ArticleNature2005
Design principles of a bacterial signalling network.
Article in Nature, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 141 papers.
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Who cites it
141 citing papers in PubMed, 301 citations in OpenAlex.
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- Phosphorylation of a conserved intrinsically disordered region is necessary for activation of a bacterial Hanks-type Ser/Thr kinase signaling pathway.bioRxiv : the preprint server for biology · 2025Article
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- Protein-protein complexes can undermine ultrasensitivity-dependent biological adaptation.Journal of the Royal Society, Interface · 2023Article
- Steady-state running rate sets the speed and accuracy of accumulation of swimming bacteria.Biophysical journal · 2022Article
- Bacterial chemotaxis to saccharides is governed by a trade-off between sensing and uptake.Biophysical journal · 2022Article
- microRNA-Mediated Encoding and Decoding of Time-Dependent Signals in Tumorigenesis.Biomolecules · 2022Review
- Suppression of cell-cell variation by cooperative interaction of phosphatase and response regulator.Biophysical journal · 2022Article
- Bacterial Proprioception: Can a Bacterium Sense Its Movement?Frontiers in microbiology · 2022Review
- Collective self-optimization of communicating active particles.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Ultrasensitivity and bistability in covalent-modification cycles with positive autoregulation.Proceedings. Mathematical, physical, and engineering sciences · 2021Article
- Non-Genetic Diversity in Chemosensing and Chemotactic Behavior.International journal of molecular sciences · 2021Review
- Adaptive tuning of cell sensory diversity without changes in gene expression.Science advances · 2020Article
- A Multi-Scale Approach to ModelingEntropy (Basel, Switzerland) · 2020Article
- Robustness in an Ultrasensitive Motor.mBio · 2020Article
- Post-Transcriptional Noise Control.BioEssays : news and reviews in molecular, cellular and developmental biology · 2019Article
- Agent-Based Modeling Reveals Possible Mechanisms for Observed Aggregation Cell Behaviors.Biophysical journal · 2018Article
81 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cellular biochemical networks have to function in a noisy environment using imperfect components. In particular, networks involved in gene regulation or signal transduction allow only for small output tolerances, and the underlying network structures can be expected to have undergone evolution for inherent robustness against perturbations. Here we combine theoretical and experimental analyses to investigate an optimal design for the signalling network of bacterial chemotaxis, one of the most thoroughly studied signalling networks in biology. We experimentally determine the extent of intercellular variations in the expression levels of chemotaxis proteins and use computer simulations to quantify the robustness of several hypothetical chemotaxis pathway topologies to such gene expression noise. We demonstrate that among these topologies the experimentally established chemotaxis network of Escherichia coli has the smallest sufficiently robust network structure, allowing accurate chemotactic response for almost all individuals within a population. Our results suggest that this pathway has evolved to show an optimal chemotactic performance while minimizing the cost of resources associated with high levels of protein expression. Moreover, the underlying topological design principles compensating for intercellular variations seem to be highly conserved among bacterial chemosensory systems.
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Registered trials
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.