Harnessing regulatory networks in Actinobacteria for natural product discovery

IF 3.2 4区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Hannah E Augustijn, Anna M Roseboom, Marnix H Medema, Gilles P van Wezel
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引用次数: 0

Abstract

Microbes typically live in complex habitats where they need to rapidly adapt to continuously changing growth conditions. To do so, they produce an astonishing array of natural products with diverse structures and functions. Actinobacteria stand out for their prolific production of bioactive molecules, including antibiotics, anticancer agents, antifungals, and immunosuppressants. Attention has been directed especially towards the identification of the compounds they produce and the mining of the large diversity of biosynthetic gene clusters (BGCs) in their genomes. However, the current return on investment in random screening for bioactive compounds is low, while it is hard to predict which of the millions of BGCs should be prioritized. Moreover, many of the BGCs for yet undiscovered natural products are silent or cryptic under laboratory growth conditions. To identify ways to prioritize and activate these BGCs, knowledge regarding the way their expression is controlled is crucial. Intricate regulatory networks control global gene expression in Actinobacteria, governed by a staggering number of up to 1000 transcription factors per strain. This review highlights recent advances in experimental and computational methods for characterizing and predicting transcription factor binding sites and their applications to guide natural product discovery. We propose that regulation-guided genome mining approaches will open new avenues toward eliciting the expression of BGCs, as well as prioritizing subsets of BGCs for expression using synthetic biology approaches. One-Sentence Summary This review provides insights into advances in experimental and computational methods aimed at predicting transcription factor binding sites and their applications to guide natural product discovery.
利用放线菌的调控网络发现天然产品
微生物通常生活在复杂的生境中,需要迅速适应不断变化的生长条件。为此,它们会产生大量结构和功能各异的天然产物。放线菌因其大量生产生物活性分子(包括抗生素、抗癌剂、抗真菌剂和免疫抑制剂)而脱颖而出。人们尤其关注对它们产生的化合物的鉴定,以及对其基因组中大量生物合成基因簇(BGC)多样性的挖掘。然而,目前对生物活性化合物进行随机筛选的投资回报率很低,而且很难预测在数百万个 BGCs 中哪些应被优先考虑。此外,许多尚未发现的天然产物的 BGCs 在实验室生长条件下是沉默的或隐蔽的。要确定优先选择和激活这些 BGCs 的方法,了解它们的表达控制方式至关重要。放线菌中错综复杂的调控网络控制着全局基因表达,每个菌株由多达 1000 个转录因子组成,数量惊人。本综述重点介绍了表征和预测转录因子结合位点的实验和计算方法的最新进展,以及这些方法在指导天然产物发现方面的应用。我们建议,以调控为导向的基因组挖掘方法将为诱导 BGCs 的表达开辟新的途径,并利用合成生物学方法优先表达 BGCs 子集。一句话总结 本综述深入介绍了旨在预测转录因子结合位点的实验和计算方法的进展及其在指导天然产物发现方面的应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Industrial Microbiology & Biotechnology
Journal of Industrial Microbiology & Biotechnology 工程技术-生物工程与应用微生物
CiteScore
7.70
自引率
0.00%
发文量
25
审稿时长
3 months
期刊介绍: The Journal of Industrial Microbiology and Biotechnology is an international journal which publishes papers describing original research, short communications, and critical reviews in the fields of biotechnology, fermentation and cell culture, biocatalysis, environmental microbiology, natural products discovery and biosynthesis, marine natural products, metabolic engineering, genomics, bioinformatics, food microbiology, and other areas of applied microbiology
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