Evidence map›Paper›PMID 24520060›Full record

ArticlemBio2014

Heteroresistance at the single-cell level: adapting to antibiotic stress through a population-based strategy and growth-controlled interphenotypic coordination.

Xiaorong Wang, Yu Kang, Chunxiong Luo, Tong Zhao, Lin Liu, Xiangdan Jiang, Rongrong Fu, Shuchang An, Jichao Chen, Ning Jiang and 5 more

Open access · goldAbstract readMulticenter Study
In one paragraph

Article in mBio, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
2.6field-weighted citation impact, top 10% of its field
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

31 citing papers in PubMed, 66 citations in OpenAlex.

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  13. Frontiers in microbiology · 2019
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  14. Activity of Moxifloxacin againstAntimicrobial agents and chemotherapy · 2018
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  20. Complete Genomic Analysis of a Kingdom-CrossingFrontiers in microbiology · 2018
    Article
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

15 authors at 7 institutions in 3 countries.

Xiaorong Wang
Yu Kang
Chunxiong Luo
Tong Zhao
Lin Liu
Xiangdan Jiang
Rongrong Fu
Shuchang An
Jichao Chen
Ning Jiang
Lufeng Ren
Qi Wang
J Kenneth Baillie
Zhancheng Gao
Jun Yu
Chinese Academy of Sciences · CNPeking University · CNPeking University People's Hospital · CNInstitute of Microbiology · CNSecond Affiliated Hospital of Dalian Medical University · CNThe Aerospace Corporation · USUniversity of Edinburgh · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

unlabelledHeteroresistance refers to phenotypic heterogeneity of microbial clonal populations under antibiotic stress, and it has been thought to be an allocation of a subset of "resistant" cells for surviving in higher concentrations of antibiotic. The assumption fits the so-called bet-hedging strategy, where a bacterial population "hedges" its "bet" on different phenotypes to be selected by unpredicted environment stresses. To test this hypothesis, we constructed a heteroresistance model by introducing a blaCTX-M-14 gene (coding for a cephalosporin hydrolase) into a sensitive Escherichia coli strain. We confirmed heteroresistance in this clone and that a subset of the cells expressed more hydrolase and formed more colonies in the presence of ceftriaxone (exhibited stronger "resistance"). However, subsequent single-cell-level investigation by using a microfluidic device showed that a subset of cells with a distinguishable phenotype of slowed growth and intensified hydrolase expression emerged, and they were not positively selected but increased their proportion in the population with ascending antibiotic concentrations. Therefore, heteroresistance--the gradually decreased colony-forming capability in the presence of antibiotic--was a result of a decreased growth rate rather than of selection for resistant cells. Using a mock strain without the resistance gene, we further demonstrated the existence of two nested growth-centric feedback loops that control the expression of the hydrolase and maximize population growth in various antibiotic concentrations. In conclusion, phenotypic heterogeneity is a population-based strategy beneficial for bacterial survival and propagation through task allocation and interphenotypic collaboration, and the growth rate provides a critical control for the expression of stress-related genes and an essential mechanism in responding to environmental stresses. IMPORTANCE: Heteroresistance is essentially phenotypic heterogeneity, where a population-based strategy is thought to be at work, being assumed to be variable cell-to-cell resistance to be selected under antibiotic stress. Exact mechanisms of heteroresistance and its roles in adaptation to antibiotic stress have yet to be fully understood at the molecular and single-cell levels. In our study, we have not been able to detect any apparent subset of "resistant" cells selected by antibiotics; on the contrary, cell populations differentiate into phenotypic subsets with variable growth statuses and hydrolase expression. The growth rate appears to be sensitive to stress intensity and plays a key role in controlling hydrolase expression at both the bulk population and single-cell levels. We have shown here, for the first time, that phenotypic heterogeneity can be beneficial to a growing bacterial population through task allocation and interphenotypic collaboration other than partitioning cells into different categories of selective advantage.

Indexed as

Adaptation, PhysiologicalDrug ToleranceAnti-Bacterial AgentsEscherichia coliMicrobial Sensitivity TestsPhenotypeAnti-Bacterial Agents

Identifiers

PMID24520060
PMCPMC3950525
OpenAlexW2042459898

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.