Multi-scale, whole-system models of liver metabolic adaptation to fat and sugar in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a serious public health issue associated with high fat, high sugar diets. However, the molecular mechanisms mediating NAFLD pathogenesis are only partially understood. Here we adopt an iterative multi-scale, systems biology approach coupled to in vitro experimentation to investigate the roles of sugar and fat metabolism in NAFLD pathogenesis. The use of fructose as a sweetening agent is controversial; to explore this, we developed a predictive model of human monosaccharide transport, signalling and metabolism. The resulting quantitative model comprising a kinetic model describing monosaccharide transport and insulin signalling integrated with a hepatocyte-specific genome-scale metabolic network (GSMN). Differential kinetics for the utilisation of glucose and fructose were predicted, but the resultant triacylglycerol production was predicted to be similar for monosaccharides; these predictions were verified by in vitro data. The role of physiological adaptation to lipid overload was explored through the comprehensive reconstruction of the peroxisome proliferator activated receptor alpha (PPARα) regulome integrated with a hepatocyte-specific GSMN. The resulting qualitative model reproduced metabolic responses to increased fatty acid levels and mimicked lipid loading in vitro. The model predicted that activation of PPARα by lipids produces a biphasic response, which initially exacerbates steatosis. Our data support the evidence that it is the quantity of sugar rather than the type that is critical in driving the steatotic response. Furthermore, we predict PPARα-mediated adaptations to hepatic lipid overload, shedding light on potential challenges for the use of PPARα agonists to treat NAFLD

Liver-Specific Expression of Transcriptionally Active SREBP-1c Is Associated with Fatty Liver and Increased Visceral Fat Mass

The pathogenesis of fatty liver is not understood in detail, but lipid overflow as well as de novo lipogenesis (DNL) seem to be the key points of hepatocyte accumulation of lipids. One key transcription factor in DNL is sterol regulatory element-binding protein (SREBP)-1c. We generated mice with liver-specific over-expression of mature human SREBP-1c under control of the albumin promoter and a liver-specific enhancer (alb-SREBP-1c) to analyze systemic perturbations caused by this distinct alteration. SREBP-1c targets specific genes and causes key enzymes in DNL and lipid metabolism to be up-regulated. The alb-SREBP-1c mice developed hepatic lipid accumulation featuring a fatty liver by the age of 24 weeks under normocaloric nutrition. On a molecular level, clinical parameters and lipid-profiles varied according to the fatty liver phenotype. The desaturation index was increased compared to wild type mice. In liver, fatty acids (FA) were increased by 50% (p<0.01) and lipid composition was shifted to mono unsaturated FA, whereas lipid profile in adipose tissue or serum was not altered. Serum analyses revealed a ∼2-fold (p<0.01) increase in triglycerides and free fatty acids, and a ∼3-fold (p<0.01) increase in insulin levels, indicating insulin resistance; however, no significant cytokine profile alterations have been determined. Interestingly and unexpectedly, mice also developed adipositas with considerably increased visceral adipose tissue, although calorie intake was not different compared to control mice. In conclusion, the alb-SREBP-1c mouse model allowed the elucidation of the systemic impact of SREBP-1c as a central regulator of lipid metabolism in vivo and also demonstrated that the liver is a more active player in metabolic diseases such as visceral obesity and insulin resistance

Allopregnanolone Promotes Regeneration and Reduces β-Amyloid Burden in a Preclinical Model of Alzheimer's Disease

Previously, we demonstrated that allopregnanolone (APα) promoted proliferation of rodent and human neural progenitor cells in vitro. Further, we demonstrated that APα promoted neurogenesis in the hippocampal subgranular zone (SGZ) and reversed learning and memory deficits in the male triple transgenic mouse model of Alzheimer's (3xTgAD). In the current study, we determined the efficacy of APα to promote the survival of newly generated neural cells while simultaneously reducing Alzheimer's disease (AD) pathology in the 3xTgAD male mouse model. Comparative analyses between three different APα treatment regimens indicated that APα administered 1/week for 6 months was maximally efficacious for simultaneous promotion of neurogenesis and survival of newly generated cells and reduction of AD pathology. We further investigated the efficacy of APα to impact Aβ burden. Treatment was initiated either prior to or post intraneuronal Aβ accumulation. Results indicated that APα administered 1/week for 6 months significantly increased survival of newly generated neurons and simultaneously reduced Aβ pathology with greatest efficacy in the pre-pathology treatment group. APα significantly reduced Aβ generation in hippocampus, cortex, and amygdala, which was paralleled by decreased expression of Aβ-binding-alcohol-dehydrogenase. In addition, APα significantly reduced microglia activation as indicated by reduced expression of OX42 while increasing CNPase, an oligodendrocyte myelin marker. Mechanistic analyses indicated that pre-pathology treatment with APα increased expression of liver-X-receptor, pregnane-X-receptor, and 3-hydroxy-3-methyl-glutaryl-CoA-reductase (HMG-CoA-R), three proteins that regulate cholesterol homeostasis and clearance from brain. Together these findings provide preclinical evidence for the optimal treatment regimen of APα to achieve efficacy as a disease modifying therapeutic to promote regeneration while simultaneously decreasing the pathology associated with Alzheimer's disease

TonEBP/NFAT5 haploinsufficiency attenuates hippocampal inflammation in high-fat diet/streptozotocin-induced diabetic mice

Recent studies have shown that overexpression of tonicity-responsive enhancer binding protein (TonEBP) is associated with many inflammatory diseases, including diabetes mellitus, which causes neuroinflammation in the hippocampus as well as hepatic steatosis. However, the exact mechanism in diabetic neuroinflammation is unknown. We report that haploinsufficiency of TonEBP inhibits hepatic and hippocampal high-mobility group box-1 (HMGB1) expression in diabetic mice. Here, mice were fed a high-fat diet (HFD) for 16 weeks and received an intraperitoneal injection of 100 mg/kg streptozotocin (STZ) and followed by continued HFD feeding for an additional 4 weeks to induce hyperglycemia and hepatic steatosis. Compared with wild-type diabetic mice, diabetic TonEBP(+/-) mice showed decreased body weight, fat mass, hepatic steatosis, and macrophage infiltration. We also found that adipogenesis and HMGB1 expression in the liver and hippocampus were lower in diabetic TonEBP(+/-) mice compared with the wild type. Furthermore, iba-1 immunoreactivity in the hippocampus was decreased in diabetic TonEBP(+/-) mice compared with that in the wild type. Our findings suggest that TonEBP haploinsufficiency suppresses diabetes-associated hepatic steatosis and neuroinflammation

A computational model for the analysis of Lipoprotein distributions in the mouse : translating FPLC profiles to Lipoprotein metabolism

Disturbances of lipoprotein metabolism are recognized as indicators of cardiometabolic disease risk. Lipoprotein size and composition, measured in a lipoprotein profile, are considered to be disease risk markers. However, the measured profile is a collective result of complex metabolic interactions, which complicates the identification of changes in metabolism. In this study we aim to develop a method which quantitatively relates murine lipoprotein size, composition and concentration to the molecular mechanisms underlying lipoprotein metabolism. We introduce a computational framework which incorporates a novel kinetic model of murine lipoprotein metabolism. The model is applied to compute a distribution of plasma lipoproteins, which is then related to experimental lipoprotein profiles through the generation of an in silico lipoprotein profile. The model was first applied to profiles obtained from wild-type C57Bl/6J mice. The results provided insight into the interplay of lipoprotein production, remodelling and catabolism. Moreover, the concentration and metabolism of unmeasured lipoprotein components could be determined. The model was validated through the prediction of lipoprotein profiles of several transgenic mouse models commonly used in cardiovascular research. Finally, the framework was employed for longitudinal analysis of the profiles of C57Bl/6J mice following a pharmaceutical intervention with a liver X receptor (LXR) agonist. The multifaceted regulatory response to the administration of the compound is incompletely understood. The results explain the characteristic changes of the observed lipoprotein profile in terms of the underlying metabolic perturbation and resultant modifications of lipid fluxes in the body. The Murine Lipoprotein Profiler (MuLiP) presented here is thus a valuable tool to assess the metabolic origin of altered murine lipoprotein profiles and can be applied in preclinical research performed in mice for analysis of lipid fluxes and lipoprotein composition