DUX4 Differentially Regulates Transcriptomes of Human Rhabdomyosarcoma and Mouse C2C12 Cells

<div><p>Facioscapulohumeral muscular dystrophy (FSHD) is linked to the deletion of the D4Z4 arrays at chromosome 4q35. Recent studies suggested that aberrant expression of double homeobox 4 (<i>DUX4</i>) from the last D4Z4 repeat causes FSHD. The aim of this study is to determine transcriptomic responses to ectopically expressed DUX4 in human and mouse cells of muscle lineage. We expression profiled human rhabdomyosarcoma (RD) cells and mouse C2C12 cells transfected with expression vectors of <i>DUX4</i> using the Affymetrix Human Genome U133 Plus 2.0 Arrays and Mouse Genome 430 2.0 Arrays, respectively. A total of 2267 and 150 transcripts were identified to be differentially expressed in the RD and C2C12 cells, respectively. Amongst the transcripts differentially expressed in the RD cells, <i>MYOD</i> and <i>MYOG</i> (2 fold, p<0.05), and six <i>MYOD</i> downstream targets were up-regulated in RD but not C2C12 cells. Furthermore, 13 transcripts involved in germline function were dramatically induced only in the RD cells expressing DUX4. The top 3 IPA canonical pathways affected by DUX4 were different between the RD (inflammation, BMP signaling and NRF-2 mediated oxidative stress) and the C2C12 cells (p53 signaling, cell cycle regulation and cellular energy metabolism). Amongst the 40 transcripts shared by the RD and C2C12 cells, <i>UTS2</i> was significantly induced by 76 fold and 224 fold in the RD and C2C12 cells, respectively. The differential expression of <i>MYOD, MYOG</i> and <i>UTS2</i> were validated using real-time quantitative RT-PCR. We further validated the differentially expressed genes in immortalized FSHD myoblasts and showed up-regulation of <i>MYOD</i>, <i>MYOG</i>, <i>ZSCAN4</i> and <i>UTS2</i>. The results suggest that DUX4 regulates overlapped and distinct groups of genes and pathways in human and mouse cells as evident by the selective up-regulation of genes involved in myogenesis and gametogenesis in human RD and immortalized cells as well as the different molecular pathways identified in the cells.</p></div

TGF-β1 protein levels in the blood serum and muscle lysates.

<p>TGF-β1 protein levels in the blood serum and muscle lysates.</p

Skeletal muscle wasting due to TGF-β1 over-expression.

<p>(A) Skeletal muscle wasting in mice over-expressing TGF-β1, which developed muscle weakness. (B) The average muscle weight (g, mean ± s.e.m.) was reduced in these mice. “*” indicates p<0.05 and “**” indicates p<0.01.</p

Active and latent TGF-β1 levels in serum and quadriceps after two weeks of <i>TGF-β1</i> over-expression.

<p>(A) The serum level of both active and latent TGF-β1 was significantly higher in mice in the EO group in comparison to LO and control littermates. (B) The level of both active and latent TGF-β1 in quadriceps was significantly higher in mice in the EO group in comparison to LO and control littermates. “*” indicates p<0.05 and “**” indicates p<0.01.</p

TGF-β1 over-expression leads to myofiber atrophy and endomysial fibrosis.

<p>(A) H&E and Pico-Sirius red staining showed smaller myofibers and collagen accumulation in the mice over-expressing TGF-β1. The differences were less prominent in the mice that did not develop muscle weakness at the time of muscle collection. Scale bar: 50 µm (B) Collagen deposition measurement after 2 weeks of TGF-β1 over-expression. The mice in the EO group showed significantly higher collagen deposition in comparison to LO and control mice. “*” indicates p<0.05 and “**” indicates p<0.01. (C) Fiber size distribution after 2 weeks of TGF-β1 over-expression. The myofiber size was reduced in both the EO and LO groups with more reduction in the EO group.</p

Muscle weakness caused by TGF-β1 over-expression in skeletal muscles after doxycycline removal.

<p>(A) Expression of the <i>TGF-β1</i> mRNA in various organs. <i>TGF-β1</i> transcripts were detected in the two muscles, quadriceps and diaphragm, examined (lanes 1 and 2), but not in the brain, heart, lung, liver, kidney or ovary (lanes 3–7, respectively). Lane 8 is a no RT control. (B) GSM showed that muscle strength was significantly reduced in mice that developed early phenotype but not the rest of the mice over-expressing TGF-β1. The asterisks indicate significant differences with <i>p</i><0.05.</p

Proteomics Analysis of the DF-1 Chicken Fibroblasts Infected with Avian Reovirus Strain S1133

<div><p>Background</p><p>Avian reovirus (ARV) is a member of the <i>Orthoreovirus</i> genus in the Reoviridae family. It is the etiological agent of several diseases, among which viral arthritis and malabsorption syndrome are the most commercially important, causing considerable economic losses in the poultry industry. Although a small but increasing number of reports have characterized some aspects of ARV infection, global changes in protein expression in ARV-infected host cells have not been examined. The current study used a proteomics approach to obtain a comprehensive view of changes in protein levels in host cells upon infection by ARV.</p><p>Methodology and Principal Findings</p><p>The proteomics profiles of DF-1 chicken fibroblast cells infected with ARV strain S1133 were analyzed by two-dimensional differential-image gel electrophoresis. The majority of protein expression changes (≥1.5 fold, <i>p</i><0.05) occurred at 72 h post-infection. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry identified 51 proteins with differential expression levels, including 25 that were upregulated during ARV infection and 26 that were downregulated. These proteins were divided into eight groups according to biological function: signal transduction, stress response, RNA processing, the ubiquitin-proteasome pathway, lipid metabolism, carbohydrate metabolism, energy metabolism, and cytoskeleton organization. They were further examined by immunoblotting to validate the observed alterations in protein expression.</p><p>Conclusion/Significance</p><p>This is the first report of a time-course proteomic analysis of ARV-infected host cells. Notably, all identified proteins involved in signal transduction, RNA processing, and the ubiquitin-proteasome pathway were downregulated in infected cells, whereas proteins involved in DNA synthesis, apoptosis, and energy production pathways were upregulated. In addition, other differentially expressed proteins were linked with the cytoskeleton, metabolism, redox regulation, and stress response. These proteomics data provide valuable information about host cell responses to ARV infection and will facilitate further studies of the molecular mechanisms underlying ARV pathogenesis.</p></div

Additional file 1: Table S1. of Diversifying selection of the anthocyanin biosynthetic downstream gene UFGT accelerates floral diversity of island Scutellaria species

List of Scutellaria species used in this study. Table S2. Likelihood statistics results of ancestral area reconstruction models implemented in BioGeoBEARS. Table S3. Paired t test of ω ratios calculated from relative rate test implemented in HyPhy. Table S4. McDonald and Kreitman test of CHS and UFGT among Taiwanese skullcap sister species pairs. Table S5. HKA test results of CHS and UFGT between Taiwanense and non-Taiwanese skullcap species. Table S6. AMOVA analysis of CHS and UFGT between Taiwanese and non-Taiwanese species. Figure S1. Mapping of the flower colours on a skullcaps phylogeny. Probability of ancestral state was mapped on the node. Colour in boxes corresponded to different flower colours. Blue: blue colours; Red: red colours; Yellow: yellow colours; Grey: white colours. Figure S2. The dN/dS (ω) vs. dS plots show a comparison of the ω distribution and the relative divergent times between Taiwanese species (T/T), non-Taiwanese and Taiwanese species (nT/T), and between non-Taiwanese species (nT/nT) for CHS (A–C) and UFGT (D–F). Horizontal lines in D–F indicate the boundary for ω = 1. Figure S3. Result of mixed effects model of evolution (MEME) analysis for the naringenin-chalcone synthase (CHS) gene. Figure S4. Result of mixed effects model of evolution (MEME) analysis for the UDP-glucose:flavonol 3-O-D-glucosyltransferase (UFGT) gene. (DOCX 1612 kb

Overview of 2D-DIGE approach.

<p>Protein extracts were prepared from mock-infected DF-1 cells at 72 h post-infection (control) and ARV-infected DF-1 cells (5 MOI) at 24, 48, and 72 h post-infection. Mixed samples containing 50 µg each of Cy2-labeled pooled protein standard, Cy3- or Cy5-labeled proteins from ARV-infected cells, and Cy3- or Cy5-labeled proteins from mock-infected cells were analyzed in the indicated combinations, and each was performed in triplicate.</p

Functional classification and subcellular locations of differentially expressed proteins in ARV-infected DF-1 cells.

<p>(A and B) functional classifications and (C and D) subcellular locations of upregulated and downregulated proteins in ARV-infected DF-1 cells identified by 2D-DIGE/MALDI-TOF MS.</p