Computational Design and Optimization of Metabolic Pathways
Open Access
- Author:
- Ng, Chiam Yu
- Graduate Program:
- Chemical Engineering
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- July 21, 2017
- Committee Members:
- Costas D. Maranas, Dissertation Advisor/Co-Advisor
Costas D. Maranas, Committee Chair/Co-Chair
Manish Kumar, Committee Member
Phillip E. Savage, Committee Member
Cooduvalli S. Shashikant, Outside Member - Keywords:
- Metabolic engineering
Glycolysis
Optimization of metabolic network
Synthetic biology
Computational biology
Metabolic pathway design
Combinatorial pathway engineering - Abstract:
- Microbial production of chemicals and fuels has often been cited as the highly viable solution to the current energy crisis. It has also been widely exploited to produce value-added products such as pharmaceuticals, nutraceuticals, food flavorings and fine chemicals. Knowledge gained from genome sequencing and functional annotations, as well as advances in genetic engineering techniques, enable us to re-code the genetic blueprint of a microbial cell to endow them with new functions such as a non-native metabolic pathway that make a specific biochemical. As the cells are often not optimized to synthesize the target product, significant rewiring of their metabolic networks is required to re-apportion carbon flux towards the target product. This should be performed with careful consideration of cellular protein resource allocation as well as energy and redox balance. However, the task is often complicated by the intricate interplay of the cellular gene-protein-reaction network. In this dissertation, we aim to address several challenges in designing and engineering metabolic pathways by combining techniques in computational biology, metabolic engineering, and synthetic biology. Each project relies extensively on optimization-based computational design, from genetic constructs to pathways and finally the entire metabolic network, to achieve the associated metabolic engineering objectives. In Chapter 1, we review the state-of-the-art metabolic engineering and synthetic biology tools for pathway and strain design. These tools lay the foundation for the development of the subsequent chapters, which deal in-depth with specific challenges in metabolic pathway design and strain optimization. One of the key challenges in metabolic engineering is to ensure a consistent supply of cofactor, which is often shared across over 100 reactions in a cell, to the desirable biosynthesis reactions. In Chapter 2, we describe the design and optimization of a synthetic metabolic pathway in E. coli to improve the availability of an essential redox cofactor NADPH. The synthetic metabolic pathway was derived from the highly active Entner-Doudoroff (ED) pathway of another prokaryote Zymomonas mobilis. Upon optimizing the expression of the multi-enzyme pathway, we obtained strains with improved NADPH production when compared to the wild-type strain. In addition to NADPH production, the ED pathway also simultaneously generates pyruvate and glyceraldehyde-3-phopshate, which are the precursors for the methylerythritol phosphate (MEP) pathway. As a proof-of-concept, we demonstrated that combination of the synthetic ED pathway and the MEP pathway improved the production of an NADPH-dependent terpenoid by up to 97%. Motivated by the intriguing roles that glycolytic pathways play in a cell and the effects of their perturbation, in Chapter 3, we switch focus to uncover the reason why specific glycolytic pathways prevail in nature despite the presence of alternatives. Although the ED pathway and the Embden-Meyerhof-Parnas (EMP) glycolytic pathways both convert glucose to pyruvate, they take different routes with different intermediates and yield one or two moles of ATP per mole of glucose. Theoretically, one could construct a thermodynamically feasible (i.e., ΔrG° < 0) glucose utilization pathway to pyruvate with up to five moles of ATP production. This raises the question as to why nature preferably employs either EMP or ED glycolysis in spite of the potential availability of pathways with improved energy yield. By computationally designing and assessing over 10,000 possible routes between glucose and pyruvate, we attempt to decipher the designing principles of the natural glycolytic pathways. The computational pipeline developed in this case study for pathway design and analysis can be applied to other important bioconversion pathways. While the earlier chapters delve on the design and optimization of a pathway for redox and energy cofactors supply, generally the entire metabolic network of a microbial cell has to be rewired to drive sufficient carbon flux towards the production pathway and prevent the formation of competing by-products. Using the optimization-based strain design procedure OptForce (in Chapter 4), we combed the entire genome-scale metabolic network to pinpoint genetic interventions including up-regulation, down-regulation and knockout that could lead to the overproduction of the target biochemicals in yeast and cyanobacteria. We further demonstrated that our computational approach not only identified genetic manipulation strategies that recapitulate experimental results but also suggested novel interventions that improve experimental yields. In Chapter 5, we conclude the dissertation by summarizing current metabolic engineering efforts and discussing the remaining challenges as well as our future perspectives on the development of microbial cell factories.