Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Emergence of synchronized multicellular mechanosensing from spatiotemporal integration of heterogeneous single-cell information transfer

Amos Zamir, Guanyu Li, Katelyn Chase, Robert Moskovitch, Bo Sun, View ORCID ProfileAssaf Zaritsky
doi: https://doi.org/10.1101/2020.09.28.316240
Amos Zamir
1Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Guanyu Li
2Department of Physics, Oregon State University, Corvallis, OR 97331, USA
3Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Katelyn Chase
3Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Robert Moskovitch
1Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Bo Sun
2Department of Physics, Oregon State University, Corvallis, OR 97331, USA
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: assafza@bgu.ac.il sunb@physics.oregonstate.edu
Assaf Zaritsky
1Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Assaf Zaritsky
  • For correspondence: assafza@bgu.ac.il sunb@physics.oregonstate.edu
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

We quantitatively characterize how noisy and heterogeneous behaviors of individual cells are integrated across a population toward multicellular synchronization by studying the calcium dynamics in mechanically stimulated monolayers of endothelial cells. We used information-theory to quantify the asymmetric information-transfer between pairs of cells and define quantitative measures of how single cells receive or transmit information in the multicellular network. We find that cells take different roles in intercellular information-transfer and that this heterogeneity is associated with synchronization. Cells tended to maintain their roles between consecutive cycles of mechanical stimuli and reinforced them over time, suggesting the existence of a cellular “memory” in intercellular information transfer. Interestingly, we identified a subpopulation of cells characterized by higher probability of both receiving and transmitting information. These “communication hub” roles were stable - once a cell switched to a “communication hub” role it was less probable to switch to other roles. This stableness property of the cells led to gradual enrichment of communication hubs that was associated with the establishment of synchronization. Our analysis demonstrated that multicellular synchronization was established by effective information spread from the (local) single cell to the (global) group scale in the multicellular network. Altogether, we suggest that multicellular synchronization is driven by single cell communication properties, including heterogeneity, functional memory and information flow.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
Back to top
PreviousNext
Posted September 28, 2020.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Emergence of synchronized multicellular mechanosensing from spatiotemporal integration of heterogeneous single-cell information transfer
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Emergence of synchronized multicellular mechanosensing from spatiotemporal integration of heterogeneous single-cell information transfer
Amos Zamir, Guanyu Li, Katelyn Chase, Robert Moskovitch, Bo Sun, Assaf Zaritsky
bioRxiv 2020.09.28.316240; doi: https://doi.org/10.1101/2020.09.28.316240
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Emergence of synchronized multicellular mechanosensing from spatiotemporal integration of heterogeneous single-cell information transfer
Amos Zamir, Guanyu Li, Katelyn Chase, Robert Moskovitch, Bo Sun, Assaf Zaritsky
bioRxiv 2020.09.28.316240; doi: https://doi.org/10.1101/2020.09.28.316240

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Cell Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3691)
  • Biochemistry (7800)
  • Bioengineering (5678)
  • Bioinformatics (21295)
  • Biophysics (10582)
  • Cancer Biology (8179)
  • Cell Biology (11946)
  • Clinical Trials (138)
  • Developmental Biology (6764)
  • Ecology (10401)
  • Epidemiology (2065)
  • Evolutionary Biology (13874)
  • Genetics (9709)
  • Genomics (13074)
  • Immunology (8150)
  • Microbiology (20020)
  • Molecular Biology (7859)
  • Neuroscience (43070)
  • Paleontology (321)
  • Pathology (1279)
  • Pharmacology and Toxicology (2260)
  • Physiology (3353)
  • Plant Biology (7232)
  • Scientific Communication and Education (1313)
  • Synthetic Biology (2008)
  • Systems Biology (5539)
  • Zoology (1128)