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Name Ms. Nicole Avalon
Organization or Institution University of South Florida, Department of Chemistry
Presentation Type Poster
Topic Biochemistry / Chem Bio.

Predictive Databases, Computational Peptide Sequencing, and Secondary Metabolite Identification from a New Antarctic Pseudovibrio species


Nicole E. Avalon1, Lucas Bishop2, Alison E. Murray2, Bill J. Baker1

Author Institution(s)

1 Department of Chemistry, University of South Florida, Tampa, FL; 2 Division of Earth and Ecosystem Sciences, Desert Research Institute, Reno, NV


Antarctic invertebrates are rich sources of secondary metabolites with high potential for bioactivity.  Many of the bioactive compounds isolated from invertebrates are thought to be produced, in whole or in part, by bacteria that are associated with the host organism.  Often present within the genome of these symbiotic or associated bacteria are biosynthetic gene clusters (BGC) responsible for the biosynthesis of non-ribosomal peptides, polyketides, as well as other compounds.  The initial stages of the elucidation of the biosynthetic pathways for secondary metabolites involves validation of compound prediction tools from computational databases.  In this project, mass spectrometry is used to validate the databases by confirming the presence of the predicted peptides based on the genomic sequencing results of Pseudovibrio sp. Tun.PSC04-5.I4.  BGCs were computationally identified in the genome of a new strain of Pseudovibrio sp., isolated from the Antarctic tunicate Synoicum adareanum.  Biomass of the bacterial isolate was processed for proteomic analysis.  Reverse phase liquid chromatography followed by nanoelectrospray were used in conjunction with a hybrid quadrupole-Orbitrap Q Exactive Plus mass spectrometer.  Preliminary data has been obtained to allow for de novo peptide sequencing and custom database searches, with particular focus on fragments of possible permutations of the predicted peptide using PEAKS 8.5 software (Bioinformatics Solutions, Inc.).  Preliminary data point to the presence of at least one of five predicted non-ribosomal peptides in the bacterial extract, with variable sites of methylation and a non-reduced c-terminus.  We have developed a method for validation of secondary metabolite prediction databases via mass spectrometry.