Potential Interaction Between the GARS-AIRS-GART Gene and CP2/LBP-1c/LSF Transcription Factor in Down Syndrome-related Alzheimer Disease

Winter is coming: Regulation of cellular metabolism by enzyme polymerization in dormancy and disease

Metabolism feeds growth. Accordingly, metabolism is regulated by nutrient-sensing pathways that converge growth promoting signals into biosynthesis by regulating the activity of metabolic enzymes. When the environment does not support growth, organisms invest in survival. For cells, this entails transitioning into a dormant, quiescent state (G0). In dormancy, the activity of biosynthetic pathways is dampened, and catabolic metabolism and stress tolerance pathways are activated. Recent work in yeast has demonstrated that dormancy is associated with alterations in the physicochemical properties of the cytoplasm, including changes in pH, viscosity and macromolecular crowding. Accompanying these changes, numerous metabolic enzymes transition from soluble to polymerized assemblies. These large-scale self-assemblies are dynamic and depolymerize when cells resume growth. Here we review how enzyme polymerization enables metabolic plasticity by tuning carbohydrate, nucleic acid, amino acid and lipid metabolic pathways, with particular focus on its potential adaptive value in cellular dormancy.

Identification of differentially expressed genes and biological pathways in para-carcinoma tissues of HCC with different metastatic potentials

Hepatocellular carcinoma (HCC) is a malignant tumor with extensive metastasis. Changes in the tumor microenvironment provide favorable conditions for tumor metastasis. However, the role of changes to the tumor microenvironment in HCC metastasis is yet to be elucidated. The Gene Expression Omnibus expression profile GSE5093 consists of 20 noncancerous tissues surrounding HCC tissues, including 9 metastasis-inclined microenvironment samples with detectable metastases and 11 metastasis-averse microenvironment samples without detectable metastases. The present study assessed 35 HCC samples to verify the results of chip analysis. In total, 712 upregulated and 459 downregulated genes were identified, with 1,033 nodes, 7,589 edges and 10 hub genes. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that the differentially expressed genes were significantly enriched in ‘cell-cell adhesion’, ‘cell proliferation’ and ‘protein binding’. The top 10 hub genes were identified via a protein-protein interaction analysis. The 3 most significant modules were identified from the protein-protein network. Moreover, an association between hub genes and patient prognosis was identified. In conclusion, these candidate genes and pathways may help elucidate the mechanisms underlying HCC metastasis and identify more options for targeted therapy.

Proteomic analysis of lymphoblastoid cell lines from schizophrenic patients

Although a number of studies have identified several convincing candidate genes or molecules, the pathophysiology of schizophrenia (SCZ) has not been completely elucidated. Therapeutic optimization based on pathophysiology should be performed as early as possible to improve functional outcomes and prognosis; to detect useful biomarkers for SCZ, which reflect pathophysiology and can be utilized for timely diagnosis and effective therapy. To explore biomarkers for SCZ, we employed fluorescence two-dimensional differential gel electrophoresis (2D-DIGE) of lymphoblastoid cell lines (LCLs) (1st sample set: 30 SCZ and 30 CON). Differentially expressed proteins were sequenced by liquid chromatography tandem-mass spectrometry (LC-MS/MS) and identified proteins were confirmed by western blotting (WB) (1st and 2nd sample set: 60 SCZ and 60 CON). Multivariate logistic regression analysis was performed to identify an optimal combination of biomarkers to create a prediction model for SCZ. Twenty protein spots were differentially expressed between SCZ and CON in 2D-DIGE analysis and 22 unique proteins were identified by LC-MS/MS. Differential expression of eight of 22 proteins was confirmed by WB. Among the eight candidate proteins (HSPA4L, MX1, GLRX3, UROD, MAPRE1, TBCB, IGHM, and GART), we successfully constructed logistic regression models comprised of 4- and 6-markers with good discriminative ability between SCZ and CON. In both WB and gene expression analysis of LCL, MX1 showed reproducibly significant associations. Moreover, Mx1 and its related proinflamatory genes (Mx2, Il1b, and Tnf) were also up-regulated in poly I:C-treated mice. Differentially expressed proteins might be associated with molecular pathophysiology of SCZ, including dysregulation of immunological reactions and potentially provide diagnostic and prognostic biomarkers.

A meta-analysis of public microarray data identifies biological regulatory networks in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a long-term degenerative disease that is caused by environmental and genetic factors. The networks of genes and their regulators that control the progression and development of PD require further elucidation.

METHODS

We examine common differentially expressed genes (DEGs) from several PD blood and substantia nigra (SN) microarray datasets by meta-analysis. Further we screen the PD-specific genes from common DEGs using GCBI. Next, we used a series of bioinformatics software to analyze the miRNAs, lncRNAs and SNPs associated with the common PD-specific genes, and then identify the mTF-miRNA-gene-gTF network.

RESULT

Our results identified 36 common DEGs in PD blood studies and 17 common DEGs in PD SN studies, and five of the genes were previously known to be associated with PD. Further study of the regulatory miRNAs associated with the common PD-specific genes revealed 14 PD-specific miRNAs in our study. Analysis of the mTF-miRNA-gene-gTF network about PD-specific genes revealed two feed-forward loops: one involving the SPRK2 gene, hsa-miR-19a-3p and SPI1, and the second involving the SPRK2 gene, hsa-miR-17-3p and SPI. The long non-coding RNA (lncRNA)-mediated regulatory network identified lncRNAs associated with PD-specific genes and PD-specific miRNAs. Moreover, single nucleotide polymorphism (SNP) analysis of the PD-specific genes identified two significant SNPs, and SNP analysis of the neurodegenerative disease-specific genes identified seven significant SNPs. Most of these SNPs are present in the 3'-untranslated region of genes and are controlled by several miRNAs.

CONCLUSION

Our study identified a total of 53 common DEGs in PD patients compared with healthy controls in blood and brain datasets and five of these genes were previously linked with PD. Regulatory network analysis identified PD-specific miRNAs, associated long non-coding RNA and feed-forward loops, which contribute to our understanding of the mechanisms underlying PD. The SNPs identified in our study can determine whether a genetic variant is associated with PD. Overall, these findings will help guide our study of the complex molecular mechanism of PD.

MicroRNA-144 is regulated by CP2 and decreases COX-2 expression and PGE2 production in mouse ovarian granulosa cells

Mammalian folliculogenesis is a complex process in which primordial follicles develop into pre-ovulatory follicles, followed by ovulation to release mature oocytes. In this study, we explored the role of miR-144 in ovulation. miR-144 was one of the differentially expressed microRNAs, which showed 5.59-fold changes, in pre-ovulatory ovarian follicles between Large White and Chinese Taihu sows detected by Solexa deep sequencing. We demonstrated that overexpression of miR-144 significantly decreased the luciferase reporter activity under the control of the cyclooxygenase-2 (COX-2) or mothers against decapentaplegic homologue 4 (Smad4) 3'-untranslated region (3'-UTR) and suppressed COX-2 and Smad4 expression. In contrast, a miR-144 inhibitor increased COX-2 and Smad4 expression in mouse granulosa cells (mGCs). Meanwhile, Smad4 upregulated COX-2 expression, but this effect was abolished when the mGCs were treated with the transforming growth factor beta signalling pathway inhibitor SB431542. Moreover, luciferase reporter, chromatin immunoprecipitation and electrophoretic mobility shift assay results showed that the transcription factor CP2 upregulated miR-144 expression, which partially contributed to the suppression of COX-2 in mGCs. Both CP2 and miR-144 alter prostaglandin E2 (PGE2) production by regulating COX-2 expression. In addition, miR-144 regulated mGC apoptosis and affected follicular atresia, but these activities did not appear to be through COX-2 and Smad4. Taken together, we revealed an important CP2/miR-144/COX-2/PGE2/ovulation pathway in mGCs.

Glycinamide ribonucleotide formyl transferase is frequently overexpressed in glioma and critically regulates the proliferation of glioma cells

AIMS

Current treatments for the most common form of brain tumor, glioma, are disappointing in their effectiveness. Low expression levels of GART, an enzyme in the core nucleotide metabolism, significantly correlate with chemosensitivity, conferring a survival advantage to tumor cells. Our study aimed to explore the expression and function of GART in glioma.

METHODS

Immunohistochemical and Western blot analysis were performed in 70 cases of human gliomas and normal brain tissues. We mainly used cell growth assay and multicellular tumor spheroid formation assay to evaluate the proliferation and chemosensitivity of glioma cells.

RESULTS

High GART expression (most cancer cells cytoplasm stained) was observed in 70 specimens and was related to the grade of malignancy. We also reviewed each grade of tumors separately and investigated whether GART expression predicted patient survival within each subgroup. In brief, GART overexpression was significantly associated with overall survival (P=0.03). Interestingly, transfecting cells with GART-siRNA suppressed proliferation and enhanced temozolomide (TMZ)-induced apoptosis in glioma cells.

CONCLUSION

The current results showed that GART expression was associated with glioma grade and that high GART protein expression might be related to poor outcome.

Control of transferrin expression by β-amyloid through the CP2 transcription factor

Accumulation of β-amyloid protein (Aβ) is one of the most important pathological features of Alzheimer's disease. Although Aβ induces neurodegeneration in the cortex and hippocampus through several molecular mechanisms, few studies have evaluated the modulation of transcription factors during Aβ-induced neurotoxicity. Therefore, in this study, we investigated the transcriptional activity of transcription factor CP2 in neuronal damage mediated by Aβ (Aβ(1-42) and Aβ(25-35) ). An unbiased motif search of the transferrin promoter region showed that CP2 binds to the transferrin promoter, an iron-regulating protein, and regulates transferrin transcription. Ectopic expression of CP2 led to increased transferrin expression at both the mRNA and protein levels, whereas knockdown of CP2 down-regulated transferrin mRNA and protein expression. Moreover, CP2 trans-activated transcription of a transferrin reporter gene. An electrophoretic mobility shift assay and a chromatin immunoprecipitation assay showed that CP2 binds to the transferrin promoter region. Furthermore, the binding affinity of CP2 to the transferrin promoter was regulated by Aβ, as Aβ (Aβ(1-42) and Aβ(25-35) ) markedly increased the binding affinity of CP2 for the transferrin promoter. Taken together, these results suggest that CP2 contributes to the pathogenesis of Alzheimer's disease by inducing transferrin expression via up-regulating its transcription.