Genome sequence-based species classification of Enterobacter cloacae complex: a study among clinical isolates.

ABSTRACT

Accurate species-level identification of Enterobacter cloacae complex (ECC) is crucial for related research. The classification of ECC is based on strain-to-strain phylogenetic congruence, as well as genomic features including average nucleotide identity (ANI) and digitalized DNA-DNA hybridization (dDDH). ANI and dDDH derived from whole-genome sequencing have emerged as a reliable metric for assessing genetic relatedness between genomes and are increasingly recognized as a standard for species delimitation. Up to now, there are two different classification methods for ECC. The first one categorizes E. hormaechei, a species within ECC, into five subspecies (E. hormaechei subsp. steigerwaltii, subsp. oharae, subsp. xiangfangensis, subsp. hoffmannii, and subsp. hormaechei). The second classifies E. hormaechei as three species E. hormaechei, "E. xiangfangensis," "E. hoffmanii." While the former is well-accepted in the academic area, the latter may have a greater ability to distinguish different species of ECC. To assess the suitability of these identification criteria for clinical ECC isolates, we conducted a comprehensive analysis involving phylogenetic analysis, ANI and dDDH value alignment, virulence gene identification, and capsule typing on 256 clinical ECC strains isolated from the bloodstream. Our findings indicated that the method of categorizing E. hormaechei into five subspecies has better correlation and consistency with the molecular characteristics of clinical ECC isolates, as evidenced by phylogenetic analysis, virulence genes, and capsule typing. Therefore, the subspecies-based classification method appears more suitable for taxonomic assignments of clinical ECC isolates. IMPORTANCE Standardizing taxonomy of the Enterobacter cloacae complex (ECC) is necessary for data integration across diverse studies. The study utilized whole-genome data to accurately identify 256 clinical ECC isolated from bloodstream infections using average nucleotide identity (ANI), digitalized DNA-DNA hybridization (dDDH), and phylogenetic analysis. Through comprehensive assessments including phylogenetic analysis, ANI and dDDH comparisons, virulence gene, and capsule typing of the 256 clinical isolates, it was concluded that the classification method based on subspecies exhibited better correlation and consistency with the molecular characteristics of clinical ECC isolates. In summary, this research contributes to the precise identification of clinical ECC at the species level and expands our understanding of ECC.