Free-energy-based framework for early forecasting of stem cell differentiation

Suresh, Hamsini; Shishvan, Siamak Soleymani; Vigliotti, Andrea; Deshpande, V.S.

doi:10.1101/692285

Cited by 3 publications

(4 citation statements)

References 37 publications

(74 reference statements)

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“…It is certainly clear that there are bounds on the * c.dunlop@surrey.ac.uk energy budget of the cell [15], with a link between cell contractility and energy consumption demonstrated [16]. Theoretically models have explored this energy budget using energy constraints as drivers of differentiation [17] or cell shape control [18].…”

mentioning

confidence: 99%

Cell strain energy costs of active control of contractility

Solowiej-Wedderburn¹,

Dunlop²

2022

Preprint

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Cell mechanosensing is implicated in the control of a broad range of cell behaviours, with cytoskeletal contractility a key component. Experimentally, it is observed that the contractility of the cell responds to increasing substrate stiffness, showing increased contractile force and changing the distribution of cytoskeletal elements. Here we show using a theoretical model of active cell contractility that upregulation of contractility need not be energetically expensive, especially when combined with changes in adhesion and contractile distribution. Indeed, we show that a feedback mechanism based on maintenance of strain energy would require an upregulation in contractile pressure on all but the softest substrates. We consider both the commonly reported substrate strain energy and active work done. We demonstrate substrate strain energy would select for the observed clustering of cell adhesions on stiffer substrates which also enable an upregulation of total contractile pressure; while localisation of contractility has the greatest impact on the internal work.

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confidence: 99%

Cell strain energy costs of active control of contractility

Solowiej-Wedderburn¹,

Dunlop²

2022

Preprint

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“…However, clear trends emerge when the statistics of these observables are analyzed. The homeostatic ensemble ( 26 ) has been shown to successfully predict these statistics for cells in a range of environments when no external loads are imposed ( 6 , 8 , 27 ). This motivates us to extend the framework to predict the response of cells on substrates subjected to cyclic loading.…”

Section: Dynamic Equilibrium Under Cyclic Strainmentioning

confidence: 99%

“…( 26 ) proposed a statistical framework, called the homeostatic ensemble, that captures the interplay between the cytoskeletal structure and cell morphology. The approach has been shown to accurately predict the distribution of observed shapes of cells, in absence of cyclic loads, in numerous environments ( 6 , 8 , 27 ). Here, we extend this framework to cyclic loading conditions.…”

Section: Introductionmentioning

confidence: 99%

Cell reorientation on a cyclically strained substrate

et al. 2022

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Cyclic strain avoidance, the phenomenon of cell and cytoskeleton alignment perpendicular to the direction of cyclic strain of the underlying two-dimensional substrate, is an important characteristic of the adherent cell organization. This alignment has typically been attributed to the stress-fiber reorganization although observations clearly show that stress-fiber reorganization under cyclic loading is closely coupled to cell morphology and reorientation of the cells. Here we develop a statistical mechanics framework that couples the cytoskeletal stress-fiber organisation with cell morphology under imposed cyclic straining and make quantitative comparisons with observations. The framework accurately predicts that cyclic strain avoidance stems primarily from cell reorientation away from the cyclic straining rather than cytoskeletal reorganisation within the cell. The reorientation of the cell is a consequence of the cell lowering its free-energy by largely avoiding the imposed cyclic straining. Furthermore, we investigate the kinetics of the cyclic strain avoidance mechanism and demonstrate that it emerges primarily due to the rigid body rotation of the cell rather than via a trajectory involving cell straining. Our results provide clear physical insights into the coupled dynamics of cell morphology and stress-fibers, which ultimately leads to cellular organization in cyclically strained tissues.

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“…The homeostatic statistical mechanics description for cells [22] has already been shown to successfully capture a range of observations for smooth muscle cells seeded on elastic substrates [22,23] and for myofibroblasts seeded on substrates micropatterned with stripes of fibronectin [24,25] as well as for the differentiation of hMSCs in response to a range of environmental cues including stiffness of substrates and sizes of adhesive islands [26]. These give us confidence in utilizing the homeostatic mechanics framework to investigate the response of cells on a dense array of micro-posts.…”

Section: Introductionmentioning

confidence: 99%

Response of cells on a dense array of micro-posts

et al. 2020

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We have analysed the response of cells on a bed of micro-posts idealized as a Winkler foundation using a homeostatic mechanics framework. The framework enables quantitative estimates of the stochastic response of cells along with the coupled analysis of cell spreading, contractility and mechanosensitivity. In particular the model is shown to accurately predict that: (i) the extent of cell spreading, actin polymerisation as well as the traction forces that cells exert increase with increasing stiffness of the foundation; (ii) the traction forces that cells exert are primarily concentrated along the cell periphery; and (iii) while the total tractions increase with increasing cell area the average tractions are reasonably Keywords Computational cell mechanics Á Mechano-sensitivity Á Cell signalling Á Focal adhesions Á Actin/myosin contractility In honor of Professor J.N. Reddy for his 75th Birthday.

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Free-energy-based framework for early forecasting of stem cell differentiation

Cited by 3 publications

References 37 publications

Cell strain energy costs of active control of contractility

Cell strain energy costs of active control of contractility

Cell reorientation on a cyclically strained substrate

Response of cells on a dense array of micro-posts

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