Use of Substrate-Induced Gene Expression in Metagenomic Analysis of an Aromatic Hydrocarbon-Contaminated Soil

Author:

Meier Matthew J.1,Paterson E. Suzanne1,Lambert Iain B.1

Affiliation:

1. Department of Biology, Carleton University, Ottawa, Ontario, Canada

Abstract

ABSTRACT Metagenomics allows the study of genes related to xenobiotic degradation in a culture-independent manner, but many of these studies are limited by the lack of genomic context for metagenomic sequences. This study combined a phenotypic screen known as substrate-induced gene expression (SIGEX) with whole-metagenome shotgun sequencing. SIGEX is a high-throughput promoter-trap method that relies on transcriptional activation of a green fluorescent protein (GFP) reporter gene in response to an inducing compound and subsequent fluorescence-activated cell sorting to isolate individual inducible clones from a metagenomic DNA library. We describe a SIGEX procedure with improved library construction from fragmented metagenomic DNA and improved flow cytometry sorting procedures. We used SIGEX to interrogate an aromatic hydrocarbon (AH)-contaminated soil metagenome. The recovered clones contained sequences with various degrees of similarity to genes (or partial genes) involved in aromatic metabolism, for example, nahG (salicylate oxygenase) family genes and their respective upstream nahR regulators. To obtain a broader context for the recovered fragments, clones were mapped to contigs derived from de novo assembly of shotgun-sequenced metagenomic DNA which, in most cases, contained complete operons involved in aromatic metabolism, providing greater insight into the origin of the metagenomic fragments. A comparable set of contigs was generated using a significantly less computationally intensive procedure in which assembly of shotgun-sequenced metagenomic DNA was directed by the SIGEX-recovered sequences. This methodology may have broad applicability in identifying biologically relevant subsets of metagenomes (including both novel and known sequences) that can be targeted computationally by in silico assembly and prediction tools.

Funder

Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada

Publisher

American Society for Microbiology

Subject

Ecology,Applied Microbiology and Biotechnology,Food Science,Biotechnology

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