Contributed by Cory Schlesener, B.S.
Historically it has been difficult to categorize prokaryotes into taxonomic units. Advances made have utilized DNA sequence identity to profile organisms at a higher resolution. Older technologies based on genomic DNA hybridization, or sequence comparison of the 16s rDNA gene (PCR amplified), have greatly advanced our understanding of phylogeny, but have limitations in resolution or scope. While 16s comparison has at times been the go-to method, there are challenges to perform unbiased PCR targeting, and while 16s is a core gene it is only one part of a genomic skeleton. Along with ambiguities brought in with horizontal gene transfer, there is a wide array of genetic variation that exists, detailing the genetic relations between organisms. With modern whole genome sequencing, an expanded view of genetic identity can be applied at a broad scale. Scaling up to categorize many organisms requires more computational resources and efficient informatic strategies. Some recent large-scale analyses demonstrating new approaches to prokaryotic taxonomy, have been based on a combined scheme of average nucleotide identity (ANI) and alignment fraction (AF). This can utilize genes shared among the organisms compared, or k-mer sippets of genetic sequence, for identity comparison and alignment of orthologous regions of the genome. The studies referenced here utilize thresholds of 95-97% identity (ANI), with 60-65% alignment (AF) as criteria for species level grouping. While these thresholds cannot produce perfect cut offs every time, they provide robust standardized metrics to group organisms. These broader analyses have been able to group previously unidentified samples, separate out divergent groups (some previously hypothesized), and parse out edge cases of misfits that may belong to their own group. These advancing strategies help us make sense of a nebulous picture (ever incomplete) of genomic spaces that are complex and interwoven.
References:
Barco, R. A., G. M. Garrity, J. J. Scott, J. P. Amend, K. H. Nealson, and D. Emerson. “A genus definition for Bacteria and Archaea based on a standard genome relatedness index.” Mbio 11, no. 1 (2020).
https://dx.doi.org/10.1128%
Parks, Donovan H., Maria Chuvochina, Pierre-Alain Chaumeil, Christian Rinke, Aaron J. Mussig, and Philip Hugenholtz. “A complete domain-to-species taxonomy for Bacteria and Archaea.” Nature Biotechnology (2020): 1-8.
https://doi.org/10.1038/
https://doi.org/10.1038/
