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Cell fate conversion-Stochastic or determinisitc?

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Posted at 2013-9-24 04:46:36 | All floors |Read mode

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Posted at 2013-9-24 06:34:13 | All floors
Last edited by zhiyuanli In 2013-9-24 06:35 Editor

Very interesting question and I'm also curious about it.
For my mind, the answer is case-specific: under certain conditions, it is deterministic; otherwise it is stochastic with certain probability of cell fate switching.

However I do think most people outside of the field needs more background information...
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Posted at 2013-9-24 14:34:34 | All floors
I'm wondering if it were deterministic, what would be the meaning of it? Is deterministic better than stochastic in some cases?

I remember there was paper talking about the cell fate of bacillus subtilis. It is randomly distributed among population, but the destination of a certain cell is deterministic.

If so, as we discussed last Saturday, it should be considered as stochastic.

However, I have no idea how to test it either experimentally or theoretically.
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Posted at 2013-10-10 14:56:34 | All floors
Here are some figures that might help to illustrate the mathematical pictures of "stochastic" and "deterministic" of cell fate transitions:

Figure1. Map cell fates into attractors.A. a coarse-grained view of cell-fate-controlling Gene Regulatory Networks(GRNs). B. a demonstration of rate equations for cell-fate related genes; C. ademonstration of the state space of gene expressions under one set of parameters;D. an intuitive picture of attractor landscape.


Figure 2. Three basic topologies forcell fates transitions. First row: Basic topologies of fate-decisions. Secondrow: State space of corresponding topology under certain parameter set. Bluedots are attractors, and red arrows are typical trajectories on state space.Third row: Bifurcation diagrams for corresponding topologies. Blue lineindicates attractor positions under different parameters, and blue-dash lineare attractor basin boundaries. Red trajectories indicate the changingdirections of cell states under increasing parameter. For B and C, thebifurcation diagram are under perfectly symmetric parameters. Fourth row:Bifurcation diagram under perturbed parameters.


Figure3. Two pictures of cell fate transition. A. Multi-attractor switching wherecell fate transition is represented by switching between different attractorsunder the same external conditions; B. Parameter induced bifurcation where cellfate transition is induced by changed attractor-landscape under shiftingexternal stimulus. Path 1 and Path 2 refer to two possible ways the landscapegradually changes. C. a representation of the Stochastic model in inducedpluripotency: two attractors co-exist on the same landscape, and cell statesfluctuate to gain the probability of entering the pluripotency attractor fromthe somatic attractor. D. a representation of the Elite model in inducedpluripotency: cells are in different parameter regions, with most of themstaying in the somatic-attractor-only landscape while a small fraction locatingin the pluripotency-favored attractor landscape. Different colors indicate differentattractor landscapes the cell states locating in.




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