ArticlePloS one2013
Single-cell dynamics reveals sustained growth during diauxic shifts.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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Who cites it
42 citing papers in PubMed, 90 citations in OpenAlex.
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- Navigating Environmental Transitions: the Role of Phenotypic Variation in Bacterial Responses.mBio · 2022Review
- Microbial metabolic noise.WIREs mechanisms of disease · 2021Review
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- A Multi-Scale Approach to ModelingEntropy (Basel, Switzerland) · 2020Article
- Bacterial metabolic heterogeneity: origins and applications in engineering and infectious disease.Current opinion in biotechnology · 2020Review
- Dynamic metabolic adaptation can promote species coexistence in competitive microbial communities.PLoS computational biology · 2020Article
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- Development and characterization of Escherichia coli triple reporter strains for investigation of population heterogeneity in bioprocesses.Microbial cell factories · 2020Article
- Microfluidics for Biotechnology: Bridging Gaps to Foster Microfluidic Applications.Frontiers in bioengineering and biotechnology · 2020Review
- Growth-dependent recombinant product formation kinetics can be reproduced through engineering of glucose transport and is prone to phenotypic heterogeneity.Microbial cell factories · 2019Article
- An ensemble of mathematical models showing diauxic growth behaviour.BMC systems biology · 2018Article
- Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software.Nature communications · 2018Article
- Cell-to-cell variation and specialization in sugar metabolism in clonal bacterial populations.PLoS genetics · 2017Article
- Statistics and simulation of growth of single bacterial cells: illustrations with B. subtilis and E. coli.Scientific reports · 2017Article
- A global resource allocation strategy governs growth transition kinetics of Escherichia coli.Nature · 2017Article
- Beyond the bulk: disclosing the life of single microbial cells.FEMS microbiology reviews · 2017Review
- Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments.Journal of the Royal Society, Interface · 2017Review
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stochasticity in gene regulation has been characterized extensively, but how it affects cellular growth and fitness is less clear. We study the growth of E. coli cells as they shift from glucose to lactose metabolism, which is characterized by an obligatory growth arrest in bulk experiments that is termed the lag phase. Here, we follow the growth dynamics of individual cells at minute-resolution using a single-cell assay in a microfluidic device during this shift, while also monitoring lac expression. Mirroring the bulk results, the majority of cells displays a growth arrest upon glucose exhaustion, and resume when triggered by stochastic lac expression events. However, a significant fraction of cells maintains a high rate of elongation and displays no detectable growth lag during the shift. This ability to suppress the growth lag should provide important selective advantages when nutrients are scarce. Trajectories of individual cells display a highly non-linear relation between lac expression and growth, with only a fraction of fully induced levels being sufficient for achieving near maximal growth. A stochastic molecular model together with measured dependencies between nutrient concentration, lac expression level, and growth accurately reproduces the observed switching distributions. The results show that a growth arrest is not obligatory in the classic diauxic shift, and underscore that regulatory stochasticity ought to be considered in terms of its impact on growth and survival.
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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.