Tumor Necrosis Factor-α Regulates Distinct Molecular Pathways and Gene Networks in Cultured Skeletal Muscle Cells

Skeletal muscle wasting is a debilitating consequence of large number of disease states and conditions. Tumor necrosis factor-α (TNF-α) is one of the most important muscle-wasting cytokine, elevated levels of which cause significant muscular abnormalities. However, the underpinning molecular mechanisms by which TNF-α causes skeletal muscle wasting are less well-understood.We have used microarray, quantitative real-time PCR (QRT-PCR), Western blot, and bioinformatics tools to study the effects of TNF-α on various molecular pathways and gene networks in C2C12 cells (a mouse myoblastic cell line). Microarray analyses of C2C12 myotubes treated with TNF-α (10 ng/ml) for 18h showed differential expression of a number of genes involved in distinct molecular pathways. The genes involved in nuclear factor-kappa B (NF-kappaB) signaling, 26s proteasome pathway, Notch1 signaling, and chemokine networks are the most important ones affected by TNF-α. The expression of some of the genes in microarray dataset showed good correlation in independent QRT-PCR and Western blot assays. Analysis of TNF-treated myotubes showed that TNF-α augments the activity of both canonical and alternative NF-κB signaling pathways in myotubes. Bioinformatics analyses of microarray dataset revealed that TNF-α affects the activity of several important pathways including those involved in oxidative stress, hepatic fibrosis, mitochondrial dysfunction, cholesterol biosynthesis, and TGF-β signaling. Furthermore, TNF-α was found to affect the gene networks related to drug metabolism, cell cycle, cancer, neurological disease, organismal injury, and abnormalities in myotubes.TNF-α regulates the expression of multiple genes involved in various toxic pathways which may be responsible for TNF-induced muscle loss in catabolic conditions. Our study suggests that TNF-α activates both canonical and alternative NF-κB signaling pathways in a time-dependent manner in skeletal muscle cells. The study provides novel insight into the mechanisms of action of TNF-α in skeletal muscle cells

Genomic Profiling of Messenger RNAs and MicroRNAs Reveals Potential Mechanisms of TWEAK-Induced Skeletal Muscle Wasting in Mice

Skeletal muscle wasting is a devastating complication of several physiological and pathophysiological conditions. Inflammatory cytokines play an important role in the loss of skeletal muscle mass in various chronic diseases. We have recently reported that proinflammatory cytokine TWEAK is a major muscle-wasting cytokine. Emerging evidence suggests that gene expression is regulated not only at transcriptional level but also at post-transcriptional level through the expression of specific non-coding microRNAs (miRs) which can affect the stability and/or translation of target mRNA. However, the role of miRs in skeletal muscle wasting is unknown.To understand the mechanism of action of TWEAK in skeletal muscle, we performed mRNA and miRs expression profile of control and TWEAK-treated myotubes. TWEAK increased the expression of a number of genes involved in inflammatory response and fibrosis and reduced the expression of few cytoskeletal gene (e.g. Myh4, Ankrd2, and TCap) and metabolic enzymes (e.g. Pgam2). Low density miR array demonstrated that TWEAK inhibits the expression of several miRs including muscle-specific miR-1-1, miR-1-2, miR-133a, miR-133b and miR-206. The expression of a few miRs including miR-146a and miR-455 was found to be significantly increased in response to TWEAK treatment. Ingenuity pathway analysis showed that several genes affected by TWEAK are known/putative targets of miRs. Our cDNA microarray data are consistent with miRs profiling. The levels of specific mRNAs and miRs were also found to be similarly regulated in atrophying skeletal muscle of transgenic mice (Tg) mice expressing TWEAK.Our results suggest that TWEAK affects the expression of several genes and microRNAs involved in inflammatory response, fibrosis, extracellular matrix remodeling, and proteolytic degradation which might be responsible for TWEAK-induced skeletal muscle loss

Targeted ablation of TRAF6 inhibits skeletal muscle wasting in mice

TRAF6 expression is enhanced during muscle atrophy and induces activation of signal transduction cascades that promote muscle wasting

Effect of PTTG on endogenous gene expression in HEK 293 cells

<p>Abstract</p> <p>Background</p> <p>Pituitary tumor transforming gene (PTTG), also known as securin, is highly expressed in various tumors including pituitary, thyroid, colon, ovary, testis, lung, and breast. An overexpression of PTTG enhances cell proliferation, induces cellular transformation <it>in vitro</it>, and promotes tumor development in nude mice. PTTG also inhibits separation of sister chromatids leading to aneuploidy and genetic instability. A great amount of work has been undertaken to understand the biology of PTTG and its expression in various tumors. However, mechanisms by which PTTG mediates its tumorigenic function are not fully understood. To utilize this gene for cancer therapy, identification of the downstream signaling genes regulated by PTTG in mediation of its tumorigenic function is necessary. For this purpose, we expressed PTTG in human embryonic kidney (HEK293) cells that do not express PTTG and analyzed the downstream genes using microarray analysis.</p> <p>Results</p> <p>A total of 22,277 genes printed on an Affymetrix HG-U133A 2.0 GeneChip™ array were screened with labeled cRNA prepared from HEK293 cells infected with adenovirus vector expressing PTTG cDNA (AdPTTG cDNA) and compared with labeled cRNA prepared from HEK293 cells infected with control adenovirus (control Ad) or adenovirus vector expressing GFP (AdGFP). Out of 22,277 genes, 71 genes were down-regulated and 35 genes were up-regulated with an FDR corrected p-value of ≤ 0.05 and a fold change of ≥2. Most of the altered genes identified are involved in the cell cycle and cell apoptosis; a few are involved in mRNA processing and nitrogen metabolism. Most of the up-regulated genes belong to the histone protein family.</p> <p>Conclusion</p> <p>PTTG is a well-studied oncogene for its role in tumorigenesis. In addition to its importance in regulation of the cell cycle, this gene has also been recently shown to play a role in the induction of cell apoptosis. The microarray analysis in the present study demonstrated that PTTG may induce apoptosis by down-regulation of oncogenes such as v-Jun and v-maf and up-regulation of the histone family of genes.</p

MicroRNA-301a mediated regulation of Kv4.2 in diabetes: identification of key modulators.

Diabetes is a metabolic disorder that ultimately results in major pathophysiological complications in the cardiovascular system. Diabetics are predisposed to higher incidences of sudden cardiac deaths (SCD). Several studies have associated diabetes as a major underlying risk for heart diseases and its complications. The diabetic heart undergoes remodeling to cope up with the underlying changes, however ultimately fails. In the present study we investigated the changes associated with a key ion channel and transcriptional factors in a diabetic heart model. In the mouse db/db model, we identified key transcriptional regulators and mediators that play important roles in the regulation of ion channel expression. Voltage-gated potassium channel (Kv4.2) is modulated in diabetes and is down regulated. We hypothesized that Kv4.2 expression is altered by potassium channel interacting protein-2 (KChIP2) which is regulated upstream by NFkB and miR-301a. We utilized qRT-PCR analysis and identified the genes that are affected in diabetes in a regional specific manner in the heart. At protein level we identified and validated differential expression of Kv4.2 and KChIP2 along with NFkB in both ventricles of diabetic hearts. In addition, we identified up-regulation of miR-301a in diabetic ventricles. We utilized loss and gain of function approaches to identify and validate the role of miR-301a in regulating Kv4.2. Based on in vivo and in vitro studies we conclude that miR-301a may be a central regulator for the expression of Kv4.2 in diabetes. This miR-301 mediated regulation of Kv4.2 is independent of NFkB and Irx5 and modulates Kv4.2 by direct binding on Kv4.2 3'untranslated region (3'-UTR). Therefore targeting miR-301a may offer new potential for developing therapeutic approaches

Gene Network Analysis in Amygdala following Taste Aversion Learning in Rats

Conditioned taste aversion (CTA) is an adaptive behavior that benefits survival of animals including humans and also serves as a powerful model to study the neural mechanisms of learning. Memory formation is a necessary component of CTA learning and involves neural processing and regulation of gene expression in the amygdala. Many studies have been focused on the identification of intracellular signaling cascades involved in CTA, but not late responsive genes underlying the long-lasting behavioral plasticity. In this study, we explored in silico experiments to identify persistent changes in gene expression associated with CTA in rats. We used oligonucleotide microarrays to identify 248 genes in the amygdala regulated by CTA. Pathway Studio and IPA software analyses showed that the differentially expressed genes in the amygdala fall in diverse functional categories such as behavior, psychological disorders, nervous system development and function, and cell-to-cell signaling. Conditioned taste aversion is a complex behavioral trait which involves association of visceral and taste inputs, consolidation of taste and visceral information, memory formation, retrieval of stored information, and extinction phase. In silico analysis of differentially expressed genes is therefore necessary to manipulate specific phase/stage of CTA to understand the molecular insight

MicroRNA signature of cis-platin resistant vs. cis-platin sensitive ovarian cancer cell lines

Abstract Background Ovarian cancer is the leading cause of death from gynecologic cancer in women worldwide. According to the National Cancer Institute, ovarian cancer has the highest mortality rate among all the reproductive cancers in women. Advanced stage diagnosis and chemo/radio-resistance is a major obstacle in treating advanced ovarian cancer. The most commonly employed chemotherapeutic drug for ovarian cancer treatment is cis-platin. As with most chemotherapeutic drugs, many patients eventually become resistant to cis-platin and therefore, diminishing its effect. The efficacy of current treatments may be improved by increasing the sensitivity of cancer cells to chemo/radiation therapies. Methods The present study is focused on identifying the differential expression of regulatory microRNAs (miRNAs) between cis-platin sensitive (A2780), and cis-platin resistant (A2780/CP70) cell lines. Cell proliferation assays were conducted to test the sensitivity of the two cell lines to cis-platin. Differential expression patterns of miRNA between cis-platin sensitive and cis-platin resistant cell lines were analyzed using novel LNA technology. Results Our results revealed changes in expression of 11 miRNAs out of 1,500 miRNAs analyzed. Out of the 11 miRNAs identified, 5 were up-regulated in the A2780/CP70 cell line and 6 were down regulated as compared to cis-platin sensitive A2780 cells. Our microRNA data was further validated by quantitative real-time PCR for these selected miRNAs. Ingenuity Pathway Analysis (IPA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis was performed for the selected miRNAs and their putative targets to identify the potential pathways and networks involved in cis-platin resistance. Conclusions Our data clearly showed the differential expression of 11 miRNAs in cis-platin resistant cells, which could potentially target many important pathways including MAPK, TGF-β signaling, actin cytoskeleton, ubiquitin mediated proteasomal pathway, Wnt signaling, mTOR signaling, Notch signaling, apoptosis, and many other signaling pathways. Manipulation of one or more of these miRNAs could be an important approach for ovarian cancer chemotherapy.</p