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Systems BiologyCurrent Biology
Peer-reviewed journal article

A bistable autoregulatory module in the developing embryo commits cells to binary fates

Jiaxi ZhaoiD, Mindy Liu Perkins, Matthew NorstadiD, Hernán G. GarcíaiD

Abstract

Positive autoregulation has been repeatedly proposed as a mechanism for cells to adopt binary fates during embryonic development through bistability. However, without quantitatively determining their parameters, it is unclear whether the plethora of positive autoregulatory modules found within developmental gene regulatory networks are actually bistable. Here, we combine in vivo live imaging with mathematical modeling to dissect the binary cell fate dynamics of the fruit fly pair-rule gene fushi tarazu (ftz), which is regulated by two known enhancers: the early (non-autoregulating) element and the autoregulatory element. Live imaging of transcription and protein concentration in the blastoderm revealed that binary Ftz cell states are achieved as ftz expression rapidly transitions from being dictated by the early element to the autoregulatory element. Moreover, we discovered that Ftz concentration alone is insufficient to activate the autoregulatory element, and that this element only becomes responsive to Ftz at a prescribed developmental time. Based on these observations, we developed a dynamical systems model, and quantitated its kinetic parameters directly from experimental measurements. Our model demonstrated that the ftz autoregulatory module is indeed bistable and that the early element transiently establishes the content of the binary cell fate decision to which the autoregulatory module then commits. Further analysis in silico revealed that the autoregulatory element locks the Ftz expression fate quickly, within 35 min of exposure to the transient signal of the early element. Overall, our work confirms the widely held hypothesis that autoregulation can establish developmental fates through bistability and, most importantly, provides a framework for the quantitative dissection of cellular decision-making based on systems dynamics models and real-time measurements of transcriptional and protein dynamics.

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