Protocol for measuring mitochondrial size in mouse and human liver tissues.

Mitochondrial dynamic process is important for cell viability, metabolic activity, and mitochondria health. Here, we present a protocol for measuring mitochondrial size through immunofluorescence staining, confocal imaging, and analysis in ImageJ. We describe the steps for tissue processing, antigen retrieval, mitochondrial staining using an integrating immunofluorescence assay, and computerized image analysis to measure each mitochondrial size in mouse and human liver tissues. This protocol reduces tissue sample volume and processing time for the preparation of primary cells. For complete details on the use and execution of this protocol, please refer to Pearah et al.1.

Blocking AMPKαS496 phosphorylation improves mitochondrial dynamics and hyperglycemia in aging and obesity.

Impaired mitochondrial dynamics causes aging-related or metabolic diseases. Yet, the molecular mechanism responsible for the impairment of mitochondrial dynamics is still not well understood. Here, we report that elevated blood insulin and/or glucagon levels downregulate mitochondrial fission through directly phosphorylating AMPKα at S496 by AKT or PKA, resulting in the impairment of AMPK-MFF-DRP1 signaling and mitochondrial dynamics and activity. Since there are significantly increased AMPKα1 phosphorylation at S496 in the liver of elderly mice, obese mice, and obese patients, we, therefore, designed AMPK-specific targeting peptides (Pa496m and Pa496h) to block AMPKα1S496 phosphorylation and found that these targeting peptides can increase AMPK kinase activity, augment mitochondrial fission and oxidation, and reduce ROS, leading to the rejuvenation of mitochondria. Furthermore, these AMPK targeting peptides robustly suppress liver glucose production in obese mice. Our data suggest these targeting peptides are promising therapeutic agents for improving mitochondrial dynamics and activity and alleviating hyperglycemia in elderly and obese patients.

Regulation of Liver Glucose and Lipid Metabolism by Transcriptional Factors and Coactivators.

The prevalence of nonalcoholic fatty liver disease (NAFLD) worldwide is on the rise and NAFLD is becoming the most common cause of chronic liver disease. In the USA, NAFLD affects over 30% of the population, with similar occurrence rates reported from Europe and Asia. This is due to the global increase in obesity and type 2 diabetes mellitus (T2DM) because patients with obesity and T2DM commonly have NAFLD, and patients with NAFLD are often obese and have T2DM with insulin resistance and dyslipidemia as well as hypertriglyceridemia. Excessive accumulation of triglycerides is a hallmark of NAFLD and NAFLD is now recognized as the liver disease component of metabolic syndrome. Liver glucose and lipid metabolisms are intertwined and carbon flux can be used to generate glucose or lipids; therefore, in this review we discuss the important transcription factors and coactivators that regulate glucose and lipid metabolism.

Far-western Blotting Detection of the Binding of Insulin Receptor Substrate to the Insulin Receptor.

Far-western blotting, derived from the western blot, has been used to detect interactions between proteins in vitro, such as receptor-ligand interactions. The insulin signaling pathway plays a critical role in the regulation of both metabolism and cell growth. The binding of the insulin receptor substrate (IRS) to the insulin receptor is essential for the propagation of downstream signaling after the activation of the insulin receptor by insulin. Here, we describe a step-by-step far-western blotting protocol for determining the binding of IRS to the insulin receptor.

Activation of the canonical ER stress IRE1-XBP1 pathway by insulin regulates glucose and lipid metabolism.

Knockout of the transcription factor X-box binding protein (XBP1) is known to decrease liver glucose production and lipogenesis. However, whether insulin can regulate gluconeogenesis and lipogenesis through XBP1 and how insulin activates the inositol-requiring enzyme-XBP1 ER stress pathway remains unexplored. Here, we report that in the fed state, insulin-activated kinase AKT directly phosphorylates inositol-requiring enzyme 1 at S724, which in turn mediates the splicing of XBP1u mRNA, thus favoring the generation of the spliced form, XBP1s, in the liver of mice. Subsequently, XBP1s stimulate the expression of lipogenic genes and upregulates liver lipogenesis as previously reported. Intriguingly, we find that fasting leads to an increase in XBP1u along with a drastic decrease in XBP1s in the liver of mice, and XBP1u, not XBP1s, significantly increases PKA-stimulated CRE reporter activity in cultured hepatocytes. Furthermore, we demonstrate that overexpression of XBP1u significantly increases cAMP-stimulated expression of rate-limiting gluconeogenic genes, G6pc and Pck1, and glucose production in primary hepatocytes. Reexpression of XBP1u in the liver of mice with XBP1 depletion significantly increases fasting blood glucose levels and gluconeogenic gene expression. These data support an important role of XBP1u in upregulating gluconeogenesis in the fasted state. Taken together, we reveal that insulin signaling via AKT controls the expression of XBP1 isoforms and that XBP1u and XBP1s function in different nutritional states to regulate liver gluconeogenesis and lipogenesis, respectively.

The P300 acetyltransferase inhibitor C646 promotes membrane translocation of insulin receptor protein substrate and interaction with the insulin receptor.

Inhibition of P300 acetyltransferase activity by specific inhibitor C646 has been shown to improve insulin signaling. However, the underlying molecular mechanism of this improvement remains unclear. In this study, we analyzed P300 levels of obese patients and found that they were significantly increased in liver hepatocytes. In addition, large amounts of P300 appeared in the cytoplasm. Inhibition of P300 acetyltransferase activity by C646 drastically increased tyrosine phosphorylation of the insulin receptor protein substrates (IRS1/2) without affecting the tyrosine phosphorylation of the beta subunit of the insulin receptor (IRß) in hepatocytes in the absence of insulin. Since IRS1/2 requires membrane translocation and binding to inositol compounds for normal functions, we also examined the role of acetylation on binding to phosphatidylinositol(4,5)P2 and found that IRS1/2 acetylation by P300 reduced this binding. In contrast, we show that inhibition of IRS1/2 acetylation by C646 facilitates IRS1/2 membrane translocation. Intriguingly, we demonstrate that C646 activates IRß's tyrosine kinase activity and directly promotes IRß interaction with IRS1/2, leading to the tyrosine phosphorylation of IRS1/2 and subsequent activation of insulin signaling even in the absence of insulin. In conclusion, these data reveal the unique effects of C646 in activating insulin signaling in patients with obesity and diabetes.

Development and Functions of Mitochondria in Early Life.

Mitochondria are highly dynamic organelles of bacterial origin in eukaryotic cells. These play a central role in metabolism and adenosine triphosphate (ATP) synthesis and in the production and regulation of reactive oxygen species (ROS). In addition to the generation of energy, mitochondria perform numerous other functions to support key developmental events such as fertilization during reproduction, oocyte maturation, and the development of the embryo. During embryonic and neonatal development, mitochondria may have important effects on metabolic, energetic, and epigenetic regulation, which may have significant short- and long-term effects on embryonic and offspring health. Hence, the environment, epigenome, and early-life regulation are all linked by mitochondrial integrity, communication, and metabolism.

Identification of Prognostic Biomarker Candidates Associated With Melanoma Using High-Dimensional Genomic Data.

Survival of patients with metastatic melanoma varies widely. Melanoma is a highly proliferative, chemo-resistant disease. With the recent availability of immunotherapies such as checkpoint inhibitors, durable response rates have improved but are often still limited to 2-3 years. Response rates to treatment range from 30 to 45% with combination therapy however no improvement in overall survival is frequently observed. Of the available therapies, many have targeted the BRAFV600E mutation that results in abnormal MAPK pathway activation which is important for regulating cell proliferation. Immune checkpoint inhibitors such as anti-PD-1 and anti-PD-L1 offer better success but response rates are still low. Identifying biomarkers to better target those who will respond and identify the right combination of treatment is the best approach. In this study, we utilize data from the Cancer Cell Line Encyclopedia (CCLE), including 62 samples, to examine features of gene expression (19K+) and copy number (20K+) in the melanoma cell lines. We perform a clustering analysis on the feature set to assess genetically similarity among the cell lines. We then discover which specific genes and combinations thereof maximize cluster density. We design a feature selection approach for high-dimensional datasets that integrates multiple disparate machine learning techniques into one cohesive pipeline. Our approach provides a small subset of genes that can accurately distinguish between the clusters of melanoma cell lines across multiple types of classifiers. In particular, we find only the 15 highest ranked genes among the original 19 K are necessary to achieve perfect or near-perfect test split classification performance. Of these 15 genes, some are known to be linked to melanoma or other cancer progressions, while others have not previously been linked to melanoma and are of interest for further examination.