CaltechAUTHORS
  A Caltech Library Service

Multi-Cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space

Mayalu, Michaëlle N. and Kim, Min-Cheol and Asada, Harry (2019) Multi-Cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space. . (Unpublished) http://resolver.caltech.edu/CaltechAUTHORS:20190123-125910370

[img] PDF - Submitted Version
Creative Commons Attribution.

1330Kb

Use this Persistent URL to link to this item: http://resolver.caltech.edu/CaltechAUTHORS:20190123-125910370

Abstract

Cells interacting through an extracellular matrix (ECM) exhibit emergent behaviors resulting from collective intercellular interaction. In wound healing and tissue development, characteristic compaction of ECM gel is induced by multiple cells that generate tensions in the ECM fibers and coordinate their actions with other cells. Computational prediction of collective cell-ECM interaction based on first principles is highly complex especially as the number of cells increase. Here, we introduce a computationally-efficient method for predicting nonlinear behaviors of multiple cells interacting mechanically through a 3-D ECM fiber network. The key enabling technique is superposition of single cell computational models to predict multicellular behaviors. While cell-ECM interactions are highly nonlinear, they can be linearized accurately with a unique method, termed Dual-Faceted Linearization. This method recasts the original nonlinear dynamics in an augmented space where the system behaves more linearly. The independent state variables are augmented by combining auxiliary variables that inform nonlinear elements involved in the system. This computational method involves a) expressing the original nonlinear state equations with two sets of linear dynamic equations b) reducing the order of the augmented linear system via principal component analysis and c) superposing individual single cell-ECM dynamics to predict collective behaviors of multiple cells. The method is computationally efficient compared to original nonlinear dynamic simulation and accurate compared to traditional Taylor expansion linearization. Furthermore, we reproduce reported experimental results of multi-cell induced ECM compaction.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/526426DOIDiscussion Paper
ORCID:
AuthorORCID
Mayalu, Michaëlle N.0000-0002-9678-0157
Kim, Min-Cheol0000-0001-6649-9463
Additional Information: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. bioRxiv preprint first posted online Jan. 21, 2019. The authors would like to thank Prof. Roger D. Kamm (MIT) and Taher Saif (UIUC) for their biological insights and advice of the studied system. The authors acknowledge support from the National Science Foundation (NSF), Science and Technology Center (STC) on Emergent Behaviors in Integrated Cellular Systems (EBICS) under Grant CBET-0939511, and Singapore-MIT Alliance of Research and Technology (SMART).
Funders:
Funding AgencyGrant Number
NSFCBET-0939511
Singapore-MIT Alliance of Research and TechnologyUNSPECIFIED
Record Number:CaltechAUTHORS:20190123-125910370
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190123-125910370
Official Citation:Multi-Cell ECM compaction is predictable via superposition of nonlinear cell dynamics linearized in augmented state space. Michaelle Ntala Mayalu, MinCheol Kim, H. Harry Asada. bioRxiv 526426; doi: https://doi.org/10.1101/526426
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92432
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:23 Jan 2019 22:19
Last Modified:23 Jan 2019 22:19

Repository Staff Only: item control page