimicrobial agents in the food industry. In this study, surface-enhanced Raman spectroscopy combined with isotope probing was employed for the analysis of the disinfection of single bacterial cells in the chicken carcass wash water. The Raman signals from single Escherichia coli O157:H7 cells were enhanced by in situ synthesis of silver nanoparticles. The ΔCD of the cells grown in presence of 0.5% hydrogen peroxide and 50 ppm chlorine was 5.86 ± 1.86% and 5.1 ± 2.3%, respectively, which showed significant reduction compared with cells grown in the absence of disinfecting agents (19.86 ± 2.51%) after 2 h of incubation. The study proved that the proposed method had the potential to assess the metabolic activity of microorganisms in other food products and optimize the disinfection process.

SERS-PLSR Analysis of Vaginal Microflora: Towards the Spectral Library of Microorganisms

The accurate identification of microorganisms belonging to vaginal microflora is crucial for establishing which microorganisms are responsible for microbial shifting from beneficial symbiotic to pathogenic bacteria and understanding pathogenesis leading to vaginosis and vaginal infections. In this study, we involved the surface-enhanced Raman spectroscopy (SERS) technique to compile the spectral signatures of the most significant microorganisms being part of the natural vaginal microbiota and some vaginal pathogens. Obtained data will supply our still developing spectral SERS database of microorganisms. The SERS results were assisted by Partial Least Squares Regression (PLSR), which visually discloses some dependencies between spectral images and hence their biochemical compositions of the outer structure. In our work, we focused on the most common and typical of the reproductive system microorganisms (Lactobacillus spp. and Bifidobacterium spp.) and vaginal pathogens: bacteria (e.g., Gardnerella vaginalis, Prevotella bivia, Atopobium vaginae), fungi (e.g., Candida albicans, Candida glabrata), and protozoa (Trichomonas vaginalis). The obtained results proved that each microorganism has its unique spectral fingerprint that differentiates it from the rest. Moreover, the discrimination was obtained at a high level of explained information by subsequent factors, e.g., in the inter-species distinction of Candida spp. the first three factors explain 98% of the variance in block Y with 95% of data within the X matrix, while in differentiation between Lactobacillus spp. and Bifidobacterium spp. (natural flora) and pathogen (e.g., Candida glabrata) the information is explained at the level of 45% of the Y matrix with 94% of original data. PLSR gave us insight into discriminating variables based on which the marker bands representing specific compounds in the outer structure of microorganisms were found: for Lactobacillus spp. 1400 cm⁻¹, for fungi 905 and 1209 cm⁻¹, and for protozoa 805, 890, 1062, 1185, 1300, 1555, and 1610 cm⁻¹. Then, they can be used as significant marker bands in the analysis of clinical subjects, e.g., vaginal swabs.

Endophytes from blueberry (Vaccinium sp.) fruit: Characterization of yeast and bacteria via label-free surface-enhanced Raman spectroscopy (SERS)

Blueberries (Vaccinium sp.) are consumed all around the globe, however, their endophytic community has not been thoroughly researched, specifically their fruit endophytes. We aimed to isolate and analyze easily cultivable blueberry fruit endophytes to help in future research, concerning probiotic microorganisms. Twelve strains were isolated in this pilot study, genetically homologous with Staphylococcus hominis, Staphylococcus cohnii, Salmonella enterica, Leuconostoc mesenteroides, and [Candida] santamariae. To determine the molecular composition of these isolates we used label-free surface-enhanced Raman spectroscopy (SERS). To our knowledge, this is the first time that SERS spectra for L. mesenteroides and C. santamariae are presented, as well as the first report of Candida yeast, isolated specifically from blueberry fruits. Our findings suggest that the differences in tested yeast and bacteria SERS spectra and subsequent differentiation are facilitated by minor shifts in spectral peak positions as well as their intensities. Moreover, we used principal component and discriminant function analyses to differentiate chemotypes within our isolate group, proving the sensitivity of the technique and its usefulness to recognize different strains in plant-associated microbe samples, which will aid to streamline future studies in biofertilizers and biocontrol agents.

Spectroscopic investigation of faeces with surface-enhanced Raman scattering: a case study with coeliac patients on gluten-free diet

Surface-enhanced Raman scattering (SERS) spectra of faecal samples can be obtained by adding AuNP to their methanol extracts according to the reported protocol, and display bands that are due to bilirubin-like species but also to xanthine and hypoxanthine, two metabolic products secreted by gut bacteria. A total of 27 faecal samples from three different groups, i.e. coeliac patients (n = 9), coeliac patients on gluten-free diet (n = 10) and a control group (n = 8), were characterized with both SERS spectroscopy and 16S rRNA sequencing analysis. Significant differences are present between SERS spectra of coeliac patients and those on gluten-free diet, with a marked increase in the relative intensity of both xanthine and hypoxanthine for the latter. Interestingly, these differences do not correlate with bacterial composition as derived from 16S rRNA sequencing.

Using Stable Isotope Probing and Raman Microspectroscopy To Measure Growth Rates of Heterotrophic Bacteria

The suitability of stable isotope probing (SIP) and Raman microspectroscopy to measure growth rates of heterotrophic bacteria at the single-cell level was evaluated. Label assimilation into Escherichia coli biomass during growth on a complex ¹³C-labeled carbon source was monitored in time course experiments. ¹³C incorporation into various biomolecules was measured by spectral "red shifts" of Raman-scattered emissions. The ¹³C- and ¹²C-isotopologues of the amino acid phenylalanine (Phe) proved to be quantitatively accurate reporter molecules of cellular isotopic fractional abundances (f_cell). Values of f_cell determined by Raman microspectroscopy and independently by isotope ratio mass spectrometry (IRMS) over a range of isotopic enrichments were statistically indistinguishable. Progressive labeling of Phe in E. coli cells among a range of ¹³C/¹²C organic substrate admixtures occurred predictably through time. The relative isotopologue abundances of Phe determined by Raman spectral analysis enabled the accurate calculation of bacterial growth rates as confirmed independently by optical density (OD) measurements. The results demonstrate that combining SIP and Raman microspectroscopy can be a powerful tool for studying bacterial growth at the single-cell level on defined or complex organic ¹³C carbon sources, even in mixed microbial assemblages. IMPORTANCE Population growth dynamics and individual cell growth rates are the ultimate expressions of a microorganism's fitness under its environmental conditions, whether natural or engineered. Natural habitats and many industrial settings harbor complex microbial assemblages. Their heterogeneity in growth responses to existing and changing conditions is often difficult to grasp by standard methodologies. In this proof-of-concept study, we tested whether Raman microspectroscopy can reliably quantify the assimilation of isotopically labeled nutrients into E. coli cells and enable the determination of individual growth rates among heterotrophic bacteria. Raman-derived growth rate estimates were statistically indistinguishable from those derived by standard optical density measurements of the same cultures. Raman microspectroscopy can also be combined with methods for phylogenetic identification. We report the development of Raman-based techniques that enable researchers to directly link genetic identity to functional traits and rate measurements of single cells within mixed microbial assemblages, currently a major technical challenge in microbiological research.

Differentiation of Closely Related Oak-Associated Gram-Negative Bacteria by Label-Free Surface Enhanced Raman Spectroscopy (SERS)

Due to the harmful effects of chemical fertilizers and pesticides, the need for an eco-friendly solution to improve soil fertility has become a necessity, thus microbial biofertilizer research is on the rise. Plant endophytic bacteria inhabiting internal tissues represent a novel niche for research into new biofertilizer strains. However, the number of species and strains that need to be differentiated and identified to facilitate faster screening in future plant-bacteria interaction studies, is enormous. Surface enhanced Raman spectroscopy (SERS) may provide a platform for bacterial discrimination and identification, which, compared with the traditional methods, is relatively rapid, uncomplicated and ensures high specificity. In this study, we attempted to differentiate 18 bacterial isolates from two oaks via morphological, physiological, biochemical tests and SERS spectra analysis. Previous 16S rRNA gene fragment sequencing showed that three isolates belong to Paenibacillus, 3-to Pantoea and 12-to Pseudomonas genera. Additional tests were not able to further sort these bacteria into strain-specific groups. However, the obtained label-free SERS bacterial spectra along with the high-accuracy principal component (PCA) and discriminant function analyses (DFA) demonstrated the possibility to differentiate these bacteria into variant strains. Furthermore, we collected information about the biochemical characteristics of selected isolates. The results of this study suggest a promising application of SERS in combination with PCA/DFA as a rapid, non-expensive and sensitive method for the detection and identification of plant-associated bacteria.

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding multiplexing ability, SERS is an effective analytical technique that has excellent potential in bioanalysis and diagnosis, as demonstrated by its increasing applications in vivo. SERS allows the rapid detection of molecular species based on direct and indirect strategies. Because it benefits from the tunable surface properties of nanostructures, it finds a broad range of applications with clinical relevance, such as biological sensing, drug delivery and live cell imaging assays. Of particular interest are early-stage-cancer detection and the fast detection of pathogens. Here, we present a comprehensive survey of SERS-based assays, from basic considerations to bioanalytical applications. Our main focus is on SERS-based pathogen detection methods as point-of-care solutions for early bacterial infection detection and chronic disease diagnosis. Additionally, various promising in vivo applications of SERS are surveyed. Furthermore, we provide a brief outlook of recent endeavours and we discuss future prospects and limitations for SERS, as a reliable approach for rapid and sensitive bioanalysis and diagnosis.

Enhancing Raman signals from bacteria using dielectrophoretic force between conductive lensed fiber and black silicon

An osmium-coated lensed fiber (OLF) probe combined with a silver-coated black silicon (SBS) substrate was used to generate a dielectrophoretic (DEP) force that traps bacteria and enables Raman signal detection from bacteria. The lensed fiber coated with a 2-nm osmium layer was used as an electrode for the DEP force and also as a lens to excite Raman signals. The black silicon coated with a 150-nm silver layer was used both as the surface-enhanced Raman scattering (SERS) substrate and the counter electrode. The enhanced Raman signal was collected by the same OLF probe and further analyzed with a spectrometer. For Raman measurements, a drop of bacterial suspension was placed between the OLF probe and the SBS substrate. By controlling the frequency of an AC voltage on the OLF probe and SBS substrate, a DEP force at 1 MHz concentrated bacteria on the SBS surface and removed the unbound micro-objects in the solution at 1 kHz. A bacteria concentration of 6 × 10⁴ CFU/mL (colony forming units per mL) could be identified in less than 15 min, using a volume of only 1 μL, by recording the variation of the Raman peak at 740 cm^-1.

Raman 18 O-labeling of bacteria in visible and deep UV-ranges

Raman stable isotope labeling with ² H, ¹³ C or ¹⁵ N has been reported as an elegant approach to investigate cellular metabolic activity, which is of great importance to reveal the functions of microorganisms in native environments. A new strategy termed Raman ¹⁸ O-labeling was developed to probe the metabolic activity of bacteria. Raman ¹⁸ O-labeling refers to the combination of Raman microspectroscopy with ¹⁸ O-labeling using H₂¹⁸ O. At an excitation wavelength of 532 nm, the incorporation of ¹⁸ O into the amide I group of proteins and DNA/RNA bases was observed in Escherichia coli cells, while for an excitation wavelength electronically resonant with DNA or aromatic amino acid absorption at 244 nm ¹⁸ O assimilation was detected using chemometric tools rather than visual inspection. Raman ¹⁸ O-labeling at 532 nm combined with 2D correlation analysis confirmed the assimilation of ¹⁸ O in proteins and nucleic acids and revealed the growth strategy of E. coli cells; they underwent protein synthesis followed by nucleic acid synthesis. Independent cultural replicates at different incubation times corroborated the reproducibility of these results. The variations in spectral features of ¹⁸ O-labeled cells revealed changes in physiological information of cells. Hence, Raman ¹⁸ O-labeling could provide a powerful tool to identify metabolically active bacterial cells.

SERS-based sensor for the detection of sexually transmitted pathogens in the male swab specimens: A new approach for clinical diagnosis

The surface-enhanced Raman scattering (SERS) has been widely tested for its usefulness in microbiological studies, providing many information-rich spectra which are a kind of 'whole-organism fingerprint' and enabling identification of bacterial species. Here we show, previously not considered, the comprehensive SERS-chemometric analysis of five bacterial pathogens, namely Neisseria gonorrhoeae, Mycoplasma hominis, Mycoplasma genitalium, Ureaplasma urealyticum, and Haemophilus ducreyi, all being responsible for sexually transmitted diseases (STDs). In the designed biosensor, the direct, intrinsic format of the spectroscopic analysis was adopted for the SERS-based screening of gonorrhea and chlamydiosis due to vibrational analysis of men's urethra swabs. Our experiments demonstrated that the applied method enables identification the individual species of the Neisseria genus with high accuracy. In order to differentiate the sexually transmitted pathogens and to classify the clinical samples of male urethra swabs, three multivariate methods were used. In the external validation the created models correctly classified the men's urethra swabs with prediction accuracy reaching 89% for SIMCA and 100% for PLS-DA. As a result, the developed protocol enables: (i) simple and non-invasive analysis of clinical samples (the collection of urethra swabs specimens could be carried out at different points of care, such as doctor's office); (ii) fast analysis (<15 min); (iii) culture-free identification; (iv) sensitive and reliable SERS-based diagnosis of STD. The simplicity of the developed detection procedure, supported by high sensitivity, reproducibility, and specificity, open a new path in the improvement of the point-of-care applications.

In Search of Spectroscopic Signatures of Periodontitis: A SERS-Based Magnetomicrofluidic Sensor for Detection of Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans

Recently, Porphyromonas gingivalis, the keystone pathogen implicated in the development of gum disease (periodontitis), was detected in the brains of Alzheimer’s disease patients, opening up a fascinating possibility that it is also involved in the pathobiology of this neurodegenerative illness. To verify this hypothesis, an unbiased, specific, and sensitive method to detect this pathogen in biological specimens is needed. To this end, our interdisciplinary studies demonstrate that P. gingivalis can be easily identified by surface-enhanced Raman scattering (SERS). Moreover, based on SERS measurements, P. gingivalis can be distinguished from another common periodontal pathogen, Aggregatibacter actinomycetemcomitans, and also from ubiquitous oral Streptococcus spp. The results were confirmed by principal component analysis (PCA). Furthermore, we have shown that different P. gingivalis and A. actinomycetemcomitans strains can easily adsorb to silver-coated magnetic nanoparticles (Fe₂O₃@AgNPs). Thus, it is possible to magnetically separate investigated bacteria from other components of a specimen using the microfluidic chip. To obtain additional enhancement of the Raman signal, the NPs adsorbed to bacterial cells were magnetically attracted to the Si/Ag SERS platform. Afterward, the SERS spectra could be recorded. Such a time-saving procedure can be very helpful in rapid medical diagnostics and thus in starting the appropriate pharmacological therapy to prevent the development of periodontitis and associated comorbidities, e.g., Alzheimerʼs disease.

Surface-Enhanced Raman Spectroscopy for Environmental Monitoring of Aerosols

Surface-enhanced Raman spectroscopy (SERS) is conducted from single aerosol particles held in a linear electrodynamic quadrupole trap. SERS measurements from two representative types of ambient aerosol particles, semi-liquid and solid aerosols, are demonstrated; aerosol composed of adenine where the metallic nanoparticles (MNPs) are volume distributed throughout the particle and aerosol composed of polystyrene latex (PSL) beads where the MNPs are surface coated. An enhancement factor > 10⁶ is demonstrated from 5 μm aerosols containing trace amounts of adenine (0.1% by mass), with a detection limit of 10^-8 M corresponding to 5 × 10⁵ molecules (equivalent to 100 ag in mass or a 50 nm diameter sphere), and a ratio of 100 adenine molecules per Ag NP. SERS signal intensities are linear with particle adenine concentration up to a saturation point. Both the linearity and enhancement factor were confirmed by SERS measurements of adenine as bulk suspensions. The SERS spectra of adenine as bulk suspensions were explored as a function of excitation wavelength ranging from 400 to 800 nm. The two main Raman peaks of adenine at 738 and 1336 cm^-1 exhibit SERS maxima for excitation in the 450-500 nm range for commercially available 40 nm spherical Ag nanoparticles (NPs) used in this study, which shifts to longer wavelengths with the addition of NaCl. Shifts in SERS and spontaneous Raman shifts were observed between aqueous and dry adenine, in agreement with the literature, demonstrating the utility of SERS to possibly study water uptake of aerosols. SERS is measured from MNP surface-coated PSL beads with an enhancement factor of 30 for 5 μm PSLs. Theoretical extrapolation demonstrates that the enhancement factor will increase for decreasing particle size with an estimated enhancement factor of 140 for 1 μm PSLs.

Reusable Surface-Enhanced Raman Spectroscopy Membranes and Textiles via Template-Assisted Self-Assembly and Micro/Nanoimprinting

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful tool for ultrasensitive fingerprint recognition of molecules with considerable potential in wearable biochemical sensing. However, previous efforts to fabricate wearable SERS devices by directly treating fabrics with plasmonic nanoparticles have generated a nonuniform assembly of nanoparticles, weakly adsorbed on fabrics via van der Waals forces. Here, we report the creation of washing reusable SERS membranes and textiles via template-assisted self-assembly and micro/nanoimprinting approaches. Uniquely, we employ the capillary force driven self-assembly process to generate micropatch arrays of Au nanoparticle (NP) aggregates within hydrophobic microstructured templates, which are then robustly bonded onto semipermeable transparent membranes and stretchable textiles using the UV-resist based micro/nanoimprinting technique. A mild reactive ion etching (RIE) treatment of SERS membranes and textiles can physically expose the SERS hotspots of Au NP-aggregates embedded within the polymer UV resist for further improvement of their SERS performance. Also, we demonstrate that the semipermeable transparent SERS membranes can keep the moisture content of meat from evaporating to enable stable in situ SERS monitoring of biochemical environments at the fresh meat surface. By contrast, stretchable SERS textiles can allow the spreading, soaking, and evaporation of solution analyte samples on the fabric matrix for continuous enrichment of analyte molecules at the hotspots in biochemical SERS detection. Due to the mechanical robustness of the UV-resist immobilized Au NP aggregates, simple detergent-water washing with ultrasound sonication or mechanical stirring can noninvasively clean contaminated hot spots to reuse SERS textiles. Therefore, we envision that washing reusable SERS membranes and textiles by template-assisted self-assembly and micro/nanoimprinting fabrication are promising for wearable biochemical sensing applications, such as wound monitoring and body fluid monitoring.

Shell-isolated nanoparticle-enhanced Raman spectroscopy for characterization of living yeast cells

Studying the biochemistry of yeast cells has enabled scientists to understand many essential cellular processes in human cells. Further development of biotechnological and medical progress requires revealing surface chemistry in living cells by using a non-destructive and molecular structure sensitive technique. In this study shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) was applied for probing the molecular structure of Metschnikowia pulcherrima yeast cells. Important function of studied cells is the ability to eliminate iron from growth media by precipitating the insoluble pigment pulcherrimin. Comparative SERS and SHINERS analysis of the yeast cells in combination with bare Au and shell-isolated Au@SiO₂ nanoparticles were performed. It was observed that additional bands, such as adenine ring-related vibrational modes appear due to interaction with bare Au nanoparticles; the registered spectra do not coincide with the spectra where Au@SiO₂ nanoparticles were used. SHINERS spectra of M. pulcherrima were significantly enhanced comparing to the Raman spectra. Based on first-principles calculations and 830-nm excited Raman analysis of pulcherrimin, the SHINERS signatures of iron pigment in yeast cells were revealed. Being protected from direct interaction of metal with adsorbate, Au@SiO₂ nanoparticles yield reproducible and reliable vibrational signatures of yeast cell wall constituents.

Properties of a modified quaternary ammonium silane formulation as a potential root canal irrigant in endodontics

OBJECTIVES

Evaluate a new modified quaternary ammonium silane irrigant solution for its antimicrobial, cytotoxic and mechanical properties of dentine substrate.

METHODS

Root canal preparation was performed using stainless steel K-files™ and F4 size protaper with irrigation protocols of 6% NaOCl + 2% CHX; 3.5% QIS; 2% QIS and sterile saline. Biofilms were prepared using E. faecalis adjusted and allowed to grow for 3 days, treated with irrigants, and allowed to grow for 7 days. AFM was performed and surface free energy calculated. MC3T3 cells were infected with endo irrigant treated E. faecalis biofilms. Raman spectroscopy of biofilms were performed after bacterial re-growth on root dentine and exposed to different irrigation protocols and collagen fibers analysed collagen fibers using TEM. Antimicrobial potency against E. faecalis biofilms and cytoxicity against 3T3 NIH cells were also. Resin penetration and MitoTracker green were also evaluated for sealer penetration and mitochondrial viability. Data were analysed using One-way ANOVA, principal component analysis and post-hoc Fisher's least-significant difference.

RESULTS

Elastic moduli were maintained amongst control (5.5 ± 0.9) and 3.5% QIS (4.4 ± 1.1) specimens with surface free energy higher in QIS specimens. MC3T3 cells showed reduced viability in 6%NaOCl+2%CHX specimens compared to QIS specimens. DNA/purine were expressed in increased intensities in control and 6% NaOCl + 2% CHX specimens with bands around 480-490 cm^-1 reduced in QIS specimens. 3.5% QIS specimens showed intact collagen fibrillar network and predominantly dead bacterial cells in confocal microscopy. 3.5% QIS irrigant formed a thin crust-type surface layer with cytoplasmic extensions of 3T3NIH spread over root dentine. Experiments confirmed MitoTracker accumulation in 3.5% treated cells.

SIGNIFICANCE

Novel QIS root canal irrigant achieved optimum antimicrobial protection inside the root canals facilitating a toxic effect against the Enterococcus faecalis biofilm. Root dentine substrates exhibited optimum mechanical properties and there was viability of fibroblastic mitochondria.

Improvement of Surface-Enhanced Raman Scattering Method for Single Bacterial Cell Analysis

Surface-enhanced Raman scattering (SERS) is a useful tool for label-free analysis of bacteria at the single cell level. However, low reproducibility limits the use of SERS. In this study, for the sake of sensitive and reproducible Raman spectra, we optimized the methods for preparing silver nanoparticles (AgNPs) and depositing AgNPs onto a cell surface. We found that fast dropwise addition of AgNO₃ into the reductant produced smaller and more stable AgNPs, with an average diameter of 45 ± 4 nm. Compared with that observed after simply mixing the bacterial cells with AgNPs, the SERS signal was significantly improved after centrifugation. To optimize the SERS enhancement method, the centrifugal force, method for preparing AgNPs, concentration of AgNPs, ionic strength of the solution used to suspend the cells, and density of the cells were chosen as impact factors and optimized through orthogonal experiments. Finally, the improved method could generate sensitive and reproducible SERS spectra from single Escherichia coli cells, and the SERS signals primarily arose from the cell envelope. We further verified that this optimal method was feasible for the detection of low to 25% incorporation of ¹³C isotopes by the cells and the discrimination of different bacterial species. Our work provides an improved method for generating sensitive and reproducible SERS spectra.

Nanoplasmonic sensor for foodborne pathogens detection. Towards development of ISO-SERS methodology for taxonomic affiliation of Campylobacter spp

According to EU summary report on zoonoses, zoonotic agents and food-borne outbreaks in 2017, Campylobacter was the most commonly reported gastrointestinal bacterial pathogen in humans in the EU. Unfortunately, the standard methods for the detection of thermotolerant Campylobacter spp. in foods are time-consuming. Additionally, the qualified staff is obligatory. For this reason, new methods of pathogens detection are needed. The present work demonstrates that surface-enhanced Raman scattering (SERS) is a reliable and fast method for detection of Campylobacter spp. in food samples. The proposed method combines the SERS measurements performed on an Ag/Si substrate with two initial steps of the ISO standard procedure. Finally, the principal component analysis (PCA) allows for statistical classification of the studied bacteria. By applying the proposed ISO-SERS-PCA method in the case of Campylobacter bacteria the total detection time may be reduced from 7 to 8 days required by ISO method to 3 to 4 days in the case of SERS-based approach.

Present and Future of Surface-Enhanced Raman Scattering

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.

Rapid differentiation of Campylobacter jejuni cell wall mutants using Raman spectroscopy, SERS and mass spectrometry combined with chemometrics

SERS was developed for intercellular and intracellular analyses. Using a series of cell wall mutants in C. jejuni we show cell wall versus cytoplasm differences.

Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools

Candida species are becoming one of the pathogens developing antifungal resistance due to inappropriate treatment and overuse of antimycotic drugs in building construction and agriculture. Further, fungal infections are often difficult to detect, also due to slow in vitro growth of the organisms from clinical specimens. Thus, fast detection and discrimination of yeast cells in direct patient materials is essential for an adequate treatment and success rate. In this work, we investigated Candida species isolated from patients, by using surface-enhanced Raman scattering (SERS) combined with computational spectroscopy tools, aiming to detect and discriminate between the three considered species, Candida albicans, Candida glabrata, and Candida parapsilosis. Density functional theory (DFT) was used to calculate Raman spectra of yeasts' main cell wall components for elucidating the origin of the observed bands. Accurate assignments of normal modes helped for a better understanding of the interaction between silver nanoparticles with yeasts' cell wall. Further, SERS spectra were used as samples in a database on which we performed multivariate analyses. By Principal component analysis (PCA), we obtained a maximum variation of 79% between the three samples. Linear discriminant analysis (LDA) was successfully used to discriminate between the three species.

Development of uncoated near-spherical gold nanoparticles for the label-free quantification of Lactobacillus rhamnosus GG by surface-enhanced Raman spectroscopy

The Surface-enhanced Raman spectroscopy (SERS) method based on gold nanoparticles as SERS substrate was investigated for the label-free detection and quantification of probiotic bacteria that are widely used in various pharmaceutical formulations. Indeed, the development of a simple and fast SERS method dedicated to the quantification of bacteria should be very useful for the characterization of such formulations in a more convenient way than the usually performed tedious and time-consuming conventional counting method. For this purpose, uncoated near-spherical gold nanoparticles were developed at room temperature by acidic treatment of star-like gold nanoparticle precursors. In this study, we first investigated the influence of acidic treatment conditions on both the nanoparticle physicochemical properties and SERS efficiency using Rhodamine 6G (R6G) as "model" analyte. Results highlighted that an effective R6G Raman signal enhancement was obtained by promoting chemical effect through R6G-anion interactions and by obtaining a suitable aggregation state of the nanoparticles. Depending on the nanoparticle synthesis conditions, R6G SERS signals were up to 10²-10³-fold greater than those obtained with star-like gold nanoparticles. The synthesized spherical gold nanoparticles were then successfully applied for the detection and quantification of Lactobacillus rhamnosus GG (LGG). In that case, the signal enhancement was especially due to the combination of anion-induced chemical enhancement and nanoparticle aggregation on LGG cell wall consecutive to non-specific interactions. Both the simplicity and speed of the procedure, achieved under 30 min, including nanoparticle synthesis, sample preparation, and acquisition of SERS spectra, appeared as very relevant for the characterization of pharmaceutical formulations incorporating probiotics. Graphical abstract.

Enhancing Disease Diagnosis: Biomedical Applications of Surface-Enhanced Raman Scattering

Surface-enhanced Raman scattering (SERS) has recently gained increasing attention for the detection of trace quantities of biomolecules due to its excellent molecular specificity, ultrasensitivity, and quantitative multiplex ability. Specific single or multiple biomarkers in complex biological environments generate strong and distinct SERS spectral signals when they are in the vicinity of optically active nanoparticles (NPs). When multivariate chemometrics are applied to decipher underlying biomarker patterns, SERS provides qualitative and quantitative information on the inherent biochemical composition and properties that may be indicative of healthy or diseased states. Moreover, SERS allows for differentiation among many closely-related causative agents of diseases exhibiting similar symptoms to guide early prescription of appropriate, targeted and individualised therapeutics. This review provides an overview of recent progress made by the application of SERS in the diagnosis of cancers, microbial and respiratory infections. It is envisaged that recent technology development will help realise full benefits of SERS to gain deeper insights into the pathological pathways for various diseases at the molecular level.

Surface-enhanced Raman spectroscopy of microorganisms: limitations and applicability on the single-cell level

Detection and characterization of microorganisms is essential for both clinical diagnostics and environmental studies. An emerging technique to analyse microbes at single-cell resolution is surface-enhanced Raman spectroscopy (surface-enhanced Raman scattering: SERS). Optimised SERS procedures enable fast analytical read-outs with specific molecular information, providing insight into the chemical composition of microbiological samples. Knowledge about the origin of microbial SERS signals and parameter(s) affecting their occurrence, intensity and/or reproducibility is crucial for reliable SERS-based analyses. In this work, we explore the feasibility and limitations of the SERS approach for characterizing microbial cells and investigate the applicability of SERS for single-cell sorting as well as for three-dimensional visualization of microbial communities. Analyses of six different microbial species (an archaeon, two Gram-positive bacteria, three Gram-negative bacteria) showed that for several of these organisms distinct features in their SERS spectra were lacking. As additional confounding factor, the physiological conditions of the cells (as influenced by e.g., storage conditions or deuterium-labelling) were systematically addressed, for which we conclude that the respective SERS signal at the single-cell level is strongly influenced by the metabolic activity of the analysed cells. While this finding complicates the interpretation of SERS data, it may on the other hand enable probing of the metabolic state of individual cells within microbial populations of interest.

Photovoltaic cells as a highly efficient system for biomedical and electrochemical surface-enhanced Raman spectroscopy analysis

Surface-enhanced Raman scattering (SERS) has been intensively used recently as a highly sensitive, non-destructive, chemical specific, and label-free technique for a variety of studies. Here, we present a novel SERS substrate for: (i) the standard ultra-trace analysis, (ii) detection of whole microorganisms, and (iii) spectroelectrochemical measurements. The integration of electrochemistry and SERS spectroscopy is a powerful approach for in situ investigation of the structural changes of adsorbed molecules, their redox properties, and for studying the intermediates of the reactions. We have developed a conductive SERS platform based on photovoltaic materials (PV) covered with a thin layer of silver, especially useful in electrochemical SERS analysis. These substrates named Ag/PV presented in this study combine crucial spectroscopic features such as high sensitivity, reproducibility, specificity, and chemical/physical stability. The designed substrates permit the label-free identification and differentiation of cancer cells (renal carcinoma) and pathogens (Escherichia coli and Bacillus subtilis). In addition, the developed SERS platform was adopted as the working electrode in an electrochemical SERS approach for p-aminothiophenol (p-ATP) studies. The capability to monitor in real-time the electrochemical changes spectro-electro-chemically has great potential for broadening the application of SERS.

Label-Free SERS Discrimination and In Situ Analysis of Life Cycle in Escherichia coli and Staphylococcus epidermidis

Surface enhanced Raman spectroscopy (SERS) has been proven suitable for identifying and characterizing different bacterial species, and to fully understand the chemically driven metabolic variations that occur during their evolution. In this study, SERS was exploited to identify the cellular composition of Gram-positive and Gram-negative bacteria by using mesoporous silicon-based substrates decorated with silver nanoparticles. The main differences between the investigated bacterial strains reside in the structure of the cell walls and plasmatic membranes, as well as their biofilm matrix, as clearly noticed in the corresponding SERS spectrum. A complete characterization of the spectra was provided in order to understand the contribution of each vibrational signal collected from the bacterial culture at different times, allowing the analysis of the bacterial populations after 12, 24, and 48 h. The results show clear features in terms of vibrational bands in line with the bacterial growth curve, including an increasing intensity of the signals during the first 24 h and their subsequent decrease in the late stationary phase after 48 h of culture. The evolution of the bacterial culture was also confirmed by fluorescence microscope images.

Steel Wire Mesh as a Thermally Resistant SERS Substrate

In this paper, we present novel type of Surface-enhanced Raman spectroscopy (SERS) platform, based on stainless steel wire mesh (SSWM) covered with thin silver layer. The stainless steel wire mesh, typically used in chemical engineering industry, is a cheap and versatile substrate for SERS platforms. SSWM consists of multiple steel wires with diameter of tens of micrometers, which gives periodical structure and high stiffness. Moreover, stainless steel provides great resistance towards organic and inorganic solvents and provides excellent heat dissipation. It is worth mentioning that continuous irradiation of the laser beam over the SERS substrate can be a source of significant increase in the local temperature of metallic nanostructures, which can lead to thermal degradation or fragmentation of the adsorbed analyte. Decomposition or fragmentation of the analysed sample usually causea a significant decrease in the intensity of recorded SERS bands, which either leads to false SERS responses or enables the analysis of spectral data. To our knowledge, we have developed for the first time the thermally resistant SERS platform. This type of SERS substrate, termed Ag/SSWM, exhibit high sensitivity (Enhancement Factor (EF) = 10⁶) and reproducibility (Relative Standard Deviation (RSD) of 6.4%) towards detection of p-mercaptobenzoic acid (p-MBA). Besides, Ag/SSWM allows the specific detection and differentiation between Gram-positive and Gram-negative bacterial species: Escherichia coli and Bacillus subtilis in label-free and reproducible manner. The unique properties of designed substrate overcome the limitations associated with photo- and thermal degradation of sensitive bacterial samples. Thus, a distinctive SERS analysis of all kinds of chemical and biological samples at high sensitivity and selectivity can be performed on the developed SERS-active substrate.

Comparison of time-gated surface-enhanced raman spectroscopy (TG-SERS) and classical SERS based monitoring of Escherichia coli cultivation samples

The application of Raman spectroscopy as a monitoring technique for bioprocesses is severely limited by a large background signal originating from fluorescing compounds in the culture media. Here, we compare time-gated Raman (TG-Raman)-, continuous wave NIR-process Raman (NIR-Raman), and continuous wave micro-Raman (micro-Raman) approaches in combination with surface enhanced Raman spectroscopy (SERS) for their potential to overcome this limit. For that purpose, we monitored metabolite concentrations of Escherichia coli bioreactor cultivations in cell-free supernatant samples. We investigated concentration transients of glucose, acetate, AMP, and cAMP at alternating substrate availability, from deficiency to excess. Raman and SERS signals were compared to off-line metabolite analysis of carbohydrates, carboxylic acids, and nucleotides. Results demonstrate that SERS, in almost all cases, led to a higher number of identifiable signals and better resolved spectra. Spectra derived from the TG-Raman were comparable to those of micro-Raman resulting in well-discernable Raman peaks, which allowed for the identification of a higher number of compounds. In contrast, NIR-Raman provided a superior performance for the quantitative evaluation of analytes, both with and without SERS nanoparticles when using multivariate data analysis. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 34:1533-1542, 2018.

Surface-Enhanced Raman Scattering (SERS) in Microbiology: Illumination and Enhancement of the Microbial World

The microbial world forms a huge family of organisms that exhibit the greatest phylogenetic diversity on Earth and thus colonize virtually our entire planet. Due to this diversity and subsequent complex interactions, the vast majority of microorganisms are involved in innumerable natural bioprocesses and contribute an absolutely vital role toward the maintenance of life on Earth, whilst a small minority cause various infectious diseases. The ever-increasing demand for environmental monitoring, sustainable ecosystems, food security, and improved healthcare systems drives the continuous search for inexpensive but reproducible, automated and portable techniques for detection of microbial isolates and understanding their interactions for clinical, environmental, and industrial applications and benefits. Surface-enhanced Raman scattering (SERS) is attracting significant attention for the accurate identification, discrimination and characterization and functional assessment of microbial cells at the single cell level. In this review, we briefly discuss the technological advances in Raman and Fourier transform infrared (FT-IR) instrumentation and their application for the analysis of clinically and industrially relevant microorganisms, biofilms, and biological warfare agents. In addition, we summarize the current trends and future prospects of integrating Raman/SERS-isotopic labeling and cell sorting technologies in parallel, to link genotype-to-phenotype in order to define community function of unculturable microbial cells in mixed microbial communities which possess admirable traits such as detoxification of pollutants and recycling of essential metals.

Detection of Foodborne Pathogens by Surface Enhanced Raman Spectroscopy

Food safety has become an important public health issue in both developed and developing countries. However, as the foodborne illnesses caused by the pollution of foodborne pathogens occurred frequently, which seriously endangered the safety and health of human beings. More importantly, the traditional techniques, such as PCR and enzyme-linked immunosorbent assay, are accurate and effective, but their pretreatments are complex and time-consuming. Therefore, how to detect foodborne pathogens quickly and sensitively has become the key to control food safety. Because of its sensitivity, rapidity, and non-destructive damage to the sample, the surface enhanced Raman scattering (SERS) is considered to be a powerful testing technology that is widely used to different fields. This review aims to give a systematic and comprehensive understanding of SERS for rapid detection of pathogen bacteria. First, the related concepts of SERS are stated, such as its work principal, active substrate, and biochemical origins of the detection of bacteria by SERS. Then the latest progress and applications in food safety, from detection and characterization of targets in label-free method to label method, is summarized. The advantages and limitations of different SERS substrates and methods are discussed. Finally, there are still several hurdles for the further development of SERS techniques into real-world applications. This review comes up with the perspectives on the future trends of the SERS technique in the field of foodborne pathogens detection and some problems to be solved urgently. Therefore, the purpose is mainly to understand the detection of foodborne pathogens and to make further emphasis on the importance of SERS techniques.

Application of stable-isotope labelling techniques for the detection of active diazotrophs

Investigating active participants in the fixation of dinitrogen gas is vital as N is often a limiting factor for primary production. Biological nitrogen fixation is performed by a diverse guild of bacteria and archaea (diazotrophs), which can be free-living or symbionts. Free-living diazotrophs are widely distributed in the environment, yet our knowledge about their identity and ecophysiology is still limited. A major challenge in investigating this guild is inferring activity from genetic data as this process is highly regulated. To address this challenge, we evaluated and improved several 15 N-based methods for detecting N2 fixation activity (with a focus on soil samples) and studying active diazotrophs. We compared the acetylene reduction assay and the 15 N2 tracer method and demonstrated that the latter is more sensitive in samples with low activity. Additionally, tracing 15 N into microbial RNA provides much higher sensitivity compared to bulk soil analysis. Active soil diazotrophs were identified with a 15 N-RNA-SIP approach optimized for environmental samples and benchmarked to 15 N-DNA-SIP. Lastly, we investigated the feasibility of using SIP-Raman microspectroscopy for detecting 15 N-labelled cells. Taken together, these tools allow identifying and investigating active free-living diazotrophs in a highly sensitive manner in diverse environments, from bulk to the single-cell level.