Peak Annotation and Verification Engine for Untargeted LC-MS Metabolomics
CABBI Theme: Conversion
Keywords: Metabolomics, Software
Wang L., Xing X., Chen L., Yang L., Su X., Rabitz H., Lu W., Rabinowitz J.D. Dec. 26, 2018. Peak Annotation and Verification Engine for Untargeted LC-MS Metabolomics, GitHub Repository, https://github.com/xxing9703/PAVE.
Untargeted metabolomics can detect more than 10 000 peaks in a single LC-MS run. The correspondence between these peaks and metabolites, however, remains unclear. Here, we introduce a Peak Annotation and Verification Engine (PAVE) for annotating untargeted microbial metabolomics data. The workflow involves growing cells in 13C and 15N isotope-labeled media to identify peaks from biological compounds and their carbon and nitrogen atom counts. Improved deisotoping and deadducting are enabled by algorithms that integrate positive mode, negative mode, and labeling data. To distinguish metabolites and their fragments, PAVE experimentally measures the response of each peak to weak in-source collision induced dissociation, which increases the peak intensity for fragments while decreasing it for their parent ions. The molecular formulas of the putative metabolites are then assigned based on database searching using both m/z and C/N atom counts.
Peaks Annotations (18MB)
Wang, L., Xing, X., Chen, L., Yang, L., Su, X., Rabitz, H., Lu, W., Rabinowitz, J.D. Dec. 26, 2018. “Peak Annotation and Verification Engine for Untargeted LC-MS Metabolomics.” Analytical Chemistry. 91:1838-1846. DOI: 10.1021/acs.analchem.8b03132.