Symmetry Breaking and Collective Cell Growth in Drosophila Oogenesis

项目总结 在包括哺乳动物在内的许多被研究的动物物种中，未来的卵母细胞在一群细胞中发育，这些细胞 通过细胞质桥梁网络交换分子和细胞器，这些网络是由稳定的 以及强化的细胞动态沟。而这类有趣的多细胞生物的形成和结构 人们对系统进行了广泛的研究，但对其动力学了解甚少，留下了许多关于 卵母细胞的确定和发育未得到回答。我将在果蝇身上调查其中两个问题，一个 继续为动物卵子发生的一般机制提供有价值的见解的实验模型。 使用实验、建模和计算方法，我将研究生殖系中的一个细胞是如何 选择细胞团作为未来的卵母细胞，以及生殖系细胞团如何包括卵母细胞和 支持哺乳细胞在发育过程中生长。具体地说，目标1旨在评估差异 卵母细胞决定的前图案化和自组织机制的贡献。专注于 纺锤体，一种膜结构，在早期卵子发生和其他过程中对细胞间的交流是必不可少的 最近发现的一个涉及mRNA本地化和翻译的正反馈环，我将建立数据- 用于卵母细胞选择的驱动数学模型。与此同时，目标2将研究卵母细胞的生长和 支持细胞，使用生殖系集群作为一个可处理的系统来探索比例定律 通过对单个细胞生长的研究发现，当细胞生长在一起时，细胞的生长会发生变化。特别是，我将把重点放在 关于细胞核和核仁的大小调节，旨在了解它们的大小是如何随着细胞的快速增长而调整的 生殖系细胞团内的体积。完成这些拟议的研究，并由 强劲的初步结果，包括用于3D图像重建的机器学习方法和 形态计量学分析，应该会为动物卵子发生的一些第一步提供新的见解。

PROJECT SUMMARY In many studied animal species, including mammals, the future oocyte develops within a cluster of cells that exchange molecules and organelles through a network of cytoplasmic bridges, which are formed by stabilized and reinforced cytokinetic furrows. While the formation and structure of this interesting class of multicellular systems has been extensively studied, their dynamics is poorly understood, leaving many critical questions about oocyte determination and development unanswered. I will investigate two of these questions in Drosophila, an experimental model that continues to provide valuable insights into general mechanisms of animal oogenesis. Using experimental, modeling, and computational approaches, I will investigate how one cell within the germline cell cluster is chosen to be the future oocyte and how the germline cell cluster comprising the oocyte and supporting nurse cells grows during development. Specifically, Aim 1 is designed to evaluate the differential contributions of the prepatterning and self-organizing mechanisms of oocyte determination. Focusing on the fusome, a membranous structure that is essential for intercellular communication in early oogenesis, and on a recently discovered positive feedback loop involving mRNA localization and translation, I will establish data- driven mathematical models for oocyte selection. In parallel, Aim 2 will investigate growth of the oocyte and supporting cells, using the germline cluster as a tractable system for exploring how the scaling laws established by studies of single cell growth are altered when cells grow together. In particular, I will focus on size regulation of nuclei and nucleoli, aiming to understand how their sizes adjust to rapidly increasing cell volumes within the germline cell cluster. The completion of these proposed studies, which are supported by strong preliminary results, including a machine learning approach for 3D image reconstructions and morphometric analysis, should provide new insights into some of the first steps of animal oogenesis.