Biology subjects

Prater, A. G.

Publications and source records attributed to Prater, A. G..

3 recordsLinked to original sources

bioRxiv2020

Daptomycin resistance in Enterococcus faecium can be delayed by disruption of the LiaFSR stress response pathway

The LiaFSR signaling pathway plays a major role in mediating daptomycin (DAP) resistance for both Enterococcus faecalis and Enterococcus faecium. LiaFSR inhibition induces DAP hypersusceptibility but could also potentially delay the acquisition of DAP resistance in a combinatorial therapy of DAP with a LiaFSR inhibitor. To evaluate the potential efficacy of this approach, the adaptation to DAP by both E. faecalis and E. faecium lacking a functional LiaFSR were examined. Here, clinical isolates of E. faecium with liaR deletions were evolved to DAP resistance using in vitro experimental evolution. Genomic analysis of resistant populations was used to identify both the alleles and their relative frequencies in driving DAP resistance. Microscopic and biochemical analyses were then employed to investigate how those adaptive alleles contributed to DAP resistance. We found that deletion of liaR from the E. faecium genome significantly delayed the onset of DAP resistance. Unsurprisingly, resistance strategies emerged eventually. These alternative strategies were influenced by both environment and ancestral genome. The delay in the acquisition of DAP resistance when liaR was deleted supports the concept of developing a LiaFSR pathway inhibitor to prolong DAP efficacy against enterococci. The loss of a functional LiaFSR pathway reset the adaptive landscape and forced adaptation to progress in new ways that were slower in providing DAP tolerance. The observed adaptive trajectories were strongly influenced by both the environment and ancestral genome.

microbiology↗

bioRxiv2019

Environment Shapes the Accessible Daptomycin Resistance Mechanisms in Enterococcus faecium

Daptomycin binds to bacterial cell membranes and disrupts essential cell envelope processes leading to cell death. Bacteria respond to daptomycin by altering their cell envelopes to either decrease antibiotic binding to the membrane or by diverting binding away from vulnerable septal targets to remodeled anionic phospholipid membrane patches. In Enterococcus faecalis, daptomycin resistance is typically coordinated by the three-component cell-envelope-stress-response system, LiaFSR. Here, studying a clinical strain of multidrug-resistant Enterococcus faecium containing alleles associated with activation of the LiaFSR signaling pathway, we found that specific environments selected for different evolutionary trajectories leading to high-level daptomycin resistance. Planktonic environments favored pathways that increased cell surface charge via yvcRS upregulation of dltABCD and mprF, causing a reduction in daptomycin binding. Alternatively, environments favoring complex structured communities, including biofilms, evolved both diversion and repulsion strategies via divIVA and oatA mutations, respectively. Both environments subsequently converged on cardiolipin synthase (cls) mutations, suggesting the importance of membrane modification across strategies. Our findings indicate that E. faecium can evolve diverse evolutionary trajectories to daptomycin resistance that are shaped by the environment to produce a combination of resistance strategies. The accessibility of multiple and different biochemical pathways simultaneously suggests that the outcome of daptomycin exposure results in a polymorphic population of resistant phenotypes making E. faecium a recalcitrant pathogen.

evolutionary biology↗

bioRxiv2018

The essential role of hypermutation in rapid adaptation to antibiotic stress

A common outcome of antibiotic exposure in patients and in vitro is the evolution of a hypermutator phenotype that enables rapid adaptation by pathogens. While hypermutation is a robust mechanism for rapid adaptation, it requires trade-offs between the adaptive mutations and the more common \"hitchhiker\" mutations that accumulate from the increased mutation rate. Using quantitative experimental evolution, we examined the role of hypermutation in driving adaptation of Pseudomonas aeruginosa to colistin. Metagenomic deep sequencing revealed 2,657 mutations at > 5% frequency in 1,197 genes and 761 mutations in 29 end point isolates. By combining genomic information, phylogenetic analyses, and statistical tests, we showed that evolutionary trajectories leading to resistance could be reliably discerned. In addition to known alleles such as pmrB, hypermutation allowed identification of additional adaptive alleles with epistatic relationships. Although hypermutation provided a short-term fitness benefit, it was detrimental to overall fitness. Alarmingly, a small fraction of the colistin adapted population remained colistin susceptible and escaped hypermutation. In a clinical population, such cells could play a role in re-establishing infection upon withdrawal of colistin. We present here a framework for evaluating the complex evolutionary trajectories of hypermutators that applies to both current and emerging pathogen populations.\n\nImportance\n\nBacteria can increase mutation rates in response to stress as an evolutionary strategy to avoid extinction. However, the complex mutational landscape of hypermutators makes it difficult to distinguish truly adaptive mutations from hitchhikers that follow similar evolutionary trajectories. We provide a framework for evaluating the complex evolutionary trajectories of hypermutators that can be applied to both current and emerging pathogen populations. Using Pseudomonas aeruginosa evolving to colistin as a model system, we examine the essential role of hypermutation in the evolution of resistance. Additionally, our results highlight the presence of a subset of cells that survive and remain susceptible during colistin exposure which can serve as a reservoir for re-infection upon withdrawal of the drug in clinical infections. This study provides a broad understanding of hypermutation during adaptation and describes a series of analyses that will be useful in identifying adaptive mutations in well annotated and novel bacterial mutator populations.

evolutionary biology↗