Browsing by Author "Leaman, Eric Joshua"

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    An Experimentally-validated Agent-based Model to Study the Emergent Behavior of Bacterial Communities
    Leaman, Eric Joshua (Virginia Tech, 2016-12-09)
    Swimming bacteria are ubiquitous in aqueous environments ranging from oceans to fluidic environments within a living host. Furthermore, engineered bacteria are being increasingly utilized for a host of applications including environmental bioremediation, biosensing, and for the treatment of diseases. Often driven by chemotaxis (i.e. biased migration in response to gradients of chemical effectors) and quorum sensing (i.e. number density dependent regulation of gene expression), bacterial population dynamics and emergent behavior play a key role in regulating their own life and their impact on their immediate environment. Computational models that accurately and robustly describe bacterial population behavior and response to environmental stimuli are crucial to both understanding the dynamics of microbial communities and efficiently utilizing engineered microbes in practice. Many existing computational frameworks are finely-detailed at the cellular level, leading to extended computational time requirements, or are strictly population scale models, which do not permit population heterogeneities or spatiotemporal variability in the environment. To bridge this gap, we have created and experimentally validated a scalable, computationally-efficient, agent-based model of bacterial chemotaxis and quorum sensing (QS) which robustly simulates the stochastic behavior of each cell across a wide range of bacterial populations, ranging from a few to several hundred cells. We quantitatively and accurately capture emergent behavior in both isogenic QS populations and the altered QS response in a mixed QS and quorum quenching (QQ) microbial community. Finally, we show that the model can be used to predictively design synthetic genetic components towards programmed microbial behavior.
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    Rational Engineering of Bacteria and Biohybrids for Enhanced Transport and Colonization in the Tumor Microenvironment
    Leaman, Eric Joshua (Virginia Tech, 2021-08-13)
    One of the principal impediments to the broad success of conventional chemotherapy is poor delivery to and transport within the tumor microenvironment (TME), caused by irregular and leaky vasculature, the lack of functional lymphatics, and underscored by the overproduction of extracellular matrix (ECM) proteins such as collagen. Coupled with limited specificity, the high chemotherapeutic doses needed to effectively treat tumors often lead to unacceptable levels of damage to healthy tissues. Bacteria-based cancer therapy (BBCT) is an innovative alternative. Attenuated strains of species such as Salmonella Typhimurium have been shown to preferentially replicate in the TME, competing for cellular resources and imparting intrinsic and immune-mediated cytotoxic effects on cancer cells. Nevertheless, the immense successes observed in in vitro and immunocompromised murine models have not translated to the clinic, attributable to the lack of sufficient tumor colonization. Synthetic biology today enables the precision engineering of microbes with traits for improved survival, penetration, and replication in the TME, rationally optimizable through computational modeling. In this dissertation, we explore several facets of rationally engineering of bacteria toward augmenting bacterial penetration and retention in the TME. Namely, we (1) develop a novel assay to interrogate the neutrophil migratory response to pathogens and characterize the effects of modifying the molecular structure of the outer membrane (OM) of S. Typhimurium, (2) develop a mathematical model of bacterial intratumoral transport and growth and explore the effects of nutrient availability and the tumor ECM on colonization, (3) engineer bacteria that constitutively secrete collagenase and show significantly augmented transport in collagen hydrogels and collagen-rich tumor spheroids, and (4) develop computational models to explore control schemes for the programmed behavior of bacteria-based biohybrid systems, which will leverage the engineered bacteria to deliver therapeutics to the TME. Our work serves as the foundation for the logical and efficient design of the next generation of BBCTs.