Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Gene expression of murine B cells activated via TLR4 or TLR4 + CD40: Group1 naM-CM-/ve B cells, Group2 LPS activated B cells 24h, Group3 LPS + anti-CD40 activated B cells 24h, Group4 LPS activated B cells 72h, and Group5 LPS + anti-CD40 activated B cells 72h.

ABSTRACT: Murine B cells can be activated via the surface receptors TLR4 and CD40. For a global assessment of differences in gene expression between these two different modes of B cell activation a genome wide transcriptome analysis was performed. In order to dissect different gene expression profiles of B cells, activation was induced by LPS or LPS + anti-CD40 for 24h and 72h. Both activation states were compared to each other but also to naM-CM-/ve B cells. Gene expression profiles of naM-CM-/ve B cells, B cells activated with LPS and B cells activated with LPS + anti-CD40. Affymetrix MG 430 2.0 whole genome arrays were performed in quadruplicates for naM-CM-/ve B cells, B cells activated via TLR4 for 24 h and 72 h, and B cells activated via TLR4 + CD40 for 24 h and 72 h (20 arrays in total). To obtain genes significantly regulated upon stimulation with LPS, the expression profiles of naM-CM-/ve B cells, B cells activated with LPS for 24 h, and B cells activated with LPS for 72 h were compared to each other. After total RNA extraction, reverse transcription, cDNA extraction, the biotinylated cRNA was transcribed, fragmented, and 15 M-BM-5g cRNA hybridized in quadruplicates for each of the five groups to the 20 GeneChip arrays: Group1 naM-CM-/ve B cells, Group2 LPS activated B cells 24h, Group3 LPS + anti-CD40 activated B cells 24h, Group4 LPS activated B cells 72h, and Group5 LPS + anti-CD40 activated B cells 72h. Access to PDF: http://dx.doi.org/10.1038/nature12979 All chips were imported into BioRetis (http://www.bioretis-analysis.de) and are open to the community now. If you want to obtain one or more lists of HPCDA significant genes you should click on a link of single chips (e.g. GSM879034) to get a description how to manage this.

ORGANISM(S): Mus musculus

SUBMITTER: Joachim GrM-CM-<n

PROVIDER: E-GEOD-35998 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

IL-35-producing B cells are critical regulators of immunity during autoimmune and infectious diseases.

Shen Ping P Roch Toralf T Lampropoulou Vicky V O'Connor Richard A RA Stervbo Ulrik U Hilgenberg Ellen E Ries Stefanie S Dang Van Duc VD Jaimes Yarúa Y Daridon Capucine C Li Rui R Jouneau Luc L Boudinot Pierre P Wilantri Siska S Sakwa Imme I Miyazaki Yusei Y Leech Melanie D MD McPherson Rhoanne C RC Wirtz Stefan S Neurath Markus M Hoehlig Kai K Meinl Edgar E Grützkau Andreas A Grün Joachim R JR Horn Katharina K Kühl Anja A AA Dörner Thomas T Bar-Or Amit A Kaufmann Stefan H E SHE Anderton Stephen M SM Fillatreau Simon S

Nature 20140223 7492

B lymphocytes have critical roles as positive and negative regulators of immunity. Their inhibitory function has been associated primarily with interleukin 10 (IL-10) because B-cell-derived IL-10 can protect against autoimmune disease and increase susceptibility to pathogens. Here we identify IL-35-producing B cells as key players in the negative regulation of immunity. Mice in which only B cells did not express IL-35 lost their ability to recover from the T-cell-mediated demyelinating autoimmun ...[more]

PMID: 24572363

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Project description:To determine characterize human B cells that express IL-10 on a molecular level, we compared the global gene expression of primary CD19pos B cells secreting IL-10 or not, upon activation with anti-CD40, IL-4 and CpG for 2 days. Human B cells from healthy donors were sorted according to CD19 expression by magnetic cell separation. The cells were stimulated at 2.5E06 cells/ml by activating anti-CD40 mAb (1 M-BM-5g/ml, clone 82111, RnD Systems), recombinant human IL-4 (10 ng/ml, Immunotools) and CpG2006 (3 M-BM-5g/ml) for 2 days following restimulation for 3 h with phorbol myristate acetate (PMA, 10 ng/ml) and ionomycin (1 M-BM-5g/ml). Staining of viable IL-10 secreting human CD19pos B cells was performed by the IL-10 capture assay according the manufacturers instructions (Miltenyi Biotec, n=2). Finally, the cells were sorted into IL-10posCD69pos and IL-10negCD69pos cells by flow cytometric cell sorting on a BD Aria II sorter (Becton Dickinson). Dead cells were excluded using propidium iodide. Total RNA was extracted using the RNeasy Mini kit (Qiagen). The integrity and amount of isolated RNA was assessed for each sample using an Agilent 2100 Bioanalyzer (Agilent, Waldbronn, Germany) and a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE). Double-stranded complementary RNA was synthesized from 1 M-BM-5g total RNA using Message AmpII Biotin (Ambion, USA). Fifteen micrograms of fragmented cRNA of each sample were hybridized to four HG-U133A plus 2.0 GeneChips (Affymetrix). Hybridization was performed in a Hybridization Oven 640, and chips were washed and stained in the Fluidics Station 400 (both Affymetrix). Finally, the arrays were scanned with a GeneChip Scanner 3000 using the GCOS software, version 1.4, both Affymetrix. All relevant GCOS data of quality checked microarrays were analyzed with High Performance Chip Data Analysis (HPCDA, unpublished), using the BioRetis database (www.bioretis-analysis.de), as described and validated previously.

Project description:Gene expression profiling of cells isolated ex vivo is a unique tool to assess gene expression in vivo. Exemplified for CD4+CD45RO+ effector/memory T helper (T E/M) lymphocytes of human peripheral blood, we have analyzed different isolation procedures and storage conditions for the introduction of bias. Cells from clinical samples can be sorted to high purity by a flow cytometric sorter and assessed for their gene expression pattern but storage/shipping conditions and often necessary pre-enrichment due to low initial population frequencies bears the danger of introducing artificial changes. To test for changes introduced by different procedures, cells were enriched either by magnetic cell sorting (MACS) with Whole-Blood CD4 beads, density gradient centrifugation, alone or in combination with CD3 MACS, or by lysis of erythrocytes followed by MACS depletion of CD15+ cells prior to fluorescence-activated cell sorting (FACS) as CD3+CD4+CD45RO+ cells. A total of 7 different protocols were compared among each other and to T cells stimulated for 3 hours after isolation with Phorbol-12-myristate-13-acetate and Ionomycin (PMA/Iono). Preparation-induced de novo transcription was blocked in one of the protocols by addition of 2 M-BM-5g/ml Actinomycin D (ActD). To test for changes introduced by delays in sample preparation blood samples were drawn and either processed directly or kept at 4 M-BM-0C or room temperature (RT) for 2 or 6 hours before T E/M cells were isolated. Gene expression was compared among the various cell preparations and to T E/M cells isolated from 1 day old buffy coat fractions stored at RT. Sorted cells were lysed in TRIzol (Invitrogen) and frozen at -80M-BM-0C until used for RNA extraction. Total RNA was extracted using the miRNeasy kit (Qiagen). The integrity and amount of isolated RNA was assessed for each sample using an Agilent 2100 Bioanalyzer (Agilent, Waldbronn, Germany) and a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE). Double-stranded complementary RNA was synthesized from 1 M-BM-5g total RNA using Message AmpII Biotin (Ambion, USA). Fifteen micrograms of fragmented cRNA of each sample were hybridized to 26 HG-U133A plus 2.0 GeneChips (Affymetrix). Hybridization was performed in a Hybridization Oven 640, and chips were washed and stained in the Fluidics Station 400 (both Affymetrix). Finally, the arrays were scanned with a GeneChip Scanner 3000 using the GCOS software, version 1.4, both Affymetrix. All relevant GCOS data of quality checked microarrays were analyzed with High Performance Chip Data Analysis (HPCDA, unpublished), using the BioRetis database (www.bioretis-analysis.de), as described and validated previously.

Project description:In order to identify genes that are activated in differentiating WT ESCs, but are missing in Tal-1-/- and Runx1-/- ESCs, and which might be involved in the generation of definitive hematopoietic progenitors and their specification thereafter, we performed microarray analyses on purified Flk-1+ cells, differentiated from these ESCs for 4, 5, and 6 days M-bM-^@M-^\in vitroM-bM-^@M-^]. Gene-expression profiling of three biological replicates was performed at days 4, 5, and 6 during the differentiation process of WT J1 ESCs (9 samples), and at day 6 during the differentiation process of either Runx1-/- J1 or Tal-1-/- J1 ESCs (3 samples each). Total RNA was extracted using the RNeasy Mini kit (Qiagen). The integrity and amount of isolated RNA was assessed for each sample using an Agilent 2100 Bioanalyzer (Agilent, Waldbronn, Germany) and a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE). Complementary DNA was synthesized from 3-5 M-NM-<g total RNA, using reagents recommended in the technical manual GeneChip Expression Analysis (Affymetrix, Santa Clara, CA). The in vitro transcription, necessary for the synthesis of biotinylated complementary RNA (cRNA) was performed using the Enzo RNA Transcript Labeling kit (Affymetrix). Fifteen micrograms of fragmented cRNA of each sample were hybridized to nine Mouse Genome 430-2 arrays (Affymetrix). Hybridization was performed in a Hybridization Oven 640, and chips were washed and stained in the Fluidics Station 400 (both Affymetrix), according to procedure 2 as described in the technical manual. Finally, the arrays were scanned with a GeneChip Scanner 3000 using the GCOS software, both Affymetrix. All relevant GCOS data of quality checked microarrays were analyzed with High Performance Chip Data Analysis (HPCDA, unpublished), using the BioRetis database (www.bioretis-analysis.de), as described and validated previously (55). Used query parameters for database filtering process was described earlier several times (56). For hierarchical cluster analysis, we used the program Genes@Work (57) with gene vectors for normalization and Pearson w/mean for similarity measure. As cluster type, we used center of mass.

Project description:This study demonstrates quantitative and qualitative differences between type I IFN signatures in autoimmunity and viral infection using purified CD4pos T cells and CD16pos- and CD16neg-monocyte subsets. We were able to discriminate between cell-specific viral response signatures and the pathogenically amplified IFN signatures observed in autoimmunity. The differences were of both a qualitative and quantitative nature, as the signatures in the patients with SLE were characterized by much more complexly compiled gene patterns with increased absolute gene expression levels. Collection of cells from Systemic Lupus Erythematosus (SLE) patients: For CD4pos T cells, six patients with SLE (average age: 29.0 +/- 7.6) and four normal healthy donors (ND; 24.8 +/- 0.5) were recruited. For CD16neg monocytes, four patients with SLE (26.5 +/- 1.7) and four NDs (24.8 +/- 0.5) were recruited. For CD16pos monocytes, four patients with SLE (26.5 +/- 1.7) and three NDs (24.7 +/- 0.6) were recruited. All patients and NDs were female. The same NDs were examined before and after immunisation with yellow fever vaccine (YFV). Collection of cells from yellow-fever vaccinated individuals: ND were immunised with a vaccine against the wild-type YF virus, which is a single-stranded RNA virus without adjuvants. This vaccine consists of a live but attenuated strain of the yellow fever virus (YFV-17D). Based on its vaccination-associated clinical and serological manifestations, this immunisation can be regarded as a real viral infection. A total of 50 ml peripheral blood was taken 7 days after immunisation, when sufficient numbers of CD19pos/CD27high plasmablasts were detected by flow cytometry. Cell sorting: A total of 50 ml peripheral blood was collected in Vacutainer heparin tubes and erythrocytes were lysed in EL buffer. Subsequently, granulocytes were depleted using CD15-conjugated microbeads (MACS). The CD15-depleted fraction was stained with a CD14-fluorescein isothiocyanate (FITC) antibody, a CD16-APC-Cy7 antibody, a CD3-Vioblue antibody and a CD4-FITC antibody. Using a FACSAria cell sorter, CD4pos T cells, CD16neg monocytes and CD16pos monocytes were isolated with purities and viabilities of >97%. After sorting, the cells were immediately lysed with RLT buffer and frozen at -70 M-BM-0C. Total RNA was isolated using an RNeasy mini kit, and quality control was ensured by Bioanalyser measurements.Total RNA was extracted using the RNeasy Mini kit. The integrity and amount of isolated RNA was assessed for each sample using an Agilent 2100 Bioanalyzer and a NanoDrop ND-1000 spectrophotometer. Biotinylated complementary RNA (cRNA) was synthesized from 100 ng total RNA, using reagents as recommended in the technical manual from Affymetrix. Fifteen micrograms of fragmented cRNA of each sample were hybridized to HG-U133 plus 2.0 arrays. Hybridization was performed according to procedure 2 as described in the technical manual. Finally, the arrays were scanned with a GeneChip Scanner 3000 using the GCOS software. All relevant GCOS data of quality checked microarrays were analyzed with High Performance Chip Data Analysis (HPCDA, unpublished), using the BioRetis database (www.bioretis-analysis.de), as described and validated previously.

Dataset Information

Gene expression of murine B cells activated via TLR4 or TLR4 + CD40: Group1 naM-CM-/ve B cells, Group2 LPS activated B cells 24h, Group3 LPS + anti-CD40 activated B cells 24h, Group4 LPS activated B cells 72h, and Group5 LPS + anti-CD40 activated B cells 72h.

Publications

IL-35-producing B cells are critical regulators of immunity during autoimmune and infectious diseases.

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