The Characterization of Novel Tissue Microbiota Using an Optimized 16S Metagenomic Sequencing Pipeline

PLoS One. 2015 Nov 6;10(11):e0142334. doi: 10.1371/journal.pone.0142334. eCollection 2015.

Abstract

Background: Substantial progress in high-throughput metagenomic sequencing methodologies has enabled the characterisation of bacteria from various origins (for example gut and skin). However, the recently-discovered bacterial microbiota present within animal internal tissues has remained unexplored due to technical difficulties associated with these challenging samples.

Results: We have optimized a specific 16S rDNA-targeted metagenomics sequencing (16S metabarcoding) pipeline based on the Illumina MiSeq technology for the analysis of bacterial DNA in human and animal tissues. This was successfully achieved in various mouse tissues despite the high abundance of eukaryotic DNA and PCR inhibitors in these samples. We extensively tested this pipeline on mock communities, negative controls, positive controls and tissues and demonstrated the presence of novel tissue specific bacterial DNA profiles in a variety of organs (including brain, muscle, adipose tissue, liver and heart).

Conclusion: The high throughput and excellent reproducibility of the method ensured exhaustive and precise coverage of the 16S rDNA bacterial variants present in mouse tissues. This optimized 16S metagenomic sequencing pipeline will allow the scientific community to catalogue the bacterial DNA profiles of different tissues and will provide a database to analyse host/bacterial interactions in relation to homeostasis and disease.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Structures / microbiology*
  • Animals
  • Computational Biology
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Metagenomics*
  • Mice
  • Mice, Inbred C57BL
  • Microbiota / genetics*
  • RNA, Ribosomal, 16S / genetics*
  • Sequence Analysis, DNA

Substances

  • RNA, Ribosomal, 16S

Grant support

This work was carried out with the financial support from the DAEI (Direction de l’Action Économique et de l’Innovation) of the Midi-Pyrénées Region, France. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Vaiomer SAS provided support in the form of salaries for authors [JL, FS, SP, CV, MC, BL], but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the “Author contributions” section.