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Dissertation/Thesis Abstract

Tracing Metabolism from Sugars and One-Carbon Substrates Using Stable Isotopes
by Gonzalez, Jacqueline Eve, Ph.D., University of Delaware, 2018, 276; 10817133
Abstract (Summary)

The production of chemicals through bioconversion has received much attention over the past decade. Focus is now shifting towards the utilization of cheap, renewable and waste feedstocks for chemical production. With the availability of these feedstocks, metabolic engineering efforts are targeted towards engineering organisms to utilize one or more of these substrates and produce value-added chemicals. Therefore, it is of critical importance to evaluate the economic feasibility of bioprocesses, determine the capabilities of microbial systems, identify targets for improvements, and select ideal candidates for industrial implementation. A powerful method for characterizing in vivo metabolism is through the use of 13C-labeled substrates (or 13C-tracers). Tracing techniques allow quantitative evaluation of the flow of carbon from feedstocks to central metabolism and further into the desired products. Additionally, advanced techniques, such as 13C-metaboic flux analysis (13C-MFA), can be applied to gain a fine-grained picture of native metabolism and metabolic changes that result from genetic manipulations. Isotopic tracers are easy to implement and can be used to achieve a wealth of new information about metabolism. However, there has been limited application of tracers and therefore, their potential has not been realized. We aim to demonstrate how tracers can be applied to various systems to gain a detailed understanding of pathway utilization. The systems studied here include ones with multiple substrates, engineered pathways, and one-carbon substrates. Additionally, we develop new methods of MFA that allow for its application to a broader range of systems. Sugars are the main product of lignocellulose hydrolysis and a common feedstock for bioprocesses. While glucose and xylose are the two most abundant sugars derived from the breakdown of lignocellulosic biomass, there have been few studies of their metabolism under various environmental conditions. In the absence this experimental data, constraint-based approaches cannot be used to guide new metabolic engineering designs. In this work, we have addressed this critical gap by performing comprehensive characterizations of glucose and xylose metabolism under aerobic and anaerobic conditions, including applying 13C-MFA, measuring biomass composition and biomass turnover, and quantifying co-factor requirements. Additionally, we examine more efficient E. coli strains that can co-utilize these two sugars through application of 13C-MFA and interrogation of their sugar uptake profile. Through this analysis, we identified the ideal uptake profile to be linear and non-biased towards a specific substrate, focusing future efforts towards the development of novel transport systems. Another interesting feedstock, methane, the main component of natural gas, can be used to produce methanol which can be further converted to other valuable products. There is increasing interest in using biological systems for the production of fuels and chemicals from methanol, termed methylotrophy. Here, we first examine methanol assimilation metabolism in a synthetic methylotrophic E. coli strain. Through our investigations, we proposed specific metabolic pathways that, when activated, correlated with increased methanol assimilation. These pathways are normally repressed by the leucine-responsive regulatory protein (lrp), a global regulator of metabolism associated with the feast-and-famine response in E. coli. By deleting lrp, we were able to further enhance the methylotrophic ability of our synthetic strain, as demonstrated through increased incorporation of 13C carbon from 13C-methanol into biomass. Additionally, we study the methanogen, Methanosarcina acetivorans, a model organism for studying the conversion of various substrates into methane and a possible host for the conversion of methane into value-added products. Here, we characterize this organism during growth on the one-carbon substrate, methanol. Typically, estimating fluxes during growth on one-carbon substrates requires more advanced computational approaches and precise sampling of metabolic intermediates compared to 13C-MFA. Here, we applied classical 13C-MFA to validate the network model and generate the first flux map for M. acetivorans, demonstrating the successful application of classical 13C-MFA to a one-carbon system. Lastly, we aim to extend the reach of metabolic flux analysis. To apply 13C-MFA, it is assumed that the system being interrogated is at metabolic and isotopic steady state, where fluxes and isotopic labeling remain constant over time. This assumption limits the application of 13C-MFA to systems where these assumptions do not hold. Here, we address the need for metabolic flux analysis methods that can be used for atypical systems, ones that are not at isotopic or metabolic steady state. We present an extension of DMFA to include isotopic labeling measurements (13C-DMFA) and evaluate established MFA methods (13C-MFA, 13C-NMFA, and 13C-DMFA) and their ability to estimate fluxes for various conditions. It was concluded that 13C-MFA can be used for systems at isotopic steady state, 13C-NMFA can be used for systems at metabolic steady state, and 13C-DMFA can be used for metabolic and isotopic non-steady state. This work is the first demonstration of 13C-DMFA and clearly outlines how and when each established method should be applied, substantially increasing the range of systems and organisms that can be studied.

Indexing (document details)
Advisor: Antoniewicz, Maciek R.
Commitee: Ardis, Ann L., Furst, Eric M., Ogunnaike, Babatunde A.
School: University of Delaware
Department: Chemical Engineering
School Location: United States -- Delaware
Source: DAI-B 79/12(E), Dissertation Abstracts International
Subjects: Engineering, Chemical engineering
Keywords: Metabolism, One-carbon substrates, Stable isotopes, Sugars
Publication Number: 10817133
ISBN: 978-0-438-24519-8
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