Montenegro-Burke, J. R. | Search bioRxiv

bioRxiv2026

An atlas of the human metabolome

Despite the emergence of cellular atlases like the Human Protein Atlas, no equivalent atlas exists for the human metabolome. Here, we present the Human Metabolome Atlas (HMA, hma.ccbr.utoronto.ca), a comprehensive map containing metabolomic profiles of 70 human cell lines across 22 tissues. With an [~]8-fold increase in coverage compared to other resources, the HMA contains quantitative data for 1768 metabolites at the highest identification confidence, encompassing over 50 lipid classes and a broad range of metabolic pathways. This constitutes the most extensive human metabolomic atlas available. Leveraging the HMA, we identified specific metabolic regulation within pathways and cell types and characterized metabolic processes like glycosylation and ferroptosis. Lastly, we developed a publicly available, interactive web-portal to facilitate custom data analysis for the broader scientific community.

systems biology↗

bioRxiv2017

Exposing the Exposome with Global Metabolomics andCognitive Computing

Concurrent exposure to a wide variety of xenobiotics and their combined toxic effects can play a pivotal role in health and disease, yet are largely unexplored. Investigating the totality of these exposures, i.e. the exposome, and their specific biological effects constitutes a new paradigm for environmental health but still lacks high-throughput, user-friendly technology. We demonstrate the utility of mass spectrometry-based global exposure metabolomics combined with tailored database queries and cognitive computing for comprehensive exposure assessment and the straightforward elucidation of biological effects. The METLIN Exposome database has been redesigned to help identify environmental toxicants, food contaminants and supplements, drugs, and antibiotics as well as their biotransformation products, through its expansion with over 700,000 chemical structures to now include more than 950,000 unique small molecules. More importantly, we demonstrate how the XCMS/METLIN platform now allows for the readout of the biological effect of a toxicant through metabolomic-derived pathway analysis and further, cognitive computing provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the outstanding methodological challenges current exposome research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health.

epidemiology↗