Mechanistic modeling for escherichia coli-based cell-free expression for systems characterization
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Han, Yue
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Abstract
Cell-free expression (CFE) systems have emerged as a powerful platform in synthetic biology, enabling applications in biomanufacturing, rapid prototyping, and point-of-care diagnostics. Despite their promise, lysate-based CFE systems face challenges such as high variability and limited systematic characterization, which restrict their broader industrial applications. This dissertation addresses key hurdles in developing mechanistic models for CFE systems characterization to enable predictive capabilities and deeper mechanistic understanding.
First, this work tackles the challenge of quantifying metabolomics data for model integration and systematic characterization in actively metabolizing systems such as CFE systems. A novel computational framework was developed to estimate absolute metabolite concentrations from relative abundances. Second, the thesis explored the conditions under which regulatory networks can be accurately identified despite limited or noisy data. This research highlights key factors influencing modeling strategies in data-constrained environments. Lastly, a mechanistic ordinary differential equation (ODE) model was developed to elucidate plasmid crosstalk in CFE systems, a previously unexplained phenomenon. This model captured experimental trends and provided predictive insights into the interplay between plasmid concentrations, promoter strength, and gene expression. Together, these contributions advance the predictive modeling and characterization of lysate-based CFE systems, offering tools and frameworks to address variability, improve experimental reproducibility, and unlock the potential of these systems for broader applications in synthetic biology.
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2025-01-13
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Dissertation