Quantitative Cell Geometry - Defining Cell State at the Organelle Level

定量细胞几何学 - 在细胞器水平定义细胞状态

• 批准号: 1515456
• 负责人: Wallace Marshall
• 金额: $ 90万
• 依托单位: University of California-San Francisco
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-15 至 2019-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1515456&HistoricalAwards=false
• 关键词: Quantitative; Cell; Geometry; Defining; State

Cells are complex machines filled with molecules that can perform simple logic functions like the circuits inside a computer. Many cells can perform complex behaviors such as engulfing other cells, movement towards a source of food, and remembering past events. Even though most cellular components are believed to be discovered, it is still unclear how the molecules in a cell work together to perform relatively complex actions. This project seeks to solve the problem by applying concepts from theoretical computer science to understand how the cell switches from one activity to another. This will open up new possibilities for re-engineering cells by reprogramming their internal controls. This research program will create novel educational and outreach opportunities based on exposing students from a variety of scientific backgrounds, as well as members of the public with interests in electronics and computer hobbies, to the idea that cells can be viewed as computing machines; therefore awareness of quantitative cell biology among the next generation of engineering students will increase. While general understanding of the molecular biology of cells is constantly increasing, it has proven difficult to integrate this molecular scale information into a global view of how cells make decisions and perform complex behaviors like migration, phagocytosis, and division. The goal of this project is to connect the huge gap in complexity and detail from the molecular scale to the level of cell behavior by using concepts from computer science. In computer science, the highly complex details of electronic circuitry can often be understood, analyzed, and designed by using abstract models in which a complex system is represented by a finite set of states, allowing behavior to be represented by transitions between states. Such models are called finite state automata and they are the most fundamental representation of a computing device. In this project cells are described as finite state automata, by using organelle size measurements to identify and define distinct states. It is hypothesized that an organelle-level state description will allow for the reduction of the dimensionality of the state space from millions of dimensions corresponding to individual molecules in the cell down to a much smaller number of dimensions based on organelle morphological measurements that are readily observable in living cells. Large numbers of cells will be imaged at high resolution, numerical descriptors of each organelle will be described, and a state space for cellular organization will be defined using statistically rigorous methods to define states and state transitions. The investigators will explore how chemical and mechanical inputs to the cell drive transitions within this state space, thus providing a way to view the cell as a type of finite-state automaton. Such a representation will also provide a framework for synthetic biology applications in which the regulatory pathways that determine state transitions could be re-wired to produce different behaviors, essentially turning a single cell into a programmable microdevice. The conceptual framework of the cell as a decision-making computational device will be harnessed to present outreach exhibits at Maker Faires, which are an ongoing series of events that bring together electronics, computer, and crafts hobbyists. This project is co-funded by the program in Cellular Dynamics and Function in the division of Molecular and Cellular Biosciences in the Directorate of Biological Sciences and the programs in Statistics and Mathematical Biology in the division of Mathematical Sciences in the Directorate of Mathematics and Physical Sciences.

细胞是充满分子的复杂机器，可以执行简单的逻辑功能，就像计算机内部的电路一样。许多细胞可以执行复杂的行为，如吞噬其他细胞，向食物源移动，并记住过去的事件。尽管大多数细胞成分被认为已经被发现，但仍然不清楚细胞中的分子如何协同工作以执行相对复杂的行动。该项目旨在通过应用理论计算机科学的概念来理解细胞如何从一种活动切换到另一种活动来解决这个问题。这将为通过重新编程细胞的内部控制来重新设计细胞开辟新的可能性。这项研究计划将创造新的教育和推广机会，让来自各种科学背景的学生以及对电子和计算机爱好感兴趣的公众了解细胞可以被视为计算机器的想法;因此，下一代工程专业学生对定量细胞生物学的认识将增加。 虽然对细胞分子生物学的一般理解不断增加，但事实证明，很难将这种分子尺度的信息整合到细胞如何做出决定和执行复杂行为（如迁移，吞噬和分裂）的全局视图中。该项目的目标是通过使用计算机科学的概念，将分子尺度上的复杂性和细节的巨大差距与细胞行为水平联系起来。 在计算机科学中，电子电路的高度复杂的细节通常可以通过使用抽象模型来理解，分析和设计，其中复杂系统由有限的状态集表示，允许行为由状态之间的转换表示。这种模型被称为有限状态自动机，它们是计算设备的最基本表示。在这个项目中，细胞被描述为有限状态自动机，通过使用细胞器尺寸测量来识别和定义不同的状态。假设细胞器水平的状态描述将允许状态空间的维度从对应于细胞中的单个分子的数百万个维度降低到基于在活细胞中容易观察到的细胞器形态测量的小得多的维度。大量的细胞将在高分辨率下成像，每个细胞器的数字描述符将被描述，并将使用统计上严格的方法来定义状态和状态转换来定义细胞组织的状态空间。研究人员将探索细胞的化学和机械输入如何驱动该状态空间内的转换，从而提供一种将细胞视为有限状态自动机的方法。这种表示还将为合成生物学应用提供一个框架，其中决定状态转换的调节途径可以重新连接以产生不同的行为，基本上将单个细胞转变为可编程的微器件。细胞作为一个决策计算设备的概念框架将被利用来在Maker Faires展示外展展览，这是一个持续的系列活动，汇集了电子，计算机和手工艺爱好者。该项目由生物科学理事会分子和细胞生物科学部门的细胞动力学和功能计划以及数学和物理科学理事会数学科学部门的统计学和数学生物学计划共同资助。