By using high-density DNA microarrays, we analyzed the gene-expression profile of SHSY5Y neuroblastoma cells after treatment with cobalt chloride
Investigation of Endogenous Retrovirus Sequences in the Neighborhood of Genes Up-regulated in a Neuroblastoma Model after Treatment with Hypoxia-Mimetic Cobalt Chloride.
Specimen part, Cell line
View SamplesAlternative splicing (AS) is a post-transcriptional gene regulatory mechanism that contributes to proteome diversity. Aberrant splicing mechanisms (mutations, polymorphisms, insertion/deletion etc.) contribute to various cancers and muscle related conditions such as Duchenne muscular dystrophy. However, dysregulation of AS in Cancer Cachexia (CC) patients remains unexplored. Our objectives were (i) to profile alternatively spliced genes (ASGs) on a genome-wide scale, and (ii) to identify DE alternatively spliced genes (DASGs) associated with CC. Rectus abdominis muscle biopsies obtained from cancer patients were stratified into cachectic cases (n=21, classified based on International consensus diagnostic framework for CC) and non-cachectic controls (n=19, weight stable cancer patients). Human Transcriptome array 2.0 was used for profiling ASGs using the total RNA isolated from muscle biopsies. Representative DASG signatures were validated using semi-quantitative RT-PCR. We identified 8960 ASGs, of which 922 DASGs (772 up-regulated, 150 down-regulated) were identified at > 1.4 fold-change and p < 0.05. Representative DASGs when validated by semi-quantitative RT-PCR also showed similar trends, confirming the primary findings from the genome-wide arrays. Identified DASGs were associated with myogenesis, adipogenesis, protein ubiquitination and inflammation. Up to 10% of the DASGs exhibited cassette exon (exon included or skipped) as a predominant form of AS event. We also observed other forms of AS events such as intron retention, alternate promoters. Overall, we have, for the first time conducted global profiling of muscle tissue to identify DASGs associated with CC. The mechanistic roles of the identified DASGs in CC pathophysiology using model systems is warranted, as well as replication of findings in independent cohorts.
Small RNAome profiling from human skeletal muscle: novel miRNAs and their targets associated with cancer cachexia.
Specimen part
View SamplesThe transcriptional regulator AmpR controls expression of the AmpC -lactamase in P. aeruginosa and other bacteria. Studies have demonstrated that in addition to regulating ampC expression, AmpR also regulates the expression of the sigma factor AlgT/U and the production of some quorum-sensing regulated virulence factors. In order to understand the ampR regulon, we compared the expression profiles of PAO1 and its isogenic ampR mutant, PAOampR in the presence and absence of sub-MIC -lactam stress. The analysis demonstrates that the ampR regulon is much more extensive than previously thought, with the deletion of ampR affecting the expression of over 300 genes. Expression of an additional 207 genes are affected by AmpR when the cells are exposed to sub-MIC -lactam stress, indicating that the ampR regulon in P. aeruginosa is much more extensive than previously thought.
The regulatory repertoire of Pseudomonas aeruginosa AmpC ß-lactamase regulator AmpR includes virulence genes.
Specimen part
View SamplesThe retinoblastoma tumor suppressor protein (Rb) regulates early G1 phase checkpoints, including the DNA damage response, as well as cell cycle exit and differentiation. The widely accepted model of G1 cell cycle progression proposes that cyclin D:Cdk4/6 partially inactivates the Rb tumor suppressor during early G1 phase by progressive multi-phosphorylation, termed hypo-phosphorylation, resulting in release of E2F transcription factors. However, this model remains largely unproven biochemically and the biologically active form(s) of Rb remains unknown. Here we find that Rb is un-phosphorylated in G0 cells and becomes exclusively mono-phosphorylated throughout all of early G1 phase by cyclin D:Cdk4/6. Early G1 phase mono-phosphorylated Rb is composed of 14 independent isoforms that are all targeted by the E1a oncoprotein, but each shows a preferential binding pattern to specific E2F1-4 transcription factors. At the late G1 Restriction Point, cyclin E:Cdk2 inactivates Rb by a quantum hyper-phosphorylation (>12 phosphates/Rb). Cells undergoing a DNA damage response activate cyclin D:Cdk4/6 to generate mono-phosphorylated Rb that regulates global transcription. In contrast, a non-phosphorylatable ?Cdk-Rb allele was non-functional for regulating a DNA damage response, but functional for driving cell cycle exit and differentiation during myogenesis. These observations fundamentally change our understanding of G1 cell cycle progression and show that there is no progressive multi-phosphorylation or hypo-phosphorylation inactivation of Rb during early G1 phase by cyclin D:Cdk4/6. Instead, cyclin D:Cdk4/6 generates functionally active, mono-phosphorylated Rb that is the only Rb isoform present in cells during early G1 phase.
Cyclin D activates the Rb tumor suppressor by mono-phosphorylation.
Specimen part
View SamplesTranscriptional profiling was utilized to define the biological pathways of gingival epithelial cells modulated by co-culture with the oral pathogenic Porphyromonas gingivalis and Aggregatibacter (formerly actinobacillus) actinomycetemcomitans.
Distinct transcriptional profiles characterize oral epithelium-microbiota interactions.
No sample metadata fields
View SamplesIn C. elegans, ablation of germline stem cells (GSCs) extends lifespan, but also increases fat accumulation and alters lipid metabolism, raising the intriguing question of how these effects might be related. Here we show that a lack of GSCs results in a broad transcriptional reprogramming, in which the conserved detoxification regulator SKN-1/Nrf increases stress resistance, proteasome activity, and longevity. SKN-1 also activates diverse lipid metabolism genes and reduces fat storage, thereby alleviating the increased fat accumulation caused by GSC absence. Surprisingly, SKN-1 is activated by signals from this fat, which appears to derive from unconsumed yolk that was produced for reproduction. We conclude that SKN-1 plays a direct role in maintaining lipid homeostasis, in which it is activated by lipids. This SKN-1 function may explain the importance of mammalian Nrf proteins in fatty liver disease, and suggests that particular endogenous or dietary lipids might promote health through SKN-1/Nrf. Overall design: Samples were prepared from ~5,000 synchronized, L1 arrested day-one adult animals cultured at 25°C. Worms were synchronized by sodium hypochlorite (bleach) treatment, as previously described (Porta-de-la-Riva et al., 2012). Bleach solution (9 mL ddH2O; 1 mL 1 N NaOH; 4 mL Clorox bleach) was freshly prepared before each experiment. Worms were bleached for 5 minutes, washed 5x in M9, and arrested at the L1 stage at 25°C in M9 containing 10 µg/mL cholesterol. Feeding RNAi was started at the L1 stage. This approach only partially reduces skn-1 function, but allows analysis of larger samples than would be feasible with skn-1 mutants, which are sterile (Bowerman et al., 1992). Because these animals were not treated with FUdR, the WT adults contained an intact germline and eggs. As is explained in the Results section, we therefore confined our analysis to genes that were overrepresented in glp-1(ts) animals, which lack eggs and most of the germline, and established a high-confidence cutoff for genes that were upregulated by GSC absence as opposed to simply being expressed specifically in somatic tissues. RNA was extracted using the same protocol for qRT-PCR samples. Purified RNA samples were DNase treated and assigned a RIN quality score using a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA). Only matched samples with high RIN scores were sent for sequencing. Single read 50 bp RNA sequencing with poly(A) enrichment was performed at the Dana-Farber Cancer Institute Center for Computational Biology using a HiSeq 2000 (Illumina, San Diego, CA). FASTQ output files were aligned to the WBcel235 (Feb 2014) C. elegans reference genome using STAR (Dobin et al., 2013). These files have been deposited at the Gene Expression Omnibus (GEO) with the accession number GSE63075. Samples averaged 75% mapping of sequence reads to the reference genome. Differential expression analysis was performed using a custom R and Bioconductor RNA-seq pipeline (http://bioinf.wehi.edu.au/RNAseqCaseStudy/) (Gentleman et al., 2004; Anders et al., 2013; R Core Team, 2014). Quantification of mapped reads in the aligned SAM output files was performed using featureCounts, part of the Subread package (Liao et al., 2013, 2014). We filtered out transcripts that didn't have at least one count per million reads in at least two samples. Quantile normalization and estimation of the mean-variance relationship of the log-counts was performed by voom (Law et al., 2014). Linear model fitting, empirical Bayes analysis and differential expression analysis was then conducted using limma (Smyth, 2005). To identify genes that are upregulated in a SKN-1-dependent manner by GSC loss, we sought genes for which glp-1(ts) expression was higher than WT, and for which glp-1(ts);skn-1(-) expression was reduced relative to glp-1(ts). To test for this pattern, if a gene's expression change was higher in the comparison of glp-1(ts) vs. WT and lower in the comparison of glp-1(ts);skn-1(-) vs. glp-1(ts), then we calculated the minimum (in absolute value) of the t-statistics from these two comparisons, and assessed the significance of this statistic by comparing to a null distribution derived by applying this procedure to randomly generated t-statistics. We corrected for multiple testing in this and the differential expression analysis using the false discovery rate (FDR) (Benjamini and Hochberg, 1995). Heatmaps were generated using heatmap.2 in the gplots package (Warnes et al., 2014). Functional annotations and phenotypes were obtained from Wormbase build WS246. SKN-1 transcription factor binding site analysis of hits was conducted with biomaRt, GenomicFeatures, JASPAR, MotifDb, motifStack, MotIV, and Rsamtools (Sandelin et al., 2004; Durinck et al., 2005; Durinck et al., 2009; Lawrence et al., 2013; Ou et al., 2013; Mercier and Gottardo, 2014; Shannon, 2014). JASPAR analysis was performed with the SKN-1 matrix MA0547.1 using 2 kb upstream sequences obtained from Ensembl WBcel235 (Staab et al., 2013). modENCODE SKN-1::GFP ChIP-seq analysis of hits was performed using biomaRt, ChIPpeakAnno, IRanges, and multtest (Durinck et al., 2005; Durinck et al., 2009; Gerstein et al., 2010; Zhu et al., 2010; Niu et al., 2011; Lawrence et al., 2013). SKN-1::GFP ChIP-seq peaks were generated by Michael Snyder's lab. We used the peak data generated from the first 3 larval stages: L1 (modENCODE_2622; GSE25810), L2 (modENCODE_3369), and L3 (modENCODE_3838; GSE48710). Human ortholog matching was performed using Wormbase, Ensembl, and OrthoList (Shaye and Greenwald, 2011). Gene lists were evaluated for functional classification and statistical overrepresentation with Database for Annotation, Visualization and Integrated Discovery (DAVID) version 6.7 (Dennis et al., 2003).
Lipid-mediated regulation of SKN-1/Nrf in response to germ cell absence.
Cell line, Subject
View SamplesMouse glioblastomas were induced by lentiviral vector expressing HrasG12V and shRNA against p53. Tumor tissues were isolated from mice reached clinical endpoints. RNA was isolated using the RNeasy kit according to manufacturer’s protocol with the addition of DNase (Qiagen). cDNA libraries were prepared using the TruSeq RNA Sample Prep kit (Illumina). RNA sequencing was performed using a HiSeq 2500 Sequencing System (Illumina). Overall design: 3 normal mouse brain samples compared to 5 glioblastoma samples by standard RNAseq method.
Targeting NF-κB in glioblastoma: A therapeutic approach.
Specimen part, Subject
View SamplesArray analysis of total lung RNAs from female BALB/c mice collected at 12, 48 and 96 h post-infection with highly and less virulent influenza A (H3N2) viruses. Viruses (designated as LVI and HVI) were derived from influenza strain virus A/Aichi/2/68 (Aichi68). LVI is Aichi68 propagated in eggs, and HVI is mouse adapted Aichi68.
Differential pulmonary transcriptomic profiles in murine lungs infected with low and highly virulent influenza H3N2 viruses reveal dysregulation of TREM1 signaling, cytokines, and chemokines.
Sex, Specimen part, Treatment
View SamplesCharacterization of the selectivity of SMN splicing modifiers in SMA type I fibroblasts by RNASeq Overall design: In total 12 samples were analyzed, divided into four distinct groups (treated with SMN-C3 @ 500 nM; controls for SMN-C3; treated with SMN-C1 @ 100 nM; controls for SMN-C1) containing 3 replicates each.
Motor neuron disease. SMN2 splicing modifiers improve motor function and longevity in mice with spinal muscular atrophy.
No sample metadata fields
View SamplesThe innate immune system is the organisms first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level. In addition to forming macrophages and dendritic cells, monocytes in adult peripheral blood retain the ability to develop into osteoclasts, mature bone-resorbing cells. The extensive morphological and functional transformations that occur during osteoclast differentiation require substantial reprogramming of gene and protein expression. Here we employ -omic-scale technologies to examine in detail the molecular changes at discrete developmental stages in this process (precursor cells, intermediate osteoclasts, and multinuclear osteoclasts), quantitatively comparing their transcriptomes and proteomes.
Characterization of functional reprogramming during osteoclast development using quantitative proteomics and mRNA profiling.
Specimen part, Cell line
View Samples