LanguageTerm (authority = ISO 639-3:2007); (type = text)
English
Abstract (type = abstract)
Diabetes mellitus (DM) is a chronic disease that affects nearly 10% of the population worldwide. The most well-known symptom of DM is hyperglycemia, which causes nearly 2 million direct death each year with a series of complications including stroke, blindness and heart attack. Enhanced glucagon signaling, insulin resistance, and altered substrate availability have been offered as explanations of the elevated gluconeogenesis, but collectively their in vivo contributions and interactions in gluconeogenesis remain unclear. Since gluconeogenesis is a relatively complicated pathway that involves multiple substrates, enzymes and hormonal regulations, a comprehensive metabolic flux analysis (MFA) across multiple diabetic mouse models are required. The aim of this dissertation is to develop a tool for the flux analysis of gluconeogenesis and use this tool to analyze multiple diabetic models which mimics the effect of glucagon signaling, insulin resistance and high fat diet (HFD) feeding.
We first described how the gluconeogenic flux model was designed and constructed in detail (Chapter 2). Then we used this flux model to study the relative contribution of glycogen, lactate and glycerol in glucose production of male C57BL/6J-albino mice after 6, 12 and 18 hours of fasting (Chapter 3). We found that during both short and prolonged fasting, lactate served as the largest direct gluconeogenic substrate but a minor source for the net carbon contribution. In contrast, glycerol served as the second largest direct substrate and the dominant net carbon source in both short and prolonged fasting. We next used the flux model to study the effect of hepatic glucagon signaling and HFD feeding on gluconeogenesis (Chapter 4). We used constitutive protein kinase a (PKA) activation to mimic the enhanced hepatic glucagon signaling plus a classic HFD approach to model the diet-induced obesity in mice. We found that HFD feeding alone increased gluconeogenic flux from glycerol but not from lactate. In contrast, PKA activation increased gluconeogenic flux from both glycerol and lactate. Interestingly, when two effects were combined, a more than additive increase of gluconeogenesis flux from both substrates were observed. Further investigation revealed a synergistic effect of glycerol and PKA activation in up-regulating G6pc expression. Finally, we used the same strategy to investigate the effect of hepatic insulin resistance on gluconeogenesis under both normal chow and HFD feeding (Chapter 5). We used liver insulin receptor knockout (LIRKO) to model hepatic insulin resistance. We found LIRKO only mildly increase the gluconeogenic flux from both glycerol and lactate in normal chow fed mice. In the context of HFD feeding, LIRKO significantly decreased the flux from glycerol but increased that from lactate compared to the HFD control mice, suggesting a shift of substrate preference from glycerol to lactate. Further investigation showed that this shift of substrate preference is related to the down-regulation of glycerol kinase (Gyk) caused by LIRKO.
In summary, MFA is a useful, powerful and unique tool to investigate the metabolism in complicated pathways like gluconeogenesis. Our result suggests neither enzyme activity nor substrate concentration alone is sufficient to represent the metabolic flux. To accurately quantify the metabolism in vivo and distinguish its changes under different conditions, MFA seems to be the only reliable solution so far. Further studies should focus on simplify the procedure of MFA experiments and make it more accessible and suitable for clinical purpose.
Subject (authority = local)
Topic
Diabetes
Subject (authority = RUETD)
Topic
Microbiology and Molecular Genetics
RelatedItem (type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier (type = RULIB)
ETD
Identifier
ETD_10681
PhysicalDescription
Form (authority = gmd)
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (xiii, 179 pages)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = vita)
Includes vita
RelatedItem (type = host)
TitleInfo
Title
School of Graduate Studies Electronic Theses and Dissertations
Identifier (type = local)
rucore10001600001
Location
PhysicalLocation (authority = marcorg); (displayLabel = Rutgers, The State University of New Jersey)
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