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Pool, J.

Publications and source records attributed to Pool, J..

4 recordsLinked to original sources

Antibiotic tolerance due to filamentation shapes β-lactam pharmacodynamics in Escherichia coli

Pharmacodynamic curves describe how changes in drug concentration affect pathogen growth. They are essential for designing treatments that promote pathogen eradication and minimize the evolution of antibiotic resistance. The classical function for modelling pharmacodynamics is a phenomenological, S-shaped curve with stable growth and death rates separated by a single drop. In this study, we characterized the pharmacodynamic curve of the {beta}-lactam antibiotic cefotaxime (CTX) acting against Escherichia coli. We found that the relationship between CTX concentration and net growth rate diverged from classical model predictions, instead yielding a two-step curve defined by distinct phases of growth, population maintenance, and killing. We hypothesized that the intermediate phase arose from antibiotic tolerance conferred by bacterial filaments. Microscopic assessment of treated cells indeed showed a difference in degree of filamentation with concentration. We further sought to explain this with a semi-mechanistic pharmacodynamic function, modelling the binding of CTX to its cellular targets, penicillin binding proteins (PBP) 1 and 3. By incorporating the preferential concentration-dependent binding of CTX to PBP3 and then PBP1, yielding filaments or lysed cells respectively, we replicated the two-step curve in silico. We also assessed the pharmacodynamics of CTX against mutants conferring resistance; these displayed further altered curves, in line with their fitness costs. Altogether, our results show that CTX has a two-step pharmacodynamic curve against E. coli arising from multiple targets separated in their affinity for the antibiotic. We present a model offering a mechanistically grounded framework for capturing such dynamics. These pharmacodynamic curves deserve careful consideration when defining optimal dosing.

microbiology↗

Experimental evolution of collective β-lactam resistance in Escherichia coli via activation of a dormant outermembrane porin

Understanding the mechanisms that drive antibiotic resistance is relevant for both evolutionary theory and the design of effective drug therapies. A specific challenge are collective resistance mechanisms, where bacterial populations survive drug concentrations that kill individual bacteria. Here, we explore the evolvability of collective resistance mechanisms in bacterial strains expressing antibiotic-degrading {beta}-lactamases with different levels of privatization. Four strains of Escherichia coli, with or without outermembrane porin OmpF to affect drug permeability and expressing either a low or high-activity periplasmic {beta}-lactamase, were subjected to lineage selection in a gradient of the drug cefotaxime. Strains with a low-activity enzyme increased cell-level resistance, while strains with low permeability, and hence a more private {beta}-lactamase function, increased collective resistance. Remarkably, increased collective resistance in the strain with a private high-activity {beta}-lactamase came with decreased cell-level resistance. This tradeoff was primarily caused by the activation of a dormant outermembrane porin, NmpC, via the excision of an insertion sequence. Increased drug permeability through NmpC explained both its lower cell-level resistance and its greater collective resistance through faster drug removal and growth recovery via enhanced filamentation at high cell density. The recovery advantage of the NmpC mutant also explained its initial invasion within the ancestral population, suggesting that drug permeability is a readily evolvable collective-resistance mechanism in bacteria with high-activity {beta}-lactamases. Our findings highlight the role of filamentation and drug permeability in {beta}-lactamase-mediated collective resistance to these widely used drugs.

evolutionary biology↗

Broad geographic sampling reveals predictable and pervasive seasonal adaptation in Drosophila

To advance our understanding of adaptation to temporally varying selection pressures, we identified signatures of seasonal adaptation occurring in parallel among Drosophila melanogaster populations. Specifically, we estimated allele frequencies genome-wide from flies sampled early and late in the growing season from 20 widely dispersed populations. We identified parallel seasonal allele frequency shifts across North America and Europe, demonstrating that seasonal adaptation is a general phenomenon of temperate fly populations. Seasonally fluctuating polymorphisms are enriched in large chromosomal inversions and we find a broad concordance between seasonal and spatial allele frequency change. The direction of allele frequency change at seasonally variable polymorphisms can be predicted by weather conditions in the weeks prior to sampling, linking the environment and the genomic response to selection. Our results suggest that fluctuating selection is an important evolutionary force affecting patterns of genetic variation in Drosophila.

evolutionary biology↗

A functional connectome phenotyping dataset including cognitive state and personality measures

The dataset enables exploration of higher-order cognitive faculties, self-generated mental experience, and personality features in relation to the intrinsic functional architecture of the brain. We provide multimodal magnetic resonance imaging (MRI) data and a broad set of state and trait phenotypic assessments: mind-wandering, personality traits, and cognitive abilities. Specifically, 194 healthy participants (between 20 and 75 years of age) filled out 31 questionnaires, performed 7 tasks, and reported 4 probes of in-scanner mind-wandering. The scanning session included four 15.5-min resting-state functional MRI runs using a multiband EPI sequence and a high-resolution structural scan using a 3D MP2RAGE sequence. This dataset constitutes one part of the MPI-Leipzig Mind-Brain-Body database.

neuroscience↗