Collaborative Research: Spatiotemporal Dynamics of Synthetic Microbial Consortia

合成生物学的目标是设计细胞的遗传密码，用于实际应用，如生产生物燃料和遗传疗法。然而，大多数人工合成的微生物是在单细胞水平上发挥作用的。这些生物体无法协调它们的活动，从而限制了它们产生巨大影响的能力。相比之下，合成多细胞系统是由旨在协调行动以实现目标的细胞组成的。这种群体的协调行为可能比不协调的细胞集合更复杂、更灵活、更有影响力。创造这种多细胞系统的一种方法是通过工程合成微生物联合体--各种基因工程微生物的聚集体，它们共同完成任务。一个联合体内组成菌株的协调活动可能会显示出难以改造成单一菌株的紧急行为。在它们的核心，合成联合体中的单个菌株与其他合成工程微生物相似，因为它们的基因序列被故意改变。合成联合体中的单个细胞通过细胞间信号通路相互通信。因此，在设计合成微生物联合体时，必须考虑到更大种群内细胞和菌株的不断变化的空间排列。然而，微生物联合体内细胞间信号传递的时空动力学还知之甚少，限制了我们设计大型合成多细胞联合体的能力。在这里，PI将开发数学方法来描述合成微生物联合体的动力学。为了做到这一点，他们将使用一种结合实验合成生物学、微流体工程和数学生物学的跨学科方法。通过审查日益复杂的财团，私人投资促进机构将开发复杂的数学和计算模型的层次结构。这项工作的总体目标是更好地了解合成微生物联合体的复杂、新兴的动力学，并通过在空间和时间上协调基因活动来设计实现特定目标的联合体。大多数合成基因电路已经建立在单个菌株中，并在单细胞水平上运行。然而，为了实现合成生物学的全部潜力，我们需要能够设计出能够在不同菌株内和不同菌株之间相互作用的有机体。合成微生物联盟可以协调整个种群的基因表达，或者通过在集体内承担不同的责任来专门化。这使得联合体比非相互作用的细胞社区更有效率，并具有更广泛的功能。然而，联合体越大，就越难协调组成细胞的行为。这是因为分子在细胞外介质中的有限扩散使得很难协调通过细胞间信号相互作用的基因网络的活动。为了理解、合理设计和控制大种群，有必要开发和验证描述大规模种群范围基因调控的基因网络动力学的数学和计算模型。这是具有挑战性的，因为微生物群落的动力学是随机的、非线性的、空间上不均匀的和多尺度的。模型必须考虑单个细胞内遗传电路的非线性动力学，调节细胞之间相互作用的信号分子的空间扩散，以及由于细胞生长和分裂而改变空间构型的多个混合细菌种群的动力学。在拟议的工作中，PI将开发合成微生物群落的时空动力学的数学和计算模型。为了做到这一点，他们将使用一种结合实验合成生物学、微流体工程和数学生物学的跨学科方法。通过审查日益复杂的财团，私人投资促进机构将建立一个日益复杂的数学和计算模型的层次结构。这项工作的总体目标是更好地了解合成微生物联合体的复杂、紧急动态，并设计跨空间和时间协调基因活动的工程联合体。

Synthetic biology aims to engineer the genetic code of cells for practical applications such as the production of biofuels and genetic therapies. However, most synthetically engineered microbes act at the single-cell level. Such organisms cannot coordinate their activity, limiting their ability to make large impacts. In contrast, synthetic multicellular systems are composed of cells designed to act in concert to achieve their goals. The coordinated behaviors of such populations can be more complex, flexible and impactful than that of uncoordinated collections of cells. One method of creating such multicellular systems is through the engineering of synthetic microbial consortia - conglomerations of various strains of genetically engineered microbes that work together to achieve tasks. The coordinated activity of constituent strains within a consortium can display emergent behaviors that are difficult to engineer into a single strain. At their core, the individual strains in a synthetic consortium are similar to other synthetically engineered microbes, as their genetic sequences have been purposefully altered. Individual cells within a synthetic consortium communicate with one another through intercellular signaling pathways. Therefore, when designing synthetic microbial consortia, one must take into account the continually changing spatial arrangement of cells and strains within the greater population. However, the spatio-temporal dynamics of intercellular signaling within microbial consortia are poorly understood, limiting our ability to engineer large synthetic multicellular consortia. Here, the PIs will develop mathematical approaches for describing the dynamics of synthetic microbial consortia. To do so, they will use an interdisciplinary approach that combines experimental synthetic biology, microfluidic engineering, and mathematical biology. By examining increasingly complex consortia, the PIs will develop a hierarchy of sophisticated mathematical and computational models. The overall goal of this work is to better understand the complex, emergent dynamics of synthetic microbial consortia, and to engineer consortia that achieve specific goals by coordinating gene activity across space and time.The majority of synthetic gene circuits have been built within a single strain and operate at the single-cell level. Yet, to realize the full potential of synthetic biology we need to be able to design organisms that can interact with each other within and across different strains. Synthetic microbial consortia can coordinate gene expression across a population or specialize by assuming different responsibilities within the collective. This allows consortia to be more efficient, and have a wider range of functions than communities of non-interacting cells. However, the larger the consortium, the harder it is to coordinate behaviors of the constituent cells. This is because the limited diffusion of molecules in the extracellular medium makes it difficult to coordinate the activity of gene networks interacting through intercellular signals. To understand, rationally design, and control large populations it is necessary to develop and validate mathematical and computational models of gene network dynamics that describe large-scale population-wide gene regulation. This is challenging because the dynamics of microbial collectives is stochastic, nonlinear, spatially inhomogeneous, and multi-scale. Models must account for the nonlinear dynamics of genetic circuits within individual cells, the spatial diffusion of signaling molecules that mediate interactions between cells, and the dynamics of multiple, co-mingled bacterial populations whose spatial configurations change due to cellular growth and division. In the proposed work, the PIs will develop such mathematical and computational models of the spatio-temporal dynamics of synthetic microbial consortia. To do so, they will use an interdisciplinary approach that combines experimental synthetic biology, microfluidic engineering, and mathematical biology. By examining increasingly complex consortia, the PIs will develop a hierarchy of increasingly sophisticated mathematical and computational models. The overall goal of this work is to better understand the complex, emergent dynamics of synthetic microbial consortia, and to engineer consortia that coordinate gene activity across space and time.