Chemical and Biomolecular Engineering Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/2751
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Item ANALYSIS OF OBJECTIVES AND CONSTRAINTS TOWARDS PREDICTIVE MODELING OF COMPLEX METABOLISM(2020) Boruah, Navadeep; Sriram, Ganesh; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The central theme of this dissertation is predictive modeling of metabolism in complex biological systems with genome-scale stoichiometric metabolic models to (i) gain nontrivial insight on cellular metabolism and (ii) provide justifications for hitherto unexplained metabolic phenomena. The crux of high-quality predictive modeling with genome-scale stoichiometric metabolic models is appropriate selection of (i) a biologically relevant objective function and (ii) a set of constraints based on experimental data. However, in many complex systems, like a plant tissue with its wide array of specialized cells, a biological objective is not always apparent. Additionally, generation of experimental data to develop biochemically relevant constraints can be nearly impossible in systems that cannot be cultured under a controlled environment for the duration of an experiment. Such limitations necessitate careful reformulation of the biological question, development of novel methods and data analysis strategies. Here, we push the boundaries of predictive modeling by demonstrating its first application in deciphering hitherto unexplained metabolic phenomena and in developing novel hypotheses on metabolism. Towards achieving this goal, we developed several novel approaches and employed them in diverse biological systems. Firstly, we investigated the selection of carbohydrate degrading pathway employed by Saccharophagus degradans, an aerobic cellulosic marine bacterium. Flux balance analyses of its growth in nutrient rich hypoxic marine environment predicted that the selection of carbohydrate degrading pathway is possibly influenced by inorganic nutrient availability. Secondly, multi-tissue genome-scale metabolic modeling of Populus trichoparpa, a perennial woody tree, and analyses with a novel strategy based on multiple biologically relevant metrics provided a metabolic justification for the predominance of glutamine as the predominant nitrogen transport amino acid for internal nitrogen recycling. Thirdly, predictive modeling of maize grain filling predicted amino acid fermentation as a mechanism for expending excess reductant cofactors for continual starch synthesis in the hypoxic environment of endosperm. Finally, we developed bilevel optimization framework to integrate publicly available transcriptome datasets with metabolic networks. This framework predicted accumulation of specific classes of maize endosperm storage protein at distinct stages of grain filling. We anticipate that the employment of these aforementioned approaches in other biological systems will lead to the generation of a wide array of nontrivial hypothesis on cellular metabolism and to develop targeted experiments to validate them.Item Droplet Dynamics in Microfluidic Junctions(2012) Boruah, Navadeep; Dimitrakopoulos, Panagiotis; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The dynamics of droplets in confined microfluidic geometries is a problem of fundamental interest as such flow conditions occur in multiphase flows in porous media, biological systems, microfluidics and material science applications. In this thesis, we investigate computationally the dynamics of naturally buoyant droplets, with constant surface tension, in cross-junctions and T-junctions constructed from square microfluidic channels. A three-dimensional fully-implicit interfacial spectral boundary element method is employed to compute the interfacial dynamics of the droplets in the junctions and investigate the problem physics for a wide range of flow rates, viscosity ratios and droplet sizes. Our investigation reveals that as the flow rate or the droplet size increases, the droplets show a rich deformation behavior as they move inside the microfluidic devices. In the cross-junction, after obtaining a bullet-like shape before the flow intersection, the droplet become very slender inside the junction (to accommodate the intersecting flows), then it obtains an inverse-bullet shape as it exits the junction which reverts to a more pointed bullet-like shape far downstream. In the T-junction, the droplet obtains a skewed-bullet shape and a highly deformed slipper shape after entering the flows intersection. The viscosity ratio also has strong effects on the droplet deformation especially for high-viscosity droplets which do not have the time to accommodate the much slower deformation rate during their channel motion. Our results are in agreement with experimental findings, and provide physical insight on the confined droplet deformation.