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Bartell, J. A.

Publications and source records attributed to Bartell, J. A..

3 recordsLinked to original sources

The high persister phenotype of Pseudomonas aeruginosa is associated with increased fitness and persistence in cystic fibrosis airways

Despite intensive antibiotic treatment of cystic fibrosis (CF) patients, Pseudomonas aeruginosa often persists in patient airways for decades, and can do so without the development of antibiotic resistance. Using a high-throughput screening assay of survival after treatment with high concentrations of ciprofloxacin, we have determined the prevalence of high-persister variants (Hip) in a large patient cohort. In a screen of 467 longitudinal clinical isolates of P. aeruginosa from 40 CF patients, we classified 25.7% as Hip. Hip were identified in 26 patients, but only a few bacterial lineages were dominated by Hip. Instead, the emergence of Hip increased over time, suggesting that CF airways treated with ciprofloxacin select for Hip with an increased fitness in this environment. We generally observed diverse genetic changes in the Hip isolate population (as many co-occurring routes to increased fitness exist), but interestingly elevated mutation counts in the RpoN gene of 18 Hip isolates suggest that this sigma factor plays a role in shaping levels of antibiotic tolerance. To probe the impact of the Hip phenotype in a CF-similar environment, we tested the fitness properties of otherwise genotypically and phenotypically similar low-persister (Lop) and Hip isolates in co-culture using a specialized flow-cell biofilm system mimicking pharmacokinetic/-dynamic antibiotic dosing. Hip survived ciprofloxacin treatment far better than Lop isolates. The results of this investigation provide novel insights into persister dynamics and fitness contributions to survival in the CF lung, and show that the Hip phenotype of antibiotic susceptible bacteria plays an important role in long-term infections. SignificanceAntibiotic resistance is emphasized as a rapidly increasing health threat, but antibiotic tolerance via the occurrence of persister cells in antibiotic-treated bacterial populations is clinically and publicly neglected. In 40 CF patients representing a well-established human infection model - long-term lung infections by Pseudomonas aeruginosa - we show the emergence and accumulation of persister variants in a clinical population heavily reliant on antibiotic therapy. We observe that the high-persister (Hip) phenotype is independent of resistance and likely the consequence of numerous genetic alterations, complicating surveillance and inhibition in the clinic. Furthermore, we find Hip are selected for over time, survive better than normal bacteria, and can outcompete them in CF-similar conditions, ultimately affecting 65% of patients in an early disease cohort.

microbiology↗

Memote: A community-driven effort towards a standardized genome-scale metabolic model test suite

Several studies have shown that neither the formal representation nor the functional requirements of genome-scale metabolic models (GEMs) are precisely defined. Without a consistent standard, comparability, reproducibility, and interoperability of models across groups and software tools cannot be guaranteed.\n\nHere, we present memote (https://github.com/opencobra/memote) an open-source software containing a community-maintained, standardized set of metabolic model tests. The tests cover a range of aspects from annotations to conceptual integrity and can be extended to include experimental datasets for automatic model validation. In addition to testing a model once, memote can be configured to do so automatically, i.e., while building a GEM. A comprehensive report displays the models performance parameters, which supports informed model development and facilitates error detection.\n\nMemote provides a measure for model quality that is consistent across reconstruction platforms and analysis software and simplifies collaboration within the community by establishing workflows for publicly hosted and version controlled models.

systems biology↗

Evolutionary highways to persistent infection by Pseudomonas aeruginosa

Persistent infections require bacteria to evolve from their naive colonization state by optimizing fitness in the host. This optimization involves coordinated adaptation of multiple traits, obscuring evolutionary trends and complicating infection management. Accordingly, we screen 8 infection-relevant phenotypes of 443 longitudinal Pseudomonas aeruginosa isolates from 39 young cystic fibrosis patients over 10 years. Using statistical modeling, we map evolutionary trajectories and identify trait correlations accounting for patient-specific influences. By integrating previous genetic analyses of 474 isolates, we provide a window into early adaptation to the host, finding: 1) a 2-3 year timeline of rapid adaptation after colonization, 2) variant \"naive\" and \"adapted\" states reflecting discordance between phenotypic and genetic adaptation, 3) adaptive trajectories leading to persistent infection via 3 distinct evolutionary modes, and 4) new associations between phenotypes and pathoadaptive mutations. Ultimately, we effectively deconvolute complex trait adaptation, offering a framework for evolutionary studies and precision medicine in clinical microbiology.

evolutionary biology↗