Machine Learning-Driven SERS Nanoendoscopy and Optophysiology.

A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological context in situ, where the molecular-level information is indicative of health status, therapeutic efficacy, and fundamental biochemical function of the host. Following the completion of the Human Genome Project, current research aims to link genes to functions of an organism and investigate how the environment modulates functional properties of organisms. New analytical methods have been developed to detect chemical changes with high spatial and temporal resolution, including minimally invasive surface-enhanced Raman scattering (SERS) nanofibers using the principles of endoscopy (SERS nanoendoscopy) or optical physiology (SERS optophysiology). Given the large spectral data sets generated from these experiments, SERS nanoendoscopy and optophysiology benefit from advances in data science and machine learning to extract chemical information from complex vibrational spectra measured by SERS. This review highlights new opportunities for intracellular, extracellular, and in vivo chemical measurements arising from the combination of SERS nanosensing and machine learning.

Label-Free SERS for Rapid Differentiation of SARS-CoV-2-Induced Serum Metabolic Profiles in Non-Hospitalized Adults.

COVID-19 represents a multi-system infectious disease with broad-spectrum manifestations, including changes in host metabolic processes connected to the disease pathogenesis. Understanding biochemical dysregulation patterns as a consequence of COVID-19 illness promises to be crucial for tracking disease course and clinical outcomes. Surface-enhanced Raman scattering (SERS) has attracted considerable interest in biomedical diagnostics for the sensitive detection of intrinsic profiles of unique fingerprints of serum biomolecules indicative of SARS-CoV-2 infection in a label-free format. Here, we applied label-free SERS and chemometrics for rapid interrogation of temporal metabolic dynamics in longitudinal sera of mildly infected non-hospitalized patients (n = 22), at 4 and 16 weeks post PCR-positive diagnosis, and compared them with negative controls (n = 8). SERS spectral markers revealed distinct metabolic profiles in patient sera that significantly deviated from the healthy metabolic state at the two sampling time intervals. Multivariate and univariate analyses of the spectral data identified abundance dynamics in amino acids, lipids, and protein vibrations as the key spectral features underlying the metabolic differences detected in convalescent samples and perhaps associated with patient recovery progression. A validation study performed using spontaneous Raman spectroscopy yielded spectral data results that corroborated SERS spectral findings and confirmed the detected disease-specific molecular phenotypes in clinical samples. Label-free SERS promises to be a valuable analytical technique for rapid screening of the metabolic phenotype induced by SARS-CoV-2 infection to allow appropriate healthcare intervention.

Metabolism in action: stable isotope probing using vibrational spectroscopy and SIMS reveals kinetic and metabolic flux of key substrates.

Microbial communities play essential functions which drive various ecosystems supporting animal and aquatic life. However, linking bacteria with specific metabolic functions is difficult, since microbial communities consist of numerous and phylogenetically diverse microbes. Stable isotope probing (SIP) combined with single-cell tools has emerged as a novel culture-independent strategy for unravelling microbial metabolic roles and intertwined interactions in complex communities. In this study, we applied Raman and Fourier-transform infrared (FT-IR) spectroscopies, secondary ion mass spectrometry (SIMS) with SIP to probe the rate of 13C incorporation in Escherichia coli at 37 and 25 °C. Our results indicate quantitative enrichment and flow of 13C into E. coli at various time points. Multivariate and univariate analyses of Raman and FT-IR data demonstrated distinctive 13C concentration-dependent trends that were due to vibrational bands shifting to lower frequencies and these shifts were a result of incubation time and metabolic rate. SIMS results were in complete agreement with the spectroscopy findings, and confirmed the detected levels of 13C incorporation into microbial biomass at the investigated conditions. Having established that FT-IR and Raman spectroscopy with SIP can measure metabolism kinetics in this simple system, we have applied the kinetics concept to study the metabolism of phenol by Pseudomonas putida and metabolic interactions within a two-species consortia with E. coli that could not degrade phenol. Raman spectroscopy combined with SIP identified quantitative shifts in P. putida due to temporal assimilation of phenol. Although E. coli was unable to grow on phenol, in co-culture with P. putida, general metabolic probing using deuterated water for SIP revealed that E. coli displayed increasing metabolic activity, presumably due to cross feeding from metabolites generated by P. putida. This study clearly demonstrates that Raman and FT-IR combined with SIP provide rapid and sensitive detection of carbon incorporation rates and microbial interactions. These novel findings may guide the identification of primary substrate consumers in complex microbial communities in situ, which is a key step towards the characterisation of novel genes, enzymes and metabolic flux analysis in microbial consortia.

Discrimination of bacteria using whole organism fingerprinting: the utility of modern physicochemical techniques for bacterial typing.

Rapid and accurate classification and discrimination of bacteria is an important task and has been highlighted recently for rapid diagnostics using real-time results. Coupled with a recent report by Jim O'Neill [] that if left unaddressed antimicrobial resistance (AMR) in bacteria could kill 10 million people per year by 2050, which would surpass current cancer mortality, this further highlights the need for unequivocal identification of microorganisms. Whilst traditional microbiological testing has offered insights into the characterisation and identification of a wide range of bacteria, these approaches have proven to be laborious and time-consuming and are not really fit for purpose, considering the modern day speed and volume of international travel and the opportunities it creates for the spread of pathogens globally. To overcome these disadvantages, modern analytical methods, such as mass spectrometry (MS) and vibrational spectroscopy, that analyse the whole organism, have emerged as essential alternative approaches. Currently within clinical microbiology laboratories, matrix assisted laser desorption ionisation (MALDI)-MS is the method of choice for bacterial identification. This is largely down to its robust analysis as it largely measures the ribosomes which are always present irrespective of how the bacteria are cultured. However, MALDI-MS requires large amounts of biomass and infrared spectroscopy and Raman spectroscopy are attractive alternatives as these physicochemical bioanalytical techniques have the advantages of being rapid, reliable and cost-effective for analysing various types of bacterial samples, even at the single cell level. In this review, we discuss the fundamental applications, advantages and disadvantages of modern analytical techniques used for bacterial characterisation, classification and identification.

Ferulic Acid Decarboxylase Controls Oxidative Maturation of the Prenylated Flavin Mononucleotide Cofactor.

Prenylated flavin mononucleotide (prFMN) is a recently discovered modified flavin cofactor containing an additional nonaromatic ring, connected to the N5 and C6 atoms. This cofactor underpins reversible decarboxylation catalyzed by members of the widespread UbiD enzyme family and is produced by the flavin prenyltransferase UbiX. Oxidative maturation of the UbiX product prFMNH2 to the corresponding oxidized prFMNiminium is required for ferulic acid decarboxylase (Fdc1; a UbiD-type enzyme) activity. However, it is unclear what role the Fdc1 enzyme plays in this process. Here, we demonstrate that, in the absence of Fdc1, prFMNH2 oxidation by O2 proceeds via a transient semiquinone prFMNradical species and culminates in a remarkably stable prFMN-hydroperoxide species. Neither forms of prFMN are able to support Fdc1 activity. Instead, enzyme activation using O2-mediated oxidation requires prFMNH2 binding prior to oxygen exposure, confirming that UbiD enzymes play a role in O2-mediated oxidative maturation. In marked contrast, alternative oxidants such as potassium ferricyanide support prFMNiminium formation both in solution and in Fdc1.

Surface Enhanced Raman Spectroscopy for Quantitative Analysis: Results of a Large-Scale European Multi-Instrument Interlaboratory Study.

Surface-enhanced Raman scattering (SERS) is a powerful and sensitive technique for the detection of fingerprint signals of molecules and for the investigation of a series of surface chemical reactions. Many studies introduced quantitative applications of SERS in various fields, and several SERS methods have been implemented for each specific application, ranging in performance characteristics, analytes used, instruments, and analytical matrices. In general, very few methods have been validated according to international guidelines. As a consequence, the application of SERS in highly regulated environments is still considered risky, and the perception of a poorly reproducible and insufficiently robust analytical technique has persistently retarded its routine implementation. Collaborative trials are a type of interlaboratory study (ILS) frequently performed to ascertain the quality of a single analytical method. The idea of an ILS of quantification with SERS arose within the framework of Working Group 1 (WG1) of the EU COST Action BM1401 Raman4Clinics in an effort to overcome the problematic perception of quantitative SERS methods. Here, we report the first interlaboratory SERS study ever conducted, involving 15 laboratories and 44 researchers. In this study, we tried to define a methodology to assess the reproducibility and trueness of a quantitative SERS method and to compare different methods. In our opinion, this is a first important step toward a "standardization" process of SERS protocols, not proposed by a single laboratory but by a larger community.

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

The Gram-negative bacterial pathogen Campylobacter jejuni is a major cause of foodborne gastroenteritis worldwide. Rapid detection and identification of C. jejuni informs timely prescription of appropriate therapeutics and epidemiological investigations. Here, for the first time, we report the applicability of Raman spectroscopy, surface-enhanced Raman scattering (SERS) and matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-TOF-MS) combined with chemometrics, for rapid differentiation and characterisation of mutants of a single isogenic C. jejuni strain that disrupt the production of prominent surface features (capsule, flagella and glycoproteins) of the bacterium. Multivariate analysis of the spectral data obtained from these different physicochemical tools revealed distinctive biochemical differences which consistently discriminated between these mutants. In order to generate biochemical and phenotypic information from different locations in the cell-cell wall versus cytoplasm - we developed two different in situ methods for silver nanoparticle (AgNP) production, and compared this with simple mixing of bacteria with pre-synthesised AgNPs. This SERS trilogy (simple mixing with premade AgNPs and two in situ AgNP production methods) presents an integrated platform with potential for rapid, accurate and confirmatory detection of pathogenic bacteria based on cell envelope or intracellular molecular dynamics. Our spectral findings demonstrate that Raman, SERS and MALDI-TOF-MS are powerful metabolic fingerprinting techniques capable of discriminating clinically relevant cell wall mutants of a single isogenic bacterial strain.

Rapid Detection and Quantification of Novel Psychoactive Substances (NPS) Using Raman Spectroscopy and Surface-Enhanced Raman Scattering.

With more than a million seizures of illegal drugs reported annually across Europe, the variety of psychoactive compounds available is vast and ever-growing. The multitude of risks associated with these compounds are well-known and can be life threatening. Hence the need for the development of new analytical techniques and approaches that allow for the rapid, sensitive, and specific quantitative detection and discrimination of such illicit materials, ultimately with portability for field testing, is of paramount importance. The aim of this study was to demonstrate the application of Raman spectroscopy and surface-enhanced Raman scattering (SERS) combined with chemometrics approaches, as rapid and portable techniques for the quantitative detection and discrimination of a wide range of novel psychoactive substances (methcathinone and aminoindane derivatives), both in powder form and in solution. The Raman spectra of the psychoactive compounds provided clear separation and classification of the compounds based on their core chemical structures; viz. methcathinones, aminoindanes, diphenidines, and synthetic cannabinoids. The SERS results also displayed similar clustering patterns, with improved limits of detections down to ~2 mM (0.41 g L-1). As mephedrone is currently very popular for recreational use we performed multiplexed quantitative detection of mephedrone (4-methylmethcathinone), and its two major metabolites (nor-mephedrone and 4-methylephedrine), as tertiary mixtures in water and healthy human urine. These findings readily illustrate the potential application of SERS for simultaneous detection of multiple NPS as mixtures without the need for lengthy prior chromatographic separation or enrichment methods.

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.

Quantitative detection of isotopically enriched E. coli cells by SERS.

It is clear that investigating how bacterial cells work by analysing their functional roles in microbial communities is very important in environmental, clinical and industrial microbiology. The benefits of linking genes to their respective functions include the reliable identification of the causative agents of various diseases, which would permit appropriate and timely treatment in healthcare systems. In industrial and municipal wastewater treatment and management, such knowledge may allow for the manipulation of microbial communities, such as through bioaugmentation, in order to improve the efficiency and effectiveness of bioremediation processes. Stable isotope probing coupled with identification techniques has emerged to be a potentially reliable tool for the discrimination, identification and characterization of bacteria at community and single cell levels, knowledge which can be utilized to link microbially mediated bioprocesses to phylogeny. Development of the surface-enhanced Raman scattering (SERS) technique offers an exciting alternative to the Raman and Fourier-transform infrared spectroscopic techniques in understanding the metabolic processes of microorganisms in situ. SERS employing Ag and Au nanoparticles can significantly enhance the Raman signal, making it an exciting candidate for the analysis of the cellular components of microorganisms. In this study, Escherichia coli cells were cultivated in minimal medium containing different ratios of 12C/13C glucose and/or 14N/15N ammonium chloride as the only carbon and nitrogen sources respectively, with the overall final concentrations of these substrates being constant. After growth, the E. coli cells were analyzed with SERS employing an in situ synthesis of Ag nanoparticles. This novel investigation of the SERS spectral data with multivariate chemometrics demonstrated clear clusters which could be correlated to the SERS spectral shifts of biomolecules from cells grown and hence labelled with 13C and 15N atoms. These shifts reflect the isotopic content of the bacteria and quantification of the isotope levels could be established using chemometrics based on partial least squares regression.

Combining Raman and FT-IR spectroscopy with quantitative isotopic labeling for differentiation of E. coli cells at community and single cell levels.

There is no doubt that the contribution of microbially mediated bioprocesses toward maintenance of life on earth is vital. However, understanding these microbes in situ is currently a bottleneck, as most methods require culturing these microorganisms to suitable biomass levels so that their phenotype can be measured. The development of new culture-independent strategies such as stable isotope probing (SIP) coupled with molecular biology has been a breakthrough toward linking gene to function, while circumventing in vitro culturing. In this study, for the first time we have combined Raman spectroscopy and Fourier transform infrared (FT-IR) spectroscopy, as metabolic fingerprinting approaches, with SIP to demonstrate the quantitative labeling and differentiation of Escherichia coli cells. E. coli cells were grown in minimal medium with fixed final concentrations of carbon and nitrogen supply, but with different ratios and combinations of (13)C/(12)C glucose and (15)N/(14)N ammonium chloride, as the sole carbon and nitrogen sources, respectively. The cells were collected at stationary phase and examined by Raman and FT-IR spectroscopies. The multivariate analysis investigation of FT-IR and Raman data illustrated unique clustering patterns resulting from specific spectral shifts upon the incorporation of different isotopes, which were directly correlated with the ratio of the isotopically labeled content of the medium. Multivariate analysis results of single-cell Raman spectra followed the same trend, exhibiting a separation between E. coli cells labeled with different isotopes and multiple isotope levels of C and N.