Bayesian Cell Force Estimation Considering Force Directions
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Traction force microscopy is a useful technique for measuring mechanical forces generated by cells. In this method, fluorescent nano beads are embedded in the elastic substrate of cell culture, on which cells are cultured. Then, cellular forces are estimated from bead displacements, which represent the force-induced deformation of the substrate under the cell. Estimating the forces from the bead displacements is not easy when the bead density is low or the locations of cellular attachments are unknown. In this study, we propose a Bayesian algorithm by introducing a prior force direction that is based on cellular morphology. We apply the Bayesian framework to synthetic datasets in conditions under which the bead density is low and cellular attachment points are unknown. We demonstrate that the Bayesian algorithm improves accuracy in force estimation compared with the previous algorithms.
KeywordsTraction force microscopy Cellular force estimation Inverse problem Hierarchical Bayesian model
This work was supported by a JSPS Grant-in-Aid for Scientific Research (C) (25330341) and Scientific Research on Innovative Areas (25102010).
- 5.Edmondson JC, Hatten ME (1987) Glial-guided granule neuron migration in vitro: a high-resolution time-lapse video microscopic study. J Neurosci 7(6):1928–1934Google Scholar
- 14.Stricker J, Sabass B, Schwarz US, Gardel ML (2010) Optimization of traction force microscopy for micron-sized focal adhesions. J Phys 22:194104Google Scholar
- 15.Bridgman PC, Dave S, Asnes CF, Tullio AN, Adelstein RS (2001) Myosin IIB is required for growth cone motility. J Neurosci 21(16):6159–6169Google Scholar
- 20.Landau LD, Lifshitz EM (1970) Theory of elasticity. Course of theoretical physics, 2nd edn. Pergamon, OxfordGoogle Scholar