Evaluation of an Adapted Semi-Automated DNA Extraction for Human Salivary Shotgun Metagenomics

Biomolecules. 2023 Oct 11;13(10):1505. doi: 10.3390/biom13101505.

Abstract

Recent attention has highlighted the importance of oral microbiota in human health and disease, e.g., in Parkinson's disease, notably using shotgun metagenomics. One key aspect for efficient shotgun metagenomic analysis relies on optimal microbial sampling and DNA extraction, generally implementing commercial solutions developed to improve sample collection and preservation, and provide high DNA quality and quantity for downstream analysis. As metagenomic studies are today performed on a large number of samples, the next evolution to increase study throughput is with DNA extraction automation. In this study, we proposed a semi-automated DNA extraction protocol for human salivary samples collected with a commercial kit, and compared the outcomes with the DNA extraction recommended by the manufacturer. While similar DNA yields were observed between the protocols, our semi-automated DNA protocol generated significantly higher DNA fragment sizes. Moreover, we showed that the oral microbiome composition was equivalent between DNA extraction methods, even at the species level. This study demonstrates that our semi-automated protocol is suitable for shotgun metagenomic analysis, while allowing for improved sample treatment logistics with reduced technical variability and without compromising the structure of the oral microbiome.

Keywords: DNA extraction; automation; oral microbiome; shotgun metagenomics.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • DNA* / chemistry
  • DNA* / genetics
  • Humans
  • Metagenome
  • Microbiota* / genetics
  • RNA, Ribosomal, 16S / genetics
  • Sequence Analysis, DNA / methods

Substances

  • RNA, Ribosomal, 16S
  • DNA

Grants and funding

This research was funded, in part, by Aligning Science Across Parkinson’s (Grant number: ASAP-000420) through the Michael J. Fox Foundation for Parkinson’s Research (MJFF). For the purpose of open access, the author has applied a CC BY 4.0 public copyright license to all Author Accepted Manuscripts arising from this submission. E.M. is supported by a Royal Free Charity Fellowship. M.A. provided additional funding from the MetaGenoPolis grant ANR-11-DPBS-0001.