Phylogenies of the 16S rRNA gene and its hypervariable regions lack concordance with core genome phylogenies

Abstract

Background The 16S rRNA gene is used extensively in bacterial phylogenetics, in species delineation, and now widely in microbiome studies. However, the gene suffers from intragenomic heterogeneity, and reports of recombination and an unreliable phylogenetic signal are accumulating. Here, we compare core gene phylogenies to phylogenies constructed using core gene concatenations to estimate the strength of signal for the 16S rRNA gene, its hypervariable regions, and all core genes at the intra- and inter-genus levels. Specifically, we perform four intra-genus analyses (Clostridium, n = 65; Legionella, n = 47; Staphylococcus, n = 36; and Campylobacter, n = 17) and one inter-genus analysis [41 core genera of the human gut microbiome (31 families, 17 orders, and 12 classes), n = 82]. Results At both taxonomic levels, the 16S rRNA gene was recombinant and subject to horizontal gene transfer. At the intra-genus level, the gene showed one of the lowest levels of concordance with the core genome phylogeny (50.7% average). Concordance for hypervariable regions was lower still, with entropy masking providing little to no benefit. A major factor influencing concordance was SNP count, which showed a positive logarithmic association. Using this relationship, we determined that 690 ± 110 SNPs were required for 80% concordance (average 16S rRNA gene SNP count was 254). We also found a wide range in 16S-23S-5S rRNA operon copy number among genomes (1–27). At the inter-genus level, concordance for the whole 16S rRNA gene was markedly higher (73.8% — 10th out of 49 loci); however, the most concordant hypervariable regions (V4, V3-V4, and V1-V2) ranked in the third quartile (62.5 to 60.0%). Conclusions Ramifications of a poor phylogenetic performance for the 16S rRNA gene are far reaching. For example, in addition to incorrect species/strain delineation and phylogenetic inference, it has the potential to confound community diversity metrics if phylogenetic information is incorporated — for example, with popular approaches such as Faith’s phylogenetic diversity and UniFrac. Our results highlight the problematic nature of these approaches and their use (along with entropy masking) is discouraged. Lastly, the wide range in 16S rRNA gene copy number among genomes also has a strong potential to confound diversity metrics.

Building a genome-based understanding of bacterial pH preferences

“…The ASVs with estimated pH preferences were matched to the annotated Genome Taxonomy Database (GTDB release 207, (42)), using vsearch (v2.21.1, ( 65)) to identify representative genomes. We acknowledge that the representative genome identified for any given ASV will not necessarily be an identical match to the genome of that taxon in situ as even bacterial taxa with identical 16S rRNA genes can have distinct genomes (66).…”

Isolation and Genomics of Futiania mangrovii gen. nov., sp. nov., a Rare and Metabolically Versatile Member in the Class Alphaproteobacteria

“…Like our observation in Alphaproteobacteria , the topological difference between the 16S rRNA gene phylogeny and the genome phylogeny has been widely documented in diverse taxa, for example, Intrasporangiaceae and Mycobacteriaceae from the phylum Actinomycetota ( 28 ), Pseudomonas ( 29 ), and Aeromonas ( 30 ) from the phylum Pseudomonadota as well as the class Negativicutes in the phylum Bacillota ( 31 ). Although the 16S rRNA gene is one of the most common phylogenetic markers, sometimes it does not provide enough resolution to determine the precise phylogenetic relationship at higher taxonomic ranks ( 32 ). Moreover, subtle nucleotide variations between multiple rRNA operons in one genome and possible horizontally transferred 16S rRNA genes may give rise to distorted phylogenetic placements ( 33 – 35 ).…”

Multi-factorial examination of amplicon sequencing workflows from sample preparation to bioinformatic analysis

“…This problem becomes compounded when attempting to use data at low taxonomic levels. The 16S rRNA gene is reported to have poor phylogenetic concordance and it is preferred to use whole genome sequences or multiple coding ribosomal gene sequences for species delineation instead (52). While the negative impacts of inaccurate workflows depend upon the downstream application, a small number of errors may still be correctly classified and result in the same conclusions.…”