ArticlePLoS computational biology2010
Adaptable functionality of transcriptional feedback in bacterial two-component systems.
Article in PLoS computational biology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
- Multiple input-multiple output (MIMO) designs in two-component signalling systems of Mycobacterium tuberculosis.FEMS microbiology reviews · 2026Review
- ModelingbioRxiv : the preprint server for biology · 2025Article
- Mycobacterial MutT1-mediated dephosphorylation of the sensor histidine kinases reveals a new link in the regulation of the two-component signaling.Nucleic acids research · 2025Article
- Structural properties and asymptotic behavior of bacterial two-component systems.Frontiers in systems biology · 2025Article
- Sequestration of histidine kinases by non-cognate response regulators establishes a threshold level of stimulation for bacterial two-component signaling.Nature communications · 2023Article
- An Evolutionary Paradigm Favoring Cross Talk between Bacterial Two-Component Signaling Systems.mSystems · 2022Article
- Robustness and the evolution of length control strategies in the T3SS and flagellar hook.Biophysical journal · 2021Article
- Role of a local transcription factor in governing cellular carbon/nitrogen homeostasis in Pseudomonas fluorescens.Nucleic acids research · 2021Article
- Chaperone-Mediated Stress Sensing in Mycobacterium tuberculosis Enables Fast Activation and Sustained Response.mSystems · 2021Article
- Overlaid positive and negative feedback loops shape dynamical properties of PhoPQ two-component system.PLoS computational biology · 2021Article
- Doxycycline inhibits pre-rRNA processing and mature rRNA formation in E. coli.The Journal of antibiotics · 2019Article
- Identification via Numerical Computation of Transcriptional Determinants of a Cell Phenotype Decision Making.Frontiers in genetics · 2019Article
- Intrinsic limits of information transmission in biochemical signalling motifs.Interface focus · 2018Article
- Importance of Feedback and Feedforward Loops to Adaptive Immune Response Modeling.CPT: pharmacometrics & systems pharmacology · 2018Review
- Overcoming the Cost of Positive Autoregulation by Accelerating the Response with a Coupled Negative Feedback.Cell reports · 2018Article
- Article
- Origins of heterogeneity in Streptococcus mutans competence: interpreting an environment-sensitive signaling pathway.Physical biology · 2017Article
- Role of Autoregulation and Relative Synthesis of Operon Partners in Alternative Sigma Factor Networks.PLoS computational biology · 2016Article
- Survival of Phenotypic Information during Cellular Growth Transitions.ACS synthetic biology · 2016Article
- Article
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2 authors.
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Abstract
A widespread mechanism of bacterial signaling occurs through two-component systems, comprised of a sensor histidine kinase (SHK) and a transcriptional response regulator (RR). The SHK activates RR by phosphorylation. The most common two-component system structure involves expression from a single operon, the transcription of which is activated by its own phosphorylated RR. The role of this feedback is poorly understood, but it has been associated with an overshooting kinetic response and with fast recovery of previous interrupted signaling events in different systems. Mathematical models show that overshoot is only attainable with negative feedback that also improves response time. Our models also predict that fast recovery of previous interrupted signaling depends on high accumulation of SHK and RR, which is more likely in a positive feedback regime. We use Monte Carlo sampling of the parameter space to explore the range of attainable model behaviors. The model predicts that the effective feedback sign can change from negative to positive depending on the signal level. Variations in two-component system architectures and parameters may therefore have evolved to optimize responses in different bacterial lifestyles. We propose a conceptual model where low signal conditions result in a responsive system with effectively negative feedback while high signal conditions with positive feedback favor persistence of system output.
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