Evidence map›Paper›PMID 42613926›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2026

Programmable 3D Microfluidics Reveals Motility-Driven Antibiotic Resistance Evolution in Gradients.

Xiaobo Li, Jianan Yin, Yanqing Song, Andrew Glidle, William Sloan, He Huang, Maggie Cusack, Cindy J Smith, Huabing Yin

Abstract read
PubMed Publisher
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2026. 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

9 authors.

Xiaobo LiJames Watt School of Engineering, Advanced Research Centre (ARC), University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0001-9108-7815
Jianan YinSchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin Key Laboratory of Biological and Pharmaceutical Engineering, Tianjin University, Tianjin, China.
Yanqing SongJames Watt School of Engineering, Advanced Research Centre (ARC), University of Glasgow, Glasgow, UK.
Andrew GlidleJames Watt School of Engineering, Advanced Research Centre (ARC), University of Glasgow, Glasgow, UK.
William SloanJames Watt School of Engineering, Advanced Research Centre (ARC), University of Glasgow, Glasgow, UK.
He HuangSchool of Synthetic Biology and Biomanufacturing, State Key Laboratory of Synthetic Biology, Tianjin Key Laboratory of Biological and Pharmaceutical Engineering, Tianjin University, Tianjin, China.ORCID https://orcid.org/0000-0003-3008-4869
Maggie CusackMunster Technological University, Cork, Ireland.
Cindy J SmithJames Watt School of Engineering, Advanced Research Centre (ARC), University of Glasgow, Glasgow, UK.
Huabing YinJames Watt School of Engineering, Advanced Research Centre (ARC), University of Glasgow, Glasgow, UK.ORCID https://orcid.org/0000-0001-7693-377X

Funding

EPSRC EP/K038885/1NERC NE/P011063/1NERC NE/W005115/1UKRI MR/Z50628X/1
6 · The paper itself

Abstract

Antibiotic resistance has become a serious threat to global health. It frequently emerges in real-world environments such as biofilms, where antibiotic gradients impose selective pressures that drive bacterial adaptation. However, the mechanisms underlying resistance development remain poorly understood, largely due to challenges in experimentally controlling confounding parameters. Here, we report a 3D microfluidic platform that enables real-time monitoring of bacterial dynamics under well-defined antibiotic gradients, along with programmable cell retrieval to identify key factors in resistance development. We show that motile Escherichia coli migrated randomly within the gradients regardless of antibiotic class (i.e., gentamicin, ciprofloxacin, and ampicillin). Resistance emerged only when a critical mass of bacteria sustained migration through the gradient for a sufficiently duration, revealing a previously unrecognized migration-duration threshold for adaptive evolution. Whole-genome resequencing revealed gene mutations in the resistant cells, including mutations in ATP synthase-related genes (i.e., atpG, atpD, and atpF). A trade-off between resistance and cell growth was also observed. Similar phenomena were observed in other motile bacteria species, including Serratia marcescens. Overall, we demonstrate that cell motility is a critical determinant of resistance development in heterogeneous antibiotic landscapes. Targeting cell motility and growth could offer effective strategies to combat antibiotic resistance in motile bacteria.

Indexed as

Anti-Bacterial AgentsDrug Resistance, BacterialDrug Resistance, MicrobialMicrofluidicsEscherichia coliMutationAnti-Bacterial Agentsantibiotic resistancegradientsmicrofluidicsmigrationmotilitysingle cells

Identifiers

PMID42613926

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.