Investigating energy efficiency, information processing and control architectures of microbial community interaction networks
Abstract
Communication networks make the coordinated function of collectives of individuals possible. The most intricate communication architectures occur in the natural world, where communities of microbial cells form networks spanning many scales of complexity and perform the dynamic process of information exchange to coordinate group and individual behavior. Biological communication architectures also utilize multiple layers of network organization, from single cells to complex communities and into the multicellular realm. Optimizing the flow of information through designed networks may be achieved by borrowing insights from these complex biological communities, where solutions to minimizing the energetic cost of information exchange have evolved and await our discovery. Our team recognizes that an opportunity exists at the crossroads of our combined disciplines: we will merge new technological advances in studying biological communities with recent theoretical developments in modeling collective behavior and information processing in complex systems. In so doing, we will identify universal principles that govern information flow within biological communities, illuminating the basis of how these natural interaction networks optimize information transfer under uncertain conditions while simultaneously minimizing energetic costs. Our vision is to develop a comprehensive model of biological communication, by integrating four interconnected aspects of information flow within networks that span multiple scales of biological organization: 1) the connection between single-cell heterogeneity and decision-making within populations; 2) the optimization of information flow over multiple length and time scales; 3) the robustness and controllability of complex dynamic systems; 4) information exchange between multiple layers of biological organization and the scaling of communication architectures for unicellular organisms to networks of multicellular organisms. We will integrate our findings in each area towards a comprehensive model of information exchange in complex networks. The proposed research examines fundamental principles of information exchange in distinct types of natural systems, including wild quorum sensing bacteria, a three-member consortia of soil bacteria, isolates from the human microbiome, and social insect communities and their symbiotic microbiota. Theoretical approaches are applied from information theory, dynamical systems, Bayesian networks, communication sciences, data science, biophysics, machine learning, control theory, artificial neural networks and deep learning, and evolutionary game theory. Experimental approaches include the development of microfluidic technologies, synthetic biology tools, single-cell microscopy, single-molecule imaging techniques, high-throughput cell culture, behavioral analysis of social insect interactions, whole-insect microbiome sequencing and imaging, and confocal imaging of biofilm dynamics. Elucidating the universal principles of networked interactions will meet the long-term vision of enhancing the network architectures of DoD communication and personnel systems. As we clarify these aspects of complex communication networks, we will integrate our discoveries towards a comprehensive, computational understanding of the rules that govern information transfer in biological networks. This work will enable a paradigm shift in the design and implementation of information network architectures, potentially generating transformative changes in DoD communication and personnel systems.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- May 20, 2019
- Source ID
- W911NF1910269
Entities
People
- James Q Boedicker
Organizations
- Army Contracting Command
- United States Army
- University of Southern California