Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies

Mykhaylo Usyk, Brandilyn A. Peters, Smruthi Karthikeyan, Daniel McDonald, Christopher C. Sollecito, Yoshiki Vazquez-Baeza, Justin P. Shaffer, Marc D. Gellman, Gregory A. Talavera, Martha L. Daviglus, Bharat Thyagarajan, Rob Knight, Qibin Qi, Robert Kaplan, Robert D. Burk

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades.

Original languageEnglish (US)
Article number100391
JournalCell Reports Methods
Volume3
Issue number1
DOIs
StatePublished - Jan 23 2023

Keywords

  • 16S rrna
  • CP: genetics
  • CP: microbiology
  • HCHS/SOL
  • ITS1
  • amplicon
  • epidemiology
  • fungi
  • harmonization
  • meta-analysis
  • metagenomic
  • shotgun

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Biochemistry, Genetics and Molecular Biology (miscellaneous)
  • Genetics
  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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