Date of Award:
5-2016
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Computer Science
Committee Chair(s)
Nicholas Flann
Committee
Nicholas Flann
Committee
Vladimir Kulyukin
Committee
Xiajun Qi
Abstract
Bio-reactors, also known as microbial factories are used extensively to produce various industrially valuable products. However, scalability and stability of these factories are limited as it is difficult to deliver nutrients and extract product and waste from a large system. Current solution approaches explore changes in the physical configuration of the bio-reactors. Inspired from the nutrient delivery mechanisms of large organisms in nature, this work studies the possibilities of exploiting self-organizing bio-engineered cells which are capable of organizing into a vessel network to support the producer cells in the factory.
Primary goal of this dissertation is to design a proof-of-concept bio-reactor simulation in which self-organized vessel network function as the nutrient delivery and waste removal mechanism, which can be formed from a random distribution of bio-engineered vessel cells. A computational model simulates development of vessels from randomly distributed endothelial-like cells and the resultant network functioning to deliver nutrients and extract product from the cell culture.
Microbial factories with vascular networks are evaluated for their scalability, robustness, and productivity compared to the cell factories without a vascular network. Initial studies demonstrate at least an order of magnitude increase in production is possible; the system can be scaled up, and that the self-organization of the efficient vascular network is robust. The work suggests that bioengineered multicellularity may offer efficiency improvements difficult to achieve with physical engineering approaches.
Checksum
d4684b86079d36722e5430f2a438781f
Recommended Citation
Davis, Delin, "Exploiting Self-Organization in Bioengineered Systems: A Computational Approach" (2016). All Graduate Theses and Dissertations, Spring 1920 to Summer 2023. 4914.
https://digitalcommons.usu.edu/etd/4914
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