Accelerating the design-build-test-learn cycle for the development of microbial cell factories

Xue, Pu

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https://hdl.handle.net/2142/117521 Copy

Description

Title

Accelerating the design-build-test-learn cycle for the development of microbial cell factories

Author(s)

Xue, Pu

Issue Date

2022-08-09

Director of Research (if dissertation) or Advisor (if thesis)

Zhao, Huimin

Doctoral Committee Chair(s)

Zhao, Huimin

Committee Member(s)

• Rao, Christopher V
• Sweedler, Jonathan V
• Kraft, Mary L

Department of Study

Chemical & Biomolecular Engr

Discipline

Chemical Engineering

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• Synthetic biology
• Directed evolution
• Lab automation
• Mass spectrometry
• High-throughput screening
• Design-Build-Test-Learn cycle
• Microbial cell factories
• Free fatty acids
• DNA assembly

Abstract

In the emerging era of bioeconomy, microbial cell factories (MCFs) have been applied to produce functional molecules such as chemicals, fuels, materials, and proteins in a sustainable, cheap, and environmentally friendly manner. The goal of MCF is to achieve a high titer, rate, and yield of both native and nonnative metabolites by rewiring and optimizing the production process with the help of metabolic engineering and synthetic biology design-build-test-learn (DBTL) cycle. In the past few years, several natural microorganisms, such as Escherichia coli and Saccharomyces cerevisiae, have been identified and used intensively for the production and optimization of value-added biomolecules for therapeutic, biotechnological, and industrial applications. However, to fully utilize microbes as cell factories to achieve the titer, rate, and yield of desired product as petrochemical industry does; extensive engineering, better library construction and screening tools, and more comprehensive understanding of the cell metabolism via gene editing and regulatory network studies are necessary. This dissertation describes my efforts in developing lab automation tools and high-throughput screening strategies to accelerate the synthetic biology DBTL cycle for MCFs. In Chapter 2, a mass spectrometry (MS)-based high-throughput screening method for engineering fatty acid synthases with improved production of medium-chain fatty acids (MCFAs) in S. cerevisiae is developed. MCFAs are key components of crucial nutrients, soaps, industrial chemicals, and fuels. By using membrane lipids as a proxy, shorter acyl chain phosphatidylcholines from membrane lipids can be detected through the colony-based method at a rate of ~2 sec per sample. This quick preliminary screening tool serves as an effective approach for engineering microbial fatty acid compositions. In Chapter 3, a versatile, automated, and high-throughput platform is built for the fundamental DNA assembly technology. By integrating the DNA assembly method and the software with a robotic system named Illinois Biological Foundry for Advanced Biomanufatcuring (iBioFAB), researchers can be relieved from complicated and error-prone manual library construction processes. This workflow also serves as a proof of concept that demonstrates the strength and robustness of our integrated biofoundry for handling synthetic biology projects. In Chapter 4, the importance of regulators contributes to the degree of target gene expression with correlation to free fatty acid (FFA) production in S. cerevisiae is investigated. Based on the knowledge gained and tools developed from Chapter 2 and Chapter 3, a combinatorial library of 175 transcription factors with single, double, and triple gene knockouts is constructed using iBioFAB and further characterized with a newly developed high-throughput quantitative screening method. In Chapter 5, the emphasis is more on the resources that help S. cerevisiae strains grow, and how the static and dynamic allocations of different nutrients affect the growth optimization of S. cerevisiae as MCF. Key global regulators cyclic AMP (cAMP) and GCN2 are studied to examine whether they can maximize cellular growth rates under different nutrient conditions and different inhibitor perturbations.

Graduation Semester

2022-12

Type of Resource

Thesis

Copyright and License Information

Copyright 2022 Pu (Mason) Xue

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