Mycobacteriales taxonomy using network analysis-aided, context-uniform phylogenomic approach for non-subjective genus demarcation

Abstract

Genomics allows accurately pinpointing microbial ancestry for taxonomic purposes, yet there is currently no consensus to genus definition based on genome data. Different metrics and criteria are used, with an increasing trend toward genera over-splitting. Here, we report a method for prokaryotic genus assignment that combines normalized tree clustering and network analysis of several genomic relatedness indices. Objectivity is maximized by linear application of the same partitioning thresholds across an entire middle/high taxonomic rank context (order level), with the classical (“pre-genomic”) genera as demarcation reference, ensuring continuity in taxonomy and nomenclature. We tested the method with the Mycobacteriales, where recent examples of genus fragmentation divided Mycobacterium into five genera, or made Rhodococcus paraphyletic by creating the genus Prescottella for the sublineage containing the animal and human pathogen, Rhodococcus equi. Our approach did not support the mycobacterial five-genus split or the Prescottella nested genus, but identified a basal branch in each of the mycobacterial and rhodococcal radiations warranting genus status (Mycobacteroides, and novel genus Rhodococcoides for the Rhodococcus fascians clade, respectively). The median average amino acid identity (AAI) between the demarcated genera was 56% to 59%, consistent with the <65% AAI genus boundary standard. Shifting the demarcation threshold to the Prescottella/mycobacterial five-genus level systematically elevated the intrageneric sublineages to genus rank, leading to taxonomic atomization (≈threefold increase in potential Mycobacteriales genera). The proposed approach provides a standardizable methodological framework for non-subjective prokaryotic genus delineation.