Mapping combinatorial stress responses in bacteria using chimeric proteins and probabilistic modelling

生命系统为了生存、生长和繁殖而适应不断变化的环境。迄今为止，适应性反应的特征已经以相当一维的方式进行了研究，但我们知道细胞是通过负责细胞生长和活力的关键参与者之间的相互作用网络来运作的。这些参与者可以感受到压力，有些会导致新的参与者出现在细胞中，有些会以不同的方式克服压力。然而，这些不同的参与者之间的关系及其运作水平在很大程度上是未知的。特别是是否一个单一的唯一解决方案，一组强加的条件是所有可以合理地在细胞中运作是一个主要的未知数。细胞可接受的边界条件的知识将极大地帮助推进需要细胞特殊性质的工作，例如在许多生物技术和合成生物学环境中。通过研究两种重要的但相对易于实验的单细胞细菌，我们将研究当细胞对压力做出反应时细胞成分的变化以及它们的反应模式如何对压力做出综合反应。为了做到这一点，我们将收集细胞活动的几个不同区域的数据，并将使用新的控制蛋白质干扰细胞，以重新定向反应，使其远离特定的强加压力。将进行数据分析和数学建模，以整合和描述观察到的细胞行为，并帮助解释有助于细胞反应的过程如何作为一个整体工作。数据收集的直接目标是为细胞反应机制模型的开发和评价提供信息。我们选择在两种不同的细菌有机体中进行相同的实验程序。这一比较维度的拟议研究项目使我们能够探索潜在的进化方面的压力，是密切相关的细菌发病机制的反应。这也有可能为合成生物学的未来分析或指导微生物进化的尝试提供信息。在研究计划结束时，我们希望能够更好地预测细胞如何科普环境的巨大变化，通过了解细胞内的哪些活动是实现适应压力的关键。这项工作的结果应该提供关于细胞如何为特定目的向前进化的见解，并确定可能存在的特定弱点，这些弱点可能为补救疗法提供新的靶点，如新的抗生素靶点。

Living systems adapt to changing environments in order to survive and to grow and reproduce. Features of an adaptive response have to date been studied in a fairly one dimensional way, yet we know that the cell operates using networks of interactions between the key players that are responsible for the cells growth and viability. These players can sense stress, some will cause new players to appear in the cell, and some of these will work to overcome the stress in different ways. However the relationships between these different players and the levels at which they operate are largely unknown. In particular whether or not a single unique solution to a set of imposed conditions is all that can reasonably operate in the cell is a major unknown. Knowledge of the boundary conditions acceptable to a cell will greatly help advance work where special properties of a cell are desirable, as for example in many biotechnological and synthetic biology settings. By studying two important but relatively experimentally amenable single cell bacteria we will study what cell components change when the cells respond to stress and how their patterns of response amount to an integrated response to stress. To do so we will collect data across several different areas of cell activity, and will perturb cells using novel control proteins to redirect responses away from particular imposed stresses. Data analysis coupled to mathematical modelling will be conducted in order to integrate and describe the observed cellular behaviour, and to help explain how the processes contributing to the cell's responses work as a whole. The collection of data is targeted directly at informing the development and evaluation of mechanistic models of cell response. We have chosen to conduct the same experimental programme in two different bacterial organisms. This comparative dimension to the proposed research project allows us to explore the evolutionary aspects underlying the response to stresses that are intimately linked to bacterial pathogenesis. This also has the potential to inform future analyses in synthetic biology or attempts to direct microorganismal evolution. At the end of the research program we expect to able to better predict how cells cope with large changes in their environments, through a knowledge of which activities within the cell are key to achieving adaptation to stress. Outcomes of the work should provide insights into how cells might be forward evolved for particular purposes, and identify where particular vulnerabilities might exist that may suggest new targets for remedial therapies such as new antibiotic targets.