The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Tensegrity II. How structural networks influence cellular information processing networks
Abstract
The major challenge in biology today is biocomplexity: the need to explain how cell and tissue behaviors emerge from collective interactions within complex molecular networks. Part I of this two-part article, described a mechanical model of cell structure based on tensegrity architecture that explains how the mechanical behavior of the cell emerges from physical interactions among the different molecular filament systems that form the cytoskeleton. Recent work shows that the cytoskeleton also orients much of the cell's metabolic and signal transduction machinery and that mechanical distortion of cells and the cytoskeleton through cell surface integrin receptors can profoundly affect cell behavior. In particular, gradual variations in this single physical control parameter (cell shape distortion)can switch cells between distinct gene programs (e.g. growth, differentiation and apoptosis), and this process can be viewed as a biological phase transition. Part II of this article covers how combined use of tensegrity and solid-state mechanochemistry by cells may mediate mechanotransduction and facilitate integration of chemical and physical signals that are responsible for control of cell behavior. In addition, it examines how cell structural networks affect gene and protein signaling networks to produce characteristic phenotypes and cell fate transitions during tissue development.
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Cites
Flow-mediated endothelial mechanotransduction
Davies, P. F. (1995) · Physiological Reviews · doi:10.1152/physrev.1995.75.3.519 · Cited by 2,802
Role of cell shape in growth control
Folkman, J., & Moscona, A. (1978) · Nature · doi:10.1038/273345a0 · Cited by 2,422
Reverse engineering of biological complexity
Csete, M. E., & Doyle, J. C. (2002) · Science · doi:10.1126/science.1069981 · Cited by 1,215
Opas, M. (1989) · Developmental Biology · doi:10.1016/s0012-1606(89)80001-6 · Cited by 114
Extracellular matrix controls tubulin monomer levels in hepatocytes by regulating protein turnover.
Mooney, D. J., Hansen, L. K., Langer, R., Vacanti, J. P., & Ingber, D. E. (1994) · Molecular Biology of the Cell · doi:10.1091/mbc.5.12.1281 · Cited by 53
Self-citation
Cited by
Local force and geometry sensing regulate cell functions
Vogel, V., & Sheetz, M. (2006) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm1890 · Cited by 2,328
Mediation of biomaterial-cell interactions by adsorbed proteins: a review
Wilson, C. J., Clegg, R. E., Leavesley, D. I., & Pearcy, M. J. (2005) · Tissue Engineering · doi:10.1089/ten.2005.11.1 · Cited by 1,696
Conserved microtubule–actin interactions in cell movement and morphogenesis
Rodriguez, O. C., Schaefer, A. W., Mandato, C. A., Forscher, P., Bement, W. M., & Waterman-Storer, C. M. (2003) · Nature Cell Biology · doi:10.1038/ncb0703-599 · Cited by 844
Micropatterning as a tool to decipher cell morphogenesis and functions
Théry, M. (2010) · Journal of Cell Science · doi:10.1242/jcs.075150 · Cited by 730
Universal physical responses to stretch in the living cell
Trepat, X., Deng, L., An, S. S., Navajas, D., Tschumperlin, D. J., Gerthoffer, W. T., Butler, J. P., & Fredberg, J. J. (2007) · Nature · doi:10.1038/nature05824 · Cited by 699
Metadata
- Authors
- Ingber, D. E.
- Venue
- Journal of Cell Science
- Publisher
- The Company of Biologists
- Published
- 2003-04-15
- Volume
- 116
- Issue
- 8
- Pages
- 1397-1408
- ISSN
- 0021-9533 (ISSN-L)
- 1477-9137
- OpenAlex
- W2156289700
- Cited by
- 839
- References
- 5
- FWCI
- 15.74
- Type
- journal article
- Language
- en
- Open access
- closed
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