Graduation Year

2023

Document Type

Thesis

Degree

M.S.

Degree Name

Master of Science (M.S.)

Degree Granting Department

Chemistry

Major Professor

Bill J. Baker, Ph.D.

Committee Member

Alison Murray, Ph.D.

Committee Member

Henry L. Woodcock, Ph.D.

Committee Member

James Leahy, Ph.D.

Keywords

antiSMASH, Confidence, Identification Scoring, LC-MS QToF

Abstract

Marine sediment-associated bacteria house many new and exciting novel secondary metabolites. These metabolites can be tested for bioactivity against various types of cancer and fungal, bacterial, and viral infections. In this thesis, we investigated the combination of biosynthetic gene cluster information with mass spectra to perform a chemical profiling of sediment- associated bacteria. Furthermore, we utilized a scoring technique to provide an identification and confidence score to each annotated compound. The sediment was collected from east Arthur Harbor, Palmer Station, Antarctica, at depths of 20 ft and 60 ft. After plating on agar, 52 unique bacterial strains were isolated, with the major phyla being Actinobacteria, Firmicutes, and Proteobacteria. Using NCBI BLAST we investigated the full genomes of neighboring taxa and look for biosynthetic gene clusters, which produce secondary metabolites of interest. These biosynthetic gene clusters, coming from the DNA sequences, through a metabolic pathway produce complex secondary metabolites of pharmaceutical value. These molecules can then be analyzed through mass spectral data, collected from the LC-MS QToF. This coupling allows us to use mass spectrometry with genomic information to annotate putative secondary metabolites provided by the biosynthetic gene clusters. After collecting the mass spectra for a subset of five isolates, each metabolite was annotated by its BGC and look at the fragmentation pattern in the data. To assist us with this, we utilized a scoring technique that awarded points to each compound based on the precursor ion and MS2 fragment ions. After totaling the points for each metabolite, the confidence scores ranged from fair, good, and strong. Applying this technique asserted a level of confidence behind each annotation of the parent ion and mass fragment ions. The three bacteria analyzed here were Streptomyces libani, Bacillus inaquosorum, and Sporosarcina globispora. Each strain was grown in tryptic soy broth and marine tryptic soy broth (at 3.5% salinity), centrifuged to separate the supernatant and cells, then prepared for mass spectrometry analysis. The metabolites that were annotated and given a confidence score between good and strong were streptomycin, antipain, caniferolide A, caniferolide B, caniferolide D, muraymycin C1, aurantinin B, and petrobactin. The analysis, including the mass error and mass resolution, for each molecule and their fragmentation patterns is provided.

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