Patterning mechanisms that restrict cardiac cushion formation in zebrafish

描述(由申请人提供)：心脏瓣膜通过促进单向血流在心脏功能中发挥关键作用，也是先天性心脏病的常见靶点。房室瓣的形成是由精确定位于房室交界处(也称为房室管或AVC)的信号触发的。这些信号指示局部的心内膜膨胀到心管的管腔中，形成被称为心垫的结构，这些结构后来重塑为瓣叶。对斑马鱼的研究表明，在AVC的典型Wnt途径活动促进了编码BMP信号的基因的表达，从而诱导缓冲形成。心脏的正常发育需要将这些诱导信号限制到AVC，但我们并不了解导致这种限制的机制。我们也不知道这个系统的重要的一般属性，例如WNT信令模式本身还是它是否中继上行模式。我将追求两个具体目标，以扩大我们对AVC图案化网络的组件和系统级属性的了解。我的第一个目标是研究5-羟色胺信号，我们的初步数据表明，它在AVC模式中起着关键作用。用5-羟色胺受体拮抗剂酮丝氨酸处理胚胎后，Bmp4的异位表达超出了AVC的界限。这种表型是通过敲除5-羟色胺受体htr2a来概括的，这表明通过该受体传递的5-羟色胺信号是必不可少的。我推测，5-羟色胺信号参与了缓冲诱导信号对AVC的限制。为了验证这一假设，我将首先检查一组标记，以彻底描述htr2a缺陷胚胎中的缓冲图案缺陷。接下来，我将使用药理学扰动来确定5-羟色胺信号对AVC模式至关重要的时间窗口。我还将检查Wnt途径的读数，并进行上位性实验，以确定5-羟色胺是否作用于Wnt途径的上游或下游，以限制缓冲诱导。最后，我将使用全球5-羟色胺水平的药理学扰动和htr2a的错误表达来确定5-羟色胺信号对于缓冲限制是有指导意义的还是允许的。在我的第二个目标中，我将测试WNT信号模式本身的假设，即自组织。自组织系统具有一些有用的性质，如稳定性和对波动的稳健性。这些系统通常包含一个自我放大的部分(正反馈)，它被自身产生的抑制(自抑制)或竞争对手的自我放大所平衡 控制相邻域的组件(抑制串扰)。我将使用新的光遗传学技术和现场信号记者相结合的方法来确定AVC中的Wnt信号是否显示出自组织系统的特征，如正反馈、自抑制和抑制性串扰。总之，这些研究将揭示AVC模式网络的重要机制信息和系统水平的特性，这将有助于我们理解先天性心脏缺陷的病因。

DESCRIPTION (provided by applicant): Heart valves play a critical role in cardiac function by promoting unidirectional blood flow and are a frequent target of congenital heart disease. Atrioventricular valve formation is triggered by signals that are precisely localized to the junctin between chambers (also known as the atrioventricular canal or AVC). These signals instruct the local endocardium to bulge into the lumen of the heart tube, forming structures known as cardiac cushions that later remodel into valve leaflets. Studies in zebrafish have shown that canonical Wnt pathway activity at the AVC promotes the expression of genes encoding Bmp signals that induce cushion formation. Proper heart development necessitates the restriction of these inductive signals to the AVC, yet we do not understand the mechanisms responsible for this confinement. We also do not know important general properties of this system, such as whether Wnt signaling patterns itself or if it relays an upstream pattern. I will pursue two specifc aims to expand our knowledge of the components and systems-level properties of the AVC patterning network. My first aim investigates serotonin signaling, which our preliminary data suggest has a critical role in AVC patterning. Treatment of embryos with the serotonin receptor antagonist ketanserin results in ectopic bmp4 expression beyond the boundaries of the AVC. This phenotype is recapitulated by knockdown of the serotonin receptor htr2a, suggesting that serotonin signaling through this receptor is essential. I hypothesize that serotonin signaling participates in the confinement of cushion-inducing signals to the AVC. To test this hypothesis, I will first examine a panel of markers to thoroughly characterize the cushion patterning defect in htr2a-deficient embryos. I will next use pharmacological perturbations to determine the time window when serotonin signaling is critical for AVC patterning. I will also examine Wnt pathway readouts and perform epistasis experiments to determine whether serotonin acts upstream or downstream of the Wnt pathway to restrict cushion induction. Finally, I will use pharmacological perturbations of global serotonin levels in combination with htr2a misexpression to determine whether serotonin signaling is instructive or permissive for cushion restriction. In my second aim, I will test the hypothesis that Wnt signaling patterns itself, i.e. self- organizes. Self-organizing systems have several useful properties such as stability and robustness to fluctuations. These systems often contain a self-amplifying component (positive feedback) that is balanced by inhibition generated either by itself (autoinhibition) or by a rival self-amplifying component that dominates an adjacent domain (inhibitory crosstalk). I will use a combination of novel optogenetic techniques and live signaling reporters to determine whether Wnt signaling in the AVC displays hallmark characteristics of self-organizing systems, such as positive feedback, autoinhibition, and inhibitory crosstalk. Together, these studies will reveal important new mechanistic information and systems-level properties of the AVC patterning network, which will help us to understand the etiology of congenital heart defects.