Mapping gene clusters within arrayed metagenomic libraries to expand the structural diversity of biomedically relevant natural products. Academic Article uri icon

Overview

abstract

  • Complex microbial ecosystems contain large reservoirs of unexplored biosynthetic diversity. Here we provide an experimental framework and data analysis tool to facilitate the targeted discovery of natural-product biosynthetic gene clusters from the environment. Multiplex sequencing of barcoded PCR amplicons is followed by sequence similarity directed data parsing to identify sequences bearing close resemblance to biosynthetically or biomedically interesting gene clusters. Amplicons are then mapped onto arrayed metagenomic libraries to guide the recovery of targeted gene clusters. When applied to adenylation- and ketosynthase-domain amplicons derived from saturating soil DNA libraries, our analysis pipeline led to the recovery of biosynthetic clusters predicted to encode for previously uncharacterized glycopeptide- and lipopeptide-like antibiotics; thiocoraline-, azinomycin-, and bleomycin-like antitumor agents; and a rapamycin-like immunosuppressant. The utility of the approach is demonstrated by using recovered eDNA sequences to generate glycopeptide derivatives. The experiments described here constitute a systematic interrogation of a soil metagenome for gene clusters capable of encoding naturally occurring derivatives of biomedically relevant natural products. Our results show that previously undetected biosynthetic gene clusters with potential biomedical relevance are very common in the environment. This general process should permit the routine screening of environmental samples for gene clusters capable of encoding the systematic expansion of the structural diversity seen in biomedically relevant families of natural products.

publication date

  • July 3, 2013

Research

keywords

  • Biological Products
  • Biosynthetic Pathways
  • Chromosome Mapping
  • Drug Discovery
  • Metagenome
  • Multigene Family
  • Soil Microbiology

Identity

PubMed Central ID

  • PMC3718090

Scopus Document Identifier

  • 84880370987

Digital Object Identifier (DOI)

  • 10.1073/pnas.1222159110

PubMed ID

  • 23824289

Additional Document Info

volume

  • 110

issue

  • 29