Vein fate determined by flow-based but time-delayed integration of network architecture

  1. Sophie Marbach
  2. Noah Ziethen
  3. Leonie Bastin
  4. Felix K Bäuerle
  5. Karen Alim  Is a corresponding author
  1. New York University, United States
  2. Max Planck Institute for Dynamics and Self-Organization, Germany
  3. Technical University of Munich, Germany

Abstract

Veins in vascular networks, such as in blood vasculature or leaf networks, continuously reorganize, grow or shrink, to minimize energy dissipation. Flow shear stress on vein walls has been set forth as the local driver for a vein's continuous adaptation. Yet, shear feedback alone cannot account for the observed diversity of vein dynamics - a puzzle made harder by scarce spatiotemporal data. Here, we resolve network-wide vein dynamics and shear rate during spontaneous reorganization in the prototypical vascular networks of Physarum polycephalum. Our experiments reveal a plethora of vein dynamics (stable, growing, shrinking) where the role of shear is ambiguous. Quantitative analysis of our data reveals that (a) shear rate indeed feeds back on vein radius, yet, with a time delay of 1-3 min. Further, we reconcile the experimentally observed disparate vein fates by developing a model for vein adaptation within a network and accounting for the observed time delay. The model reveals that (b) vein fate is determined by parameters - local pressure or relative vein resistance - which integrate the entire network's architecture, as they result from global conservation of fluid volume. Finally, we observe avalanches of network reorganization events that cause entire clusters of veins to vanish. Such avalanches are consistent with network architecture integrating parameters governing vein fate as vein connections continuously change. As the network architecture integrating parameters intrinsically arise from laminar fluid flow in veins, we expect our findings to play a role across ow-based vascular networks.

Data availability

Original microscopic images of all the specimens used for this study are available as movies in MP4 format.Data sharing plan:All data used to generate the figures and the custom written matlab codes will be available on the open access data repository platform mediaTUM if the paper is accepted and which will correspond to the final versions of the figures.

Article and author information

Author details

  1. Sophie Marbach

    Courant Institute of Mathematical Sciences, New York University, New York, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2427-2065
  2. Noah Ziethen

    Max Planck Institute for Dynamics and Self-Organization, Goettingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  3. Leonie Bastin

    Max Planck Institute for Dynamics and Self-Organization, Goettingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  4. Felix K Bäuerle

    Max Planck Institute for Dynamics and Self-Organization, Goettingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  5. Karen Alim

    Department of Bioscience, Technical University of Munich, Garching, Germany
    For correspondence
    k.alim@tum.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-2527-5831

Funding

MRSEC Program of the National Science Foundation (Award Number DMR- 1420073)

  • Sophie Marbach

Max Planck Society

  • Karen Alim

European Research Council under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 947630,FlowMem)

  • Karen Alim

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

Copyright

© 2023, Marbach 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.

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  1. Sophie Marbach
  2. Noah Ziethen
  3. Leonie Bastin
  4. Felix K Bäuerle
  5. Karen Alim
(2023)
Vein fate determined by flow-based but time-delayed integration of network architecture
eLife 12:e78100.
https://doi.org/10.7554/eLife.78100

Share this article

https://doi.org/10.7554/eLife.78100

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