Evidence map›Paper›PMID 39325970›Full record

ArticleThe ISME journal2024

Pathogen non-planktonic phases within the urinary tract impact early infection and resistance evolution.

Michael Raatz, Amanda de Azevedo-Lopes, Karolina Drabik, Arne Traulsen, Bartlomiej Waclaw

Abstract read
In one paragraph

Article in The ISME journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Michael RaatzDepartment of Theoretical Biology, Max Planck Institute for Evolutionary Biology, 24306 Plön, Germany.
Amanda de Azevedo-LopesDepartment of Theoretical Biology, Max Planck Institute for Evolutionary Biology, 24306 Plön, Germany.
Karolina DrabikDioscuri Centre for Physics and Chemistry of Bacteria, Institute of Physical Chemistry (IChF), Polish Academy of Sciences, 01-224 Warsaw, Poland.
Arne TraulsenDepartment of Theoretical Biology, Max Planck Institute for Evolutionary Biology, 24306 Plön, Germany.
Bartlomiej WaclawDioscuri Centre for Physics and Chemistry of Bacteria, Institute of Physical Chemistry (IChF), Polish Academy of Sciences, 01-224 Warsaw, Poland.

Funding

Dioscuri, a program initiated by the Max Planck Society, jointly managed with the National Science Centre in Poland, and mutually funded by Polish Ministry of Science and Higher Education, and German Federal Ministry of Education and Research UMO-2019/02/H/NZ6/00003NAWA Polish Returns PPN/PPO/2019/1/00030/U/0001Research Training Group "Translational Evolutionary Research" 400993799
6 · The paper itself

Abstract

Treatment of urinary tract infections and the prevention of their recurrence is a pressing global health problem. In a urinary infection, pathogenic bacteria not only reside in the bladder lumen but also attach to and invade the bladder tissue. Planktonic, attached, and intracellular bacteria face different selection pressures from physiological processes such as micturition, immune response, and antibiotic treatment. Here, we use a mathematical model of the initial phase of infection to unravel the effects of these different selective pressures on the ecological and evolutionary dynamics of urinary infections. We explicitly model planktonic bacteria in the bladder lumen, bacteria attached to the bladder wall, and bacteria that have invaded the epithelial cells of the bladder. We find that the presence of non-planktonic bacteria substantially increases the risk of infection establishment and affects evolutionary trajectories leading to resistance during antibiotic treatment. We also show that competitive inoculation with a fast-growing non-pathogenic strain can reduce the pathogen load and increase the efficacy of an antibiotic, but only if the antibiotic is used in moderation. Our study shows that including different compartments is essential to create more realistic models of urinary infections, which may help guide new treatment strategies.

Indexed as

Anti-Bacterial AgentsUrinary Tract InfectionsBacteriaDrug Resistance, BacterialHumansModels, TheoreticalUrinary BladderAnti-Bacterial Agentsantibiotic therapyevolution-informed medicinemathematical modelingresistance evolution

Identifiers

PMID39325970
PMCPMC11499890

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.