Abstract:
As products of billions of years of evolution, secondary metabolites perform a
wide range of activities ensuring the survival of organisms in competitive envi-
ronments. These natural products synthesized by diverse living beings through-
out the tree of life have been a valuable resource for many industrial applica-
tions. Specifically, in pharmaceutical ventures, natural products are used pro-
foundly against cancer, pests and microorganisms. Peaked in the golden era
of antibiotics, drug discovery against infectious diseases was mainly centered
around natural products from fungi and bacteria. Consequently however, mi-
crobes have made impressive and frightening progress in gaining resistance
against antimicrobials fueled by their improper usage. Coupled with the stag-
nation in discovery rates of novel natural products, antimicrobial resistance has
become a destructive phenomenon damaging humanity financially and health-
wise. To fight off such resistant microbes, it is of paramount importance that we
find and produce novel secondary metabolites with antimicrobial features. With
the vast improvements in sequencing technologies and analysis algorithms, we
possess repositories swarming with “multiomics”-based data, ready to be mined.
Now, a crucial thing to do is to enable the prioritization of such data for the sub-
sequent processes in wet-lab applications.
In this thesis, I have built command line tools as well as web-based databases
and pipelines to I) detect genes conferring antibiotic resistance in order to find
promising biosynthetic gene clusters that might encode for novel antibiotics and
II) prioritize target genes for genetic manipulation that could be used to increase
the production of secondary metabolites.
Natural products,
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