The evolution of genome mining in microbes - a review

被引:463
作者
Ziemert, Nadine [1 ,2 ]
Alanjary, Mohammad [1 ,2 ]
Weber, Tilmann [3 ]
机构
[1] Univ Tubingen, Interfac Inst Microbiol & Infect Med Tubingen IMI, Microbiol & Biotechnol, Tubingen, Germany
[2] Partner Site Tubingen, German Ctr Infect Res DZIF, Tubingen, Germany
[3] Tech Univ Denmark, Novo Nordisk Fdn Ctr Biosustainabil, Horsholm, Denmark
关键词
BIOSYNTHETIC GENE CLUSTERS; NONRIBOSOMAL PEPTIDE SYNTHETASES; SECONDARY-METABOLITE BIOSYNTHESIS; NATURAL-PRODUCT DISCOVERY; IN-SILICO PREDICTION; STREPTOMYCES-COELICOLOR; POLYKETIDE SYNTHASE; ANTIBIOTIC-RESISTANCE; LASSO PEPTIDES; HETEROLOGOUS EXPRESSION;
D O I
10.1039/c6np00025h
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
The computational mining of genomes has become an important part in the discovery of novel natural products as drug leads. Thousands of bacterial genome sequences are publically available these days containing an even larger number and diversity of secondary metabolite gene clusters that await linkage to their encoded natural products. With the development of high-throughput sequencing methods and the wealth of DNA data available, a variety of genome mining methods and toots have been developed to guide discovery and characterisation of these compounds. This article reviews the development of these computational approaches during the last decade and shows how the revolution of next generation sequencing methods has led to an evolution of various genome mining approaches, techniques and toots. After a short introduction and brief overview of important milestones, this article will focus on the different approaches of mining genomes for secondary metabolites, from detecting biosynthetic genes to resistance based methods and "evo-mining" strategies including a short evaluation of the impact of the development of genome mining methods and tools on the field of natural products and microbial ecology.
引用
收藏
页码:988 / 1005
页数:18
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