Exposome-Scale Investigations Guided by Global Metabolomics, Pathway Analysis, and Cognitive Computing

Abstract

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, artificial intelligence provides a means of assessing the role of a potential toxicant. The presented workflow addresses many of the methodological challenges current exposomics research is facing and will serve to gain a deeper understanding of the impact of environmental exposures and combinatory toxic effects on human health.

Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases

“…Because the metabolome reflects the phenotype, which is a function of the interplay of genes, their expression and the environment (Figure ), metabolomics has the potential to provide insights on how the environment influences traits, and diseases. The metabolome could be studied, and environmental information collected in prospective cohort studies that follow subjects before the exhibition of disease symptoms, sometimes beginning as early as in utero, which have already resulted in certain success . However, it is important to note that whereas metabolomics is applied on correlating changes in metabolites with disease causes, progression, and outcomes, causation of altered metabolism in relation to diseases should be test in animal models, and much of the ability to potentially modulate diseases is on the environmental/exposure side.…”

“…,172 However, it is important to note that whereas metabolomics is applied on correlating changes in metabolites with disease causes, progression, and outcomes, causation of altered metabolism in relation to diseases should be test in animal models, and much of the ability to potentially modulate diseases is on the environmental/exposure side. Altogether, such approaches can draw contextual functions of metabolites and can guide further research related to human diseases.…”

Metabolomics reveals that dietary xenoestrogens alter cellular metabolism induced by palbociclib/letrozole combination cancer therapy

“…Bruker Compass Data Analysis 4.3 software was used for additional manual data evaluation and verification. Metabolite identification was based on matching MS/MS spectra, mainly through the METLIN database (Smith et al, 2005), which housed nearly one million unique metabolites at that time (Warth et al, 2017b). In many cases the metabolite identities were further validated by comparison with authentic reference standards.…”

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

“…This platform has also been used on a phase I clinical trial drug for a Parkinson’s disease immunotherapy that was found to target the tryptophan pathway and later validated with targeted metabolomics 20 . More recently, cellular responses to chemical exposure of a xenoestrogen on breast cancer cells have been studied and found to alter tRNA charging and ribonucleoside salvage pathways 21 . In addition, our study of altering carbon sources in an Escherichia coli model system was crucial in the development of the XCMS Online systems biology platform and implicated glycolysis and amino acid biosynthesis pathways as significantly dysregulated 9 .…”

“…In addition, our study of altering carbon sources in an Escherichia coli model system was crucial in the development of the XCMS Online systems biology platform and implicated glycolysis and amino acid biosynthesis pathways as significantly dysregulated 9 . Currently, the system has been optimized for >7,600 organisms and has been shown to be effective in cell culture and tissue-based studies 9,21 .…”