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Biological systems display remarkable complexity that is not properly accounted for in small, reductionistic models. Increasingly, big data approaches using genomics, proteomics, metabolomics etc. are being applied to predicting and modifying the emergent phenotypes produced by complex biological systems. In this research, several novel tools were developed to assist in the acquisition and analysis of biological big data for a variety of applications. In total, two entirely new tools were created and a third, relatively new method, was evaluated by applying it to questions of clinical importance. 1) To assist in the quantification of metabolites at the subcellular level, a strategy for localized in-vivo enzymatic assays was proposed. A proof of concept for this strategy was conducted in which the local availability of acetyl-CoA in the peroxisomes of yeast was quantified by the production of polyhydroxybutyrate (PHB) using three heterologous enzymes. The resulting assay demonstrated the differences in acetyl-CoA availability in the peroxisomes under various culture conditions and genetic alterations. 2) To assist in the design of genetically modified microbe strains that are stable over many generations, software was developed to automate the selection of gene knockouts that would result in coupling cellular growth with production of a desired chemical. This software, called OptQuick, provides advantages over contemporary software for the same purpose. OptQuick can run considerably faster and uses a free optimization solver, GLPK. Knockout strategies generated by OptQuick were compared to case studies of similar strategies produced by contemporary programs. In these comparisons, OptQuick found many of the same gene targets for knockout. 3) To provide an inexpensive and non-invasive alternative for bladder cancer screening, Raman-based urinalysis was performed on clinical urine samples using RametrixTM software. RametrixTM has been previously developed and employed to other urinalysis applications, but this study was the first instance of applying this new technology to bladder cancer screening. Using a pool of 17 bladder cancer positive urine samples and 39 clinical samples exhibiting a range of healthy or other genitourinary disease phenotypes, RametrixTM was able to detect bladder cancer with a sensitivity of 94% and a specificity of 54%. 4) Methods for urine sample preservation were tested with regard to their effect on subsequent analysis with RametrixTM. Specifically, sterile filtration was tested as a potential method for extending the duration at which samples may be kept at room temperature prior to Raman analysis. Sterile filtration was shown to alter the chemical profile initially, but did not prevent further shifts in chemical profile over time. In spite of this, both unfiltered and filtered urine samples alike could be used for screening for chronic kidney disease or bladder cancer even after being stored for 2 weeks at room temperature, making sterile filtration largely unnecessary. / Doctor of Philosophy / Biological systems display remarkable complexity that is not properly accounted for in conventional, reductionistic models. Thus, there is a growing trend in biological studies to use computational analysis on large databases of information such as genomes containing thousands of genes or chemical profiles containing thousands of metabolites in a single cell. In this research, several new tools were developed to assist with gathering and processing large biological datasets. In total, two entirely new tools were created and a third, relatively new method, was evaluated by applying it to questions of medical importance. The first two tools are for bioengineering applications. Bioengineers often want to understand the complex chemical network of a cell’s metabolism and, ultimately, alter that network so as to force the cell to make more of a desired chemical like a biofuel or medicine. The first tool discussed in this dissertation offers a way to measure the concentration of key chemicals within a cell. Unlike previous methods for measuring these concentrations, however, this method limits its search to a specific compartment within the cell, which is important to many bioengineering strategies. The second technology discussed in this paper uses computer simulations of the cells entire metabolism to determine what genetic alterations might lead to better produce a chemical of interest. The third tool involves analyzing the chemical makeup of urine samples to screen for diseases such as bladder cancer. Two studies were conducted with this third tool. The first study shows that Raman spectroscopy can distinguish between bladder cancer and related diseases. The second v study addresses whether sterilizing the urine samples through filtration is necessary to preserve the samples for analysis. It was found that filtration was neither beneficial nor necessary.

The development of biofuels has received much attention due to the global warming and limited resources associated with fossil fuels. Butanol has been identified as a potential option due to its advantages over ethanol, for example higher energy density, compatibility with current infrastructure and its possibility to be blended with gasoline at any ratio. Yeast Saccharomyces cerevisiae can be used as a producer of butanol. However, butanol toxicity to the host limits the yield produced. In this study, four strains of yeast isolated from the habitats of lager beer, ale, wine and baker ́s yeast were grown in YPD media containing isobutanol concentrations of 1.5 %, 2 %, 3 % and 4 %. Growth was measured to determine the most tolerant strain. Gene expression for the genes RPN4, RTG1 and ILV2 was also measured, to determine its involvement in butanol stress. The genes have in previous studies seen to be involved in butanol tolerance or production, and the hypothesis was that they all should be upregulated in response to butanol exposure. It was found that the yeast strain isolated from lager beer was most tolerant to isobutanol concentrations of 2 % and 3 %. It was also found that the gene RPN4 was upregulated in response to isobutanol stress. There was no upregulation of RTG1 or ILV2, which was unexpected. The yeast strain isolated from lager beer and the gene RPN4 is proposed to be investigated further, to be able to engineer a suitable producer of the biofuel butanol.

The development of sustainable replacements for fossil fuels has been spurred by concerns over global warming effects. Biofuels are typically produced through fermentation of edible crops, or forest or agricultural residues requiring cost-intensive pretreatment. An alternative is to use photosynthetic cyanobacteria to directly convert CO2 and sunlight into fuel. In this thesis, the cyanobacterium Synechocystis sp. PCC 6803 was genetically engineered to produce the biofuel n­-butanol. Several metabolic engineering strategies were explored with the aim to increase butanol titers and tolerance. In papers I-II, different driving forces for n-butanol production were evaluated. Expression of a phosphoketolase increased acetyl-CoA levels and subsequently butanol titers. Attempts to increase the NADH pool further improved titers to 100 mg/L in four days. In paper III, enzymes were co-localized onto a scaffold to aid intermediate channeling. The scaffold was tested on a farnesene and polyhydroxybutyrate (PHB) pathway in yeast and in E. coli, respectively, and could be extended to cyanobacteria. Enzyme co-localization increased farnesene titers by 120%. Additionally, fusion of scaffold-recognizing proteins to the enzymes improved farnesene and PHB production by 20% and 300%, respectively, even in the absence of scaffold. In paper IV, the gene repression technology CRISPRi was implemented in Synechocystis to enable parallel repression of multiple genes. CRISPRi allowed 50-95% repression of four genes simultaneously. The method will be valuable for repression of competing pathways to butanol synthesis. Butanol becomes toxic at high concentrations, impeding growth and thus limiting titers. In papers V-VI, butanol tolerance was increased by overexpressing a heat shock protein or a stress-related sigma factor. Taken together, this thesis demonstrates several strategies to improve butanol production from cyanobacteria. The strategies could ultimately be combined to increase titers further.

Microbial metabolism can be tailored to meet human specifications, but the degree to which these living systems can be repurposed is still unknown. Artificial biological control strategies are being developed with the goal of enabling the predictable implementation of novel biological functions (e.g., engineered metabolism). This dissertation project contributes genetic tools useful for modulating gene expression levels (extending promoters with UP elements) and isolating transcription and translation of engineered DNA from the endogenous cellular network (expression by orthogonal cellular machinery), which have been demonstrated in Escherichia coli for the production of lycopene, a 40-carbon tetraterpene carotenoid with antioxidant activity and a number of other desirable properties.

Social, economic and political pressures have driven the development of renewable alternatives to fossil fuels. Biofuels, such as bioethanol, have proved to be successful alternatives. Mature technologies are crop-based, but this has brought criticism due to the conflicting use of land for fuel versus food production. Therefore, bioethanol production technologies have shifted to utilising the sugars that derive from the degradation of lignocellulosic biomass. The thermophilic, Gram-positive bacterium, Geobacillus thermoglucosidasius, can naturally utilise a large fraction of these sugars, and metabolic engineering has been used to create a strain that produces ethanol as the major product of fermentation. This strain, G. thermoglucosidasius TM242 (Δldh, Δpfl, pdhup), does however, produce small but significant quantities of acetate, an undesirable by-product of fermentation. Therefore, acetate metabolism in the G. thermoglucosidasius TM242 strain was the focus of this study. During fermentation, ethanol is generated from the central metabolite acetyl-CoA through the activities of a bifunctional enzyme: aldehyde dehydrogenase/alcohol dehydrogenase (ADHE). On the other hand, acetate is generated from acetyl-CoA through catalysis by phosphotransacetylase (PTA) and acetate kinase (AK). Acetate metabolism in G. thermoglucosidasius TM242 was studied in this project by investigating the enzyme activities governing flux from acetyl-CoA, and the feasibility of reduced acetate production was investigated by a pta-deletion strategy. This thesis reports the characterisation of PTA and AK, by studying activities from both native cell lysates and recombinantly expressed proteins. The results indicate that the activities of PTA and AK are greater than those of ADHE, suggesting that the potential metabolic flux is greater towards acetate production than to ethanol. However, the ethanol yield from G. thermoglucosidasius TM242 fermentations is greater than that of acetate, suggesting the existence of a regulatory mechanism controlling acetyl-CoA flux. Several possible regulatory mechanisms were studied in this project and are reported here. The viability of creating a strain that reduces acetate accumulation, and potentially increases ethanol yields, was investigated and reported in this thesis. The gene encoding PTA was deleted from G. thermoglucosidasius TM242, and the resulting strain was characterised. The Δpta strain had approximately 5% of the PTA activity measured in TM242, but acetate was still generated from pentose and hexose fermentations. Additional phosphotransacylase (PTAC) enzymes were discovered in G. thermoglucosidasius TM242 that could catalyse the conversion of acetyl-CoA and orthophosphate to acetyl-phosphate and CoA. A series of PTAC null strains were created and analysed, the results of which indicated that phosphotransbutyrylase (PTB) could be involved in acetate production in vivo. It was discovered that the cell lysates of G. thermoglucosidasius strains carrying deletions to both pta and ptb could no longer catalyse the conversion of acetyl-CoA and orthophosphate to acetyl-phosphate and CoA. However, these strains still accumulated acetate, suggesting the presence of alternative acetate-producing pathways in this organism. In addition, G. thermoglucosidasius strains carrying deletions to both pta and ptb could ferment glucose but not xylose, suggesting that the production of ATP by the PTA-AK pathway is crucial for micro-aerobic growth on pentose sugars.

Due to its availability, low-price, and higher degree of reduction than lignocellulosic sugars, glycerol has become an attractive carbon source for the production of fuels and reduced chemicals. However, this high degree of reduction of carbon atoms in glycerol also results in significant challenges in regard to its utilization under fermentative conditions. Therefore, in order to unlock the full potential of microorganisms for the fermentative conversion of glycerol into fuels and chemicals, a detailed understanding of the anaerobic fermentation of glycerol is required. The work presented here highlights a comprehensive experimental investigation into fermentative glycerol metabolism in Escherichia coli, which has elucidated several key pathways and mechanisms. The activity of both the fermentative and respiratory glycerol dissimilation pathways was found to be important for maximum glycerol utilization, a consequence of the metabolic cycle and downstream effects created by the essential involvement of PEP-dependent dihydroxyacetone kinase (DHAK) in the fermentative glycerol dissimilation pathway. The decoupling of this cycle is of central importance during fermentative glycerol metabolism, and while multiple decoupling mechanisms were identified, their relative inefficiencies dictated not only their level of involvement, but also implicated the activity of other pathways/enzymes, including fumarate reductase and pyruvate kinase. The central role of the PEP-dependent DHAK, an enzyme whose transcription was found to be regulated by the cyclic adenosine monophosphate (cAMP) receptor protein (CRP)-cAMP complex, was also tied to the importance of multiple fructose 1,6-bisphosphotases (FBPases) encoded by fbp, glpX, and yggF. The activity of these FBPases, and as a result the levels of fructose 1,6-bisphosphate, a key regulatory compound, appear to also play a role in the involvement of several other enzymes during fermentative glycerol metabolism including PEP carboxykinase. Using this improved understanding of fermentative glycerol metabolism as a platform, E. coli has been engineered to produce high yields and titers of ethanol (19.8 g/L, 0.46 g/g), co-produced along with hydrogen, and 1,2-propanediol (5.6 g/L, 0.21 g/g) from glycerol, demonstrating its potential as a carbon source for the production of fuels and reduced chemicals.

A systematic approach based on bacteriophage Lambda (Lambda Red) and flippase-flippase recognition targets (FLP-FRT) recombinations was proposed for genomic engineering of Escherichia coli. For demonstration purposes, DNA operons containing heterologous genes (i.e. pac encoding E. coli penicillin acylase and palB2 encoding Pseudozyma antarctica lipase B mutant) engineered with regulatory elements, such as strong/inducible promoters (i.e. Ptrc and ParaB), operators, and ribosomal binding sites, were integrated into the E. coli genome at designated locations (i.e. lacZYA, dbpA, and lacI-mhpR loci) either as a gene replacement or gene insertion using various antibiotic selection markers (i.e. kanamycin and chloramphenicol) under various genetic backgrounds (i.e. HB101 and DH5α). The expression of the inserted foreign genes was subject to regulation using appropriate inducers [Isopropyl β-D-1-thiogalactopyranoside (IPTG) and arabinose] at tuneable concentrations. The developed approach has paved an effective way to “tailor” plasmid-free E. coli strains with desired genotypes suitable for various biotechnological applications, such as biomanufacturing and metabolic engineering.

The field of biochemical systems modeling and analysis is faced with an unprecedented flood of data from experimental methodologies of molecular biology. While these techniques continue to leapfrog ahead in the speed, volume and finesse with which they generate data, the methods of data analysis and interpretation, however, are still playing the catch-up game. The notions of systems analysis have found a new foothold, under the banner of Systems Biology, with the promise of uncovering the rationale for the designs of biological systems from their parts lists, as they are generated by experimentation and sorted and managed by bioinformatics tools. With an aim to complement hypothesis-driven and reductionistic biological research, and not replace it, a systems biologist relies on the tools of mathematical and computational modeling to be able to contribute meaningfully to any ongoing bio-molecular systems research. These systems analysis tools, however, should not only have their roots steeped well in the theoretical foundations of biochemistry, mathematics and numerical computation, but they should be married to a framework that facilitates the required systems way of thought for all its users computational scientists, experimentalists and molecular biologists alike. Hopefully, such framework-based tools would go beyond just providing fancy GUIs, numerical packages for integrating ODEs and/or optimization libraries. The intent of this thesis is to present a framework and toolbox for biochemical systems modeling, with an application in metabolic pathway analysis and/or metabolic engineering. The research presented here builds upon the tenets of a very well established and generic approach to biological systems modeling and analysis, called Biochemical Systems Theory (BST), which is almost forty years old. The nuances of modeling and practical hurdles to analysis are presented in the context of a real-time case study of analyzing the glucolytic pathway in the bacterium Lactococcus lactis. Alongside, the thesis presents the features of a MATLAB-based software application that has been built upon the framework of BST and is aptly named as Biochemical Systems Toolbox (BSTBox). The thesis presents novel contributions, made by the author during the course of his research, to state-of-the-art techniques in parameter estimation, and robustness and sensitivity analysis topics that, as this thesis will show, remain to be the most restrictive bottlenecks in the world of biological systems modeling and analysis.

Metabolic engineering has enabled the advancement of biotechnology over the past few decades through the use of cells as biochemical factories. Cellular factories have now provided many new safe and sustainable routes to fuels, pharmaceuticals, polymers, and specialty chemicals. Many of these successes have been achieved using the yeast Saccharomyces cerevisiae, which has been used and shaped by humans for millennia for the production of food and drink. Consequently, S. cerevisiae is one of the most studied eukaryotic organisms in existence, and has established genetic tools for engineering efforts. However, despite the many achievements in metabolic engineering of S. cerevisiae, it is still significantly more difficult to engineer than its prokaryotic counterpart, Escherichia coli. As a result, there is an unmet need to further develop genetic tools in yeast and to do so in the context of metabolic pathway engineering. The work presented here addresses this need through the study and engineering of heterologous gene expression. First, a new biosynthetic pathway is engineered for the production of muconic acid in yeast. Muconic acid is a dicarboxylic acid that can serve as a platform chemical for the production of several bio-polymers. The final muconic acid producing strain was developed through significant metabolic engineering efforts and reached a titer of nearly 141 mg/L muconic acid, a value nearly 24-fold higher than the initial strain. Second, a new method of engineering promoters is presented that allows for increased expression of native promoters and the de novo design of synthetic promoters. The highest expression synthetic promoter is within the top 6th percentile of native yeast promoters. Third, a study of native and synthetic terminators for heterologous gene expression is completed for the first time. This study demonstrates that terminators can tune heterologous expression by as much as an order of magnitude. Fourth, a comparative study of plasmid components dissects the different contributions to plasmid burden, copy number, and gene expression level. Collectively, this work represents a significant step forward in the metabolic engineering of yeast through the establishment of a new pathway and the study and engineering of new tools for heterologous gene expression. / text