Surface-enhanced Raman scattering as a discrimination method of Streptococcus spp. and alternative approach for identifying capsular types of S. pneumoniae isolates

Unmasking Bacterial Identities: Exploiting Silver Nanoparticle 'Masks' for Enhanced Raman Scattering in the Rapid Discrimination of Diverse Bacterial Species and Antibiotic-Resistant Strains

Unraveling bacterial identity through Raman scattering techniques has been persistently challenging due to homogeneously amplified Raman signals across a wide variety of bacterial molecules, predominantly protein- or nucleic acid-mediated. In this study, we present an approach involving the use of silver nanoparticles to completely and uniformly "mask" adsorption on the surface of bacterial molecules through sodium borohydride and sodium chloride. This approach enables the acquisition of enhanced surface-enhanced Raman scattering (SERS) signals from all components on the bacterial surface, facilitating rapid, specific, and label-free bacterial identification. For the first time, we have characterized the identity of a bacterium, including its DNA, metabolites, and cell walls, enabling the accurate differentiation of various bacterial strains, even within the same species. In addition, we embarked on an exploration of the origin and variability patterns of the main characteristic peaks of Gram-positive and Gram-negative bacteria. Significantly, the SERS peak ratio was found to determine the inflection point of accelerated bacterial death upon treatment with antimicrobials. We further applied this platform to identify 15 unique clinical antibiotic-resistant bacterial strains, including five Escherichia coli strains in human urine, a first for Raman technology. This work has profound implications for prompt and accurate identification of bacteria, particularly antibiotic-resistant strains, thereby significantly enhancing clinical diagnostics and antimicrobial treatment strategies.

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.

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.

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.