Abstract
BackgroundThe 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.ResultsWe 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.ConclusionIn 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.3nxsJdGTQ9H2opeBgDwtgJVideo
Highlights
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 sci‐ ences
Studies on marine protists intended to estimate biomass from 18S counts have shown that Ribosomal gene copy number per cell (Rc) correlated linearly with cell volume (Vc) [18] or cell length [19] when plotted on double log scales, indicating an Rc dependence on size
The fit instead revealed that Rc follows well (R2 = 0.86) a power function of Cell volume (Vc) with an exponent significantly lower than unity, and indistinguishable from 2/3 (0.66 ± 0.03; ± SE) across nine orders of magnitude in cell volume
Summary
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 sci‐ ences. Systematic biases to this approach based on the demonstrable variability of ribosomal operon copy number per genome were recognized early. The rRNA gene approach to microbiome analyses, either based on amplicon or metagenomic sequencing, relies on the tacit assumption that the counts of this marker gene translate into a robust measure or proxy for microbial abundance. Studies on marine protists intended to estimate biomass from 18S counts have shown that Rc correlated linearly with cell volume (Vc) [18] or cell length [19] when plotted on double log scales, indicating an Rc dependence on size
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