bioRxiv Science⌕ Search

bioRxiv · 10.64898/2026.04.09.712135

Mobile element-mediated carbapenem resistance in Enterobacter hormaechei in a Nigerian intensive care unit

Abstract

Carbapenem-resistant Gram-negative bacteria pose a critical public health threat. The role of mobile genetic elements in driving their transmission and persistence remains poorly defined. In 2022, we investigated a suspected outbreak of carbapenem-resistant Acinetobacter baumannii (CRAB) in a Nigerian adult intensive care unit (ICU), using short-read whole genome sequencing (WGS) of carbapenem-resistant clinical and environmental isolates during the cluster period. Mobile element dynamics were then inferred from hybrid assemblies of Illumina and Oxford Nanopore reads. The suspected CRAB outbreak was ruled out by WGS but a carbapenem-resistant Enterobacter hormaechei ST114 bloodstream isolate was found to be indistinguishable from two environmental isolates, all recovered during the Acinetobacter surge. Hybrid assemblies revealed a strikingly conserved [~]19 Kb resistance island shared across all ST114 genomes. The island contained a blaNDM-5 cassette alongside many other antimicrobial resistance genes, within class 1 integronns and flanked by insertions sequences, located on a 46,176 bp plasmid. Using the ST114 plasmids hybrid assembly as scaffold, the same plasmid was identified in the genome of a Klebsiella pneumoniae ST15 isolate from the ICU environment during the same period. Additionally, re-interrogation of genomic surveillance data uncovered four clonal 2020 ST109 Enterobacter bloodstream isolates from the same facility that carried the resistance genes in the same context on a large 267,242 bp plasmid. Carbapenem resistance in hospital Enterobacterales is driven by both clonal expansion and horizontal spread of mobile resistance elements. These findings underscore the need to track mobile elements alongside bacterial lineages to inform evidence-based infection control, especially in low-resource settings. Impact StatementCarbapenem resistance among Enterobacterales remains a major public health threat, yet how mobile genetic elements contribute to their persistence and spread in hospital settings is still poorly understood. In this study, we investigated a suspected outbreak of carbapenem-resistant Acinetobacter baumannii in an adult intensive care unit in Nigeria. Although the outbreak was eventually ruled out, genomic analysis has shown the importance of careful interpretation of suspected outbreak cases in hospital settings. Our findings highlight the importance of close monitoring of ICU environments, the implementation of blood culture-based diagnostics, and the value of genomic support in outbreak investigations. These findings demonstrate that carbapenem resistance in hospital Enterobacterales is driven not only by clonal expansion but also by the horizontal dissemination of a highly stable blaNDM-5-associated MDR island capable of integrating into diverse plasmid backbones. This study emphasizes the need for genomic surveillance that tracks both mobile elements and bacterial lineages to strengthen outbreak investigations, especially in low-resource settings. It further underscores the links between clinical and environmental AMR reservoirs and reinforces the value of a One Health approach to controlling carbapenem resistance. Data summaryFASTQ sequences were deposited in the NCBI BioSample database under accession numbers SAMN55915584 - SAMN55915597.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Mba, I. E., Odih, E. E., Adekanmbi, O., Oaikhena, A. O., Sunmonu, G. T., Adebiyi, I., Gbaja, A. T., Animashaun, O., Osadebamwen, P., Idowu, O., Aanensen, D. M., Okeke, I. N.. 2026-04-10. Mobile element-mediated carbapenem resistance in Enterobacter hormaechei in a Nigerian intensive care unit. https://doi.org/10.64898/2026.04.09.712135

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A population-scale landscape of the subgingival microbiome reveals divergent routes to periodontal dysbiosis

Periodontitis is an archetypical mucosal inflammatory disease in which microbiome dysbiosis at the tooth-epithelial interface interacts with host genetic and behavioral risk factors to drive immune-mediated tissue destruction. Although subgingival microbiome compositional shifts are thought to parallel disease severity, microbiome variation at the population-level and its relationship to periodontal clinical phenotypes and disease-modifying factors remain poorly defined. Here, we use unsupervised manifold learning to map the compositional landscape of the subgingival microbiome in 1,355 adults spanning periodontal health to severe periodontitis. We identified eight latent microbiome states organized along a branching continuum from eubiosis to dysbiosis. An intermediate microbial configuration marked ecological destabilization and bifurcation into two distinct periodontitis-associated dysbiotic trajectories, distinguished by links to gingival inflammation and smoking. Although the microbiome trajectories broadly tracked periodontal destruction, a minority of individuals showed discordant microbiome-clinical phenotypes, with some individuals with periodontitis retaining otherwise eubiotic microbiomes enriched for low-abundance pathobionts, while some cases of health or mild disease had highly dysbiotic communities, suggesting distinct host susceptibility. Together, these findings define a population-scale ecological landscape of the subgingival microbiome, reveal divergent trajectories to periodontal dysbiosis, and highlight heterogeneity in the relationship between microbial community structure and clinical disease expression.

microbiology↗

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗

Taxonomic and functional concordance between full-length ONT 16S and ONT shotgun metagenomics in the canine gut microbiome

Background: Full-length Oxford Nanopore Technologies (ONT) 16S rRNA sequencing provides a scalable view of microbial community composition and can support phylogeny-based functional prediction, but it is not equivalent to shotgun metagenomics. We asked which biological conclusions are preserved when the same canine fecal specimens are profiled by full-length ONT 16S and ONT whole-genome shotgun (WGS) sequencing, and how their agreement depends on analytical scale, reference representation and classifier. Methods: Ninety-seven fecal specimens from 51 dogs were profiled with both assays from the same DNA extract. Functional profiles predicted from NanoASV/NanoPredict with PICRUSt2 were compared with WGS-supported KEGG Ortholog (KO) profiles generated by Kadath. Taxonomy was benchmarked in a source-genome-matched RefSeq universe and in a host-specific DogMAG universe using minitax and Kraken2. Agreement was evaluated at whole-profile, feature-abundance, detection, between-sample structure and biological-inference scales. Age-associated transfer was assessed with dog-aware continuous mixed models, grouped signed-score analyses and paired/dog-blocked PERMANOVA. Results: Functional whole-profile concordance was high: median within-sample CLR Spearman correlations ranged from 0.781 to 0.860 across developmental strata, while between-sample functional structure remained significant by Mantel (rho=0.543) and Procrustes (r=0.693; both p=0.001). Feature-wise transfer was substantially weaker (median KO-wise CLR Spearman=0.318). Continuous age-associated KO slopes showed substantial cross-assay concordance (Spearman=0.727; signed-score Spearman=0.753; direction agreement=77.9%), although 1,290/5,258 eligible KOs retained significant assay-by-age interactions. Taxonomically, exact genus/species abundance agreement was much lower than agreement in between-sample ecological structure. Host-specific DogMAG improved species-level median Spearman from 0.261 to 0.656 for minitax SpeciesEstimate and from 0.181 to 0.512 for Kraken2. The classifier effect was independent of reference choice: under both RefSeq and DogMAG, minitax yielded stronger 16S-WGS concordance than Kraken2, with all eight prespecified RefSeq paired genus/species endpoints and all 10 DogMAG primary paired endpoints significant after BH correction. The same ordering extended to developmental inference, with DogMAG genus/species age-slope concordance of 0.795/0.799 for SpeciesEstimate versus 0.693/0.702 for Kraken2. Taxonomic Aitchison PERMANOVA detected age-associated structure in every assay/reference/classifier/rank combination, whereas age-by-assay interactions were consistently significant but small (R2 approximately 1.1 to 2.2%). Stricter NanoASV identity thresholds removed substantial 16S abundance without improving species-level agreement. Conclusions: The extent of cross-assay agreement depends on the level of analysis. Full-length ONT 16S preserves broad functional organization, ecological structure and much of the direction of age-associated change, but exact fine-rank composition, individual-feature abundance and effect magnitude remain assay dependent. Host-specific reference representation substantially narrows the taxonomic gap, and classifier choice exerts an additional independent effect: within the same matched reference set, minitax consistently yields stronger 16S-WGS concordance than Kraken2 across abundance, detection, ecological-distance and developmental-inference endpoints. Full-length ONT 16S is therefore well suited to broad ecological screening and hypothesis generation, whereas WGS remains preferable when conclusions depend on quantitative fine-rank composition, directly supported gene content or precise feature-level effect estimates.

microbiology↗