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，大多数合成工程微生物在单细胞水平上起作用。这些生物无法协调它们的活动，限制了它们产生巨大影响的能力。相比之下，合成的多细胞系统是由旨在协调行动以实现其目标的细胞组成的。这些群体的协调行为可能比不协调的细胞集合更加复杂，灵活和有效。创建这种多细胞系统的一种方法是通过合成微生物聚生体的工程化-各种基因工程微生物菌株的聚集体，它们共同工作以实现任务。在一个聚生体中，组成菌株的协调活性可以显示出难以工程化为单一菌株的紧急行为。在其核心，合成财团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已经被有目的地改变。在一个合成的聚生体中的单个细胞通过细胞间的信号传导途径相互通信。因此，当设计合成微生物聚生体时，必须考虑到更大群体内细胞和菌株的不断变化的空间排列。然而，微生物聚生体中细胞间信号传导的时空动力学知之甚少，限制了我们设计大型合成多细胞聚生体的能力。在这里，PI将开发数学方法来描述合成微生物财团的动态。为此，他们将使用跨学科的方法，结合实验合成生物学，微流体工程和数学生物学。通过研究日益复杂的财团，PI将开发一个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菌群的复杂、涌现的动力学，并通过协调跨空间和时间的基因活动来设计实现特定目标的菌群。大多数合成基因电路都建立在单一菌株内，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生物体。合成微生物聚生体可以协调整个种群的基因表达，或者通过在集体中承担不同的责任来专门化。这使得聚生体比非相互作用的细胞群体更有效，并且具有更广泛的功能。然而，联合体越大，就越难协调组成细胞的行为。这是因为细胞外介质中分子的有限扩散使得难以协调通过细胞间信号相互作用的基因网络的活性。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，因为微生物群体的动力学是随机的，非线性的，空间不均匀的，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，介导细胞间相互作用的信号分子的空间扩散，以及多个混合细菌种群的动力学，这些细菌种群的空间配置由于细胞生长和分裂而发生变化。在拟议的工作中，PI将开发合成微生物聚生体时空动态的数学和计算模型。为此，他们将使用跨学科的方法，结合实验合成生物学，微流体工程和数学生物学。通过研究日益复杂的财团，PI将开发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财团的复杂，新兴的动态，并设计跨空间和时间协调基因活动的财团。

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.