المؤلفون: Sachdeva V; Graduate Program in Biophysical Sciences, University of Chicago, Chicago, Illinois, United States of America., Mora T; Laboratoire de physique de l'École normale supérieure, Centre National de la Recherche Scientifique, Paris, France.; Paris Sciences et Lettres University Paris, Paris, France.; Sorbonne Université Paris, Paris, France.; Université de Paris, Paris, France., Walczak AM; Laboratoire de physique de l'École normale supérieure, Centre National de la Recherche Scientifique, Paris, France.; Paris Sciences et Lettres University Paris, Paris, France.; Sorbonne Université Paris, Paris, France.; Université de Paris, Paris, France., Palmer SE; Department of Organismal Biology and Anatomy, University of Chicago, Chicago, Illinois, United States of America.; Department of Physics, University of Chicago, Chicago, Illinois, United States of America.

المصدر: PLoS computational biology [PLoS Comput Biol] 2021 Mar 08; Vol. 17 (3), pp. e1008743. Date of Electronic Publication: 2021 Mar 08 (Print Publication: 2021).

نوع المنشور: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.

بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE

مواضيع طبية MeSH: Computational Biology* , Models, Biological* , Models, Statistical*, Biological Evolution ; Environment ; Gene Frequency ; Genetics, Population ; Movement

مستخلص: Responding to stimuli requires that organisms encode information about the external world. Not all parts of the input are important for behavior, and resource limitations demand that signals be compressed. Prediction of the future input is widely beneficial in many biological systems. We compute the trade-offs between representing the past faithfully and predicting the future using the information bottleneck approach, for input dynamics with different levels of complexity. For motion prediction, we show that, depending on the parameters in the input dynamics, velocity or position information is more useful for accurate prediction. We show which motion representations are easiest to re-use for accurate prediction in other motion contexts, and identify and quantify those with the highest transferability. For non-Markovian dynamics, we explore the role of long-term memory in shaping the internal representation. Lastly, we show that prediction in evolutionary population dynamics is linked to clustering allele frequencies into non-overlapping memories.
Competing Interests: The authors have declared that no competing interests exist.

المؤلفون: Mora T; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, New Jersey, United States of America., Yu H, Sowa Y, Wingreen NS

المصدر: PLoS computational biology [PLoS Comput Biol] 2009 Oct; Vol. 5 (10), pp. e1000540. Date of Electronic Publication: 2009 Oct 23.

نوع المنشور: Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't

بيانات الدورية: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE

مواضيع طبية MeSH: Bacterial Physiological Phenomena* , Models, Biological*, Bacterial Proteins/*physiology , Molecular Motor Proteins/*physiology, Algorithms ; Computer Simulation ; Rotation ; Torque

مستخلص: The bacterial flagellar motor is a highly efficient rotary machine used by many bacteria to propel themselves. It has recently been shown that at low speeds its rotation proceeds in steps. Here we propose a simple physical model, based on the storage of energy in protein springs, that accounts for this stepping behavior as a random walk in a tilted corrugated potential that combines torque and contact forces. We argue that the absolute angular position of the rotor is crucial for understanding step properties and show this hypothesis to be consistent with the available data, in particular the observation that backward steps are smaller on average than forward steps. We also predict a sublinear speed versus torque relationship for fixed load at low torque, and a peak in rotor diffusion as a function of torque. Our model provides a comprehensive framework for understanding and analyzing stepping behavior in the bacterial flagellar motor and proposes novel, testable predictions. More broadly, the storage of energy in protein springs by the flagellar motor may provide useful general insights into the design of highly efficient molecular machines.