Computational Metabolomics: A Framework for the Million Metabolome

Area of Science:

• Environmental Science
• Toxicology
• Computational Chemistry

Background:

• The human exposome includes over 400,000 environmental chemicals, with most uncharacterized regarding health impacts.
• Mass spectrometry detects over 200,000 unidentified ions in human samples, posing a challenge for toxicology.
• 80-85% of human diseases are linked to environmental exposures, highlighting the need for exposome research.

Purpose of the Study:

• To review progress in computational metabolomics for chemical identification.
• To establish a foundation for unambiguous designation of unidentified ions for toxicological study.
• To support a system for documenting unidentified ions in environmental surveillance and human biomonitoring.

Main Methods:

• Utilizing accurate mass m/z, chromatographic retention time, and adduct/isotopic/fragment correlations.
• Analyzing collision-induced dissociation products, collision cross-section, and chirality.
• Leveraging computational metabolomics for probability-based annotation of ions to known chemicals.

Main Results:

• Computational metabolomics offers a path beyond single-chemical analysis.
• Methods for ion characterization enable unambiguous designation of unidentified compounds.
• Progress in computational metabolomics supports the characterization of the human chemical experience.

Conclusions:

• Reliable and affordable analytical methods are crucial for understanding the health impacts of environmental chemicals.
• Computational metabolomics provides a framework for identifying and assessing the risks of low-abundance environmental chemicals.
• This approach can lead to a better understanding of the health risks associated with the extensive human chemical exposure.