Finding Small Molecules and their Metabolites in Big Data

Invited presentation for the AI3SD Autumn Seminar Series (virtual) held December 15th, 2021 (Event Link).
Thanks to Sami Kanza for the invitation and opportunity.

Details:

Finding Small Molecules and their Metabolites in Big Data

Emma L. Schymanski

Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 avenue du Swing, 4367 Belvaux, Luxembourg. ORCID: 0000-0001-6868-8145.

Abstract:

The environment and the chemicals to which we are exposed is incredibly complex, with over 111 million chemicals in the largest open chemical databases, 300,000 estimated in global inventories of high use, and over 70,000 in household use alone. Detectable molecules in environmental samples, metabolomics and exposomics can now be captured using high resolution mass spectrometry (HRMS), which provides a “snapshot” of all chemicals present in a sample and allows for retrospective data analysis through digital archiving. However, there is no “one size fits all” analytical method, and scientists cannot yet identify most of the tens of thousands of features in each sample, let alone associate them with health or disease, leading to critical bottlenecks in identification and data interpretation. Defining the chemical space to search is a huge challenge, especially considering that chemicals transform in both organisms (metabolism) and the environment (both biotic and abiotic processes). This talk will cover European and worldwide community initiatives and resources to help find and identify small molecules and their metabolites (transformation products) - from compound databases to spectral libraries, from literature mining to transformation prediction. It will show how FAIR and Open interdisciplinary efforts and data sharing can facilitate research in many areas of small molecule research. Various contributors to this massive collaborative effort will be acknowledged throughout the talk.