Developing genome mining tools for the discovery of bioactive secondary metabolites

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Dokumentart: Dissertation
Date: 2018-10-25
Language: English
Faculty: 7 Mathematisch-Naturwissenschaftliche Fakultät
Department: Informatik
Advisor: Ziemert, Nadine (Prof. Dr.)
Day of Oral Examination: 2018-10-10
DDC Classifikation: 004 - Data processing and computer science
500 - Natural sciences and mathematics
Keywords: Genom , Antibiotikum
Other Keywords:
Genome mining
Natural products
antibiotic resistance
License: Publishing license including print on demand
Order a printed copy: Print-on-Demand
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With the rise of Multi-resistant strains of previously treatable pathogenic microorganisms, some of which immune to all known antibiotics, we face a public health crisis that threatens the lives of anyone prone to infection. This challenge needs to be faced on many fronts and an important step to finding a solution is to replenish our antibiotic arsenals with new drugs that evade current antibiotic resistance strategies. The majority of these compounds have traditionally been sourced from, or inspired by, natural products – compounds produced by living things. This continues to be a valuable resource as the millennia of development through natural selection has made for precisely adapted molecules with desired antibiotic properties. Unfortunately natural products research has experienced stagnation due to high rates of rediscovery and low returns on research investment. Fortunately the widespread use of cheap sequencing technologies, influx of complete whole genomes, and tools used to process them have simultaneously been on the rise. These “genome mining” tools have only begun to highlight chemical potential that has been hidden from traditional approaches from a diverse set of genera. As the detection of various classes of Biosynthetic Gene Clusters (BGCs), areas of the genome responsible for production of these compounds, has matured there are now more leads generated than can be experimentally verified. The problem now is to prioritize these leads for those that have the highest potential for downstream experiments. Common prioritization schemes include: using comparative genomics to highlight unique or shared BGCs, focusing on novel genera besides the traditional prolific producing organisms, and highlighting BGCs that imply antibiotic activity via antibiotic resistance determinates. This research is focused on providing automated and accessible tools to preform these analyses in high-throughput. In addition to the prioritization and de-replication of potential BGCs, applications to enrich for novel leads via resistance determinant and target screening are also presented. As the number of genomes from different taxa begins to rise, shifting from a single genome analysis to a comparative pan-genome approach also shows promise to reinvigorate natural products research. The tools in this research that leverage these approaches will be continually maintained on free public servers for the furthered research and discovery of new antibiotic and anti-infective compounds to ensure the threat of antibiotic resistance is controlled.

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