A restriction enzyme reduced representation sequencing approach for low-cost, high-throughput metagenome profiling

PLoS One. 2020 Apr 3;15(4):e0219882. doi: 10.1371/journal.pone.0219882. eCollection 2020.

Abstract

Microbial community profiles have been associated with a variety of traits, including methane emissions in livestock. These profiles can be difficult and expensive to obtain for thousands of samples (e.g. for accurate association of microbial profiles with traits), therefore the objective of this work was to develop a low-cost, high-throughput approach to capture the diversity of the rumen microbiome. Restriction enzyme reduced representation sequencing (RE-RRS) using ApeKI or PstI, and two bioinformatic pipelines (reference-based and reference-free) were compared to bacterial 16S rRNA gene sequencing using repeated samples collected two weeks apart from 118 sheep that were phenotypically extreme (60 high and 58 low) for methane emitted per kg dry matter intake (n = 236). DNA was extracted from freeze-dried rumen samples using a phenol chloroform and bead-beating protocol prior to RE-RRS. The resulting sequences were used to investigate the repeatability of the rumen microbial community profiles, the effect of laboratory and analytical method, and the relationship with methane production. The results suggested that the best method was PstI RE-RRS analyzed with the reference-free approach, which accounted for 53.3±5.9% of reads, and had repeatabilities of 0.49±0.07 and 0.50±0.07 for the first two principal components (PC1 and PC2), phenotypic correlations with methane yield of 0.43±0.06 and 0.46±0.06 for PC1 and PC2, and explained 41±8% of the variation in methane yield. These results were significantly better than for bacterial 16S rRNA gene sequencing of the same samples (p<0.05) except for the correlation between PC2 and methane yield. A Sensitivity study suggested approximately 2000 samples could be sequenced in a single lane on an Illumina HiSeq 2500, meaning the current work using 118 samples/lane and future proposed 384 samples/lane are well within that threshold. With minor adaptations, our approach could be used to obtain microbial profiles from other metagenomic samples.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Bacteria / genetics
  • Female
  • Gastrointestinal Microbiome*
  • High-Throughput Nucleotide Sequencing / economics
  • High-Throughput Nucleotide Sequencing / methods*
  • Male
  • Metagenome
  • Metagenomics / economics
  • Metagenomics / methods*
  • Microbiota
  • RNA, Ribosomal, 16S / genetics
  • Rumen / microbiology*
  • Sheep / microbiology*

Substances

  • RNA, Ribosomal, 16S

Grants and funding

Financial support was provided by the AgResearch Curiosity fund (JCM), the MBIE funded Genomics for Production and Security in a Biological Economy (C10X1306) Programme (JCM), the Microbes to Predict Methane project funded by Global Research Alliance Global Partnerships in Livestock Emissions Research (SOW-AGR-GPLER-SP5; SJR), the Pastoral Greenhouse Gas Research Consortium (PGgRc.co.nz; SJR, JCM, PHJ) and New Zealand Agricultural Greenhouse Gas Research Centre. (NZAGRC.org.nz; SJR, JCM, PHJ). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript; however, they approved the publication.