A synthetic biology approach to analyze evolution of programmed bacterial death

描述（由申请人提供）： 程序性死亡通常与细菌对压力条件的反应有关，例如饥饿，竞争对手的存在和抗生素治疗。由于死亡对其行为者没有任何好处，细菌程序性死亡的进化是生物学中一个基本的、未解决的问题。一种流行的解释是，死亡是“利他主义的”：它可以为幸存者提供直接或间接的利益。换句话说，死亡可能是合作的最终形式。通过这一假设，可以在公益合作的一般框架下分析程序性死亡的演变。利用这一框架，研究表明，各种细菌病原体的死亡可能产生公共产品。然而，在对微生物社会行为的最终理解方面仍然存在根本性的差距，特别是细菌的程序性死亡。事实上，利他主义死亡的优势从未在实验系统中得到明确证明。解决这一问题的一个主要挑战是自然生物过程的复杂性，其中许多混杂因素模糊了对与死亡有关的益处的解释和定量分析。例如，以前的研究受到了批评，因为涉及的基因操纵导致了多种效应，因此很难区分不同的适应性后果。这些问题使得结果对其他解释开放，例如PCD代表对压力的适应不良反应。我们建议使用合成生物学技术和微流体技术的组合来克服这些限制。特别是，使用一组合成的基因电路在大肠杆菌中实现可调的利他死亡，我们将定量定义的条件下，利他死亡可以成为有利的人口水平，并检查他们的进化动力学中存在的作弊。为了实现这样的分析，我们将开发一个新的基于液滴的平台来研究不同条件下的进化动力学。基于这样的理解，我们将开发和评估新的治疗策略，将利用进化动力学。我们的愿景是， 将产生广泛的影响。首先，它将填补我们对程序性死亡进化的理解中的关键概念空白。其次，它将产生新的见解，了解细菌如何应对病原体介导的压力，这对设计针对细菌病原体的新治疗策略具有重要意义。

DESCRIPTION (provided by applicant): A synthetic biology approach to analyze evolution of programmed bacterial death Programmed death is commonly associated with a bacterial response to stressful conditions, such as starvation, presence of competitors, and antibiotic treatment. As death offers no benefit to its actor, evolution of programmed bacterial death is a fundamental, unresolved problem in biology. A popular explanation is that the death is "altruistic": it can provide direct or indirect benefitsto the survivors. In other words, death may represent the ultimate form of cooperation. By making this assumption, evolution of programmed death can be analyzed under the general framework of public-good cooperation. Using this framework, studies have suggested possible public goods resulting from death in various bacterial pathogens. However, there remains a fundamental gap in the definitive understanding of microbial social behavior in general and programmed bacterial death in particular. Indeed, advantage of altruistic death has never been unequivocally demonstrated in an experimental system. A major challenge in tackling this problem is the complexity of natural biological processes, where numerous confounding factors obscure interpretation and quantitative analysis of the benefits associated with death. For example, previous work has been criticized because gene manipulations involved led to multiple effects and so it is hard to tease apart different fitness consequences. These issues make the results open to alternative explanations, such as PCD representing a maladaptive response to stress. We propose to use a combination of synthetic-biology techniques and microfluidics to overcome these limitations. In particular, using a set of synthetic gene circuits in bacterium Escherichia coli to implement tunable altruistic death, we will quantitatively define the condition under which altruistic death can become advantageous at the population level and examine their evolutionary dynamics in the presence of cheating. To enable such analysis, we will develop a novel droplet-based platform to examine the evolutionary dynamics under different conditions. Building on such understanding, we will develop and evaluate new treatment strategies that will exploit the evolutionary dynamics. It is our vision that the proposed research will have several broad impacts. First, it will fill the critical conceptual gap in our understandig of the evolution of programmed death. Second, it will generate novel insights into how bacteria respond to antibiotic-mediated stress, which has implications for designing novel therapeutic strategies against bacterial pathogens.