Phylogenetic and chemical redundancy in microbial libraries has resulted in a high rediscovery rate of known compounds and, consequently, a large divestment in natural product drug discovery. To rapidly reduce the taxonomic and natural product redundancy in our microbial libraries we developed IDBac- a rapid, mass spectrometry based bioinformatics platform for characterizing protein and small molecule fingerprints of microorganisms. Designed to work with a few, to thousands of samples it has become a powerful tool both in reducing taxonomic and natural product redundancy and generating hypotheses in a variety of contexts. Since the release of version 1.0 in 2019, IDBac has the added benefit of being designed for extensibility, providing powerful data management and advanced workflows to manipulate and analyze MALDI-TOF MS data at any scale. Using IDBac we have shown how to reduce taxonomic and natural product redundancy in expedition-scale isolation campaigns. Additionally, with this single method, we have compared population differences and directly interrogated the correlation of phylogeny and specialized metabolism within readily-cultured bacteria from freshwater sponges. This represents significant advancement not only in how MALDI-TOF MS can be used to screen isolates entering drug discovery pipelines but in how the same data can be used to inform future sample collection efforts.
History
Advisor
Murphy, Brian T
Chair
Murphy, Brian T
Department
Pharmaceutical Sciences
Degree Grantor
University of Illinois at Chicago
Degree Level
Doctoral
Degree name
PhD, Doctor of Philosophy
Committee Member
Sanchez, Laura M
Orjala, Jimmy
Mankin, Alexander S
Cruz, Isabel F