Mechanobiology of Cardiac Outflow Tract Morphogenesis

项目摘要 心脏流出道（OFT）正常生长、分隔和成熟为带瓣主动脉和肺动脉 出口对于出生后的氧合循环至关重要。1-2%的活产婴儿和高达30%的早产胎儿 死亡有先天性心脏缺陷，其中许多影响瓣膜间隔原始组织的重塑， 称为近端和远端流出缓冲垫。尽管人们花了很多努力来揭示早期OFT的遗传基础， 垫形成，这种理解并没有解释临床相关的阶段的增长，冷凝 并延伸成裂孔和隔膜。此外，新出现的证据表明， 心瓣膜中隔装置的成熟与心室的成熟相结合。先天性大瓣膜 畸形引起发育中的心室内的血液动力学变化（通过狭窄和/或回流）， 导致它们的肌纤维结构和小梁图案的结构差异。虽然其中许多 畸形是妊娠期存活的结构性瓣膜缺陷，如二尖瓣脱垂， 发育起源，也会引起心室过早衰竭和猝死的风险。目前未知 血流动力学扰动如何驱动胎儿心室和瓣膜重塑，部分原因是 流行的遗传学工具缺乏将遗传学因果关系与血液动力学因果关系分开的能力。屠夫实验室 开创性的创新技术1）量化心脏流入，心室， 和OFT结构域，并将它们与局部原位基因/蛋白质表达进行配准，2）非侵入性地可视化 并且精确消融心内组织而没有体内附带损伤，以及3）直接评估局部空间 整个薄切片上的细胞转录组。这一CAROL法案补充将扩大目前的资助 研究瓣膜和心室重塑如何与其共享的血流动力学相关联的项目 环境首先，新兴的最先进的高分辨率空间转录组学将首先应用于实现 在全尺寸胎儿心脏区域（10 x10 mm区域）上实现真正的单细胞空间分辨率。这将适用于 在胚胎中唯一识别流入房室、心室和流出道细胞转录谱 接受假治疗或血流动力学紊乱的情况，导致建立心脏结构 畸形这将在畸形的早期和晚期进一步进行，通过创新的 用于冷冻切片的精确平面应用的装置。接下来，我们将应用新的细胞邻域分析 工具来确定独特的和共享的社区，与当地的结构变化， 房室瓣、致密和小梁心室域和流出道。细胞邻域 然后通过第二免疫荧光方法验证候选物。这些结果将显著 提高我们对瓣膜相关畸形如何诱导不良心室重构的理解 功能寿命受损，并确定多细胞指纹签名，可以预测 这些风险。

PROJECT SUMMARY Proper growth, septation, and maturation of the cardiac outflow tract (OFT) into valved aortic and pulmonary outlets are essential for oxygenated circulation after birth. 1-2% of live births and up to 30% of pre-term fetal deaths have congenital heart defects, many of which affect the remodeling of the valvuloseptal primordial tissues, called the proximal and distal outflow cushions. Despite much effort uncovering the genetic basis of early OFT cushion formation, this understanding has not explained the clinically relevant phases of growth, condensation and elongation into valves and septa. Further, emerging evidence suggests that the formation, growth, and maturation of the valvuloseptal appratus is coupled with that of the ventricles. Gross congenital valve malformations induce hemodynamic changes within the developing ventricles (via stenosis and/or regurgitation), leading to structural differences in their myofiber architecture and trabecular patterning. While many of these malformations are gestationally survivable, structrural valvular defects like mitral valve prolapse, which have a developmental origin, also incur premature ventricular failure and risk of sudden death. It is currently unknown how hemodynamic perturbations drive shared fetal ventricular and valvular remodeling, in part because prevailing genetic tools lack the power to separate genetic from hemodynamic causality. The Butcher lab has pioneered innovative technology 1) to quantify local in vivo mechanical forces within cardiac inflow, ventricular, and OFT domains, and register them with local in situ gene/protein expression, 2) to non-invasively visualize and precisely ablate intracardiac tissues without collateral damage in vivo, and 3) to directly assess local spatial cellular transcriptomes across entire thin sections. This CAROL Act Supplement will expand the current funded project to interrogate how valvular and ventricular remodeling is coupled to their shared hemodynamic environment. First, emerging state of the art high-resolution spatial transcriptomics will be applied to achieve first ever true single-cell spatial resolution across full-size fetal heart domains (10x10 mm areas). This will be applied to uniquely identify inflow atrioventricular, ventricular, and outflow tract cellular transcriptional profiles in embryos treated with sham or hemodynamically perturbed conditions leading to established cardiac structural malformations. This will be further performed at early and late stages of malformation, enabled by an innovative device for precise planar application of cryosections. Next, we will apply novel cellular neighborhood analysis tools to determine unique and shared neighborhoods that associate with local structural changes in the atrioventricular valves, compact and trabecular ventricular domains, and outflow tracts. Cellular neighborhood candidates will then be verified by secondary immunofluorescence methods. These results will dramatically improve our understanding of how valve-related malformations induce undesirable ventricular remodeling towards impaired functional longevity, and identify multi-cellular fingerprint signatures that could be predictive of these risks.