Browse views: by Year, by Function, by GLF, by Subfunction, by Conference, by Journal

Data-independent microbial metabolomics with ambient ionization mass spectrometry

Rath, CM, Yang, JY, Alexandrov, T and Dorrestein, PC (2013) Data-independent microbial metabolomics with ambient ionization mass spectrometry. Journal of the American Society for Mass Spectrometry. pp. 1167-1176.

Abstract

Atmospheric ionization methods are ideally suited for prolonged MS/MS analysis. Data-independent MS/MS is a complementary technique for analysis of biological samples as compared to data-dependent analysis. Here, we pair data-independent MS/MS with the ambient ionization method nanospray desorption electrospray ionization (nanoDESI) for untargeted analysis of bacterial metabolites. Proof-of-principle data and analysis are illustrated by sampling Bacillus subtilis and Pseudomonas aeruginosa directly from Petri dishes. We found that this technique enables facile comparisons between strains via MS and MS/MS plots which can be translated to chemically informative molecular maps through MS/MS networking. The development of novel techniques to characterize microbial metabolites allows rapid and efficient analysis of metabolic exchange factors. This is motivated by our desire to develop novel techniques to explore the role of interspecies interactions in the environment, health, and disease. This is a contribution to honor Professor Catherine C. Fenselau in receiving the prestigious ASMS Award for a Distinguished Contribution in Mass Spectrometry for her pioneering work on microbial mass spectrometry. [Figure not available: see fulltext.] 2013 American Society for Mass Spectrometry

Item Type: Article
Additional Information: pubid: 60 nvp_institute: NIBR contributor_address: (Rath, Alexandrov, Dorrestein) Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California at San Diego, San Diego, CA, United States (Yang, Dorrestein) Department of Chemistry and Biochemistry, University of California at San Diego, San Diego, CA, United States (Alexandrov) Center for Industrial Mathematics, University of Bremen, Bremen, Germany (Rath) Novartis Institute for Biomedical Research, Emeryville, CA, United States
Date Deposited: 13 Oct 2015 13:13
Last Modified: 13 Oct 2015 13:13
URI: https://oak.novartis.com/id/eprint/21907

Search