Unknown,Transcriptomics,Genomics,Proteomics

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The effect of palmitate on gene expression profile in proliferating myoblasts

ABSTRACT: High-fat diet or exposure to saturated fatty acids affects skeletal muscle growth and function. The aim of the present study was to investigate the effect of palmitate on the transcriptomic profile of mouse C2C12 myoblasts. Global gene expression was evaluated using whole mouse genome oligonucleotide microarrays, and the results were validated through real-time PCR. A total of 4047genes were identified as differentially expressed, including 3492 down-regulated and 555 up-regulated genes during 48-h-exposure to palmitate (0.1 mmol/l). Functional classification showed the involvement of PA-regulated genes in several processes which regulate cell growth. In conclusion, palmitate modifies the expression of genes associated with: i) myoblast responsiveness to hormones and growth factors, ii) cytokine and growth factor expression, and iii) regulation of cell-cell cell-matrix communication. Such alterations can affect myoblast growth and differentiation, however further studies in this field are required. To whom the correspondence should be addressed: Dr K. Grzelkowska-Kowalczyk; e-mail: k_grzel_kow@poczta.fm, tel/fax: (48 22) 847 24 52 After scanning of hybridized microarrays, quantitation of slide images was performed using Feature Extraction Software (Agilent) using default parameters and the raw data were exported to GeneSpring GX 12 (Agilent, Santa Clara, CA) and log2 transformed. For identification of genes significantly altered in cell compared with the control normal gene set. Total detected entities were filtered by flags (detected, non detected) and error (coefficient of variation: CV < 50.0 percent) to remove very low signal entities and to select reproducible signal values of entities among the replicated experiments, respectively. In statistical analysis, separated for experiment with myoblasts treated with palmitate acid was used t-test unpaired (p < 0.05) with multiple testing correction: Benjamini-Hochberg <0.05, all significant changes over fold change 1.6 were selected.

ORGANISM(S): Mus musculus

SUBMITTER: Zofia Wicik

PROVIDER: E-GEOD-75378 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:The purpose of the study was to investigate the effect of IFN-M-NM-3 on transcriptomic profile of differentiating mouse C2C12 myogenic cells. Global gene expression was evaluated using the oligonucleotide whole mouse genome microarrays and was validated with real-time PCR method. Exogenous IFN-M-NM-3 (1 ng/ml) increased myoblast proliferation, but decreased cell viability, the fusion index and the cellular content of myosin heavy chain, MyHC in C2C12 cultures on the 3rd day of differentiation. IFN-M-NM-3 up-regulated genes were mainly involved in biological processes such as: cell cycle, regulation of cell proliferation, programmed cell death, inflammatory, vasculature development, regulation of cytokine, transmembrane receptor protein tyrosine kinase signaling pathway, and chemotaxis, whereas down-regulated genes contributed mainly to: regulation of transcription, cell-cell signaling, nitrogen compound biosynthetic process, transmembrane receptor protein ser/thr protein kinase signaling pathway, and regulation of Wnt receptor signaling pathway. IFN-M-NM-3 up-regulated the expression of cytokines/growth factors controlling cell proliferation (Cxcl10, Il15, Ccl2, Fgf7, Figf, Csf1, Vegfc, Hgf). Moreover, IFN-M-NM-3: i) down-regulated genes encoding factors that are anabolic for muscle cells (Fst, Igf-1); ii) inhibited pro-myogenic transcription (via Mef2a, Nfkb1, and Pparg); iii) decreased expression of genes controlling cell adhesion and sarcolemma/cytoskeleton organization; and iv) activated the proteolytic pathways: proteasomes and catepsins, leading to protein degradation and impaired myotube growth. Our data suggest that the effect of IFN-M-NM-3 on mygenesis is, at least partly, associated with the regulation of muscle cell secretom at the transcriptional level. To whom the correspondence should be addressed: Dr K. Grzelkowska-Kowalczyk; e-mail: k_grzel_kow@poczta.fm, tel/fax: (48 22) 847 24 52 After scanning of hybridized microarrays, quantitation of slide images was performed using Feature Extraction Software (Agilent) using default parameters and the raw data were exported to GeneSpring GX 12 (Agilent, Santa Clara, CA) and log2 transformed. For identification of genes significantly altered in cell compared with the control normal gene set, total detected entities were filtered by flags (present, marginal) to remove very low signal entities and to select reproducible signal values of entities among the replicated experiments, respectively. In statistical analysis, separated for experiment with myoblasts treated with IFNG (IFNG vs CTRL 1-4) was used t-test unpaired (p < 0.05) with multiple testing correction: Benjamini-Hochberg <0.05, all significant changes over fold change 2 were selected. Analysis of GO, GSEA and signaling pathway was carried out using GeneSpring GX 12 (Agilent) and the DAVID Classification System (p<0.05).

Project description:GDF8 (myostatin) is a unique cytokine strongly affecting the skeletal muscle phenotype in human and animals. The aim of the present study was to elucidate the molecular mechanism of myostatin influence on the differentiation of mouse C2C12 myoblasts, using the global-transcriptome analysis with the DNA microarray technique. Treatment with exogenous GDF8 strongly affected the growth and development of C2C12 mouse myoblasts. This was manifested by the inhibition of proliferation and differentiation as well as the impairment of cell fusion. DNA microarray analysis revealed 778 genes regulated by GDF8 in differentiating myoblasts (543 down-regulated and 235 up-regulated). Ontological analysis revealed their involvement in 17 types of biological processes, 10 types of molecular functions and 68 different signaling pathways. The effect of GDF8 was mainly mediated by the disruption of the cell cycle, calcium and insulin signaling pathways and expression of cytoskeletal and muscle specific proteins. The identified key-genes that could play a role as GDF8 targets in differentiating myoblasts are: Mef2, Hgf, Ilb1, Itgb1, Edn1, Ppargc1a. After scanning of hybridized microarrays, quantitation of slide images was performed using Feature Extraction Software (Agilent) using default parameters. The raw data were normalized by Loess normalization method, and then the normalized raw data was exported to GeneSpring GX 11.0.5 (Agilent, Santa Clara, CA). For identification of genes significantly altered in cell compared with the control normal gene set, total detected entities were filtered by flags (present, marginal) to remove very low signal entities and to select reproducible signal values of entities among the replicated experiments, respectively. In statistical analysis, separated for experiment with myoblasts treated with GDF8 ([C2C12]-[GDF8]1-4) was used t-test unpaired (p < 0.05) and fold change over 1.6. Analysis of GO and signaling pathway was carried out using GeneSpring GX 12 (Agilent), KEGG and PANTHER Classification System (http://www.pantherdb.org/). In the analysis of signaling pathways using Panther, a total of 68 cellular pathways were identified.

Project description:Background: Follistatin (FS) is an activin-binding glycoprotein, known for its antagonistic action on the TGF-M-NM-2 super-family of cytokines. It has ability to prevent muscle atrophy and to stimulate muscle growth through binding of myostatin (GDF8). FS does not cause these changes only by inhibition of GDF8 but this mechanism is still not well elucidated. In order to identify GDF8-dependent and GDF8-independent action of FS, we performed comprehensive transcriptomic analysis of differentiating C2C12 mouse myoblasts. Results: To evaluate influence of FS-288 (200ng/ml) on differentiating C2C12 myoblasts was used immunofluorescence analysis of MyHC protein expression in the culture and counting of the number and type of myotubes. Differentiating myoblasts treated with FS showed increase in number and size of myotubes. Microarray studies performed by us identified 30 genes oppositely regulated by FS and GDF8. Analyses of the transcriptomic profiles showed that FS has highly significant influence, associated with GDF8 binding, on the regulation of cell cycle, transport processes, cell communication, cell adhesion, cell motion, developmental processes and binding functions. The signalling pathways that may play a primary role in the myogenesis stimulation by FS are associated with TGF-M-NM-2, Delta-Notch and Wnt signalling pathways, integrin and actin cytoskeleton signalling and adipogenesis regulation. Changes in expression of Hgf, Sort1, Trdn, Stmn2, Hdac1 genes, significantly involved in the process of myoblasts differentiation were validated with Real-Time PCR method. Conclusions: Our results implicate which aspects of transcriptional regulation of myogenesis process by FS could have significant and protective influence. We have shown that FS activity is associated not only with GDF8 binding but also with inhibited expression of genes involved in TGF-M-NM-2 signalling and by regulating of genes associated with vesicle transport apoptosis signalling pathway, inflammatory pathways and adipogenesis expression. Our analysis showed that follistatin GDF8-independent on differentiating myotubes involves regulation of localization processes, cell-matrix adhesion, mRNA processing, apoptosis, fatty acid metabolic processes, SNAP receptor activity functions and partial regulation of transcription processes. These results give a new and complete image of the follistatin role in the muscle cell differentiation and indicate target genes for FS which in the future may be a good therapeutic approach. After scanning of hybridized microarrays, quantitation of slide images were performed using Feature Extraction Software 10.7.3.1 (Agilent) using default parameters. Normalized raw data was exported to GeneSpring GX 11.0.5 (Agilent, Santa Clara, CA). For identification of genes significantly altered in cells treated with FSl compared with untreated cells. T total detected entities were filtered by flags (present, marginal) and error (coefficient of variation: CV < 50.0 percent) to remove very low signal entities and to select reproducible signal values of entities among the replicated experiments, respectively. In statistical analysis, separated for experiment with myoblasts treated with FS(FS vs. CTRL 1-4) was used t-test unpaired (p < 0.05) with multiple testing correction: Benjamini-Hochberg <0.05, all significant changes over fold change 1.6 were selected. Analysis of GO, GSEA and signaling pathway was carried out using GeneSpring GX 12 (Agilent) and the DAVID, KEEG and PANTHER Classification System (p<0.01). In the analysis of signaling pathways using GeneSpring GX 12 (Agilent) and Ariadne Pathway Studio.

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The effect of palmitate on gene expression profile in proliferating myoblasts

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