Designing and analyzing multi-generational switching in gene circuits for single cell biology

记忆是所有生物体的核心，从单细胞细菌到人类，但人们对记忆在生物学中是如何控制的知之甚少。该项目计划通过建立能够在细菌中记忆的电路来揭开这个长期存在的谜团。细菌系统是这项研究的理想选择，因为它们比多细胞生物体更容易获得，并且可以进行超高精度的测量。该项目依靠创新的生物友好芯片来收集活细菌的流数据。这项研究中涉及的具体问题是：(1)在细菌中，记忆是如何通过数百代人遗传的？(2)记忆如何足够强大，以承受分子水平的巨大变化，如蛋白质的合成和降解？该项目将对科学教学产生很大影响；许多课程已经采用了这项工作的初步例子。更广泛地说，由于这个项目的目标是证明工程电路可以准确地在活细胞中执行预定的任务，这一努力将从根本上改变我们为医学和其他用途开发新工具的方式。合成生物学的主要目标之一是构建遗传电路，其特性不仅随着条件的变化而平均稳健，而且可以在单个细胞中准确地运行而不受随机波动的破坏。在许多情况下，动力学还需要在多代时间尺度上进行，这特别具有挑战性，因为即使分子硬件被更换，也必须记住状态。自然系统经常面临类似的挑战，尽管表观遗传记忆通常与高等有机体有关，但细菌也必须在可以维持数十代甚至数百代的替代状态之间做出决定。基于化学反应随机理论的见解，并受到大量初步成功的鼓舞，该项目将在单个电池中建造具有多代动力学和高精度计时的合成振荡器和开关。它还将描述表现出缓慢切换的自然遗传电路的开启和关闭状态，特别关注DNA环路。最后，将结合经典细菌遗传学、微流体工程、合成遗传振荡器、基于DNA环的脉冲发生器和数学分析来探索鞭毛启动子的缓慢动力学，这再次揭示了耐人寻味的多代效应。因此，该项目采用了一种广泛的系统和综合方法来量化单个细菌细胞水平上的多代切换。

Memory is central to all living organisms from single-celled bacteria to humans and yet very little is known about how memory is controlled in biology. This project proposes to uncover this long-standing mystery by building circuits that are capable of memory in bacteria. Bacterial systems are ideal for this study because they are more accessible than multi-cellular organisms, and they allow for ultra-high precision measurements. The project relies on innovative biologically friendly chips to collect streaming data from live bacteria. Specific questions address in this study are (1) How is memory inherited through hundreds of generations in bacteria? (2) How might memory be robust enough to withstand large changes at the molecular level such as synthesis and degradation of proteins? The project will have a large impact on the teaching of science; many courses have already adopted preliminary examples from this work. More broadly, since the goal of this project is to demonstrate that engineered circuits can accurately perform predefined tasks in living cells, this effort will fundamentally change the way we develop new tools for medicine and other uses.One of the main goals of synthetic biology is to construct genetic circuits whose properties are not only robust on average as conditions change, but which can operate accurately in single cells without being corrupted by stochastic fluctuations. In many cases the dynamics also need to play out on a multi-generational time scale, which is particularly challenging because the states must be remembered even though the molecular hardware is replaced. Natural systems often face similar challenges, and though epigenetic memory is typically associated with higher organisms, bacteria must also decide between alternative states that can be maintained for tens or even hundreds of generations. Based on insights from stochastic theory for chemical reactions, and encouraged by substantial preliminary successes, this project will build synthetic oscillators and switches with multigenerational dynamics and highly precise timing in single cells. It will also characterize the on- and off-states of natural genetic circuits that exhibit slow switching, with a particular focus on DNA looping. Finally, a combination of classic bacterial genetics, microfluidic engineering, synthetic genetic oscillators, pulse generators based on DNA looping, and mathematical analyses will be used to probe the slow dynamics of flagellar promoters, which again reveal intriguing multi-generational effects. Thus, the project takes a broad systems and synthetic approach to quantify multigenerational switching at the level of individual bacterial cells.