ArticlemBio2014
Heteroresistance at the single-cell level: adapting to antibiotic stress through a population-based strategy and growth-controlled interphenotypic coordination.
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.
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Who cites it
31 citing papers in PubMed, 66 citations in OpenAlex.
- Potential in-host evolution ofMicrobiology spectrum · 2025Article
- Flying under the radar: vancomycin heteroresistance inASM case reports · 2025Article
- Bacterial strain type and TEM-1 enzyme allele impact antibiotic susceptibility distribution in monoclonal populations: a single-cell droplet approach.Royal Society open science · 2025Article
- Plasmid-mediated phenotypic noise leads to transient antibiotic resistance in bacteria.Nature communications · 2024Article
- Microfluidic approaches in microbial ecology.Lab on a chip · 2024Review
- Single-Cell Motility Rapidly Quantifying Heteroresistance in Populations ofSmall science · 2022Article
- Bistable Bacterial Growth Dynamics in the Presence of Antimicrobial Agents.Antibiotics (Basel, Switzerland) · 2021Article
- Genomic characterization of an emerging Enterobacteriaceae species: the first case of co-infection with a typical pathogen in a human patient.BMC genomics · 2020Article
- Dynamic motility selection drives population segregation in a bacterial swarm.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Droplet-based digital antibiotic susceptibility screen reveals single-cell clonal heteroresistance in an isogenic bacterial population.Scientific reports · 2020Article
- Antibiotic resilience: a necessary concept to complement antibiotic resistance?Proceedings. Biological sciences · 2019Article
- Changes in Cellular Elasticities and Conformational Properties of Bacterial Surface Biopolymers of Multidrug-ResistantCell surface (Amsterdam, Netherlands) · 2019Article
- Review
- Activity of Moxifloxacin againstAntimicrobial agents and chemotherapy · 2018Article
- Saccharomyces cerevisiae adapted to grow in the presence of low-dose rapamycin exhibit altered amino acid metabolism.Cell communication and signaling : CCS · 2018Article
- Rocking Aspergillus: morphology-controlled cultivation of Aspergillus niger in a wave-mixed bioreactor for the production of secondary metabolites.Microbial cell factories · 2018Article
- Linezolid Kills Acid-Phase and Nonreplicative-Persister-Phase Mycobacterium tuberculosis in a Hollow-Fiber Infection Model.Antimicrobial agents and chemotherapy · 2018Article
- Effect of cryopreservation and lyophilization on viability and growth of strict anaerobic human gut microbes.Microbial biotechnology · 2018Article
- Article
- Complete Genomic Analysis of a Kingdom-CrossingFrontiers in microbiology · 2018Article
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Authors and funding
15 authors at 7 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
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.
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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.