Identification of PKS Gene Clusters from Metagenomic Libraries Using a Next-Generation Sequencing Approach

基因组 计算生物学 生物 福斯密德 聚酮合酶 霰弹枪测序 聚酮 鉴定(生物学) DNA测序 异源表达 基因 遗传学 生态学 重组DNA 生物合成
作者
Alinne L. R. Santana-Pereira
出处
期刊:Methods in molecular biology 卷期号:: 73-90 被引量:1
标识
DOI:10.1007/978-1-0716-2795-2_5
摘要

Microbial secondary metabolites have been an important source of bioactive compounds with diverse applications from medicine to agriculture, noticeably those encoded by polyketide synthase (PKS) clusters due to their astounding chemical diversity. While most discovered compounds originate from culturable microorganisms, yet-to-be cultured microbes represent a reservoir of previously inaccessible compounds. The advent and development of metagenomics have allowed not only the characterization of these microorganisms but also their metabolic potential, making viable the prospection of environmental PKS for natural product discovery.Study of environmental PKSs often relies on the construction of metagenomic libraries and their mining, with clones containing PKS clusters identified via amplification of conserved domains and then screened for an activity of interest. Compounds produced by clones exhibiting the desired bioactivity can be isolated and characterized. However, these approaches can be less sensitive and biased against more divergent clusters, in addition to precluding the use of bioinformatics for cluster characterization prior to expression. While direct shotgun sequencing of metagenomes has identified and profiled a great number of PKSs from different environments and yet-to-be cultured microorganisms, it does not lend itself well to heterologous expression, the cruxes of natural product discovery.Here, we describe a strategy for sequencing entire metagenomic libraries while maintaining correspondence between sequence and clone, allowing the full characterization and annotation of all clusters present in a library using bioinformatic tools and then seamlessly passing clones of interest for activity screening through heterologous expression. Once a library is sequenced, the methods herein can be adapted for the mining of any biosynthetic gene cluster of interest within a metagenomic library.
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