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  Non-asymptotic transients away from steady states determine cellular responsiveness to dynamic spatial-temporal signals

Nandan, A. P., & Koseska, A. (2023). Non-asymptotic transients away from steady states determine cellular responsiveness to dynamic spatial-temporal signals. bioRxiv: the preprint server for biology, 526969. doi:10.1101/2023.02.03.526969.

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2023.02.03.526969v2.full.pdf (Preprint), 8MB
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2023.02.03.526969v2.full.pdf
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2023
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The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.

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https://hdl.handle.net/21.11116/0000-000D-964F-2 (Verlagsversion)
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article in PLoS computational biology
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https://doi.org/10.1371/journal.pcbi.1011388 (Verlagsversion)
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article in PLoS computational biology
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 Urheber:
Nandan, Akhilesh P.1, Autor                 
Koseska, Aneta1, Autor                 
Affiliations:
1Lise Meitner Group Cellular Computations and Learning, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society, ou_3361763              

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 Zusammenfassung: Majority of the theory on cell polarization and the understanding of cellular sensing and responsiveness to localized chemical cues has been based on the idea that non-polarized and polarized cell states can be represented by stable asymptotic switching between them. The existing model classes that describe the dynamics of signaling networks underlying polarization are formulated within the framework of autonomous systems. However these models do not simultaneously capture both, robust maintenance of polarized state longer than the signal duration, and retained responsiveness to novel signals. Using recent experimental evidence for criticality organization of biochemical networks, we challenge the current concepts and demonstrate that non-asymptotic signaling dynamics arising at criticality uniquely ensures optimal responsiveness to changing chemoattractant fields. We provide a framework to characterize non-asymptotic dynamics of system’s state trajectories through a non-autonomous treatment of the system, further emphasizing the importance of (long) transient dynamics, as well as the necessity to change the mathematical formalism when describing biological systems that operate in changing environments.

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Sprache(n): eng - English
 Datum: 2023-02-04
 Publikationsstatus: Online veröffentlicht
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 Inhaltsverzeichnis: -
 Art der Begutachtung: Keine Begutachtung
 Identifikatoren: DOI: 10.1101/2023.02.03.526969
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Titel: bioRxiv : the preprint server for biology
  Kurztitel : bioRxiv
Genre der Quelle: Zeitschrift
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Seiten: - Band / Heft: - Artikelnummer: 526969 Start- / Endseite: - Identifikator: ZDB: 2766415-6
CoNE: https://pure.mpg.de/cone/journals/resource/2766415-6