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Anti-Infective Agents

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ISSN (Print): 2211-3525
ISSN (Online): 2211-3533

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Review Article

Prospects for New Antibiotics Discovered through Genome Analysis

Author(s): Arun Kumar Singh, Rishabha Malviya* and Rishav Sharma

Volume 21, Issue 5, 2023

Published on: 29 August, 2023

Article ID: e170723218816 Pages: 11

DOI: 10.2174/2211352521666230717164854

Price: $65

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Abstract

Antibiotic-resistant illnesses are on the rise worldwide, and the pipeline for developing new antibiotics is drying up. As a result, researchers need to create novel compounds with antimicrobial action. Recent decades have seen a dearth of novel antibiotics because of the reliance on conventional empirical screening procedures using both natural and synthetic chemicals to find them. There is hope that the massive amount of bacterial genome sequence data that has become accessible since the sequencing of the first bacterial genome more than 20 years ago might help lead to the development of new antibiotic drugs. Genes with significant levels of conservation both within and between bacterial species can be found using comparative genomic techniques; these genes may be involved in essential bacterial functions. Bioactive chemicals found in natural products have been successfully used in treating everything from infectious diseases to cancer, but over the past 20-30 years, the effectiveness of screening methods based on fermentation has decreased. Researchers urgently need answers to the unmet demand for bacterial infection resistance. Now more than ever, with the advent of cheap, highthroughput genomic sequencing technology, natural product discovery can be revitalized. Using bioinformatics, investigators may foretell whether or not a certain microbial strain would generate compounds with novel chemical structures, which may have novel modes of action in inhibiting bacterial growth. This manuscript describes how this potential might be utilised, with a particular emphasis on manipulating the expression of dormant biosynthetic gene clusters that are hypothesised to encode new antibiotics. Additionally, it consolidates the work of the past and the present to utilise bacterial genomic data in the identification and development of new antibiotics.

Graphical Abstract

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