Summary of project PR002080
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR002080. The data can be accessed directly via it's Project DOI: 10.21228/M8RJ9N This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
| Project ID: | PR002080 |
| Project DOI: | doi: 10.21228/M8RJ9N |
| Project Title: | Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives |
| Project Type: | Bacteria supernatant |
| Project Summary: | Disruptions in microbial metabolite interactions due to gut microbiome dysbiosis and metabolomic shifts may contribute to Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and other immune-related conditions. The aryl hydrocarbon receptor (AhR), activated upon binding various tryptophan metabolites, modulates host immune responses. This study investigates whether the metabolic diversity—the concentration distribution—of bacterial indole pathway metabolites can differentiate bacterial strains and classify ME/CFS samples. A fast-targeted liquid chromatography-parallel reaction monitoring method with a 4-minute cycle time was developed for large-scale analysis. This method revealed significant metabolic diversity in indole derivatives among B. uniformis strains cultured from human isolates. Principal component analysis identified two major components (PC1, 68.9%; PC2, 18.7%), accounting for 87.6% of the variance and distinguishing two distinct B. uniformis clusters. The metabolic diversity between clusters was particularly evident in the contributions of indole-3-acrylate and indole-3-aldehyde. We explored the metabolic diversity of indole derivatives as potential biomarkers for ME/CFS by analyzing fecal samples from patients and healthy controls using the fast-targeted metabolomics method. An AdaBoost-LOOCV model achieved moderate classification success. Our findings suggest that the local indole diversity of tryptophan degradation is a promising biomarker for differentiating bacterial strains and classifying ME/CFS samples. The fast-targeted metabolomics method and data analysis enable accurate and precise quantitative measurements of metabolic diversity in indole derivatives, facilitating the study of microbial contributions to ME/CFS and other immune-related conditions. |
| Institute: | University of Connecticut |
| Department: | Chemistry |
| Laboratory: | Yao Lab |
| Last Name: | Tian |
| First Name: | Huidi |
| Address: | 55 N. Eagleville Road, Unit 3060, Storrs CT 06269 |
| Email: | huidi.tian@uconn.edu |
| Phone: | 8606341143 |
| Funding Source: | NIH |
Summary of all studies in project PR002080
| Study ID | Study Title | Species | Institute | Analysis(* : Contains Untargted data) | Release Date | Version | Samples | Download(* : Contains raw data) |
|---|---|---|---|---|---|---|---|---|
| ST003344 | Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives - gut bacterial cultures | Bacteroides uniformis | University of Connecticut | MS | 2025-10-05 | 1 | 216 | Uploaded data (181.3M)* |
| ST003346 | Fast Targeted Metabolomics for Analyzing Metabolic Diversity of Bacterial Indole Derivatives - fecal samples | Homo sapiens | University of Connecticut | MS | 2025-10-05 | 1 | 180 | Uploaded data (202.3M)* |
