Bacterial discrimination by Fourier transform infrared spectroscopy, MALDI-mass spectrometry and whole-genome sequencing.

Aim: Proof-of-concept study, highlighting the clinical diagnostic ability of FT-IR compared with MALDI-TOF MS, combined with WGS. Materials & methods: 104 pathogenic isolates of Neisseria meningitidis, Streptococcus pneumoniae, Streptococcus pyogenes and Staphylococcus aureus were analyzed. Results: Overall prediction accuracy was 99.6% in FT-IR and 95.8% in MALDI-TOF-MS. Analysis of N. meningitidis serogroups was superior in FT-IR compared with MALDI-TOF-MS. Phylogenetic relationship of S. pyogenes was similar by FT-IR and WGS, but not S. aureus or S. pneumoniae. Clinical severity was associated with the zinc ABC transporter and DNA repair genes in S. pneumoniae and cell wall proteins (biofilm formation, antibiotic and complement permeability) in S. aureus via WGS. Conclusion: FT-IR warrants further clinical evaluation as a promising diagnostic tool.

We tested a technique (FT-IR) to identify four different, common bacteria from 104 children with serious infections and compared it to lab methods for diagnosis. FT-IR was more accurate. We tested if it could identify subtypes of bacteria, which is important in outbreaks. It was able to subtype two species, but not the two other species. However, it is a much faster and cheaper technique than the gold standard. It may be useful in certain outbreaks. We also investigated the trends between genes and the length of hospital stay. This can support further laboratory research. As a fast, low-cost test, FT-IR warrants further testing before it is applied to clinical labs.

Monitoring Phenotype Heterogeneity at the Single-Cell Level within Bacillus Populations Producing Poly-3-hydroxybutyrate by Label-Free Super-resolution Infrared Imaging.

Phenotypic heterogeneity is commonly found among bacterial cells within microbial populations due to intrinsic factors as well as equipping the organisms to respond to external perturbations. The emergence of phenotypic heterogeneity in bacterial populations, particularly in the context of using these bacteria as microbial cell factories, is a major concern for industrial bioprocessing applications. This is due to the potential impact on overall productivity by allowing the growth of subpopulations consisting of inefficient producer cells. Monitoring the spread of phenotypes across bacterial cells within the same population at the single-cell level is key to the development of robust, high-yield bioprocesses. Here, we discuss the novel development of optical photothermal infrared (O-PTIR) spectroscopy to probe phenotypic heterogeneity within Bacillus strains by monitoring the production of the bioplastic poly-3-hydroxybutyrate (PHB) at the single-cell level. Measurements obtained on single-point and in imaging mode show significant variability in the PHB content within bacterial cells, ranging from whether or not a cell produces PHB to variations in the intragranular biochemistry of PHB within bacterial cells. Our results show the ability of O-PTIR spectroscopy to probe PHB production at the single-cell level in a rapid, label-free, and semiquantitative manner. These findings highlight the potential of O-PTIR spectroscopy in single-cell microbial metabolomics as a whole-organism fingerprinting tool that can be used to monitor the dynamic of bacterial populations as well as for understanding their mechanisms for dealing with environmental stress, which is crucial for metabolic engineering research.

Metabolomics of Escherichia coli for Disclosing Novel Metabolic Engineering Strategies for Enhancing Hydrogen and Ethanol Production.

The biological production of hydrogen is an appealing approach to mitigating the environmental problems caused by the diminishing supply of fossil fuels and the need for greener energy. Escherichia coli is one of the best-characterized microorganisms capable of consuming glycerol-a waste product of the biodiesel industry-and producing H2 and ethanol. However, the natural capacity of E. coli to generate these compounds is insufficient for commercial or industrial purposes. Metabolic engineering allows for the rewiring of the carbon source towards H2 production, although the strategies for achieving this aim are difficult to foresee. In this work, we use metabolomics platforms through GC-MS and FT-IR techniques to detect metabolic bottlenecks in the engineered ΔldhΔgndΔfrdBC::kan (M4) and ΔldhΔgndΔfrdBCΔtdcE::kan (M5) E. coli strains, previously reported as improved H2 and ethanol producers. In the M5 strain, increased intracellular citrate and malate were detected by GC-MS. These metabolites can be redirected towards acetyl-CoA and formate by the overexpression of the citrate lyase (CIT) enzyme and by co-overexpressing the anaplerotic human phosphoenol pyruvate carboxykinase (hPEPCK) or malic (MaeA) enzymes using inducible promoter vectors. These strategies enhanced specific H2 production by up to 1.25- and 1.49-fold, respectively, compared to the reference strains. Other parameters, such as ethanol and H2 yields, were also enhanced. However, these vectors may provoke metabolic burden in anaerobic conditions. Therefore, alternative strategies for a tighter control of protein expression should be addressed in order to avoid undesirable effects in the metabolic network.

Unlocking the secrets of the microbiome: exploring the dynamic microbial interplay with humans through metabolomics and their manipulation for synthetic biology applications.

Metabolomics is a powerful research discovery tool with the potential to measure hundreds to low thousands of metabolites. In this review, we discuss the application of GC-MS and LC-MS in discovery-based metabolomics research, we define metabolomics workflows and we highlight considerations that need to be addressed in order to generate robust and reproducible data. We stress that metabolomics is now routinely applied across the biological sciences to study microbiomes from relatively simple microbial systems to their complex interactions within consortia in the host and the environment and highlight this in a range of biological species and mammalian systems including humans. However, challenges do still exist that need to be overcome to maximise the potential for metabolomics to help us understanding biological systems. To demonstrate the potential of the approach we discuss the application of metabolomics in two broad research areas: (1) synthetic biology to increase the production of high-value fine chemicals and reduction in secondary by-products and (2) gut microbial interaction with the human host. While burgeoning in importance, the latter is still in its infancy and will benefit from the development of tools to detangle host-gut-microbial interactions and their impact on human health and diseases.

Optical photothermal infrared spectroscopy: A novel solution for rapid identification of antimicrobial resistance at the single-cell level via deuterium isotope labeling.

The rise and extensive spread of antimicrobial resistance (AMR) has become a growing concern, and a threat to the environment and human health globally. The majority of current AMR identification methods used in clinical setting are based on traditional microbiology culture-dependent techniques which are time-consuming or expensive to be implemented, thus appropriate antibiotic stewardship is provided retrospectively which means the first line of treatment is to hope that a broad-spectrum antibiotic works. Hence, culture-independent and single-cell technologies are needed to allow for rapid detection and identification of antimicrobial-resistant bacteria and to support a more targeted and effective antibiotic therapy preventing further development and spread of AMR. In this study, for the first time, a non-destructive phenotyping method of optical photothermal infrared (O-PTIR) spectroscopy, coupled with deuterium isotope probing (DIP) and multivariate statistical analysis was employed as a metabolic fingerprinting approach to detect AMR in Uropathogenic Escherichia coli (UPEC) at both single-cell and population levels. Principal component-discriminant function analysis (PC-DFA) of FT-IR and O-PTIR spectral data showed clear clustering patterns as a result of distinctive spectral shifts (C-D signature peaks) originating from deuterium incorporation into bacterial cells, allowing for rapid detection and classification of sensitive and resistant isolates at the single-cell level. Furthermore, the single-frequency images obtained using the C-D signature peak at 2,163 cm-1 clearly displayed the reduced ability of the trimethoprim-sensitive strain for incorporating deuterium when exposed to this antibiotic, compared to the untreated condition. Hence, the results of this study indicated that O-PTIR can be employed as an efficient tool for the rapid detection of AMR at the single-cell level.

Simultaneous Raman and infrared spectroscopy: a novel combination for studying bacterial infections at the single cell level.

Sepsis is a life-threatening clinical condition responsible for approximately 11 million deaths worldwide. Rapid and accurate identification of pathogenic bacteria and its antimicrobial susceptibility play a critical role in reducing the morbidity and mortality rates related to sepsis. Raman and infrared spectroscopies have great potential to be used as diagnostic tools for rapid and culture-free detection of bacterial infections. Despite numerous reports using both methods to analyse bacterial samples, there is to date no study collecting both Raman and infrared signatures from clinical samples simultaneously due to instrument incompatibilities. Here, we report for the first time the use of an emerging technology that provides infrared signatures via optical photothermal infrared (O-PTIR) spectroscopy and Raman spectra simultaneously. We use this approach to analyse 12 bacterial clinical isolates including six isolates of Gram-negative and six Gram-positive bacteria commonly associated with bloodstream infection in humans. To benchmark the single cell spectra obtained by O-PTIR spectroscopy, infrared signatures were also collected from bulk samples via both FTIR and O-PTIR spectroscopies. Our findings showed significant similarity and high reproducibility in the infrared signatures obtained by all three approaches, including similar discrimination patterns when subjected to clustering algorithms. Principal component analysis (PCA) showed that O-PTIR and Raman data acquired simultaneously from bulk bacterial isolates displayed different clustering patterns due to the ability of both methods to probe metabolites produced by bacteria. By contrast, signatures of microbial pigments were identified in Raman spectra, providing complementary and orthogonal information compared to infrared, which may be advantageous as it has been demonstrated that certain pigments play an important role in bacterial virulence. We found that infrared spectroscopy showed higher sensitivity than Raman for the analysis of individual cells. Despite the different patterns obtained by using Raman and infrared spectral data as input for clustering algorithms, our findings showed high data reproducibility in both approaches as the biological replicates from each bacterial strain clustered together. Overall, we show that Raman and infrared spectroscopy offer both advantages and disadvantages and, therefore, having both techniques combined in one single technology is a powerful tool with promising applications in clinical microbiology.

Metabolic Fingerprint Analysis of Cytochrome b 5-producing E. coli N4830-1 Using FT-IR Spectroscopy.

Optimization of recombinant protein expression in bacteria is an important task in order to increase protein yield while maintaining the structural fidelity of the product. In this study, we employ Fourier transform infrared (FT-IR) spectroscopy as a high throughput metabolic fingerprinting approach to optimize and monitor cytochrome b 5 (CYT b 5) production in Escherichia coli N4830-1, as the heterologous host. Cyt b5 was introduced as a plasmid with between 0 and 6 copies under a strong promoter. The FT-IR spectroscopy results combined with multivariate chemometric analysis illustrated discriminations among culture conditions as well as revealing features that correlated to the different cytb 5 gene copy numbers. The second derivative of the FT-IR spectral data allowed for the quantitative detection of Cyt b5 directly inside the intact cells without the need for extraction, and highlighted changes in protein secondary structure that was directly correlated to the cytb 5 gene copy number and protein content, and was in complete agreement with quantitative findings of standard traditional techniques such as SDS-PAGE and western blot analysis.

Metabolomics for the design of new metabolic engineering strategies for improving aerobic succinic acid production in Escherichia coli.

INTRODUCTION: Glycerol is a byproduct from the biodiesel industry that can be biotransformed by Escherichia coli to high added-value products such as succinate under aerobic conditions. The main genetic engineering strategies to achieve this aim involve the mutation of succinate dehydrogenase (sdhA) gene and also those responsible for acetate synthesis including acetate kinase, phosphate acetyl transferase and pyruvate oxidase encoded by ackA, pta and pox genes respectively in the ΔsdhAΔack-ptaΔpox (M4) mutant. Other genetic manipulations to rewire the metabolism toward succinate consist on the activation of the glyoxylate shunt or blockage the pentose phosphate pathway (PPP) by deletion of isocitrate lyase repressor (iclR) or gluconate dehydrogenase (gnd) genes on M4-ΔiclR and M4-Δgnd mutants respectively. OBJECTIVE: To deeply understand the effect of the blocking of the pentose phosphate pathway (PPP) or the activation of the glyoxylate shunt, metabolite profiles were analyzed on M4-Δgnd, M4-ΔiclR and M4 mutants. METHODS: Metabolomics was performed by FT-IR and GC-MS for metabolite fingerprinting and HPLC for quantification of succinate and glycerol. RESULTS: Most of the 65 identified metabolites showed lower relative levels in the M4-ΔiclR and M4-Δgnd mutants than those of the M4. However, fructose 1,6-biphosphate, trehalose, isovaleric acid and mannitol relative concentrations were increased in M4-ΔiclR and M4-Δgnd mutants. To further improve succinate production, the synthesis of mannitol was suppressed by deletion of mannitol dehydrogenase (mtlD) on M4-ΔgndΔmtlD mutant that increase ~ 20% respect to M4-Δgnd. CONCLUSION: Metabolomics can serve as a holistic tool to identify bottlenecks in metabolic pathways by a non-rational design. Genetic manipulation to release these restrictions could increase the production of succinate.

Simultaneous Raman and Infrared Spectroscopy of Stable Isotope Labelled Escherichia coli.

We report the use of a novel technology based on optical photothermal infrared (O-PTIR) spectroscopy for obtaining simultaneous infrared and Raman spectra from the same location of the sample allowing us to study bacterial metabolism by monitoring the incorporation of 13C- and 15N-labeled compounds. Infrared data obtained from bulk populations and single cells via O-PTIR spectroscopy were compared to conventional Fourier transform infrared (FTIR) spectroscopy in order to evaluate the reproducibility of the results achieved by all three approaches. Raman spectra acquired were concomitant with infrared data from bulk populations as well as infrared spectra collected from single cells, and were subjected to principal component analysis in order to evaluate any specific separation resulting from the isotopic incorporation. Similar clustering patterns were observed in infrared data acquired from single cells via O-PTIR spectroscopy as well as from bulk populations via FTIR and O-PTIR spectroscopies, indicating full incorporation of heavy isotopes by the bacteria. Satisfactory discrimination between unlabeled (viz. 12C14N), 13C14N- and 13C15N-labeled bacteria was also obtained using Raman spectra from bulk populations. In this report, we also discuss the limitations of O-PTIR technology to acquire Raman data from single bacterial cells (with typical dimensions of 1 × 2 µm) as well as spectral artifacts induced by thermal damage when analyzing very small amounts of biomass (a bacterium tipically weighs ~ 1 pg).

The Role of Raman Spectroscopy Within Quantitative Metabolomics.

Ninety-four years have passed since the discovery of the Raman effect, and there are currently more than 25 different types of Raman-based techniques. The past two decades have witnessed the blossoming of Raman spectroscopy as a powerful physicochemical technique with broad applications within the life sciences. In this review, we critique the use of Raman spectroscopy as a tool for quantitative metabolomics. We overview recent developments of Raman spectroscopy for identification and quantification of disease biomarkers in liquid biopsies, with a focus on the recent advances within surface-enhanced Raman scattering-based methods. Ultimately, we discuss the applications of imaging modalities based on Raman scattering as label-free methods to study the abundance and distribution of biomolecules in cells and tissues, including mammalian, algal, and bacterial cells.

Imaging Isotopically Labeled Bacteria at the Single-Cell Level Using High-Resolution Optical Infrared Photothermal Spectroscopy.

We report that the cellular uptake of stable isotope-labeled compounds by bacteria can be probed at the single-cell level using infrared spectroscopy, and this monitors the chemical vibrations affected by the incorporation of "heavy" atoms by cells and thus can be used to understand microbial systems. This presents a significant advancement as most studies have focused on evaluating communities of cells due to the poor spatial resolution achieved by classical infrared microspectrometers, and to date, there is no study evaluating the incorporation of labeled compounds by bacteria at single-cell levels using infrared spectroscopy. The development of new technologies and instrumentations that provide information on the metabolic activity of a single bacterium is critical as this will allow for a better understanding of the interactions between microorganisms as well as the function of individual members and their interactions in different microbial communities. Thus, the present study demonstrates the ability of a novel far-field infrared imaging technique, optical photothermal infrared (O-PTIR) spectroscopy, as a tool to monitor the uptake of 13C-glucose and 15N-ammonium chloride by Escherichia coli bacteria at single-cell levels using spectral signatures recorded via single-point and imaging modes. An additional novelty is that imaging was achieved using six vibrational bands in the amide I and II regions, which were analyzed with chemometrics by employing partial least squares-discriminant analysis to predict 13C/12C and 15N/14N simultaneously.

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.

Assessment of Transdermal Delivery of Topical Compounds in Skin Scarring Using a Novel Combined Approach of Raman Spectroscopy and High-Performance Liquid Chromatography.

Objective: The goal of any topical formulation is efficient transdermal delivery of its active components. However, delivery of compounds can be problematic with penetration through tough layers of fibrotic dermal scar tissue. Approach: We propose a new approach combining high-performance liquid chromatography (HPLC) and Raman spectroscopy (RS) using a topical of unknown composition against a well-known antiscar topical (as control). Results: Positive detection of compounds within the treatment topical using both techniques was validated with mass spectrometry. RS detected conformational structural changes; the 1,655/1,446 cm-1 ratio estimating collagen content significantly decreased (p < 0.05) over weeks 4, 12, and 16 compared with day 0. The amide I band, known to represent collagen and protein in skin, shifted from 1,667 to 1,656 cm-1, which may represent a change from ß-sheets in elastin to α-helices in collagen. Confirmatory elastin immunohistochemistry decreased compared with day 0, conversely the collagen I/III ratio increased in the same samples by week 12 (p < 0.05, and p < 0.0001, respectively), in keeping with normal scar formation. Optical coherence tomography attenuation coefficient representing collagen deposition was significantly decreased at week 4 compared with day 0 and increased at week 16 (p < 0.05). Innovation: This study provides a platform for further research on the simultaneous evaluation of the effects of compounds in cutaneous scarring by RS and HPLC, and identifies a role for RS in the therapeutic evaluation and theranostic management of skin scarring. Conclusions: RS can provide noninvasive information on the effects of topicals on scar pathogenesis and structural composition, validated by other analytical techniques.

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.

Targeting Methionine Synthase in a Fungal Pathogen Causes a Metabolic Imbalance That Impacts Cell Energetics, Growth, and Virulence.

There is an urgent need to develop novel antifungals to tackle the threat fungal pathogens pose to human health. Here, we have performed a comprehensive characterization and validation of the promising target methionine synthase (MetH). We show that in Aspergillus fumigatus the absence of this enzymatic activity triggers a metabolic imbalance that causes a reduction in intracellular ATP, which prevents fungal growth even in the presence of methionine. Interestingly, growth can be recovered in the presence of certain metabolites, which shows that metH is a conditionally essential gene and consequently should be targeted in established infections for a more comprehensive validation. Accordingly, we have validated the use of the tetOFF genetic model in fungal research and improved its performance in vivo to achieve initial validation of targets in models of established infection. We show that repression of metH in growing hyphae halts growth in vitro, which translates into a beneficial effect when targeting established infections using this model in vivo Finally, a structure-based virtual screening of methionine synthases reveals key differences between the human and fungal structures and unravels features in the fungal enzyme that can guide the design of novel specific inhibitors. Therefore, methionine synthase is a valuable target for the development of new antifungals.IMPORTANCE Fungal pathogens are responsible for millions of life-threatening infections on an annual basis worldwide. The current repertoire of antifungal drugs is very limited and, worryingly, resistance has emerged and already become a serious threat to our capacity to treat fungal diseases. The first step to develop new drugs is often to identify molecular targets in the pathogen whose inhibition during infection can prevent its growth. However, the current models are not suitable to validate targets in established infections. Here, we have characterized the promising antifungal target methionine synthase in great detail, using the prominent fungal pathogen Aspergillus fumigatus as a model. We have uncovered the underlying reason for its essentiality and confirmed its druggability. Furthermore, we have optimized the use of a genetic system to show a beneficial effect of targeting methionine synthase in established infections. Therefore, we believe that antifungal drugs to target methionine synthase should be pursued and additionally, we provide a model that permits gaining information about the validity of antifungal targets in established infections.

Evaluation of Sample Preparation Methods for Inter-Laboratory Metabolomics Investigation of Streptomyces lividans TK24.

In the past two decades, metabolomics has proved to be a valuable tool with many potential applications in different areas of science. However, there are still some challenges that need to be addressed, particularly for multicenter studies. These challenges are mainly attributed to various sources of fluctuation and unwanted variations that can be introduced at pre-analytical, analytical, and/or post-analytical steps of any metabolomics experiment. Thus, this study aimed at using Streptomyces lividans TK24 as the model organism in a cross-laboratory experiment in Manchester and Leuven to evaluate the reproducibility of a standard sample preparation method, and determine the optimal sample format (cell extract or quenched biomass) required to preserve the metabolic profile of the cells during cross-lab sample transportation and storage. Principal component analysis (PCA) scores plot of the gas chromatography-mass spectrometry (GC-MS) data from both laboratories displayed clear growth-dependent clustering patterns which was in agreement with the Procrustes analysis findings. In addition, the data generated in Manchester displayed tight clustering of cell pellets (quenched biomass) and metabolite extracts, confirming the stability of both sample formats during the transportation and storage period.

Radiation Tolerance of Pseudanabaena catenata, a Cyanobacterium Relevant to the First Generation Magnox Storage Pond.

Recently a species of Pseudanabaena was identified as the dominant photosynthetic organism during a bloom event in a high pH (pH ∼11.4), radioactive spent nuclear fuel pond (SNFP) at the Sellafield Ltd., United Kingdom facility. The metabolic response of a laboratory culture containing the cyanobacterium Pseudanabaena catenata, a relative of the major photosynthetic microorganism found in the SNFP, to X-ray irradiation was studied to identify potential survival strategies used to support colonization of radioactive environments. Growth was monitored and the metabolic fingerprints of the cultures, during irradiation and throughout the post-irradiation recovery period, were determined using Fourier transform infrared (FT-IR) spectroscopy. A dose of 95 Gy delivered over 5 days did not significantly affect growth of P. catenata, as determined by turbidity measurements and cell counts. Multivariate statistical analysis of the FT-IR spectral data revealed metabolic variation during the post-irradiation recovery period, with increased polysaccharide and decreased amide spectral intensities. Increases in polysaccharides were confirmed by complementary analytical methods including total carbohydrate assays and calcofluor white staining. This observed increased production of polysaccharides is of significance, since this could have an impact on the fate of the radionuclide inventory in the pond via biosorption of cationic radionuclides, and may also impact on downstream processes through biofilm formation and biofouling.

A microbiome and metabolomic signature of phases of cutaneous healing identified by profiling sequential acute wounds of human skin: An exploratory study.

Profiling skin microbiome and metabolome has been utilised to gain further insight into wound healing processes. The aims of this multi-part temporal study in 11 volunteers were to analytically profile the dynamic wound tissue and headspace metabolome and sequence microbial communities in acute wound healing at days 0, 7, 14, 21 and 28, and to investigate their relationship to wound healing, using non-invasive quantitative devices. Metabolites were obtained using tissue extraction, sorbent and polydimethylsiloxane patches and analysed using GCMS. PCA of wound tissue metabolome clearly separated time points with 10 metabolites of 346 being involved in separation. Analysis of variance-simultaneous component analysis identified a statistical difference between the wound headspace metabolome, sites (P = 0.0024) and time points (P<0.0001), with 10 out of the 129 metabolites measured involved with this separation between sites and time points. A reciprocal relationship between Staphylococcus spp. and Propionibacterium spp. was observed at day 21 (P<0.05) with a statistical correlation between collagen and Propionibacterium (r = 0.417; P = 0.038) and Staphylococcus (r = -0.434; P = 0.03). Procrustes analysis showed a statistically significant similarity between wound headspace and tissue metabolome with non-invasive wound devices. This exploratory study demonstrates the temporal and dynamic nature of acute wound metabolome and microbiome presenting a novel class of biomarkers that correspond to wound healing, with further confirmatory studies now necessary.

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.