Solu Platform detects interhospital transmission of carbapenemase-producing plasmids: case study with Enterobacter hormaechei isolates

Abstract

We used the Solu Platform to analyze an outbreak of Enterobacter hormaechei at the Brisbane region in 2015. We focused on the plasmids, and their antimicrobial resistance genes, in the samples. Different hospitals in the region had E. hormaechei samples with large genetic distances, but we found the same carbanepenemase-producing plasmid from all of them. This suggests a spread of antimicrobial resistance via plasmids. These findings show that traditional genomic surveillance may miss plasmid-mediated transmission and the spread of antimicrobial resistance, if plasmid analysis is not a part of the surveillance.

Introduction

Healthcare-associated infections (HAIs) involving multidrug-resistant (MDR) bacteria are increasingly contributing to morbidity and mortality worldwide (1). Horizontal gene transfer (HGT) is a primary mechanism that spreads resistance to antimicrobials among pathogens. It enables the transfer of genetic material between strains and even species. Plasmid conjugation (a form of HGT) can spread antimicrobial resistance genes, which makes plasmids a significant threat to healthcare. (2)

In this study, we use the Solu Platform (SP) to investigate a 2015 outbreak of Enterobacter hormaechei at the Royal Brisbane & Women’s Hospital (RWBH) in Australia. We analyze the plasmids in the samples and show how the platform can be utilized to examine the ARGs associated with these plasmids. Furthermore, we demonstrate how SP can establish a connection between samples from RWBH and those collected from other hospitals in the same region, despite a great genetic distance between the samples.

Dataset

The dataset consists of 17 samples originally collected by Roberts and colleagues. They used multiple whole-genome sequencing (WGS) technologies in their study to investigate the E. hormaechei outbreak (3). During the outbreak, 10 samples (MS7884-MS7893) were collected from three different patients at various time-points. Following the outbreak detection, three samples (MS7923-MS7925) were obtained from another hospital (A) in the same region. Four additional samples (MS7926 & MS8077-MS8079) were collected from a third regional hospital (B). The authors also continued genomic surveillance after the outbreak, but that data is excluded from this study. The data has been deposited in European Nucleotide Archive (ENA) at EMBL-EBI, under accession number PRJNA383436. The table below provides a summary of the dataset.

Methods

We input the samples’ SRA accession numbers to SP (4). The platform automatically downloaded the raw reads of the samples, assembled them and executed variety of genomic characterization and phylogenetic analyses. For more details regarding the methodology of the platform, you can refer to our description of the methodology or our platform's pre-print.

Results

Outbreak related samples

SP correctly identified the ten outbreak samples as E. hormaechei of sequence type (ST) 90. It detected several ARGs from the samples, including the bla_IMP-4 gene, which confers resistance to carbapenem. SP also reconstructed the plasmids that the pathogens were harbouring based on the assembled contigs. It identified and reconstructed various plasmids for each outbreak sample, including an IncHI2 plasmid of size ~310kb.

We compared the locations of the ARGs with the reconstructed plasmids. We observed that for each sample, SP assigned the high-risk bla_IMP-4 gene to the IncHI2 plasmid, with the exception of sample MS7889. This sample contained the IncHI2 plasmid, but the bla_IMP-4 gene gene was not included in the plasmid. As these samples were genetically very close to each other, we expect that the plasmid was spreading clonally. These findings were also observed by Roberts.

Comparison to other regional samples

There had been several observations of carbapenemase-producing E. hormaechei in the region, which raised concerns about a possible regional outbreak. However, sequencing showed that the regional samples had a different ST and over 10,000 SNP distance from the outbreak samples.

Despite the absence of clonal transmission between the outbreak and regional samples, SP found a similar IncHI2 plasmid also from the regional samples. The IncHI2 plasmids from regional samples also had similar resistance profiles, including the bla_IMP-4 gene. This suggests a connection between the outbreak and regional samples.

To verify the similarity of the outbreak and regional samples' plasmids, we computed mash distances between them. The distances were low, with the greatest mash distance being only 0.0077 and the median distance being 0.003. This strongly suggests that antimicrobial resistance is spreading within the region via horizontally transferred plasmids.

Discussion

In this study, we found that clonal transmission analysis alone provides only a partial view of the outbreak. Traditional genomic surveillance focuses on the genetic relatedness of strains but may miss critical elements of resistance transmission mediated by plasmids. Our analysis using the Solu Platform revealed that despite large genetic distances between samples, similar IncHI2 plasmids carrying the bla_IMP-4 gene were present in all samples. This suggests that plasmid-mediated horizontal gene transfer plays a role in the spread of antimicrobial resistance.

Analysing the plasmids revealed connections between seemingly unrelated samples, underscoring the need for comprehensive genomic surveillance. This approach offers insights into resistance spread mechanisms, aiding in developing effective strategies against antimicrobial resistance in healthcare.

References

1. Evans D, Sundermann A, Griffith M, et al. Empirically derived sequence similarity thresholds to study the genomic epidemiology of plasmids shared among healthcare-associated bacterial pathogens. EBioMedicine. 2023;93:104681. doi:10.1016/j.ebiom.2023.104681
2. Lerminiaux NA, Cameron ADS. Horizontal transfer of antibiotic resistance genes in clinical environments. Can J Microbiol. 2019;65(1):34-44. doi:10.1139/cjm-2018-0275
3. Roberts LW, Harris PNA, Forde BM, et al. Integrating multiple genomic technologies to investigate an outbreak of carbapenemase-producing Enterobacter hormaechei. Nat Commun. 2020;11(1):466. Published 2020 Jan 24. doi:10.1038/s41467-019-14139-5
4. Moilanen TJ, Lehtinen J, Visuri K, Sihvonen S. Solu – a cloud platform for real-time genomic pathogen surveillance. bioRxiv 2024.05.30.596434. doi:10.1101/2024.05.30.596434

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