Chemical and Biomolecular Engineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2751
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Item Investigating the metabolic landscape alterations in poplar cells induced by carbon and nitrogen deficiency via improved 13C metabolic flux analysis methodology(2015) Zhang, Xiaofeng; Sriram, Ganesh; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Plants are considered biological factories with their ability of converting solar energy into chemical energy in the form of various commercially valuable products, such as food, biofuel and pharmaceuticals. The yields of these products are directly influenced by the level of nitrogen nutrient supply. However, both biological and industrial nitrogen fixation are energetically expensive and thus managing the nitrogen cycle has been identified as one of the 14 grand challenges by the National Academy of Engineering (NAE). Therefore it is desirable to investigate how plants themselves adapt to nitrogen deficient environment and improve their nitrogen use efficiency (NUE). A powerful tool to study metabolism is isotope-assisted metabolic flux analysis (isotopic MFA), which quantifies intracellular chemical reaction rates (fluxes) via isotopic labeling experiments (ILEs) and subsequent mathematical modeling. In ILEs the labeling patterns of the metabolites can be measured at either isotopic steady state or isotopic instationary state. Between these two methods, collecting data during isotopic instationary state saves experimental time, but is computationally more challenging due to that instationary MFA involves solving ordinary differential equations (ODEs). In this study, we firstly developed an approach that combined the concept of "originomer" with an analytical based solution method to improve computational efficiency of instationary MFA. Simulation results showed that this approach reduced computational time by 23-fold for certain realistic metabolic network. Secondly, we managed to solve an intrinsic problem that affect steady state MFA in fed-batch cell culture environment - the influence of unlabeled biomass that are present before applying isotopic tracers in an ILE. We proposed a full "reflux" metabolic network model that significantly improved the accuracy of evaluated fluxes when compared to the models without "reflux". Finally, we investigated the ability of adapting nutrient deficiencies and the NUE-improving mechanisms in suspension cells of poplar, a woody perennial tree capable of efficiently managing its nitrogen reserves. Through (i) steady-state 13C MFA and (ii) transcripomic profiling via microarray on poplar cells growing under different carbon (C) and nitrogen (N) supply levels, we found a plastidic localization of oxidative pentose phosphate pathway (oxPPP), as well as a lower oxPPP flux under low nitrogen supply. Gene expression data also points to possible NUE improving mechanisms employed by poplar cells. We hope this study will shed light on potential metabolic engineering directions to improve NUE in plants.Item Mapping metabolic fluxes in plant cells to understand carbon-nitrogen interactions and nitrogen storage and cycling(2012) Nargund, Shilpa; Sriram, Ganesh; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Plants provide commodities like food, fiber, fuel and chemicals. Understanding plant metabolism will help find genetic engineering targets that enhance production of these commodities. Interactions between the macronutrients - carbon (C) and nitrogen (N) determine growth and developmental functions in plants (Nunes-Nesi, Fernie, and Stitt 2010; Sakakibara, Takei, and Hirose 2006) and are regulated by complex mechanisms that need systems-level analyses. Metabolic fluxes, the rates of C flow in metabolic pathways, provide a system-wide view of metabolism and are quantified by steady state metabolic flux analysis (MFA) wherein isotopic tracers (13C, 15N) are fed to the cells and the resulting labeling patterns of biomass components are used to fit the fluxes. In this study we i) statistically designed isotope labeling experiments (ILEs) in silico to enhance accuracy of flux estimates through the pentose phosphate pathway (PPP) ii) conducted MFA on heterotrophic cell suspensions of Arabidopsis thaliana (Arabidopsis), a model plant, to investigate regulatory role of light in cell metabolism and iii) conducted MFA on cell suspensions of poplar (Populus tremula × Populus alba; clone N 717-B4), a potential biofuel crop, to understand C-N interactions. In silico label design studies determined that accuracy of flux estimates in the PPP improves by ILEs with 1,2-13C glucose and measuring labeling patterns of sugars, especially ribose. Metabolic fluxes, estimated by the designed ILEs on Arabidopsis cells, under continuous light or dark, showed negligible changes between treatments indicating that light does not regulate central carbon metabolism in heterotrophic Arabidopsis cells. The designed ILEs improved confidences of non-oxidative PPP flux estimates by 40-80% from previous studies (Masakapalli et al. 2009a). ILEs on poplar cell suspensions, grown in batch cultures, displayed unexpected back-mixing between unlabeled seed biomass and newly synthesized labeled biomass. Novel metabolic network models were developed that successfully account for observed back-mixing. ILEs on poplar cells, subjected to different C-N supply treatments to understand C-N interactions showed significant differences in phenylalanine labeling which may implicate role of flavonoid biosynthesis pathway in C-N interactions. Design of ILEs and subsequent improvement in flux estimates and the improvements in modeling metabolic networks are the novel contributions of this work.