The allometry of cellular DNA and ribosomal gene content among microbes and its use for the assessment of microbiome community structure

Luis Gonzalez-de-Salceda, Ferran Garcia-Pichel

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: The determination of taxon-specific composition of microbiomes by combining high-throughput sequencing of ribosomal genes with phyloinformatic analyses has become routine in microbiology and allied sciences. Systematic biases to this approach based on the demonstrable variability of ribosomal operon copy number per genome were recognized early. The more recent realization that polyploidy is probably the norm, rather than the exception, among microbes from all domains of life, points to an even larger source bias. Results: We found that the number of 16S or 18S RNA genes per cell, a combined result of the number of RNA gene loci per genome and ploidy level, follows an allometric power law of cell volume with an exponent of 2/3 across 6 orders of magnitude in small subunit copy number per cell and 9 orders of magnitude in cell size. This stands in contrast to cell DNA content, which follows a power law with an exponent of ¾. Conclusion: In practical terms, that relationship allows for a single, simple correction for variations in both copy number per genome and ploidy level in ribosomal gene analyses of taxa-specific abundance. In biological terms, it points to the uniqueness of ribosomal gene content among microbial properties that scale with size. [MediaObject not available: see fulltext.]

Original languageEnglish (US)
Article number173
JournalMicrobiome
Volume9
Issue number1
DOIs
StatePublished - Dec 2021
Externally publishedYes

Keywords

  • Archaea
  • Bacteria
  • Fungi
  • Genomes
  • Microbiomes
  • Ploidy
  • Protists
  • Ribosomal genes

ASJC Scopus subject areas

  • Microbiology
  • Microbiology (medical)

Fingerprint

Dive into the research topics of 'The allometry of cellular DNA and ribosomal gene content among microbes and its use for the assessment of microbiome community structure'. Together they form a unique fingerprint.

Cite this