Systems analysis of the early phase of yeast bud formation using a combined experimental and theoretical approach

生物细胞对环境作出积极反应的能力是生物最基本的特性之一。一类这样的反应，称为极化，导致在细胞内形成可检测的“头到尾”轴。例如，刺激生长的化学物质的脉冲可能导致一个最初对称的细胞经历形态转变，通过这种转变，它获得了一个平坦而宽的前端和一个拖尾的窄后端。一旦以这种方式极化，细胞可以持续地向诱导化学物质的来源迁移。细胞极性状态与细胞的健康密切相关。形成内脏器官（如肠、卵巢或肾脏）衬里的细胞失去正常的上皮极性，将不可避免地导致细胞增殖。这样的过度生长可能变成恶性肿瘤。如果一个正常的非极性癌细胞设法获得迁移型极性，它就会变得具有运动性，并可能通过转移引起癌症的扩散。因此，理解极性建立背后的机制对生物学和特别是健康研究来说是非常重要的。细胞极性的主要问题仍然困扰着实验和理论生物学家：细胞罗盘的本质是什么？这个“装置”显然位于细胞膜上，在那里它可以感知外部方向信号，然后向细胞内部发出信号。后者是通过物理标记膜结构域来实现的，该结构域注定会与特定的蛋白质复合物一起成为“前部”或“后部”。细节可能因细胞类型而异，但利用蛋白质复合物的自组装簇来区分细胞膜的特定区域的原理似乎是普遍的。为了努力理解这些复杂的过程，我的小组使用数学和计算建模作为研究工具。为了定量表征潜在的分子机制，我们最近开发了一个模型来描述形成这些簇的蛋白质复合物内的局部化学动力学。我们的模型揭示了支撑这种复合体快速组装和拆卸的生化机制。为了解释整个细胞簇是如何响应细胞外刺激而出现的，我们建立了一个细胞尺度的模型，该模型与反应动力学一起包含了细胞膜上和细胞膜与细胞质之间的分子运输。这是一项相当复杂的工作，仔细选择特定系统对其成功至关重要。以实验数据的可得性为主要依据，我选择了发酵酵母芽的形成。个别分子和相互作用，有助于酵母芽的出现已在文献中仔细描述，但这一复杂的发育过程的整体理解仍然缺乏。我的系统建模将通过将单个元素组合在一起形成完整的图像来弥合我们知识上的差距。我们的初步结果表明，在化学中被称为自催化的非线性过程负责蛋白质簇的产生，最终将发育成完全生长的酵母芽。在我们的模型能够产生具体的实验可测试的预测之前，还需要进行更多的实验和理论工作。这项工作将与国际知名的酵母生物学家，教授密切合作。宾夕法尼亚大学的Erfei Bi和杜克大学的Daniel Lew说。他们的实验结果将被我们用来进一步改进模型，而我们的预测将为他们的实验提供信息。该项目将作为系统生物学方法解决复杂生物学问题的一个例子，供其他生物医学研究人员效仿。

The ability of biological cells to actively respond to their environment is one of the most fundamental properties of the living matter. A class of such responses, termed polarization, results in the formation of a detectable 'head-to-tail' axis within the cell. For example, a pulse of growth-stimulating chemicals may cause an initially symmetric cell to undergo a morphological transformation by means of which it acquires a flat and wide front end and a trailing narrow back end. Once polarized in such a way, the cell can persistently migrate towards the source of the inducing chemical. The cellular polarity status is intimately related to the health of the cell. Loss of the normal epithelial polarity of cells that form the lining of internal organs, such as intestine, ovaries or kidneys, will inevitably cause cellular proliferation. Such an overgrowth may become a malignant tumor. If a normally non-polar cancer cell manages to acquire the migratory-type polarity, it becomes motile and may cause the spread of cancer through metastases. The understanding of the mechanisms that underlie the polarity establishment is therefore highly important for the biology in general and the health research in particular. The major question of cell polarity that still baffles experimental and theoretical biologists is: What is the nature of the cellular compass? This 'device' is apparently located on the cellular membrane where it can perceive the external directional cues and then signal to the cellular insides. The latter is achieved by physically marking a membrane domain that is destined to become 'front' or 'back' with the specific protein complexes. The details may vary from one cell type to another, but the principle of using self-assembling clusters of protein complexes to differentiate specific areas from the rest of the cell membrane appears to be universal. Striving to understand these complex processes, my group uses mathematical and computational modeling as research tools. To quantitatively characterize the underlying molecular mechanisms, we recently developed a model that describes the local chemical kinetics within the protein complexes that form these clusters. Our model shed light on the biochemical machinery that underpins the fast assembly and disassembly of such complexes. To explain how the entire clusters emerge in response to the extracellular stimuli, we have built a cell-scale model that together with reaction dynamics also incorporates the transport of molecules on the cell membrane and between the membrane and the cytoplasm. This is a considerably more complex endeavor and the careful choice of a specific system is crucial for its success. Based on the availability of experimental data as the major criterion, I selected the formation of baking yeast bud. Individual molecules and interactions that contribute to the emergence of yeast bud had been carefully described in the literature but the overall understanding of this complex developmental process is still lacking. My systems modeling will bridge this gap in our knowledge by bringing individual elements together to form the complete picture. Our preliminary results indicate that a nonlinear process known in chemistry as the autocatalysis is responsible for the creation of the protein cluster that will eventually develop into the fully grown yeast bud. More work, both experimental and theoretical, is necessary before our model can generate concrete experimentally testable predictions. This work will be done in a close collaboration with the internationally renowned yeast biologists, Profs. Erfei Bi of the University of Pennsylvania and Daniel Lew of Duke University. Their experimental results will be used by us to further improve the model while our predictions will inform their experiments. This project will serve as an example of a systems biology approach to complex biological problems to be followed by other biomedical researchers.