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Untargeted metabolomics provides a direct window into biochemical activities but faces critical challenges in determining metabolite origins and interpreting unannotated metabolic features. Here, we present TidyMass2, an enhanced computational framework for Liquid Chromatography-Mass Spectrometry (LC-MS) untargeted metabolomics that addresses these limitations. TidyMass2 introduces three major innovations compared to its predecessor, TidyMass (1) a comprehensive metabolite origin inference capability that traces metabolites to human, microbial, dietary, pharmaceutical, and environmental sources through integration of 11 metabolite databases containing 532,488 metabolites with source information; (2) a metabolic feature-based functional module analysis approach that bypasses the annotation bottleneck by leveraging metabolic network topology to extract biological insights from unannotated metabolic features; and (3) a graphical interface that makes advanced metabolomics analyses accessible to researchers without programming expertise. Applied to longitudinal urine metabolomics data from human pregnancy, TidyMass2 identified diverse metabolites originating from human, microbiome, and environment, and uncovered 27 dysregulated metabolic modules. It increased the proportion of biologically interpretable metabolic features from 5.8% to 58.8%, revealing coordinated changes in steroid hormone biosynthesis, carbohydrate metabolism, and amino acid processing. By expanding biological interpretation beyond MS2 spectra-based annotated metabolites, TidyMass2 enables more comprehensive metabolic phenotyping while upholding open-source principles of reproducibility, traceability, and transparency.

Deployment of a cloud-based passive defecation monitoring system for continuous gut health monitoring

Identification of antimicrobial peptides from ancient gut microbiomes

To date, treating ulcerative colitis (UC) remains a significant challenge due to its complex etiology. In this study, metabolomics and proteomics analysis for multi-center cohorts reveal that both serum arginine levels and the rate-limiting enzyme argininosuccinate synthetase 1 (ASS1) are significantly elevated in UC patients. Exogenous arginine infusion and ASS1 overexpression exacerbate the pathological features of colitis in mice, while inhibiting or silencing ASS1 offers protection against experimental colitis. The induction of ASS1 is accompanied by increased levels of acetylated H3 and trimethylated H3K4, along with decreased levels of dimethyl H3K9 around the ASS1 promoters, suggesting epigenetic activation of ASS1 in colitis. The ASS1/arginine axis triggers mTOR and iNOS activation and induces gut microbiota dysbiosis, leading to experimental colitis. Additionally, we identify a screened compound, C-01, which significantly improves colitis by highly binding to ASS1. Our findings suggest that ASS1 could be a promising target for UC treatment.

Application of LLMs/Transformer-Based Models for Metabolite Annotation in Metabolomics

Application of Wearable Devices in Diabetes Management

Food recommendation towards personalized wellbeing

A multistage, multitask transformer-based framework for multi-disease diagnosis and prediction using personal proteomes

Identification of Early and Mid-Pregnancy Maternal Lipidomics and Metabolomics Signatures of Preterm and Small-for-Gestational Age Infants from Low-and Middle-income Countries …

Longitudinal urine metabolic profiling and gestational age prediction in human pregnancy