Mechanobiology of Cardiac Outflow Tract Morphogenesis

项目总结 心脏流出道(OFT)的正常生长、分隔和成熟进入带瓣的主动脉和肺 出口对于出生后的有氧循环是必不可少的。1-2%的活产儿和高达30%的早产儿 死亡患者有先天性心脏缺陷，其中许多会影响瓣膜间隔原始组织的重塑， 称为近端和远端流出气垫。尽管付出了很多努力来揭示早期OFT的遗传基础 垫层的形成，这种理解并没有解释临床上相关的生长、凝结阶段 并延伸到瓣膜和隔膜中。此外，新出现的证据表明，地球的形成、生长和 瓣膜间隔附属器的成熟与脑室的成熟是相联系的。粗大先天性瓣膜 畸形导致发育中的脑室内血流动力学变化(通过狭窄和/或返流)， 导致它们在肌纤维结构和小梁图案上的结构差异。虽然其中很多都是 畸形是妊娠可存活的结构性瓣膜缺陷，如二尖瓣脱垂，具有 发育性因素，也会导致过早的心力衰竭和猝死的风险。目前还不清楚 血流动力学紊乱如何驱动共同的胎儿心室和瓣膜重构，部分原因是 目前流行的基因工具缺乏区分遗传和血流动力学因果关系的能力。屠夫实验室有 开创性的创新技术1)量化体内局部机械力在心脏流入、心室、 和OFT结构域，并将其与局部原位基因/蛋白表达进行注册；2)非侵入性可视化 并在活体内精确消融心内组织，无附带损伤；3)直接评估局部空间 整个薄片上的细胞转录本。这项卡罗尔法案补充条款将扩大目前资助的 询问瓣膜和心室重塑如何与它们共同的血流动力学相关联的项目 环境。首先，应用新兴的高分辨率空间转录技术将实现第一 全尺寸胎儿心域(10x10 mm区域)的真正单细胞空间分辨率。这将应用于 在胚胎中唯一识别流入房室、心室和流出道的细胞转录图谱 用假的或血流动力学紊乱的情况治疗，导致建立心脏结构 畸形。这将在畸形的早期和后期进一步执行，通过创新的 用于冷冻切片的精密平面应用装置。接下来，我们将应用新的元胞邻域分析 用于确定与本地结构变化相关的唯一和共享社区的工具 房室瓣、致密和小梁室区以及流出道。蜂窝邻域 然后，候选人将通过二次免疫荧光方法进行验证。这些结果将戏剧性地 提高我们对瓣膜相关畸形如何导致不良的心室重构的理解 功能寿命受损，并识别可预测的多细胞指纹特征 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.