27Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has been shown to quickly and accurately 28 speciate microorganisms based upon their species-specific lipid profile. Previous work by members of 29 this group showed that the use of a handheld bipolar probe allowed REIMS to analyse microbial 30 cultures directly from culture plates, without any prior preparation. However, this method of analysis 31 would likely be unsuitable for a high-throughput clinical microbiology laboratory. Here, we report on 32 the creation of a customised platform which enables automated, high-throughput REIMS analysis, 33 which requires minimal user input and operation; and suitable for use in clinical microbiology 34 laboratories. The ability of this high-throughput platform to speciate clinically important 35 microorganisms was tested through the analysis of 375 different clinical isolates, collected from 36 distinct patient samples, from 25 microbial species. After optimisation of our data analysis approach, 37we achieved substantially similar results between the two REIMS approaches. For handheld bipolar 38 probe REIMS a speciation accuracy of 96.3% was achieved, whilst for high-throughput REIMS, an 39 accuracy of 93.9% was achieved. Thus, high-throughput REIMS offers an alternative mass 40 spectrometry based method for the rapid and accurate identification of clinically important 41 microorganisms in clinical laboratories without any pre-analysis preparative steps.
Background and Aims Anti-tumour necrosis factor [anti-TNF] therapy is indicated for treatment of moderate to severe inflammatory bowel disease [IBD], but has a primary non-response rate of around 30%. We aim to use metabonomic and metataxonomic profiling to identify predictive biomarkers of anti-TNF response in Crohn’s disease. Methods Patients with luminal Crohn’s disease, commencing anti-TNF therapy, were recruited with urine, faeces, and serum samples being collected at baseline and 3-monthly. Primary response was defined according to a combination of clinical and objective markers of inflammation. Samples were measured using three UPLC-MS assays: lipid, bile acid, and Hydrophillic Interaction Liquid Chromatography [HILIC] profiling with 16S rRNA gene sequencing of faeces. Results Samples were collected from 76 Crohn’s disease patients who were anti-TNF naïve and from 13 healthy controls. There were 11 responders, 37 non-responders, and 28 partial responders in anti-TNF-treated Crohn’s patients. Histidine and cysteine were identified as biomarkers of response from polar metabolite profiling [HILIC] of serum and urine. Lipid profiling of serum and faeces found phosphocholines, ceramides, sphingomyelins, and triglycerides, and bile acid profiling identified primary bile acids to be associated with non-response to anti-TNF therapy, with higher levels of phase 2 conjugates in non-responders. Receiver operating curves for treatment response demonstrated 0.94 +/ -0.10 [faecal lipid], 0.81 +/- 0.17 [faecal bile acid], and 0.74 +/- 0.15 [serum bile acid] predictive ability for anti-TNF response in Crohn’s disease. Conclusions This prospective, longitudinal cohort study of metabonomic and 16S rRNA gene sequencing analysis demonstrates that a range of metabolic biomarkers involving lipid, bile acid, and amino acid pathways may contribute to prediction of response to anti-TNF therapy in Crohn’s disease. Podcast This article has an associated podcast which can be accessed at https://academic.oup.com/ecco-jcc/pages/podcast
Members of the genus Candida, such as C. albicans and C. parapsilosis, are important human pathogens. Other members of this genus, previously believed to carry minimal disease risk, are increasingly recognised as important human pathogens, particularly because of variations in susceptibilities to widely used anti-fungal agents. Thus, rapid and accurate identification of clinical Candida isolates is fundamental in ensuring timely and effective treatments are delivered. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has previously been shown to provide a high-throughput platform for the rapid and accurate identification of bacterial and fungal isolates. In comparison to commercially available matrix assisted laser desorption ionisation time of flight mass spectrometry (MALDI-ToF), REIMS based methods require no preparative steps nor time-consuming cell extractions. Here, we report on the ability of REIMS-based analysis to rapidly and accurately identify 153 clinical Candida isolates to species level. Both handheld bipolar REIMS and high-throughput REIMS platforms showed high levels of species classification accuracy, with 96% and 100% of isolates classified correctly to species level respectively. In addition, significantly different (FDR corrected P value < 0.05) lipids within the 600 to 1000 m/z mass range were identified, which could act as species-specific biomarkers in complex microbial communities.
Pregnancy is associated with progressive hypercholanemia, hypercholesterolemia, and hypertriglyceridemia, which can result in metabolic disease in susceptible women. Gut signals modify hepatic homeostatic pathways, linking intestinal content to metabolic activity. We sought to identify whether enteric endocrine signals contribute to raised serum bile acids observed in human and murine pregnancies, by measuring fibroblast growth factor (FGF) 19/15 protein and mRNA levels, and 7α‐hydroxy‐4‐cholesten‐3‐one. Terminal ileal farnesoid X receptor (FXR)‐mediated gene expression and apical sodium bile acid transporter (ASBT) protein concentration were measured by qPCR and western blotting. Shotgun whole‐genome sequencing and ultra‐performance liquid chromatography tandem mass spectrometry were used to determine the cecal microbiome and metabonome. Targeted and untargeted pathway analyses were performed to predict the systemic effects of the altered metagenome and metabolite profiles. Dietary CA supplementation was used to determine whether the observed alterations could be overcome by intestinal bile acids functioning as FXR agonists. Human and murine pregnancy were associated with reduced intestinal FXR signaling, with lower FGF19/15 and resultant increased hepatic bile acid synthesis. Terminal ileal ASBT protein was reduced in murine pregnancy. Cecal bile acid conjugation was reduced in pregnancy because of elevated bile salt hydrolase‐producing Bacteroidetes. CA supplementation induced intestinal FXR signaling, which was not abrogated by pregnancy, with strikingly similar changes to the microbiota and metabonome as identified in pregnancy. Conclusion: The altered intestinal microbiota of pregnancy enhance bile acid deconjugation, reducing ileal bile acid uptake and lowering FXR induction in enterocytes. This exacerbates the effects mediated by reduced bile acid uptake transporters in pregnancy. Thus, in pregnant women and mice, there is reduced FGF19/15‐mediated hepatic repression of hepatic bile acid synthesis, resulting in hypercholanemia.
Rapid evaporative ionisation mass spectrometry (REIMS) is a novel technique for the real-time analysis of biological material. It works by conducting an electrical current through a sample, causing it to rapidly heat and evaporate, with the analyte containing vapour channelled to a mass spectrometer. It was used to characterise the metabolome of 45 Pseudomonas aeruginosa (P. aeruginosa) isolates from cystic fibrosis (CF) patients and compared to 80 non-CF P. aeruginosa. Phospholipids gave the highest signal intensity; 17 rhamnolipids and 18 quorum sensing molecules were detected, demonstrating that REIMS has potential for the study of virulence-related metabolites. P. aeruginosa isolates obtained from respiratory samples showed a higher diversity, which was attributed to the chronic nature of most respiratory infections. The analytical sensitivity of REIMS allowed the detection of a metabolome that could be used to classify individual P. aeruginosa isolates after repeated culturing with 81% accuracy, and an average 83% concordance with multilocus sequence typing. This study underpins the capacities of REIMS as a tool with clinical applications, such as metabolic phenotyping of the important CF pathogen P. aeruginosa, and highlights the potential of metabolic fingerprinting for fine scale characterisation at a sub-species level.
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