Graduate Studies
First Advisor
Rajib Saha
Committee Members
Hasan Otu, Hyun-Seob Song
Date of this Version
Summer 8-2024
Document Type
Thesis
Citation
A thesis presented to the faculty of the Graduate College at the University of Nebraska in partial fulfilment of requirements for the degree of Master of Science
Major: Agricultural and Biological Systems Engineering
Under thesSupervision of Professor Rajib Saha
Lincoln, Nebraska, August 2024
Abstract
Genome-Scale Models (GSMs) are important tools for simulating the metabolism of archaea, bacteria, and eukaryotic organisms in silico. Current methods of metabolic model reconstruction require extensive manual curation, which is time-consuming and laborious to produce a quality model, and often ignore problems like Thermodynamically Infeasible Cycles (TICs). These TICs can cause unbounded fluxes, negatively influencing biological consistency and model insights. To address these challenges, we introduce OptRecon, a multi-step automated optimization-based approach for model refinement and TIC resolution. OptRecon splits constructed models into minimal and secondary networks, reincorporating secondary reactions into the minimal model to create a TIC-free reconstruction by carefully steering specific directionalities. We demonstrate OptRecon’s ability to automatically refine predictive models without TICs using curated and non-curated, automatically generated models and checked them using Gene Essentiality Analysis to show improved model consistency. OptRecon’s automated approach provides researchers with a valuable method to develop, expand, or refine GSMs while effectively addressing the challenges posed by TICs.
Advisor: Rajib Saha
Comments
Copyright 2024, Eric C. Nelson. Used by permission