Incorporating 16S Gene Copy Number Information Improves Estimates of Microbial Diversity and Abundance

By Steven W. Kembel, Martin Wu, Jonathan A. Eisen, Jessica L. Green. PLoS Comput. Biol., 2012

497 citations recorded by the source corpus.

The abundance of different SSU rRNA (“16S”) gene sequences in environmental samples is widely used in studies of microbial ecology as a measure of microbial community structure and diversity. However, the genomic copy number of the 16S gene varies greatly – from one in many species to up to 15 in some bacteria and to hundreds in some microbial eukaryotes. As a result of this variation the relative abundance of 16S genes in environmental samples can be attributed both to variation in the relative abundance of different organisms, and to variation in genomic 16S copy number among those organisms. Despite this fact, many studies assume that the abundance of 16S gene sequences is a surrogate measure of the relative abundance of the organisms containing those sequences. Here we present a method that uses data on sequences and genomic copy number of 16S genes along with phylogenetic placement and ancestral state estimation to estimate organismal abundances from environmental DNA sequence data. We use theory and simulations to demonstrate that 16S genomic copy number can be accurately estimated from the short reads typically obtained from high-throughput environmental sequencing of the 16S gene, and that organismal abundances in microbial communities are more strongly correlated with estimated abundances obtained from our method than with gene abundances. We re-analyze several published empirical data sets and demonstrate that the use of gene abundance versus estimated organismal abundance can lead to different inferences about community diversity and structure and the identity of the dominant taxa in microbial communities. Our approach will allow microbial ecologists to make more accurate inferences about microbial diversity and abundance based on 16S sequence data.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/ae6df30a26d3b82bad8fe757041bc3a82219c701

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Citations in the corpus

Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences (2013, methodology): “…a common environment, including constituents of the human microbiome 18, 19 as well as extreme and contaminated environments 20, 21 Quantitative predictions also depend on accurate modeling of community member abundance, which can be affected by 16S copy-number variation 17 (Supplementary Results).”
rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development (2014, methodology): “Inferences based on relative abundance of 16S genes may therefore not be representative of true community structure (10).”
Do manure-borne or indigenous soil microorganisms influence the spread of antibiotic resistance genes in manured soil? (2017, background): “However, gene copies can vary widely in different bacteria from 1 to up to 15 (Kembel et al., 2012); while only limited number of active species may dominate under tense competition situation in soil.”
Estimation of 18S Gene Copy Number in Marine Eukaryotic Plankton Using a Next-Generation Sequencing Approach (2019, background): “Phylogeny-based approaches have been developed to estimate ribosomal gene copy numbers for prokaryotes (Kembel et al., 2012; Angly et al., 2014), however, accuracy of such estimation can be compromised for protists due to the limited number of genomes that have been sequenced.”