Merging Taxonomy with Ecological Population Prediction in a Case Study of Vibrionaceae

Abstract

ABSTRACT We synthesized population structure data from three studies that assessed the fine-scale distribution of Vibrionaceae among temporally and spatially distinct environmental categories in coastal seawater and animals. All studies used a dynamic model (AdaptML) to identify phylogenetically cohesive and ecologically distinct bacterial populations and their predicted habitats without relying on a predefined genetic cutoff or relationships to previously named species. Across the three studies, populations were highly overlapping, displaying similar phylogenetic characteristics (identity and diversity), and were predominantly congruent with taxonomic Vibrio species previously characterized as genotypic clusters by multilocus sequence analysis (MLSA). The environmental fidelity of these populations appears high, with 9 out of 12 reproducibly associating with the same predicted (micro)habitats when similar environmental categories were sampled. Overall, this meta-analysis provides information on the habitat predictability and structure of previously described species, demonstrating that MLSA-based taxonomy can, at least in some cases, serve to approximate ecologically cohesive populations.