Collaborative Research: Spatiotemporal Dynamics of Synthetic Microbial Consortia

University Of Houston, Houston TX

Investigators

Abstract

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.