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accession-icon GSE140213
A class II-restricted chlamydia-specific CD8ɣ13 T cell clone protects the genital tract during Chlamydia muridarum infection
  • organism-icon Mus musculus
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The T cell response to Chlamydia genital tract infections in humans and mice is unusual in that the majority of antigen-specific CD8 T cells are not restricted by HLA/MHC class I and therefore have been referred to as “unrestricted” or “atypical”.   We previously reported that a subset of unrestricted murine Chlamydia-specific CD8 T cells had an unusual cytokine polarization pattern that included IFN-ɣ and IL-13.  For this report, we investigated the transcriptome of Chlamydia-specific CD8ɣ13 T cells, comparing them to Chlamydia-specific multifunctional Tc1 clones using gene expression micro array analysis.  The molecular study revealed that CD8ɣ13 polarization included IL-5 in addition to IFN-γ and IL-13.  Adoptive transfer studies were performed with Tc1 clone and CD8ɣ13 T cell clones to determine whether either influenced bacterial clearance or immunopathology during Chlamydia muridarum (Cm) genital tract infections.  To our surprise, an adoptively transferred CD8ɣ13 T cell clone was remarkably proficient at preventing chlamydia immunopathology while the multifunctional Tc1 clone did not enhance clearance or significantly protect from immunopathology.  Mapping studies with MHC class I- and class II-deficient splenocytes showed our previously published Chlamydia-specific CD8 T cell clones are MHC class II-restricted.   MHC class II-restricted CD8 T cells may play important roles in protection from intracellular pathogens that limit class I antigen presentation or deplete the CD4 T cell compartment.

Publication Title

A Class II-Restricted CD8γ13 T-Cell Clone Protects During Chlamydia muridarum Genital Tract Infection.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP038863
Characterization of distinct classes of differential gene expression in osteoblast cultures from non-syndromic craniosynostosis bone
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

We report on explant osteoblast cultures from human patients, demonstrating that there are at least three sub-types of non-syndromic craniosynostosis defined by similarity of gene expression profiles. Overall design: Osteoblast growth in culture, 23 craniosynostosis skull samples (7 metopic; 8 coronal; 3 lambdoid; 5 sagittal) and 8 normal (4 cranial bones and 4 long bones)

Publication Title

Characterization of distinct classes of differential gene expression in osteoblast cultures from non-syndromic craniosynostosis bone.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE14320
Basal and kainate-induced gene expression in A-CREB mouse hippocampi
  • organism-icon Mus musculus
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

The cAMP responsive element binding protein (CREB) pathway has been involved in two major cascades of gene expression regulating neuronal function. The first one presents CREB as a critical component of the molecular switch that control longlasting forms of neuronal plasticity and learning. The second one relates CREB to neuronal survival and protection. To investigate the role of CREB-dependent gene expression in neuronal plasticity and survival in vivo, we generated bitransgenic mice expressing A-CREB, an artificial peptide with strong and broad inhibitory effect on the CREB family, in forebrain neurons in a regulatable manner. The expression of ACREB in hippocampal neurons impaired L-LTP, reduced intrinsic excitability and the susceptibility to induced seizures, and altered both basal and activity-driven gene expression. In the long-term, the chronic inhibition of CREB function caused severe loss of neurons in the CA1 subfield as well as in other brain regions. Our experiments confirmed previous findings in CREB deficient mutants and revealed new aspects of CREB-dependent gene expression in the hippocampus supporting a dual role for CREB-dependent gene expression regulating intrinsic and synaptic plasticity and promoting neuronal survival. manufacturer's protocol.

Publication Title

Inhibition of cAMP response element-binding protein reduces neuronal excitability and plasticity, and triggers neurodegeneration.

Sample Metadata Fields

Age, Treatment

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accession-icon GSE107613
Gene expression profile of juvenile R6/1 and N171-82Q brains
  • organism-icon Mus musculus
  • sample-icon 54 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

Transcriptional dysregulation in Huntingtons disease (HD) is an early event that affects the expression of genes involved in survival and neuronal functions throughout the progression of the pathology. In the last years, extensive research has focused on epigenetic and chromatin-modifying factors as a causative explanation for such dysregulation, offering attractive targets for pharmacological therapies. In this work we examined the gene expression profiles in cortex, striatum, hippocampus and cerebellum of juvenile R6/1 and N171-82Q mice, two models of fast progressive HD, to retrieve the early transcriptional signatures associated with this pathology.These profiles showed significant coincidences with the transcriptional changes in the conditional knockout for the lysine acetyltransferase CBP in postmitotic forebrain neurons.

Publication Title

Early alteration of epigenetic-related transcription in Huntington's disease mouse models.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE21479
Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome 2.0 Array (yeast2)

Description

The needs for rapid and efficient microbial cell factory design and construction are possible through the enabling technology, metabolic engineering, which is now being facilitated by systems biology approaches. Metabolic engineering is often complimented by directed evolution, where selective pressure is applied to a partially genetically engineered strain to confer a desirable phenotype. The exact genetic modification or resulting genotype that leads to the improved phenotype is often not identified or understood to enable further metabolic engineering. In this work we establish proof-of-concept that whole genome high-throughput sequencing and annotation can be used to identify single nucleotide polymorphisms (SNPs) between Saccharomyces cerevisiae strains S288c and CEN.PK113-7D. The yeast strain S288c was the first eukaryote sequenced, serving as the reference genome for the Saccharomyces Genome Database, while CEN.PK113-7D is a preferred laboratory strain for industrial biotechnology research. A total of 13,787 high-quality SNPs were detected between both strains (reference strain: S288c). Considering only metabolic genes (782 of 5,873 annotated genes), a total of 219 metabolism specific SNPs are distributed across 158 metabolic genes, with 85 of the SNPs being non-silent (e.g., encoding amino acid modifications). Amongst metabolic SNPs detected, there was pathway enrichment in the galactose uptake pathway (GAL1, GAL10) and ergosterol biosynthetic pathway (ERG8, ERG9). Physiological characterization confirmed a strong deficiency in galactose uptake and metabolism in S288c compared to CEN.PK113-7D, and similarly, ergosterol content in CEN.PK113-7D was significantly higher in both glucose and galactose supplemented cultivations compared to S288c. Furthermore, DNA microarray profiling of S288c and CEN.PK113-7D in both glucose and galactose batch cultures did not provide a clear hypothesis for major phenotypes observed, suggesting that genotype to phenotype correlations are manifested post-transcriptionally or post-translationally either through protein concentration and/or function. With an intensifying need for microbial cell factories that produce a wide array of target compounds, whole genome high-throughput sequencing and annotation for SNP detection can aid in better reducing and defining the metabolic landscape. This work demonstrates direct correlations between genotype and phenotype that provides clear and high-probability of success metabolic engineering targets. The genome sequence, annotation, and a SNP viewer of CEN.PK113-7D are deposited at www.sysbio.se/cenpk.

Publication Title

Whole genome sequencing of Saccharomyces cerevisiae: from genotype to phenotype for improved metabolic engineering applications.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE10696
Expression analysis in A431_wt vs A431_GR cells
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A431 wild-type (wt) cancer cell line is sensitive to treatment with EGFR tyrosine kinase inhibitors (TKIs). By culturing it chronically under gefitinib, it eventually becomes resistant (A431_GR cell). We know of a few proteins involved in this mechanism of drug resistance, but a cDNA exprssion array would add information to other genes that might be involved in this resistance mechanism.

Publication Title

Acquired resistance to EGFR tyrosine kinase inhibitors in cancer cells is mediated by loss of IGF-binding proteins.

Sample Metadata Fields

Specimen part

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accession-icon GSE46006
The Tight Junction Protein Claudin-2 Controls Mucosal Permeability, Immune Tolerance and Colitis in Mice
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

The mucosal epithelium plays a key role in regulating immune homeostasis. Dysregulation of epithelial barrier function is associated with mucosal inflammation. Expression of claudin-2, a pore-forming tight junction protein, is highly upregulated during inflammatory bowel disease (IBD) and, due to its association with epithelial permeability, has been postulated to promote inflammation. Furthermore, claudin-2 also regulates colonic epithelial cell proliferation and intestinal nutrient absorption. However, the precise role of claudin-2 in regulating colonic epithelial and immune homeostasis remains unclear. Here, we demonstrate, using Villin-Claudin-2 transgenic (Cl-2TG) mice, that increased colonic claudin-2 expression unexpectedly protects mice against experimentally induced colitis and colitis-associated cancer. Notably, Cl-2TG mice exhibited increased colon length and permeability as compared with wild type (WT) littermates. However, despite their leaky colon, Cl-2TG mice subjected to experimental colitis were immune compromised, with reduced induction of TLR-2, TLR-4, Myd-88 expression and NF-kB and STAT3 activation. Most importantly, colonic macrophages in Cl-2TG mice exhibited an anergic phenotype. Claudin-2 overexpression also increased colonocyte proliferation and provided protection against colitis-induced colonocyte death. Taken together, our findings have revealed a critical role of claudin-2 in regulating colonic homeostasis, suggesting novel therapeutic strategies for inflammatory conditions of the gastrointestinal tract.

Publication Title

Targeted colonic claudin-2 expression renders resistance to epithelial injury, induces immune suppression, and protects from colitis.

Sample Metadata Fields

Sex, Specimen part, Treatment

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accession-icon GSE44076
Gene expression data from healthy, adjacent normal and tumor colon cells
  • organism-icon Homo sapiens
  • sample-icon 246 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Gene expression profiles of paired normal adjacent mucosa and tumor samples from 98 individuals and 50 healthy colon mucosae, were obtained through Affymetrix Human Genome U219 Arrays. This dataset is in the context of the COLONOMICS project and to query additional information you can visit the project website www.colonomics.org.

Publication Title

Discovery and validation of new potential biomarkers for early detection of colon cancer.

Sample Metadata Fields

Sex, Age, Disease, Subject

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accession-icon SRP153037
Response of triple negative breast cancer to BAZ2A/B inhibition and BET bromodomain inhibition alone and in combination (RNAseq)
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge IconNextSeq 500

Description

Three triple negative breast cancer cell lines (MDAMB231, SUM159, and HCC1806) were treated with small molecule inhibitors (JQ1, BET bromodomain inhibitor; GSK2801, BAZ2A/B bromodomain inhibitor) alone and in combination for 72 hours Overall design: 12 experimental samples

Publication Title

GSK2801, a BAZ2/BRD9 Bromodomain Inhibitor, Synergizes with BET Inhibitors to Induce Apoptosis in Triple-Negative Breast Cancer.

Sample Metadata Fields

Cell line, Treatment, Subject

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accession-icon GSE56810
H2BGFP
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Gene 1.0 ST Array (mogene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Loss of neuronal 3D chromatin organization causes transcriptional and behavioural deficits related to serotonergic dysfunction.

Sample Metadata Fields

Sex, Specimen part

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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