Evidence map›Paper›PMID 39088440›Full record

ArticlePloS one2024

Measuring single-cell susceptibility to antibiotics within monoclonal bacterial populations.

Lena Le Quellec, Andrey Aristov, Salomé Gutiérrez Ramos, Gabriel Amselem, Julia Bos, Zeynep Baharoglu, Didier Mazel, Charles N Baroud

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
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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

8 authors.

Lena Le QuellecInstitut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France.
Andrey AristovInstitut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France.
Salomé Gutiérrez RamosInstitut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France.
Gabriel AmselemInstitut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France.
Julia BosInstitut Pasteur, Université Paris Cité, CNRS UMR3525, Bacterial Genome Plasticity Unit, Paris, France.
Zeynep BaharogluInstitut Pasteur, Université Paris Cité, CNRS UMR3525, Bacterial Genome Plasticity Unit, Paris, France.ORCID 0000-0003-3477-2685
Didier MazelInstitut Pasteur, Université Paris Cité, CNRS UMR3525, Bacterial Genome Plasticity Unit, Paris, France.
Charles N BaroudInstitut Pasteur, Université Paris Cité, Physical Microfluidics and Bioengineering, Paris, France.ORCID 0000-0002-5675-7729

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The emergence of new resistant bacterial strains is a worldwide challenge. A resistant bacterial population can emerge from a single cell that acquires resistance or persistence. Hence, new ways of tackling the mechanism of antibiotic response, such as single cell studies are required. It is necessary to see what happens at the single cell level, in order to understand what happens at the population level. To date, linking the heterogeneity of single-cell susceptibility to the population-scale response to antibiotics remains challenging due to the trade-offs between the resolution and the field of view. Here we present a platform that measures the ability of individual E. coli cells to form small colonies at different ciprofloxacin concentrations, by using anchored microfluidic drops and an image and data analysis pipelines. The microfluidic results are benchmarked against classical microbiology measurements of antibiotic susceptibility, showing an agreement between the pooled microfluidic chip and replated bulk measurements. Further, the experimental likelihood of a single cell to form a colony is used to provide a probabilistic antibiotic susceptibility curve. In addition to the probabilistic viewpoint, the microfluidic format enables the characterization of morphological features over time for a large number of individual cells. This pipeline can be used to compare the response of different bacterial strains to antibiotics with different action mechanisms.

Indexed as

Anti-Bacterial AgentsCiprofloxacinEscherichia coliMicrobial Sensitivity TestsSingle-Cell AnalysisDrug Resistance, BacterialLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesMicrofluidicsAnti-Bacterial AgentsCiprofloxacin

Identifiers

PMID39088440
PMCPMC11293721

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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.