Intragenomic heterogeneity of 16S rRNA genes causes overestimation of prokaryotic diversity

Abstract

Ever since Carl Woese introduced the use of 16S rRNA genes for determining the phylogenetic relationships of prokaryotes, this method has been regarded as the "gold standard" in both microbial phylogeny and ecology studies. However, intragenomic heterogeneity within 16S rRNA genes has been reported in many investigations and is believed to bias the estimation of prokaryotic diversity. In the current study, 2,013 completely sequenced genomes of bacteria and archaea were analyzed and intragenomic heterogeneity was found in 952 genomes (585 species), with 87.5% of the divergence detected being below the 1% level. In particular, some extremophiles (thermophiles and halophiles) were found to harbor highly divergent 16S rRNA genes. Overestimation caused by 16S rRNA gene intragenomic heterogeneity was evaluated at different levels using the full-length and partial 16S rRNA genes usually chosen as targets for pyrosequencing. The result indicates that, at the unique level, full-length 16S rRNA genes can produce an overestimation of as much as 123.7%, while at the 3% level, an overestimation of 12.9% for the V6 region may be introduced. Further analysis showed that intragenomic heterogeneity tends to concentrate in specific positions, with the V1 and V6 regions suffering the most intragenomic heterogeneity and the V4 and V5 regions suffering the least intragenomic heterogeneity in bacteria. This is the most up-to-date overview of the diversity of 16S rRNA genes within prokaryotic genomes. It not only provides general guidance on how much overestimation can be introduced when applying 16S rRNA gene-based methods, due to its intragenomic heterogeneity, but also recommends that, for bacteria, this overestimation be minimized using primers targeting the V4 and V5 regions.

Fig 1

Distribution of different 16S rRNA gene copy numbers among bacteria and archaea.

Fig 2

Average copy number for each phylum. Numbers in parentheses indicate the total number of species in the phylum.

Fig 3

Rarefaction curve indicating the overestimation caused by 16S rRNA gene intragenomic heterogeneity at the unique (A) and 0.03 (B) dissimilarity levels. Results for levels of dissimilarity of 0.05 and 0.10 are not shown because the relatively small amount of overestimation was hard to distinguish on a rarefaction curve. Solid lines, intragenomic heterogeneity was considered; dashed lines, intragenomic heterogeneity was ruled out. To better display the results, error bars were not plotted.

Fig 4

Degree of overestimation at the 3% level for archaea and bacteria, focusing on full-length and different hypervariable regions. Some error bars are too small to be seen.

Fig 5

Degree of overestimation at the 3% level for dominant phyla, focusing on full-length and different hypervariable regions. Some error bars are too small to be seen.

Fig 6

Intergenomic and intragenomic variation of 16S rRNA genes for bacteria. The variation rate was measured as the Shannon information entropy (with positions referring to the numbering for E. coli) (A) and subsequently averaged by a 25-bp window (B). The mean intragenomic variation was calculated by averaging the information entropy at each position of all 1,882 bacterial genomes studied (C).

Fig 7

Intergenomic and intragenomic variation of 16S rRNA genes for archaea. The variation rate was measured as the Shannon information entropy (with positions referring to the numbering for Sulfolobus solfataricus) (A) and subsequently averaged by a 25-bp window (B). The mean intragenomic variation was calculated by averaging the information entropy at each position of all 129 archaeal genomes studied (C).