Abstract
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 at a rate of 4 minutes per sample was developed for large-scale analysis. This method revealed significant metabolic differences 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 difference between clusters was particularly evident in the relative contributions of indole-3-acrylate and indole-3-aldehyde. We further measured concentration distributions of indole derivatives in ME/CFS by analyzing fecal samples from 10 patients and 10 healthy controls using the fast targeted metabolomics method. An AdaBoost-LOOCV model achieved moderate classification success with a mean LOOCV accuracy of 0.65 (Control: precision of 0.67, recall of 0.60, F1-score of 0.63; ME/CFS: precision of 0.64, recall of 0.7000, F1-score of 0.67). These results suggest that the metabolic diversity of indole derivatives from tryptophan degradation, facilitated by the fast targeted metabolomics and machine learning, is a potential biomarker for differentiating bacterial strains and classifying ME/CFS samples. Mass spectrometry datasets are accessible at the National Metabolomics Data Repository (ST002308, DOI: 10.21228/M8G13Q; ST003344, DOI: 10.21228/M8RJ9N; ST003346, DOI: 10.21228/M8RJ9N).