Systems approach to microbial pathogenesis: complex patterns emerge from simple interactions Public Deposited

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  • March 22, 2019
  • Vasa, Suzy M.
    • Affiliation: School of Medicine, UNC/NCSU Joint Department of Biomedical Engineering
  • Biological organisms are complex systems and modeling can provide insight into their behavior by the process of recreating it. All elements may not be known of the system under study and thus, hypotheses must be made in order to create an appropriate model. These hypotheses can lead to interesting modeling results and help guide in vitro experiments. However, modeling complexity does not necessarily require complex techniques. By modeling the simplest elements of a biological system and by defining how the elements interact, it is possible to model complex behavior as emergent properties of the system. In this manner, I model simple interactions between biological elements. First, at the lowest level of complexity, is a single molecule such as an RNA. Determining RNA secondary structure is a necessary step to understand how it interacts with other molecules to affect the biological system as a whole. The structure of an RNA is formed through simple interactions between nucleotides. I developed software that aids the process of identifying sites in an RNA where nucleotide-nucleotide or nucleotide-protein binding occurs to predict RNA secondary structure more accurately. The next level of complexity is molecule-molecule interactions that result in the emergence of patterns within an organism, such as phenotypes expressed by a cell. Using agent-based modeling, I model the proteins, RNAs, and enzymes involved in a gene regulatory network that is responsible for the emergence of the competence phenotype in Bacillus subtilis. Competence is stochastically expressed due to the variable expression of genes. My agent-based model identified several possible sources for this variation: dilution events like cell division, inheritance of molecules involved in competence and most importantly, spatial temporal interactions of molecules. And lastly, I model the simple interactions between two organisms, a virus and a host cell, to understand the molecular interactions between host and pathogen that result in the replication and assembly of a virus. In this model, I successfully modeled the self-assembly of BK Virus using an agent-based model that models from transcription to translation to the encapsidation of the BKV genome within a T=7, icosahedral structure all by simple molecule-molecule interactions.
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  • In Copyright
  • "... in partial fulfillment of the requirements for the degree Doctor of Philosophy in the Department of Biomedical Engineering."
  • Giddings, Morgan C.
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  • Chapel Hill, NC
  • Open access

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