Spatial modeling algorithms for reactions and transport in biological cells
Biological cells rely on precise spatiotemporal coordination of biochemical reactions to control their functions. Such cell signaling networks have been a common focus for mathematical models, but they remain challenging to simulate, particularly in realistic cell geometries. Here we present Spatial Modeling Algorithms for Reactions and Transport (SMART), a software package that takes in high-level user specifications about cell signaling networks and then assembles and solves the associated mathematical systems. SMART uses state-of-the-art finite element analysis, via the FEniCS Project software, to efficiently and accurately resolve cell signaling events over discretized cellular and subcellular geometries. We demonstrate its application to several different biological systems, including yes-associated protein (YAP)/PDZ-binding motif (TAZ) mechanotransduction, calcium signaling in neurons and cardiomyocytes, and ATP generation in mitochondria. Throughout, we utilize experimentally derived realistic cellular geometries represented by well-conditioned tetrahedral meshes. These scenarios demonstrate the applicability, flexibility, accuracy and efficiency of SMART across a range of temporal and spatial scales.
Authors
- Emmet A. Francis (ORCID: https://orcid.org/0000-0001-6070-805X)
- Jørgen S. Dokken (ORCID: https://orcid.org/0000-0001-6489-8858)
- Padmini Rangamani (ORCID: https://orcid.org/0000-0001-5953-4347)
- Marie E. Rognes (ORCID: https://orcid.org/0000-0002-6872-3710)
- Justin G. Laughlin (ORCID: https://orcid.org/0000-0001-8229-9760)
- Christopher T. Lee (ORCID: https://orcid.org/0000-0002-0670-2308)
- Henrik Finsberg (ORCID: https://orcid.org/0000-0003-3766-2393)
Institutions
- Lawrence Livermore National Laboratory (US)
- Simula Research Laboratory (NO)
- UC San Diego Health System (US)
- University of California San Diego (US)
Publication Details
- Journal
- Nature Computational Science
- Published
- 2024-12-19
- DOI
- https://doi.org/10.1038/s43588-024-00745-x
- Citations
- 7
- Primary Topic
- Gene Regulatory Network Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.64
Funders
- National Science Foundation
- American Society for Engineering Education
- European Commission
- Norges Forskningsråd
- University of California, San Diego
- Multidisciplinary University Research Initiative
- Air Force Office of Scientific Research