Fachbereich Informatik - Aktuell

10/10/2018

Disputation Mohammad Alanjary

am Mittwoch, 10. Oktober 2018, um 13:00 Uhr in Raum N12, Morgenstelle 28


Mohammad Alanjary


Developing genome mining tools for the discovery of bioactive
secondary metabolites


Berichterstatter 1: Prof. Dr. Nadine Ziemert
Berichterstatter 2: Prof. Dr. Daniel Huson


The rise of Multi-resistant strains of previously treatable pathogenic microorganisms
brings about a public health crisis that threatens all nations. 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 adaptations have made for precisely tailored 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
started to highlight chemical potential that has been hidden from traditional approaches
even from taxa previously thought to have none. 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 untapped
genera, 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 screening via resistance and drug targets can serve as an orthogonal
cluster detection method. As genomic data continues to surmount automated tools will be
crucial to effectively leverage this resource and ensure the threat of antibiotic resistance is
controlled.

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