The Virginia iGEM 2024 team has developed a comprehensive 40-page educational handbook to expand access to synthetic biology education. By partnering with experienced educators in the homeschooled community, we identified critical gaps in existing resources for homeschooled students. We developed a solution to address those needs and refined our handbook with expert input to ensure its applicability and value. To further our impact, we engaged directly with the homeschool community by conducting a UVA Institutional Review Board-approved survey to receive feedback for revisions and improvements for our handbook. Beyond our handbook, we also fostered research and synthetic biology involvement at the University of Virginia, collaborating with the Bridge Scholar Program to support first-year engineering students from minority backgrounds.
Since the beginning of BLISS, our team has prioritized collaboration with experts across diverse fields to shape the direction of our project and its design. These collaborations allowed us to refine our core objectives and goals for various project components, including lipase and procolipase secretion from B. subtilis, our biocontainment kill switch, modeling efforts, and education/inclusivity initiatives. Medical professionals specializing in pancreatic cancer, pancreatitis, and cystic fibrosis emphasized the severe symptoms and reduced quality of life faced by Exocrine Pancreatic Insufficiency patients, confirming the need for our device. Additionally, they emphasized the importance of a novel ethical and accessible treatment for EPI, key principles that shaped our project design. We also consulted ethics experts to better understand societal perceptions of our solution and ensure that our approach is more ethical than current treatments. Furthermore, we engaged with professionals to better understand the future directions of our project and what improvements are necessary before clinical implementation.
We developed a comprehensive model to simulate the timescale and production of lipase in response to glucose input, incorporating over 29 ordinary differential equations alongside mass action and Michaelis-Menten kinetics. This allows us to better understand and depict the relationships between our various input metabolites and enzyme output. Our model is unique due to its novel exploration of the carbon catabolite repression pathway, simplifying and condensing complex metabolic interactions into a more accessible and interpretable form. Additionally, we conducted an extensive literature review to identify a range of rate constants, permitting thorough analysis of both low-end and high-end values. Although this approach is not commonly used by other iGEM teams, we found it to be beneficial in providing a more insightful understanding of how our device functions.