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Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO2 laser) and with automation for high-throughput analysis. Laser-induced sample evaporation occurs within seconds through radiative heating with the plume guided to the MS instrument. The presented procedure includes (i) laser setup with automation, (ii) analysis of biofluids (blood/urine/stool/saliva/sputum/breast milk) and (iii) data analysis. We provide the optimal settings for biofluid analysis and quality control, enabling sensitive, precise and robust analysis. Using the automated setup, 96 samples can be analyzed in ~35-40 min per ionization mode, with no intervention required. Metabolic fingerprints are made up of 2,000-4,000 features, for which relative quantification can be achieved at high repeatability when total ion current normalization is applied. With saliva and feces as example matrices, >70% of features had a coefficient of variance ≤30%. However, to achieve acceptable long-term reproducibility, additional normalizations by, e.g., LOESS are recommended, especially for positive ionization.

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 UPLC-MS 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 cholic acid 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 due to elevated bile salt hydrolase-producing Bacteroidetes. Cholic acid 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. This article is protected by copyright. All rights reserved.

Mass spectrometry has established itself as a powerful tool in the chemical, biological, medical, environmental, and agricultural fields. However, experimental approaches and potential application areas have been limited by a traditional reliance on sample preparation, extraction, and chromatographic separation. Ambient ionization mass spectrometry methods have addressed this challenge but are still somewhat restricted in requirements for sample manipulation to make it suitable for analysis. These limitations are particularly restrictive in view of the move toward high-throughput and automated analytical workflows. To address this, we present what we consider to be the first automated sample-preparation-free mass spectrometry platform utilizing a carbon dioxide (CO2) laser for sample thermal desorption linked to the rapid evaporative ionization mass spectrometry (LA-REIMS) methodology. We show that the pulsatile operation of the CO2 laser is the primary factor in achieving high signal-to-noise ratios. We further show that the LA-REIMS automated platform is suited to the analysis of three diverse biological materials within different application areas. First, clinical microbiology isolates were classified to species level with an accuracy of 97.2%, the highest accuracy reported in current literature. Second, fecal samples from a type 2 diabetes mellitus cohort were analyzed with LA-REIMS, which allowed tentative identification of biomarkers which are potentially associated with disease pathogenesis and a disease classification accuracy of 94%. Finally, we showed the ability of the LA-REIMS system to detect instances of adulteration of cooking oil and determine the geographical area of production of three protected olive oil products with 100% classification accuracy.

Sparse data exist regarding the normal range of composition of maternal milk beyond the first postnatal weeks. This single timepoint, observational study in collaboration with the &lsquo, Parenting Science Gang&rsquo, citizen science group evaluated the metabolite and bacterial composition of human milk from 62 participants (infants aged 3&ndash, 48 months), nearly 3 years longer than previous studies. We utilised rapid evaporative ionisation mass spectrometry (REIMS) for metabolic fingerprinting and 16S rRNA gene metataxonomics for microbiome composition analysis. Milk expression volumes were significantly lower beyond 24 months of lactation, but there were no corresponding changes in bacterial load, composition, or whole-scale metabolomic fingerprint. Some individual metabolite features (~14%) showed altered abundances in nursling age groups above 24 months. Neither milk expression method nor nursling sex affected metabolite and metataxonomic fingerprints. Self-reported lifestyle factors, including diet and physical traits, had minimal impact on metabolite and metataxonomic fingerprints. Our findings suggest remarkable consistency in human milk composition over natural-term lactation. The results add to previous studies suggesting that milk donation can continue up to 24 months postnatally. Future longitudinal studies will confirm the inter-individual and temporal nature of compositional variations and the use of donor milk as a personalised therapeutic.

Of the many metabolites involved in any clinical condition, only a narrow range of biomarkers is currently being used in the clinical setting. A key to personalized medicine would be to extend this range. Metabolic fingerprinting provides a more comprehensive insight, but many methods used for metabolomics analysis are too complex and time-consuming to be diagnostically useful. Here, a rapid evaporative ionization mass spectrometry (REIMS) system for direct ex vivo real-time analysis of biofluids with minor sample pretreatment is detailed. The REIMS can be linked to various laser wavelength systems (such as optical parametric oscillator or CO

Ursodeoxycholic acid (UDCA) treatment can reduce itch and lower endogenous serum bile acids in intrahepatic cholestasis of pregnancy (ICP). We sought to determine how it could influence the gut environment in ICP to alter enterohepatic signalling. The gut microbiota and bile acid content were determined in faeces from 35 pregnant women (14 with uncomplicated pregnancies and 21 with ICP, 17 receiving UDCA). Faecal bile salt hydrolase activity was measured using a precipitation assay. Serum fibroblast growth factor 19 (FGF19) and 7α-hydroxy-4-cholesten-3-one (C4) concentrations were measured following a standardised diet for 21 hours. Women with a high ratio of Bacteroidetes to Firmicutes were more likely to be treated with UDCA (Fisher’s exact test p = 0.0178) than those with a lower ratio. Bile salt hydrolase activity was reduced in women with low Bacteroidetes:Firmicutes. Women taking UDCA had higher faecal lithocholic acid (p Bacteroidetes. These demonstrate high bile salt hydrolase activity, which deconjugates bile acids enabling secondary modification to FXR agonists, enhancing enterohepatic feedback via FGF19.

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

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.

Early stage diagnosis of colorectal cancer (CRC) is a key predictor of patient survival, highlighting the need for accurate diagnostic biomarkers. Laser Assisted - Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS) demonstrates potential for direct from sample metabolic profiling of feces. Here, we present an optimized LA-REIMS approach for fecal metabolomic analysis in CRC for the first time. A prospective, observational cohort biomarker discovery study was performed at an NHS hospital trust in the UK. Patients referred through the national two week wait cancer pathway were prospectively recruited. The primary outcome was to differentiate between adenomas or CRC and non-disease controls, the secondary outcome was to compare LA-REIMS to fecal immunochemical testing (FIT) against the gold-standard of colonoscopy or CT colonography. Those under the age of 18, pregnant, or unable to undergo colonic investigation were excluded. Fecal samples were analyzed using FIT (Kyowa Medex Co Ltd, Japan), with a detection limit of 7µg haemoglobin/g feces considered a positive result, as well as a LA-REIMS setup (Xevo G2-S QTof (Waters Corporation)), with optimized laser and instrumentation parameters (improved signal-to-noise and reduced carry-over between samples). After pre-processing, univariate and multivariate statistics were carried out in MetaboAnalyst 4.0. Random forest classification (RFC) with leave one out cross-validation (LOOCV) was performed.244 subjects (120 females, mean age 67.5 (range 21-93)) were included, of which n=135 were non-disease controls, n=82 adenoma patients, and n=27 CRC patients. Partial least square-discriminant analysis (PLS-DA) demonstrated a distinction between control vs CRC (Q2= 0.60087, R2= 0.89376). RFC with LOOCV for cancer vs control showed a sensitivity of 34.6% and specificity of 99.2% compared to 81.8% sensitivity and 87.2% specificity with FIT. PLS-DA of control vs adenoma (Q2= 0.64284, R2= 0.8898) demonstrated good separation. RFC with LOOCV for adenoma vs control had a sensitivity of 61.0 % and specificity of 94.7% compared to 33.8 % sensitivity and 87.2% specificity with FIT. Univariate analysis identified a feature tentatively assigned to the glycerolipid class (area under the receiver operating characteristic curve (AUROC) 0.986 (CI=0.957-1) to be more abundant in CRC vs control (false discovery rate (FDR) corrected p Citation Format: Petra Paizs, Monika Widlak, Alvaro Perdones-Montero, Maria Sani, Lauren Ford, James L. Alexander, Simon Cameron, Ramesh Arasaradnam, James M. Kinross, Zoltan Takats. High-throughput fecal metabolic profiling for the early detection of colorectal cancer using a direct mass spectrometry assay [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 271.

By leveraging advances in DNA synthesis and molecular cloning techniques, synthetic biology increasingly makes use of large construct libraries to explore large design spaces. For biosynthetic pathway engineering, the ability to screen these libraries for a variety of metabolites of interest is essential. If the metabolite of interest or the metabolic phenotype is not easily measurable, screening soon becomes a major bottleneck involving time-consuming culturing, sample preparation, and extraction. To address this, we demonstrate the use of automated laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS)-a form of ambient laser desorption ionization mass spectrometry-to perform rapid mass spectrometry analysis direct from agar plate yeast colonies without sample preparation or extraction. We use LA-REIMS to assess production levels of violacein and betulinic acid directly from yeast colonies at a rate of 6 colonies per minute. We then demonstrate the throughput enabled by LA-REIMS by screening over 450 yeast colonies within

The accurate and timely identification of the causative organism of infection is important in ensuring the optimum treatment regimen is prescribed for a patient. Rapid evaporative ionisation mass spectrometry (REIMS), using electrical diathermy for the thermal disruption of a sample, has been shown to provide fast and accurate identification of microorganisms directly from culture. However, this method requires contact to be made between the REIMS probe and microbial biomass; resulting in the necessity to clean or replace the probes between analyses. Here, optimisation and utilisation of ambient laser desorption ionisation (ALDI) for improved speciation accuracy and analytical throughput is shown. Optimisation was completed on 15 isolates of Escherichia coli, showing 5 W in pulsatile mode produced the highest signal-to-noise ratio. These parameters were used in the analysis of 150 clinical isolates from ten microbial species, resulting in a speciation accuracy of 99.4% - higher than all previously reported REIMS modalities. Comparison of spectral data showed high levels of similarity between previously published electrical diathermy REIMS data. ALDI does not require contact to be made with the sample during analysis, meaning analytical throughput can be substantially improved, and further, increases the range of sample types which can be analysed in potential direct-from-sample pathogen detection.

Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has been shown to quickly and accurately speciate microorganisms based upon their species-specific lipid profile. Previous work by members of this group showed that the use of a handheld bipolar probe allowed REIMS to analyse microbial cultures directly from culture plates, without any prior preparation. However, this method of analysis would likely be unsuitable for a high-throughput clinical microbiology laboratory. Here, we report on the creation of a customised platform which enables automated, high-throughput REIMS analysis, which requires minimal user input and operation; and suitable for use in clinical microbiology laboratories. The ability of this high-throughput platform to speciate clinically important microorganisms was tested through the analysis of 375 different clinical isolates, collected from distinct patient samples, from 25 microbial species. After optimisation of our data analysis approach, we achieved substantially similar results between the two REIMS approaches. For handheld bipolar probe REIMS a speciation accuracy of 96.3% was achieved, whilst for high-throughput REIMS, an accuracy of 93.9% was achieved. Thus, high-throughput REIMS offers an alternative mass spectrometry based method for the rapid and accurate identification of clinically important microorganisms in clinical laboratories without any pre-analysis preparative steps.

Rapid and reliable diagnosis of endometrial cancer (EC) in uterine aspirates is highly desirable. Current sensitivity and failure rate of histological diagnosis limit the success of this method and subsequent hysteroscopy is often necessary. Using quantitative reverse transcriptase-polymerase chain reaction on RNA from uterine aspirates samples, we measured the expression level of 20 previously identified genes involved in EC pathology, created five algorithms based on combinations of five genes and evaluated their ability to diagnose EC. The algorithms were tested in a prospective, double-blind, multicenter study. We enlisted 514 patients who presented with abnormal uterine bleeding. EC was diagnosed in 60 of the 514 patients (12%). Molecular analysis was performed on the remnants of aspirates and results were compared to the final histological diagnoses obtained through biopsies acquired by aspiration or guided by hysteroscopy, or from the specimens resected by hysterectomy. Algorithm 5 was the best performing molecular diagnostic classifier in the case-control and validation study. The molecular test had a sensitivity of 81%, specificity of 96%, positive predictive value (PPV) of 75% and negative predictive value (NPV) of 97%. A combination of the molecular and histological diagnosis had a sensitivity of 91%, specificity of 97%, PPV of 79% and NPV of 99% and the cases that could be diagnosed on uterine aspirate rose from 76 to 93% when combined with the molecular test. Incorporation of the molecular diagnosis increases the reliability of a negative diagnosis, reduces the need for hysteroscopies and helps to identify additional cases.

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 m/z mass range were identified, which could act as species-specific biomarkers in complex microbial communities.

Introduction The colorectal cancer (CRC) microbiome is niche specific and individualised. Several putative driver organisms enriched on CRCs have been identified from human studies, but few data exist which properly account for important clinical variables in CRC. In this study, we used a meta-taxonomic approach to demonstrate how the CRC microbiome varies with disease stage, histological markers of prognosis and host molecular phenotypes. Method A prospective study was performed on patients undergoing colonoscopy and elective surgery for CRC at three hospitals in UK and Czech Republic. Tissue was sampled from tumours, adenomas, adjacent normal mucosa and mucosa from healthy colon controls. The V1-2 regions of the 16S rRNA gene were sequenced (Illumina MiSeq); data were processed in Mothur and analysed in Stamp and R. Species assignment was performed with NCBI BLAST for microbial genomes. False discovery rate p value correction accounted for multiple testing. Histological analysis and tumour molecular phenotyping were performed according to Royal College of Pathology guidelines. Results One hundred and ninety six patients were recruited: 158 CRC patients, 24 adenoma patients and 14 normal colon controls (median age 70; range 35–90). Tumours were staged as 6 T0, 4 T1, 23 T2, 97 T3, 27 T4; 99 N0, 40 N1, 27 N2; 6 M1. No significant differences were seen in diversity or taxonomy between the UK and Czech cohorts. Adenoma and healthy colon control samples were taxonomically indistinct. However, CRCs were characterised by reduced Shannon diversity (p Conclusion This large prospective analysis demonstrates that the CRC microbiome is stage-specific and appears to evolve with disease progression. We conclude that oral pathobionts which colonise advanced stage disease relate to markers of tumour prognosis, raising the possibility that they may be directly influencing tumour invasion. Disclosure of Interest None Declared

Rapid and reliable diagnosis of endometrial cancer (EC) in uterine aspirates is highly desirable. Current sensitivity and failure rate of histological diagnosis limit the success of this method and subsequent hysteroscopy is often necessary. Using quantitative reverse transcriptase-polymerase chain reaction on RNA from uterine aspirates samples, we measured the expression level of 20 previously identified genes involved in EC pathology, created five algorithms based on combinations of five genes and evaluated their ability to diagnose EC. The algorithms were tested in a prospective, double-blind, multicenter study. We enlisted 514 patients who presented with abnormal uterine bleeding. EC was diagnosed in 60 of the 514 patients (12%). Molecular analysis was performed on the remnants of aspirates and results were compared to the final histological diagnoses obtained through biopsies acquired by aspiration or guided by hysteroscopy, or from the specimens resected by hysterectomy. Algorithm 5 was the best performing molecular diagnostic classifier in the case-control and validation study. The molecular test had a sensitivity of 81%, specificity of 96%, positive predictive value (PPV) of 75% and negative predictive value (NPV) of 97%. A combination of the molecular and histological diagnosis had a sensitivity of 91%, specificity of 97%, PPV of 79% and NPV of 99% and the cases that could be diagnosed on uterine aspirate rose from 76 to 93% when combined with the molecular test. Incorporation of the molecular diagnosis increases the reliability of a negative diagnosis, reduces the need for hysteroscopies and helps to identify additional cases.