TrpNet

TrpNet maps and predicts tryptophan metabolism within host-gut microbiome interactions to characterize metabolites, enzymes, and reactions across human and mouse gut bacteria.

Key Features:

• Extensive database: Contains data on 130 reactions, 108 metabolites, and 91 enzymes across 1246 human gut bacterial species and 88 mouse gut bacterial species.
• Predictive analytics: Employs a Bayesian logistic regression model to predict potential tryptophan metabolites from gut microbiome taxonomy profiles.
• Host–microbiome co-metabolic mapping: Represents co-metabolic processes between hosts (humans and mice) and their gut microbiota related to tryptophan biotransformation.
• Validation and efficacy: Validated using two gut microbiome metabolomics studies and demonstrated superior performance in predicting alterations in indole derivatives compared to other established methods.

Scientific Applications:

• Pathway elucidation: Characterizes pathways by which tryptophan is metabolized into microbial and host-associated metabolites.
• Immune modulation studies: Enables investigation of tryptophan-derived metabolites that modulate immune responses.
• Metabolic and neuronal function research: Supports analysis of metabolites implicated in metabolic functions and neuronal activities locally in the gut and at distant sites.
• Development, health, and disease research: Facilitates studies of animal development, health, and disease states influenced by host–microbiome tryptophan metabolism.

Methodology:

Uses a Bayesian logistic regression model to predict tryptophan metabolites from gut microbiome taxonomy profiles and validation was performed using two gut microbiome metabolomics studies.