Physical limits on galvanotaxis.


Journal

Physical review. E
ISSN: 2470-0053
Titre abrégé: Phys Rev E
Pays: United States
ID NLM: 101676019

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 26 09 2022
accepted: 17 10 2023
medline: 20 1 2024
pubmed: 20 1 2024
entrez: 20 1 2024
Statut: ppublish

Résumé

Eukaryotic cells can polarize and migrate in response to electric fields via "galvanotaxis," which aids wound healing. Experimental evidence suggests cells sense electric fields via molecules on the cell's surface redistributing via electrophoresis and electroosmosis, though the sensing species has not yet been conclusively identified. We develop a model that links sensor redistribution and galvanotaxis using maximum likelihood estimation. Our model predicts a single universal curve for how galvanotactic directionality depends on field strength. We can collapse measurements of galvanotaxis in keratocytes, neural crest cells, and granulocytes to this curve, suggesting that stochasticity due to the finite number of sensors may limit galvanotactic accuracy. We find cells can achieve experimentally observed directionalities with either a few (∼100) highly polarized sensors or many (∼10^{4}) sensors with an ∼6-10% change in concentration across the cell. We also identify additional signatures of galvanotaxis via sensor redistribution, including the presence of a tradeoff between accuracy and variance in cells being controlled by rapidly switching fields. Our approach shows how the physics of noise at the molecular scale can limit cell-scale galvanotaxis, providing important constraints on sensor properties and allowing for new tests to determine the specific molecules underlying galvanotaxis.

Identifiants

pubmed: 38243498
doi: 10.1103/PhysRevE.108.064411
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

064411

Auteurs

Ifunanya Nwogbaga (I)

Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA.

A Hyun Kim (AH)

Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA.

Brian A Camley (BA)

Thomas C. Jenkins Department of Biophysics, Johns Hopkins University, Baltimore, Maryland 21218, USA.
William H. Miller III Department of Physics & Astronomy, Johns Hopkins University, Baltimore, Maryland 21218, USA.

Classifications MeSH