UC San Diego

My dissertation project focuses on the bacterial genus Salinispora, a marine actinomycete and an important producer of diverse secondary metabolites including anticancer and antibiotic compounds. This genus is comprised of 3 named species (S. tropica, S. arenicola, and S. pacifica) that are closely related based on the highly conserved 16S rRNA gene. Multilocus sequence analyses (MLSA) of 5 housekeeping genes revealed a well-supported concatenated tree providing strong support for the delineation of the three species and the ancestral relationship of S. arenicola to the more recently diverged sister taxa S. tropica and S. pacifica. Recently, our laboratory obtained 119 draft Salinispora genomes, which provide an unprecedented opportunity for comparative genomic analysis. Genome analyses revealed that all 119 strains share 2362 single-copy genes. This represents the Salinispora core genome, which comprises on average 46% of the gene content of each strain. Calculation of the genome-wide Average Nucleotide Identity (gANI) and Alignment Fraction (AF) provided a new perspective of Salinispora diversity and suggested that the three currently named species would be better represented by at least five additional species. The presence/absence of predicted biosynthetic gene clusters also revealed clustering patterns that were congruent with the species phylogeny, indicating that secondary metabolism represents important functional traits that help delineate species in this lineage. The genome sequences are also being used to identify shared genes that have been duplicated or occur near or within biosynthetic gene clusters (BGCs). One hypothesis is that antibiotic-resistance genes have co-evolved with antibiotic biosynthesis as a self-protection mechanism. This new approach called Target-directed genome mining identified duplicated genes from the core genome that occur near or within biosynthetic gene clusters (BGC), with the hypothesis that the products of these genes are the targets of the compounds produced by the clusters. This new method was validated with the correlation of a candidate resistance gene (fabF/B) with the orphan BGC named as PKS44 that expressed the compound thiolactomycin. This new approach may open new avenues for the discovery of novel antibiotics.