CAREER: Probabilistic Decision-Making in Natural and Synthetic Gene Circuits

为了应对压力，一些生物有效地“掷骰子”，从各种可能的遗传程序中随机选择。 例如，在细菌枯草芽孢杆菌中，单个细胞对营养限制的反应不同：一些细胞能够从环境中吸收DNA，另一些细胞分化成健壮的孢子，而其余的细胞继续生长和分裂。 这种随机选择的能力对微生物的生存至关重要，并在多细胞生物的整个发育过程中使用。 Elowitz实验室将以土壤细菌枯草芽孢杆菌（Bacillus subtilis）为模型系统，解决基因电路如何让原本相同的细胞随机选择命运的问题。 将使用两种互补的方法分析决定形成孢子的遗传电路。 首先，自动延时荧光显微镜，连同定量图像分析，将被用来确定在决策过程中的单个细胞中的详细的基因表达动态。 其次，合成生物学技术将用于设计、构建和分析大肠杆菌中产生类似反应的更简单的遗传电路。 这些合成电路的功能是它们模拟的更复杂的自然电路的体内模型。 数学建模将为研究计划的各个方面提供信息，包括数据分析和假设的制定。 该研究的更广泛影响将包括开发系统生物学和合成生物学的新课程，以及为研究界开发工具，包括用于细菌生长延时电影单细胞分析的软件。

In response to stress, some organisms effectively 'roll the dice,' selecting randomly from among various possible genetic programs. For example, in the bacteria Bacillus subtilis, individual cells respond to nutrient limitation differently: some become competent to take up DNA from the environment, others differentiate into a robust spore, while the rest continue to grow and divide. This ability to make random choices is crucial in microbial survival, and used throughout the development of multicellular organisms. The Elowitz lab will address the question of how genetic circuits allow otherwise identical cells to choose their fate randomly, using the soil bacteria Bacillus subtilis as a model system. The well-characterized genetic circuitry underlying the decision to sporulate will be analyzed using two complementary approaches. First, automated time-lapse fluorescence microscopy, together with quantitative image analysis, will be used to determine detailed gene expression dynamics in individual cells during the decision-making process. Second, synthetic biology techniques will be used to design, construct, and analyze simpler genetic circuits in Escherichia coli that generate similar responses. These synthetic circuits function as in vivo models of the more complex natural circuits they emulate. Mathematical modeling will inform all aspects of the research program, both in the analysis of data and formulation of hypotheses. The Broader Impact of the research will include the development of new curricula in systems biology and synthetic biology and the generation of tools for the research community, including software for single-cell analysis of time-lapse movies of bacterial growth.