microbeMASST: a taxonomically informed mass spectrometry search tool for microbial metabolomics data

Area of Science:

• Microbiology
• Metabolomics
• Bioinformatics

Background:

• Untargeted metabolomics often faces challenges in microbial metabolite annotation.
• Accurate identification of microbial metabolites is crucial for understanding their ecological roles and impact on human health.

Purpose of the Study:

• To introduce microbeMASST, a novel mass spectrometry (MS) search tool designed for microbial metabolite annotation.
• To enable the identification of known and unknown microbial metabolites and their producing organisms using MS/MS fragmentation patterns.

Main Methods:

• Development of microbeMASST, incorporating a database of over 60,000 microbial monocultures.
• Utilizing taxonomically informed MS/MS spectral searching to link metabolites to microbial sources.
• Application in untargeted metabolomics workflows.

Main Results:

• Demonstrated capability to search and annotate MS/MS spectra against a comprehensive microbial metabolite database.
• Enabled the direct linkage of identified metabolites to their specific microbial producers.
• Facilitated the identification of microbe-derived metabolites without prior knowledge of the producing organism.

Conclusions:

• microbeMASST significantly improves microbial metabolite annotation in untargeted metabolomics.
• The tool enhances the understanding of microbial contributions to various ecosystems and health-related processes.
• Facilitates discovery of novel microbial metabolites and their functions.