Bioinformatic Genome Comparisons for Taxonomic and Phylogenetic Assignments Using Aeromonas as a Test Case

Prokaryotic taxonomy is the underpinning of microbiology, as it provides a framework for the proper identification and naming of organisms. The "gold standard" of bacterial species delineation is the overall genome similarity determined by DNA-DNA hybridization (DDH), a technically rigorous yet sometimes variable method that may produce inconsistent results. Improvements in next-generation sequencing have resulted in an upsurge of bacterial genome sequences and bioinformatic tools that compare genomic data, such as average nucleotide identity (ANI), correlation of tetranucleotide frequencies, and the genome-to-genome distance calculator, or in silico DDH (isDDH). Here, we evaluate ANI and isDDH in combination with phylogenetic studies using Aeromonas, a taxonomically challenging genus with many described species and several strains that were reassigned to different species as a test case. We generated improved, high-quality draft genome sequences for 33 Aeromonas strains and combined them with 23 publicly available genomes. ANI and isDDH distances were determined and compared to phylogenies from multilocus sequence analysis of housekeeping genes, ribosomal proteins, and expanded core genes. The expanded core phylogenetic analysis suggested relationships between distant Aeromonas clades that were inconsistent with studies using fewer genes. ANI values of >= 96% and isDDH values of >= 70% consistently grouped genomes originating from strains of the same species together. Our study confirmed known misidentifications, validated the recent revisions in the nomenclature, and revealed that a number of genomes deposited in GenBank are misnamed. In addition, two strains were identified that may represent novel Aeromonas species. IMPORTANCE Improvements in DNA sequencing technologies have resulted in the ability to generate large numbers of high-quality draft genomes and led to a dramatic increase in the number of publically available genomes. This has allowed researchers to characterize microorganisms using genome data. Advantages of genome sequence-based classification include data and computing programs that can be readily shared, facilitating the standardization of taxonomic methodology and resolving conflicting identifications by providing greater uniformity in an overall analysis. Using Aeromonas as a test case, we compared and validated different approaches. Based on our analyses, we recommend cutoff values for distance measures for identifying species. Accurate species classification is critical not only to obviate the perpetuation of errors in public databases but also to ensure the validity of inferences made on the relationships among species within a genus and proper identification in clinical and veterinary diagnostic laboratories.