Microbial and metabolomic profiles in correlation with depression and anxiety co-morbidities in diarrhoea-predominant IBS patients.

BACKGROUND: Psychological co-morbidities in irritable bowel syndrome (IBS) have been widely recognized, whereas less is known regarding the role of gut microbial and host metabolic changes in clinical and psychological symptoms in IBS. RESULTS: A total of 70 diarrhoea-predominant IBS (IBS-D) patients and 46 healthy controls were enrolled in this study. Stool and urine samples were collected from both groups for 16S rRNA gene sequencing and metabolomic analysis. The results showed that fecal microbiota in IBS-D featured depleted Faecalibacterium (adjusted P = 0.034), Eubacterium rectale group (adjusted P = 0.048), Subdoligranulum (adjusted P = 0.041) and increased Prevotella (adjusted P = 0.041). O-ureido-L-serine, 3,4-dihydroxybenzenesulfonic acid and (R)-2-Hydroxyglutarate demonstrated lower urinary concentrations in IBS-D patients. We further built correlation matrices between gut microbe abundance, differentiated metabolite quantities and clinical parameters. Dialister manifested negative association with IBS severity (r = - 0.285, P = 0.017), anxiety (r = - 0.347, P = 0.003) and depression level (r = - 0.308, P = 0.010). Roseburia was negatively associated with IBS severity (r = - 0.298, P = 0.012). Twenty metabolites correlated with anxiety or depression levels, including 3,4-dihydroxymandelaldehyde with SAS (r = - 0.383, P = 0.001), 1-methylxanthine with SDS (r = - 0.347, P = 0.004) and 1D-chiro-inositol with SAS (r = - 0.336, P = 0.005). In analysis of microbe-metabolite relationship, 3,4-dihydroxymandelaldehyde and 1-methylxanthine were negatively correlated with relative abundance of Clostridiumsensu stricto. CONCLUSIONS: Our findings demonstrated altered microbial and metabolomic profiles associated with clinically and psychological symptoms in IBS-D patients, which may provide insights for further investigations.

Development of a Liquid Chromatography-High Resolution Mass Spectrometry Metabolomics Method with High Specificity for Metabolite Identification Using All Ion Fragmentation Acquisition.

High-resolution mass spectrometry (HRMS)-based metabolomics approaches have made significant advances. However, metabolite identification is still a major challenge with significant bottleneck in translating metabolomics data into biological context. In the current study, a liquid chromatography (LC)-HRMS metabolomics method was developed using an all ion fragmentation (AIF) acquisition approach. To increase the specificity in metabolite annotation, four criteria were considered: (i) accurate mass (AM), (ii) retention time (RT), (iii) MS/MS spectrum, and (iv) product/precursor ion intensity ratios. We constructed an in-house mass spectral library of 408 metabolites containing AMRT and MS/MS spectra information at four collision energies. The percent relative standard deviations between ion ratios of a metabolite in an analytical standard vs sample matrix were used as an additional metric for establishing metabolite identity. A data processing method for targeted metabolite screening was then created, merging m/z, RT, MS/MS, and ion ratio information for each of the 413 metabolites. In the data processing method, the precursor ion and product ion were considered as the quantifier and qualifier ion, respectively. We also included a scheme to distinguish coeluting isobaric compounds by selecting a specific product ion as the quantifier ion instead of the precursor ion. An advantage of the current AIF approach is the concurrent collection of full scan data, enabling identification of metabolites not included in the database. Our data acquisition strategy enables a simultaneous mixture of database-dependent targeted and nontargeted metabolomics in combination with improved accuracy in metabolite identification, increasing the quality of the biological information acquired in a metabolomics experiment.

L-Homoserine: a novel excreted metabolic marker of hepatitis B abnormally produced in liver from methionine.

The hepatitis B infection leads to various profound pathological processes in liver metabolism. Some biochemical alterations detectable by blood analysis are currently used for a preliminary evaluation of the infection. Based on existing data we present here evidence that non-protein amino acid L-homoserine is a pathological, hepatitis B-induced metabolite that is formed and excreted into urine from methionine via splitting S-adenosylmethionine. The urine L-homoserine is proposed as a new marker in the pre-diagnosis examinations that is easier for the clinical analysis than currently used blood test, and is applicable to large-scale epidemiological surveys of the probability of hepatitis B.