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

This review compares and contrasts MALDI-MS, FT-IR spectroscopy and Raman spectroscopy for whole organism fingerprinting and bacterial typing.

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.

Involvement of multiple influx and efflux transporters in the accumulation of cationic fluorescent dyes by Escherichia coli

Background

It is widely believed that most xenobiotics cross biomembranes by diffusing through the phospholipid bilayer, and that the use of protein transporters is an occasional adjunct. According to an alternative view, phospholipid bilayer transport is negligible, and several different transporters may be involved in the uptake of an individual molecular type. We recognise here that the availability of gene knockout collections allows one to assess the contributions of all potential transporters, and flow cytometry based on fluorescence provides a convenient high-throughput assay for xenobiotic uptake in individual cells.

Results

We used high-throughput flow cytometry to assess the ability of individual gene knockout strains of E coli to take up two membrane-permeable, cationic fluorescent dyes, namely the carbocyanine diS-C3(5) and the DNA dye SYBR Green. Individual strains showed a large range of distributions of uptake. The range of modal steady-state uptakes for the carbocyanine between the different strains was 36-fold. Knockouts of the ATP synthase α- and β-subunits greatly inhibited uptake, implying that most uptake was ATP-driven rather than being driven by a membrane potential. Dozens of transporters changed the steady-state uptake of the dye by more than 50% with respect to that of the wild type, in either direction (increased or decreased); knockouts of known influx and efflux transporters behaved as expected, giving credence to the general strategy. Many of the knockouts with the most reduced uptake were transporter genes of unknown function (‘y-genes’). Similarly, several overexpression variants in the ‘ASKA’ collection had the anticipated, opposite effects. Similar results were obtained with SYBR Green (the range being approximately 69-fold). Although it too contains a benzothiazole motif there was negligible correlation between its uptake and that of the carbocyanine when compared across the various strains (although the membrane potential is presumably the same in each case).

Conclusions

Overall, we conclude that the uptake of these dyes may be catalysed by a great many transporters of putatively broad and presently unknown specificity, and that the very large range between the ‘lowest’ and the ‘highest’ levels of uptake, even in knockouts of just single genes, implies strongly that phospholipid bilayer transport is indeed negligible. This work also casts serious doubt upon the use of such dyes as quantitative stains for representing either bioenergetic parameters or the amount of cellular DNA in unfixed cells (in vivo). By contrast, it opens up their potential use as transporter assay substrates in high-throughput screening.

Electronic supplementary material

The online version of this article (10.1186/s12866-019-1561-0) contains supplementary material, which is available to authorized users.

Substantial Extracellular Metabolic Differences Found Between Phylogenetically Closely Related Probiotic and Pathogenic Strains of Escherichia coli

Since its first isolation a century ago, the gut inhabitant Escherichia coli strain Nissle 1917 has been shown to have probiotic activities; however, it is yet not fully elucidated which differential factors play key roles in its beneficial interactions with the host. To date, no metabolomics studies have been reported investigating the potential role of small molecules in functional strain differentiation of Nissle from its genetically close neighbors. Here, we present results of liquid chromatography coupled to high-resolution mass spectrometry characterization of extracellular metabolomes of E. coli strains as a proxy of their bioactivity potential. We found that phylogroup B2 strains exported a more diverse arsenal of metabolites than strains of other phylogroups. Zooming into the phylogroup B2 metabolome identified consistent substantial differences between metabolic output of E. coli Nissle and other strains, particularly in metabolites associated to the Argimine biosynthesis pathway. Nissle was found to release higher levels of Ornithine and Citrulline whilst depleting greater amounts of Arginine from the medium. Moreover, a novel Nissle-specific metabolite not reported before in bacteria, 5-(Carbamoylamino)-2-hydroxypentanoic acid (Citrulline/Arginic Acid related) was observed. Finally, Nissle, CFT073 and NCTC12241/ATCC25922 shared the excretion of N5-Acetylornithine, whereas other strains released N2-Acetylornithine or no N-Acetylornithine at all. Thus, we found substantial metabolic differences in phylogenetically very similar E. coli strains, an observation which suggests that it is justified to further investigate roles of small molecules as potential modulators of the gut environment by probiotic, commensal, and pathogenic strains, including E. coli Nissle 1917.

Methodological considerations for large-scale breath analysis studies: lessons from the U-BIOPRED severe asthma project

Methods for breath sampling and analysis require robust quality assessment to minimise the risk of false discoveries. Planning large-scale multi-site breath metabolite profiling studies also requires careful consideration of systematic and random variation as a result of sampling and analysis techniques. In this study we use breath sample data from the recent U-BIOPRED cohort to evaluate and discuss some important methodological considerations such as batch variation and correction, variation between sites, storage and transportation, as well as inter-instrument analytical differences. Based on this we provide a summary of recommended best practices for new large scale multi-site studies.

Classification of Bacillus and Brevibacillus species using rapid analysis of lipids by mass spectrometry

Bacillus are aerobic spore-forming bacteria that are known to lead to specific diseases, such as anthrax and food poisoning. This study focuses on the characterization of these bacteria by the detection of lipids extracted from 33 well-characterized strains from the Bacillus and Brevibacillus genera, with the aim to discriminate between the different species. For the purpose of analysing the lipids extracted from these bacterial samples, two rapid physicochemical techniques were used: matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF-MS) and liquid chromatography in conjunction with mass spectrometry (LC-MS). The findings of this investigation confirmed that MALDI-TOF-MS could be used to identify different bacterial lipids and, in combination with appropriate chemometrics, allowed for the discrimination between these different bacterial species, which was supported by LC-MS. The average correct classification rates for the seven species of bacteria were 62.23 and 77.03 % based on MALDI-TOF-MS and LC-MS data, respectively. The Procrustes distance for the two datasets was 0.0699, indicating that the results from the two techniques were very similar. In addition, we also compared these bacterial lipid MALDI-TOF-MS profiles to protein profiles also collected by MALDI-TOF-MS on the same bacteria (Procrustes distance, 0.1006). The level of discrimination between lipids and proteins was equivalent, and this further indicated the potential of MALDI-TOF-MS analysis as a rapid, robust and reliable method for the classification of bacteria based on different bacterial chemical components. Graphical abstract MALDI-MS has been successfully developed for the characterization of bacteria at the subspecies level using lipids and benchmarked against HPLC.

Analysis of multi-source metabolomic data using joint and individual variation explained (JIVE)

Metabolic profiling is increasingly being used for understanding biological processes but there is no single analytical technique that provides a complete quantitative or qualitative profiling of the metabolome. Data fusion (i.e. joint analysis of data from multiple sources) has the potential to circumvent this issue facilitating knowledge discovery and reliable biomarker identification. Another field of application of data fusion is the simultaneous analysis of metabolomic changes through several biofluids or tissues. However, metabolomics typically deals with large datasets, with hundreds to thousands of variables and the identification of shared and individual factors or structures across multiple sources is challenging due to the high variable to sample ratios and differences in intensity and noise range. In this work we apply a recent method, Joint and Individual Variation Explained (JIVE), for the integrated unsupervised analysis of metabolomic profiles from multiple data sources. This method separates the shared patterns among data sources (i.e. the joint structure) from the individual structure of each data source that is unrelated to the joint structure. Two examples are described to show the applicability of JIVE for the simultaneous analysis of multi-source data using: (i) plasma samples subjected to different analytical techniques, sample treatment and measurement conditions; and (ii) plasma and urine samples subjected to liquid chromatography-mass spectrometry measured using two ionization conditions.

High-throughput metabolic screening of microalgae genetic variation in response to nutrient limitation

Microalgae produce metabolites that could be useful for applications in food, biofuel or fine chemical production. The identification and development of suitable strains require analytical methods that are accurate and allow rapid screening of strains or cultivation conditions. We demonstrate the use of Fourier transform infrared (FT-IR) spectroscopy to screen mutant strains of Chlamydomonas reinhardtii. These mutants have knockdowns for one or more nutrient starvation response genes, namely PSR1, SNRK2.1 and SNRK2.2. Limitation of nutrients including nitrogen and phosphorus can induce metabolic changes in microalgae, including the accumulation of glycerolipids and starch. By performing multivariate statistical analysis of FT-IR spectra, metabolic variation between different nutrient limitation and non-stressed conditions could be differentiated. A number of mutant strains with similar genetic backgrounds could be distinguished from wild type when grown under specific nutrient limited and replete conditions, demonstrating the sensitivity of FT-IR spectroscopy to detect specific genetic traits. Changes in lipid and carbohydrate between strains and specific nutrient stress treatments were validated by other analytical methods, including liquid chromatography-mass spectrometry for lipidomics. These results demonstrate that the PSR1 gene is an important determinant of lipid and starch accumulation in response to phosphorus starvation but not nitrogen starvation. However, the SNRK2.1 and SNRK2.2 genes are not as important for determining the metabolic response to either nutrient stress. We conclude that FT-IR spectroscopy and chemometric approaches provide a robust method for microalgae screening.