E. coli chemotaxis is information-limited
arXiv:2102.11732 · doi:10.1038/s41567-021-01380-3
Abstract
Organisms must acquire and use environmental information to guide their behaviors. However, it is unclear whether and how information quantitatively limits behavioral performance. Here, we relate information to behavioral performance in Escherichia coli chemotaxis. First, we derive a theoretical limit for the maximum achievable gradient-climbing speed given a cell's information acquisition rate. Next, we measure cells' gradient-climbing speeds and the rate of information acquisition by the chemotaxis pathway. We find that E. coli make behavioral decisions with much less than the 1 bit required to determine whether they are swimming up-gradient. However, they use this information efficiently, performing near the theoretical limit. Thus, information can limit organisms' performance, and sensory-motor pathways may have evolved to efficiently use information from the environment.
17 pages of main text, 3 main text figures, 66 pages of supplementary text, 10 supplementary figures
References in corpus (9)
- Maxwell's demon in biochemical signal transduction with feedback loop
- The Bacterial Chemotactic Response Reflects a Compromise Between Transient and Steady State Behavior
- A Geometric Criterion for the Optimal Spreading of Active Polymers in Porous Media
- Limits of feedback control in bacterial chemotaxis
- Non-genetic diversity modulates population performance
- Persistence of direction increases the drift velocity of run and tumble chemotaxis
- Signalling noise enhances chemotactic drift of E. coli
- Predicting chemical environments of bacteria from receptor signaling
- First-principles prediction of the information processing capacity of a simple genetic circuit
Cited by in corpus (28)
- Cellular Sensing Governs the Stability of Chemotactic Fronts
- Physical constraints in intracellular signaling: the cost of sending a bit
- Energy and information flows in autonomous systems
- Microbes in porous environments: From active interactions to emergent feedback
- Colossal power extraction from active cyclic Brownian information engines
- Path Weight Sampling: Exact Monte Carlo Computation of the Mutual Information between Stochastic Trajectories
- Optimal sensing and control of run-and-tumble chemotaxis
- Universal bounds on the performance of information-thermodynamic engine
- Semantic Information in a model of Resource Gathering Agents
- Information Arbitrage in Bipartite Heat Engines
- Bacterial diffusion in disordered media, by forgetting the media
- Planetary Scale Information Transmission in the Biosphere and Technosphere: Limits and Evolution
- Theory for Optimal Estimation and Control under Resource Limitations and Its Applications to Biological Information Processing and Decision-Making
- Information propagation in Gaussian processes on multilayer networks
- Information-theoretic description of a feedback-control Kuramoto model
- Weak transcription factor clustering at binding sites can facilitate information transfer from molecular signals
- Characterizing the non-monotonic behavior of mutual information along biochemical reaction cascades
- Resource Limitations induce Phase Transitions in Biological Information Processing
- Biolocomotion and premelting in ice
- Remark on the Entropy Production of Adaptive Run-and-Tumble Chemotaxis
- Lattice ultrasensitivity amplifies signals in E. coli without fine-tuning
- Information bounds production in replicator systems
- Chemotaxing E. coli do not count single molecules
- Information Transmission via Molecular Communication in Astrobiological Environments
- Physical limits on chemical sensing in bounded domains
- Is E. coli good at chemotaxis?
- Information Thermodynamics for Deterministic Chemical Reaction Networks
- Theoretical Analysis of Resource-Induced Phase Transitions in Estimation Strategies