Chemical Proportionality within Molecular Networks

• Published in: Analytical chemistry (Washington) Vol. 93; no. 38; pp. 12833 - 12839
• Main Authors: Petras, Daniel, Caraballo-Rodríguez, Andrés Mauricio, Jarmusch, Alan K, Molina-Santiago, Carlos, Gauglitz, Julia M, Gentry, Emily C, Belda-Ferre, Pedro, Romero, Diego, Tsunoda, Shirley M, Dorrestein, Pieter C, Wang, Mingxun
• Format: Journal Article
• Language: English
• Published: Washington American Chemical Society 28.09.2021
• Subjects: Analytical chemistry; Bile acids; Biological properties; Biological samples; Biosynthesis; Chemistry; Drug metabolism; Mass spectrometry; Mass spectroscopy; Natural products; Networking; Social organization; Workflow
• ISSN: 0003-2700; 1520-6882
• DOI: 10.1021/acs.analchem.1c01520

Molecular networking of non-targeted tandem mass spectrometry data connects structurally related molecules based on similar fragmentation spectra. Here, we report the Chemical Proportionality (ChemProp) contextualization of molecular networks. ChemProp scores the changes of abundance between two connected nodes over sequential data series (e.g., temporal or spatial relationships), which can be displayed as a direction within the network to prioritize potential biological and chemical transformations or proportional changes of (biosynthetically) related compounds. We tested the ChemProp workflow on a ground truth data set of a defined mixture and highlighted the utility of the tool to prioritize specific molecules within biological samples, including bacterial transformations of bile acids, human drug metabolism, and bacterial natural products biosynthesis. The ChemProp workflow is freely available through the Global Natural Products Social Molecular Networking (GNPS) environment.