FOM Institute AMOLF, Amsterdam, The Netherlands.
PLoS Comput Biol. 2012;8(8):e1002654. doi: 10.1371/journal.pcbi.1002654. Epub 2012 Aug 30.
Embryonic development is driven by spatial patterns of gene expression that determine the fate of each cell in the embryo. While gene expression is often highly erratic, embryonic development is usually exceedingly precise. In particular, gene expression boundaries are robust not only against intra-embryonic fluctuations such as noise in gene expression and protein diffusion, but also against embryo-to-embryo variations in the morphogen gradients, which provide positional information to the differentiating cells. How development is robust against intra- and inter-embryonic variations is not understood. A common motif in the gene regulation networks that control embryonic development is mutual repression between pairs of genes. To assess the role of mutual repression in the robust formation of gene expression patterns, we have performed large-scale stochastic simulations of a minimal model of two mutually repressing gap genes in Drosophila, hunchback (hb) and knirps (kni). Our model includes not only mutual repression between hb and kni, but also the stochastic and cooperative activation of hb by the anterior morphogen Bicoid (Bcd) and of kni by the posterior morphogen Caudal (Cad), as well as the diffusion of Hb and Kni between neighboring nuclei. Our analysis reveals that mutual repression can markedly increase the steepness and precision of the gap gene expression boundaries. In contrast to other mechanisms such as spatial averaging and cooperative gene activation, mutual repression thus allows for gene-expression boundaries that are both steep and precise. Moreover, mutual repression dramatically enhances their robustness against embryo-to-embryo variations in the morphogen levels. Finally, our simulations reveal that diffusion of the gap proteins plays a critical role not only in reducing the width of the gap gene expression boundaries via the mechanism of spatial averaging, but also in repairing patterning errors that could arise because of the bistability induced by mutual repression.
胚胎发育是由决定胚胎中每个细胞命运的空间基因表达模式驱动的。虽然基因表达通常高度不稳定,但胚胎发育通常非常精确。特别是,基因表达边界不仅对胚胎内波动(如基因表达噪声和蛋白质扩散)具有稳健性,而且对形态发生梯度的胚胎间变化也具有稳健性,形态发生梯度为分化细胞提供位置信息。发育如何能够抵抗胚胎内和胚胎间的变化尚不清楚。控制胚胎发育的基因调控网络中的一个常见模式是两个相互抑制的基因对之间的相互抑制。为了评估相互抑制在基因表达模式稳健形成中的作用,我们对果蝇 hunchback(hb)和 knirps(kni)两个相互抑制的间隙基因的最小模型进行了大规模随机模拟。我们的模型不仅包括 hb 和 kni 之间的相互抑制,还包括前形态发生素 Bicoid(Bcd)对 hb 的随机和合作激活以及后形态发生素 Caudal(Cad)对 kni 的激活,以及 Hb 和 Kni 之间的扩散相邻核。我们的分析表明,相互抑制可以显著提高间隙基因表达边界的陡度和精度。与其他机制(如空间平均和合作基因激活)相比,相互抑制使得基因表达边界既陡峭又精确。此外,相互抑制极大地增强了它们对形态发生素水平胚胎间变化的稳健性。最后,我们的模拟揭示了间隙蛋白的扩散不仅通过空间平均化机制在减少间隙基因表达边界的宽度方面起着关键作用,而且在修复由于相互抑制引起的双稳性而可能产生的模式形成错误方面也起着关键作用。