<em>Mig-6</em> Plays a Critical Role in the Regulation of Cholesterol Homeostasis and Bile Acid Synthesis

<div><p>The disruption of cholesterol homeostasis leads to an increase in cholesterol levels which results in the development of cardiovascular disease. Mitogen Inducible Gene 6 (<em>Mig-6</em>) is an immediate early response gene that can be induced by various mitogens, stresses, and hormones. To identify the metabolic role of <em>Mig-6</em> in the liver, we conditionally ablated <em>Mig-6</em> in the liver using the Albumin-Cre mouse model (<em>Alb^cre/+Mig-6^f/f</em>; <em>Mig-6^d/d</em>). <em>Mig-6^d/d</em> mice exhibit hepatomegaly and fatty liver. Serum levels of total, LDL, and HDL cholesterol and hepatic lipid were significantly increased in the <em>Mig-6^d/d</em> mice. The daily excretion of fecal bile acids was significantly decreased in the <em>Mig-6^d/d</em> mice. DNA microarray analysis of mRNA isolated from the livers of these mice showed alterations in genes that regulate lipid metabolism, bile acid, and cholesterol synthesis, while the expression of genes that regulate biliary excretion of bile acid and triglyceride synthesis showed no difference in the <em>Mig-6^d/d</em> mice compared to <em>Mig-6^f/f</em> controls. These results indicate that <em>Mig-6</em> plays an important role in cholesterol homeostasis and bile acid synthesis. Mice with liver specific conditional ablation of <em>Mig-6</em> develop hepatomegaly and increased intrahepatic lipid and provide a novel model system to investigate the genetic and molecular events involved in the regulation of cholesterol homeostasis and bile acid synthesis. Defining the molecular mechanisms by which <em>Mig-6</em> regulates cholesterol homeostasis will provide new insights into the development of more effective ways for the treatment and prevention of cardiovascular disease.</p> </div

Concentration of bile acid in serum, liver, and feces.

<p>Serum and liver were collected from 8 week old <i>Mig-6^d/d</i> and <i>Mig-6^f/f</i> male mice after 24 hrs. of fasting. Feces were collected from individual mice for 3 days. 5 mice of each group were used for this experiment.</p>**<p>, <i>p</i><0.01.</p

Generation of conditional ablation of <i>Mig-6</i> in the liver.

<p>A. RT-PCR analysis of <i>Mig-6</i> mRNA expression level. 8 week old <i>Mig-6^f/f</i> and <i>Mig-6^d/d</i> male mice were sacrificed after 24 hrs of fasting and RNA was isolated from the liver, kidney, adrenal gland, lungs, muscle, and white adipose tissue. Five mice of each group were used for this experiment. The results represent the mean ± SEM of three independent RNA sets. ***, <i>p</i><0.001. B, Western blot analysis of MIG-6 in the liver of <i>Mig-6^f/f</i> and <i>Mig-6^d/d</i> mice. Liver tissue from <i>Mig-6^f/f</i> and <i>Mig-6^d/d</i> mice were lysed and equal amounts of protein were subjected to SDS-PAGE and Western blot analysis for MIG-6.</p

Serum lipid profile in <i>Mig-6 ^f/f</i> and <i>Mig-6^d/d</i> mice.

<p>Eight week old <i>Mig-6^d/d</i> and <i>Mig-6^f/f</i> male mice were sacrificed after 24 hrs of fasting and serum lipid profiles were analyzed. Five mice of each group were used for this experiment.</p>*<p>, <i>p</i><0.05;</p>**<p>, <i>p</i><0.01;</p>***<p>, <i>p</i><0.001.</p

Real-time RT-PCR analysis of metabolic genes in the liver.

<p>A, Bile acid metabolism related genes. B, Cholesterol synthesis related genes. C, Triglyceride metabolism related genes. 8 week old <i>Mig-6^d/d</i> and <i>Mig-6^f/f</i> male mice were sacrificed after 24 hrs fasting and RNA was isolated from the liver. 5 mice of each group were used for this experiment. The results represent the mean ± SEM of three independent RNA sets. *, <i>p</i><0.05; ***, <i>p</i><0.001.</p

Morphology of the liver of <i>Mig-6^f/f</i> and <i>Mig-6^d/d</i>

<p><b>mice.</b> A, Size of liver. Twelve mice of each group were used for this experiment. B, Weight of the liver adjusted to body weight. The results represent the mean ± SEM. The numbers in parentheses are the number of mice used. ***, p<0.001. C. Oil-Red-O staining. Liver tissue were fixed with 4% paraformaldehyde (vol/vol) and frozen in OCT. Sections were counterstained with hematoxylin and mounted with 15% glycerol. All of the photomicrographs are X400 magnification.</p

ACLY and ACC1 Regulate Hypoxia-Induced Apoptosis by Modulating ETV4 via α-ketoglutarate

<div><p>In order to propagate a solid tumor, cancer cells must adapt to and survive under various tumor microenvironment (TME) stresses, such as hypoxia or lactic acidosis. To systematically identify genes that modulate cancer cell survival under stresses, we performed genome-wide shRNA screens under hypoxia or lactic acidosis. We discovered that genetic depletion of acetyl-CoA carboxylase (<i>ACACA</i> or <i>ACC1</i>) or ATP citrate lyase (<i>ACLY</i>) protected cancer cells from hypoxia-induced apoptosis. Additionally, the loss of ACLY or ACC1 reduced levels and activities of the oncogenic transcription factor ETV4. Silencing ETV4 also protected cells from hypoxia-induced apoptosis and led to remarkably similar transcriptional responses as with silenced ACLY or ACC1, including an anti-apoptotic program. Metabolomic analysis found that while α-ketoglutarate levels decrease under hypoxia in control cells, α-ketoglutarate is paradoxically increased under hypoxia when ACC1 or ACLY are depleted. Supplementation with α-ketoglutarate rescued the hypoxia-induced apoptosis and recapitulated the decreased expression and activity of ETV4, likely via an epigenetic mechanism. Therefore, ACC1 and ACLY regulate the levels of ETV4 under hypoxia via increased α-ketoglutarate. These results reveal that the ACC1/ACLY-α-ketoglutarate-ETV4 axis is a novel means by which metabolic states regulate transcriptional output for life vs. death decisions under hypoxia. Since many lipogenic inhibitors are under investigation as cancer therapeutics, our findings suggest that the use of these inhibitors will need to be carefully considered with respect to oncogenic drivers, tumor hypoxia, progression and dormancy. More broadly, our screen provides a framework for studying additional tumor cell stress-adaption mechanisms in the future.</p></div

Principal Components Analyses (PCA) for Fasting to Postprandial Changes in Metabolites.^*

<p>*Changes were computed as postprandial metabolite concentration minus preprandial metabolite concentration. For these differences, PCA was performed separately for each metabolite class: fatty acids, acylcarnitines, and amino acids. Key metabolites within each component (<i>i.e.</i>, metabolites with component load ≥|0.5|) are presented.</p

Preprandial and postprandial concentrations of acylcarnitines in response to caloric restriction (CR).

<p>Baseline and three month acylcarnitine concentrations are shown for both fasting (preprandial) and postprandial assessments. The six acylcarnitines that had the largest loadings on the acylcarnitine factor (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0028190#pone-0028190-t001" target="_blank">Table 1</a>) are shown.</p

Baseline to Month Three Changes in Insulin Sensitivity: Average Group Improvements Despite Varied Individual Responses.

<p>Each bar represents insulin sensitivity improvements for participating individuals. A. By intervention group. CR = Caloric restriction; CR+EX = Caloric restriction with exercise; Control = Healthy weight maintenance diet; LCD = Liquid calorie diet B. Intervention groups combined.</p