Population structure of blaKPC-harbouring IncN plasmids at a New York City medical centre and evidence for multi-species horizontal transmission.

BACKGROUND: Carbapenem-resistant Enterobacterales (CRE) are highly concerning MDR pathogens. Horizontal transfer of broad-host-range IncN plasmids may contribute to the dissemination of the Klebsiella pneumoniae carbapenemase (KPC), spreading carbapenem resistance among unrelated bacteria. However, the population structure and genetic diversity of IncN plasmids has not been fully elucidated. OBJECTIVES: We reconstructed blaKPC-harbouring IncN plasmid genomes to characterize shared gene content, structural variability, and putative horizontal transfer within and across patients and diverse bacterial clones. METHODS: We performed short- and long-read sequencing and hybrid assembly on 45 CRE isolates with blaKPC-harbouring IncN plasmids. Eight serial isolates from two patients were included to assess intra-patient plasmid dynamics. Comparative genomic analysis was performed to assess structural and sequence similarity across plasmids. Within IncN sublineages defined by plasmid MLST and kmer-based clustering, phylogenetic analysis was used to identify closely related plasmids. RESULTS: Comparative analysis of IncN plasmid genomes revealed substantial heterogeneity including large rearrangements in serial patient plasmids and differences in structure and content across plasmid clusters. Within plasmid sublineages, core genome content and resistance gene regions were largely conserved. Closely related plasmids (≤1 SNP) were found in highly diverse isolates, including ten pST6 plasmids found in eight bacterial clones from three different species. CONCLUSIONS: Genomic analysis of blaKPC-harbouring IncN plasmids revealed the presence of several distinct sublineages as well as substantial host diversity within plasmid clusters suggestive of frequent mobilization. This study reveals complex plasmid dynamics within a single plasmid family, highlighting the challenge of tracking plasmid-mediated transmission of blaKPC in clinical settings.

Sub-inhibitory antibiotic treatment selects for enhanced metabolic efficiency.

Bacterial growth and metabolic rates are often closely related. However, under antibiotic selection, a paradox in this relationship arises: antibiotic efficacy decreases when bacteria are metabolically dormant, yet antibiotics select for resistant cells that grow fastest during treatment. That is, antibiotic selection counterintuitively favors bacteria with fast growth but slow metabolism. Despite this apparent contradiction, antibiotic resistant cells have historically been characterized primarily in the context of growth, whereas the extent of analogous changes in metabolism is comparatively unknown. Here, we observed that previously evolved antibiotic-resistant strains exhibited a unique relationship between growth and metabolism whereby nutrient utilization became more efficient, regardless of the growth rate. To better understand this unexpected phenomenon, we used a simplified model to simulate bacterial populations adapting to sub-inhibitory antibiotic selection through successive bottlenecking events. Simulations predicted that sub-inhibitory bactericidal antibiotic concentrations could select for enhanced metabolic efficiency, defined based on nutrient utilization: drug-adapted cells are able to achieve the same biomass while utilizing less substrate, even in the absence of treatment. Moreover, simulations predicted that restoring metabolic efficiency would re-sensitize resistant bacteria exhibiting metabolic-dependent resistance; we confirmed this result using adaptive laboratory evolutions of Escherichia coli under carbenicillin treatment. Overall, these results indicate that metabolic efficiency is under direct selective pressure during antibiotic treatment and that differences in evolutionary context may determine both the efficacy of different antibiotics and corresponding re-sensitization approaches.IMPORTANCEThe sustained emergence of antibiotic-resistant pathogens combined with the stalled drug discovery pipelines highlights the critical need to better understand the underlying evolution mechanisms of antibiotic resistance. To this end, bacterial growth and metabolic rates are often closely related, and resistant cells have historically been characterized exclusively in the context of growth. However, under antibiotic selection, antibiotics counterintuitively favor cells with fast growth, and slow metabolism. Through an integrated approach of mathematical modeling and experiments, this study thereby addresses the significant knowledge gap of whether antibiotic selection drives changes in metabolism that complement, and/or act independently, of antibiotic resistance phenotypes.

Tradeoff between lag time and growth rate drives the plasmid acquisition cost.

Conjugative plasmids drive genetic diversity and evolution in microbial populations. Despite their prevalence, plasmids can impose long-term fitness costs on their hosts, altering population structure, growth dynamics, and evolutionary outcomes. In addition to long-term fitness costs, acquiring a new plasmid introduces an immediate, short-term perturbation to the cell. However, due to the transient nature of this plasmid acquisition cost, a quantitative understanding of its physiological manifestations, overall magnitudes, and population-level implications, remains unclear. To address this, here we track growth of single colonies immediately following plasmid acquisition. We find that plasmid acquisition costs are primarily driven by changes in lag time, rather than growth rate, for nearly 60 conditions covering diverse plasmids, selection environments, and clinical strains/species. Surprisingly, for a costly plasmid, clones exhibiting longer lag times also achieve faster recovery growth rates, suggesting an evolutionary tradeoff. Modeling and experiments demonstrate that this tradeoff leads to counterintuitive ecological dynamics, whereby intermediate-cost plasmids outcompete both their low and high-cost counterparts. These results suggest that, unlike fitness costs, plasmid acquisition dynamics are not uniformly driven by minimizing growth disadvantages. Moreover, a lag/growth tradeoff has clear implications in predicting the ecological outcomes and intervention strategies of bacteria undergoing conjugation.