Dynamics of diffusive cell signaling relays

  1. Paul B Dieterle
  2. Jiseon Min
  3. Daniel Irimia
  4. Ariel Amir  Is a corresponding author
  1. Harvard University, United States
  2. Massachusetts General Hopital, Harvard Medical School, United States

Abstract

In biological contexts as diverse as development, apoptosis, and synthetic microbial consortia, collections of cells or sub-cellular components have been shown to overcome the slow signaling speed of simple diffusion by utilizing diffusive relays, in which the presence of one type of diffusible signaling molecule triggers participation in the emission of the same type of molecule. This collective effect gives rise to fast-traveling diffusive waves. Here, in the context of cell signaling, we show that system dimensionality – the shape of the extracellular medium and the distribution of cells within it – can dramatically affect the wave dynamics, but that these dynamics are insensitive to details of cellular activation. As an example, we show that neutrophil swarming experiments exhibit dynamical signatures consistent with the proposed signaling motif. We further show that cell signaling relays generate much steeper concentration profiles than does simple diffusion, which may facilitate neutrophil chemotaxis.

Data availability

The only dataset we analyze or generate is present and available in Reategui (2017). PMID: 29057147. Code for the figures is available at github.io/pdieterle/diffWavePropAndInit.

The following previously published data sets were used

Article and author information

Author details

  1. Paul B Dieterle

    Physics, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jiseon Min

    Department of Molecular and Cellular Biology, Harvard University, Cambridge, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Daniel Irimia

    Surgery, Massachusetts General Hopital, Harvard Medical School, Boston, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7347-2082
  4. Ariel Amir

    Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, United States
    For correspondence
    arielamir@seas.harvard.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2611-0139

Funding

National Science Foundation (MRSEC DMR 14-20570)

  • Ariel Amir

Kavli Foundation (N/A)

  • Ariel Amir

National Science Foundation (CAREER 1752024)

  • Ariel Amir

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

© 2020, Dieterle et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Paul B Dieterle
  2. Jiseon Min
  3. Daniel Irimia
  4. Ariel Amir
(2020)
Dynamics of diffusive cell signaling relays
eLife 9:e61771.
https://doi.org/10.7554/eLife.61771

Share this article

https://doi.org/10.7554/eLife.61771

Further reading

    1. Cell Biology
    2. Physics of Living Systems
    Deb Sankar Banerjee, Shiladitya Banerjee
    Research Article

    Accurate regulation of centrosome size is essential for ensuring error-free cell division, and dysregulation of centrosome size has been linked to various pathologies, including developmental defects and cancer. While a universally accepted model for centrosome size regulation is lacking, prior theoretical and experimental works suggest a centrosome growth model involving autocatalytic assembly of the pericentriolar material. Here, we show that the autocatalytic assembly model fails to explain the attainment of equal centrosome sizes, which is crucial for error-free cell division. Incorporating latest experimental findings into the molecular mechanisms governing centrosome assembly, we introduce a new quantitative theory for centrosome growth involving catalytic assembly within a shared pool of enzymes. Our model successfully achieves robust size equality between maturing centrosome pairs, mirroring cooperative growth dynamics observed in experiments. To validate our theoretical predictions, we compare them with available experimental data and demonstrate the broad applicability of the catalytic growth model across different organisms, which exhibit distinct growth dynamics and size scaling characteristics.

    1. Cell Biology
    2. Physics of Living Systems
    Marta Urbanska, Yan Ge ... Jochen Guck
    Research Article

    Cell mechanical properties determine many physiological functions, such as cell fate specification, migration, or circulation through vasculature. Identifying factors that govern the mechanical properties is therefore a subject of great interest. Here, we present a mechanomics approach for establishing links between single-cell mechanical phenotype changes and the genes involved in driving them. We combine mechanical characterization of cells across a variety of mouse and human systems with machine learning-based discriminative network analysis of associated transcriptomic profiles to infer a conserved network module of five genes with putative roles in cell mechanics regulation. We validate in silico that the identified gene markers are universal, trustworthy, and specific to the mechanical phenotype across the studied mouse and human systems, and demonstrate experimentally that a selected target, CAV1, changes the mechanical phenotype of cells accordingly when silenced or overexpressed. Our data-driven approach paves the way toward engineering cell mechanical properties on demand to explore their impact on physiological and pathological cell functions.