Literature DB >> 25763973

Stochastic phenotype transition of a single cell in an intermediate region of gene state switching.

Hao Ge1,2, Hong Qian3, X Sunney Xie1,4.   

Abstract

Multiple phenotypic states often arise in a single cell with different gene-expression states that undergo transcription regulation with positive feedback. Recent experiments show that, at least in E.coli, the gene state switching can be neither extremely slow nor exceedingly rapid as many previous theoretical treatments assumed. Rather, it is in the intermediate region which is difficult to handle mathematically. Under this condition, from a full chemical-master-equation description we derive a model in which the protein copy number, for a given gene state, follows a deterministic mean-field description while the protein-synthesis rates fluctuate due to stochastic gene state switching. The simplified kinetics yields a nonequilibrium landscape function, which, similar to the energy function for equilibrium fluctuation, provides the leading orders of fluctuations around each phenotypic state, as well as the transition rates between the two phenotypic states. This rate formula is analogous to Kramers' theory for chemical reactions. The resulting behaviors are significantly different from the two limiting cases studied previously.

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Year:  2015        PMID: 25763973     DOI: 10.1103/PhysRevLett.114.078101

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  23 in total

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3.  Time-dependent saddle-node bifurcation: Breaking time and the point of no return in a non-autonomous model of critical transitions.

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Journal:  Biophys J       Date:  2019-08-27       Impact factor: 4.033

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7.  STOCHASTIC DYNAMICS OF CELL LINEAGE IN TISSUE HOMEOSTASIS.

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8.  Switching off: The phenotypic transition to the uninduced state of the lactose uptake pathway.

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9.  Intrinsic phenotypic stability of a bi-stable auto regulatory gene.

Authors:  Azim-Berdy Besya; Andreas Grönlund
Journal:  Sci Rep       Date:  2016-03-10       Impact factor: 4.379

10.  Stochastic fluctuations can reveal the feedback signs of gene regulatory networks at the single-molecule level.

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Journal:  Sci Rep       Date:  2017-11-22       Impact factor: 4.379

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