Background
Enterobacter cloacae complex (ECC) is a group of opportunistic, nosocomial bacteria that account for 5% of Australian hospital acquired infections. ECC is increasingly showing resistance to carbapenems, a last line treatment. Inconsistency and difficulties in species identification (using MALDI-TOF) may lead to hospital outbreaks going undetected, as confidence in species identification is reduced. Communication of results between laboratories, health staff and public health officials becomes complicated when inaccurate naming occurs. To address this, our study developed a genomic framework to assist confidence in species and strain allocation within ECC.
Methods
A total of 3593 Enterobacter genomes were obtained from public genome repositories (RefSeq/Genbank). A genomic framework was developed which utilised Whole Genome Sequencing (WGS), Split kmer analysis (SKA) and Mash distance to assess pairwise genomic relatedness between isolates. Species and subspecies groupings were assigned through stepwise distance thresholds of increasing similarity and supported through phylogenetic and pan-genome analyses. Following the determination of species boundaries, a comparison of multi-locus sequence type (MLST) and antimicrobial resistance (AMR) profiles was conducted.
Results
Species boundaries are clearly defined when a Mash threshold <=0.04 is applied and subspecies are differentiated at <=0.02. Enterobacter cloacae isolates were often found to belong in other species groups, a likely result of many species being collectively regarded as E. cloacae complex. MLST sequence types are unique within species groups, therefore MLST can be employed as a rapid tool to identify a species when WGS is not available. Antimicrobial resistance (AMR) genes are widespread across the Enterobacter spp. isolates analysed.
Discussion
There is good evidence to suggest many Enterobacter spp. in public genome repositories are misidentified. This may contribute to delays and complications in detecting hospital outbreaks, and inaccuracies when utilising public databases. MLST can be used diagnostically to determine species in Enterobacter. The diversity and prevalence of AMR genes across Enterobacter spp. isolates investigated is concerning. The genomic framework developed can be applied to any pathogen where the distinguishing features are not well defined or the reference database is contaminated.