Title: Marine microbial biodiscovery - using biological questions to uncover patterns in
microbial ’omics data
Abstract: Microbial drug discovery in the ’omics era relies on three key datasets,
biosynthetic, chemical and biological (activity). Yet, to integrate and interrogate
these large and complex datasets remains a challenge and results in the low-
throughput prioritization of only a few strains based on observed antibiotic activity.
Despite this wealth of genomic and metabolomic data, linking metabolites to the
BGC responsible for their production and to observed bioactivity is limited, slow
(manual) and challenging. Furthermore, our current discovery is reliant on existing
biosynthetic, chemical and antibiotic knowledge, thus overlooking unidentified
parent ions (metabolites) or hypothetical proteins (BGCs) which is the exact
chemical and biosynthetic space which should be prioritized to identify novel
antibiotics. Here, approaches to combine data sets consisting of bacterial
genomes (and their predicted BGCs), the chemical products of these same strains
and their bioactivity profiles will be discussed. Several datasets of Actinomycetota
genomes have been mined for BGCs and these strains cultured to generate
metabolite extracts for comparative metabolomics (high resolution tandem mass
spectrometry /molecular networking) and antibiotic screening (against a panel of
clinically relevant pathogens). Driven by biological questions, tools have been
developed to establish patterns across strains and learn relationships between
BGC, spectral features and bioactivity – here we will discuss experimental data
considerations and how ’omics information is informing biodiscovery.