Date of Award

Spring 1-1-2014

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Chemical & Biochemical Engineering

First Advisor

Ryan T. Gill

Second Advisor

Joel L. Kaar

Third Advisor

Ross P. Carlson

Fourth Advisor

Mark Johnston

Fifth Advisor

Charles B. Musgrave

Abstract

Selections with collections (libraries) of synthetically engineered microbes can rapidly identify mutants with fitness increasing mutations. They investigate how a known mutant genotype affects its growth phenotype and offer a powerful method to engineer traits into strains that allow for the improved conversion of sugars into biochemicals and biofuels. Although powerful, mutant libraries are limited by the complexity of their selection mechanisms. The study here investigates these selection mechanisms in order to improve selection methods and enable better strain engineering.

To better understand the relationship between mutant growth and sugar metabolism, a novel method is developed that predicts the fluxes of metabolic enzyme deletion and overexpression mutants. Unlike many previous methods, the method requires no prior assumptions on energy (ATP) fluxes and only uses the measured fluxes of a wild type strain as an input. Mutant predictions are shown to be in very good agreement with measurements. Additionally the method quantifies cofactor recycling and predicts relative NADPH/NADH imbalances in a subset of slow growing and lethal mutants.

Natively E.coli represses the utilization of xylose, a major cellulosic sugar, until all glucose, the most abundant cellulosic sugar, is depleted. A synthetic mutant selection approach is developed to enable the simultaneous utilization of glucose and xylose. A background strain is constructed in which the main glucose transporter is deleted after which it is shortly adapted to recover glucose growth. Subsequently four genes reported to be involved in glucose metabolism are either deleted or overexpressed. These mutants are pooled and subjected to selections in glucose, xylose and a mixture of glucose and xylose. DNA sequencing technology is used to track mutant fitness dynamics and selection growth is compared with growth in individual mutant cultures. Mutants with desired sugar co-consumption rates are identified as well as mutants that cross-feed on metabolic by-products.

Mutant growth rates are also extracted by sequencing a genome-scale library (TRMR) selection. TRMR mutant growth is compared with the predictions of our flux modeling method revealing the unexpected growth of a subset of lethal mutants, one of which is confirmed to cross-feed on acetate. The methods developed here enable new applications for mutant library selections.

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