Project description:Gene expression profiles of individual bone marrow cells were acquired by Drop-Seq. Subsets of bone marrow cells were isolated using magnetic cell sorting to enrich for putative skeletal stem cells.
Project description:Gene expression profiles of individual bone marrow cells were acquired by Drop-Seq. Total bone marrow (TBM) and weakly lineage depleted bone marrow (DBM; CD235a and/or Cd45 negative) and stromal cells (STRO-1 positive or collagenase IV released) were analysed.
Project description:Autoimmune diseases are often associated with HLA molecules. Multiple sclerosis (MS) is a prototypical example with the HLA-DR15 haplotype as strongest genetic factor. How it contributes to MS is not clear, but key to understand this and other autoimmune diseases. Autoreactive CD4+ T cells and proinflammatory B cells are central pathogenetic factors, and since HLA-DR molecules present peptides to CD4+ T cells, we characterized the peptidomes of the two HLA-DR15 allomorphs DR2a and DR2b on B cells. Self-peptides from HLA-DR α- and β-chains themselves are abundantly presented on B cells. We identified autoreactive CD4+ T cell clones, which recognize HLA-DR-derived self-peptides and peptides from the MS-related infectious agents EBV and Akkermansia and the autoantigen RAS guanyl-releasing protein 2. Our data demonstrate how the two MS-associated HLA-DR15 allomorphs function as antigen-presenting structures and source of peptides during peripheral maintenance of autoreactive T cells and activation by MS-associated pathogens.
Project description:T cell antigen receptor δ (Tcrd) variable region exons are assembled by RAG-initiated V(D)J recombination. Here, we employ a high throughput method to map hundreds of thousands of RAG-initiated Tcrd D segment (Trdd1 and Trdd2) rearrangements in developing thymocytes. We find that Trdd2 joins directly to Trdv, Trdd1, and Trdj segments, but Trdd1 joining is ordered with joining to Trdd2 a prerequisite for further rearrangement. We also find frequent, previously unappreciated Trdd1 and Trdd2 rearrangements that inactivate Tcrd. Moreover, we find numerous RAG off-targets that are generated via unidirectional RAG tracking across the loop-domain containing Trdd1, Trdd2 and Trdj. Correspondingly, disruption of the upstream domain boundary causes spreading of on- and off-target RAG activity to the proximal Trdv domain. RAG-initiatd Tcrd D segment rearrangements in developing thymocytes were generated by deep sequencing using illumine Miseq
Project description:Chromatin looping mediated by the CCCTC binding factor CTCF regulates V(D)J recombination at antigen receptor loci. CTCF-mediated looping can influence recombination signal sequence accessibility by regulating enhancer activation of germline promoters. CTCF-mediated looping has also been shown to limit directional tracking of the RAG recombinase along chromatin, and to regulate through-space interactions between recombination signal sequences, independent of the RAG recombinase. However, in all prior instances in which CTCF-mediated looping was shown to influence V(D)J recombination, it was not possible to fully resolve the relative contributions to the V(D)J recombination phenotype of changes in accessibility, RAG-tracking, and RAG-independent long-distance interactions. Here, to assess mechanisms by which CTCF-mediated looping can impact V(D)J recombination, we introduced an ectopic CTCF binding element (CBE) immediately downstream of Eδ in the murine Tcra-Tcrd locus. The ectopic CBE impaired inversional rearrangement of Trdv5 in the absence of measurable effects on Trdv5 transcription and chromatin accessibility. Moreover, although the ectopic CBE limited directional RAG tracking from the Tcrd recombination center, such tracking cannot account for Trdv5-to-Trdd2 inversional rearrangement. Rather, the defect in Trdv5 rearrangement could only be attributed to a reconfigured chromatin loop organization that limited RAG-independent through-space interactions between the Trdv5 and Trdd2 RSSs. We conclude that CTCF can regulate V(D)J recombination by segregating RSSs into distinct loop domains and inhibiting RSS synapsis, independent of any effects on transcription, RSS accessibility and RAG tracking. RAG-initiatd Tcrd D segment rearrangements in developing thymocytes were generated by deep sequencing using illumine Miseq
Project description:Gene expression profiles of individual bone marrow cells were acquired by Drop-Seq. Total bone marrow (TBM) and weakly depleted bone marrow (DBM; Ter119/Cd45 negative cells) were analysed.
Project description:The reconstruction of cell type- and patient-specific metabolic models from easily and reliably measurable features such as transcriptomics data will be increasingly important at the age of personalized medicine. Current reconstruction methods suffer from high computational effort and arbitrary threshold setting. Moreover, understanding the underlying epigenetic regulation might allow the identification of putative intervention points within metabolic networks. Genes under high regulatory load from multiple enhancers or super-enhancers are known key genes for disease and cell identity. However, their role in regulation of metabolism and their placement within the metabolic networks has not been studied. Here we present FASTCORMICS, a fast and robust workflow for the creation of high-quality metabolic models from transcriptomics data. FASTCORMICS is devoid of arbitrary parameter settings and due to its low computational demand allows cross-validation assays.. Applying FASTCORMICS, we have generated models for 63 primary human cell types from microarray data, revealing significant differences in their metabolic networks. To understand the cell type-specific regulation of the alternative metabolic pathways we built multiple models during differentiation of primary human monocytes to macrophages and performed ChIP-Seq experiments for histone H3 K27 acetylation (H3K27ac) to map the active enhancers in macrophages. Focusing on the metabolic genes under high regulatory load from multiple enhancers or super-enhancers, we found these genes to show the most cell type-restricted and abundant expression profiles within their respective pathways. Importantly, the high regulatory load genes are associated to reactions enriched for transport reactions and other pathway entry points, suggesting that they are critical regulatory control points for cell type-specific metabolism. By integrating metabolic modelling and epigenomic analysis we have identified high regulatory load as a common feature of metabolic genes at pathway entry points such as transporters within the macrophage metabolic network. Analysis of these control points through further integration of metabolic and gene regulatory networks in various contexts could be beneficial in multiple fields from identification of disease intervention strategies to cellular reprogramming. ChIP-Seq was performed with chromatin from macrophages differentiated in vitro for 11 days from primary human CD14+ monocytes isolated from the blood of three different anonymous male donors. For each donor one ChIP sample using an antibody against H3K27ac and one input sample were sequenced. Please see the individual samples for further details.
Project description:In this study, we analyzed transcriptome gene expression microarray, epigenomic miRNA microarray and methylome sequencing data simultaneously in PBMs from 5 high hip BMD subjects and 5 low hip BMD subjects. Through integrating the transcriptomic and epigenomic data, firstly we identified BMD-related genetic factors, including 9 protein coding genes and 2 miRNAs, of which 3 genes (FAM50A, ZNF473 and TMEM55B) and one miRNA (hsa-mir-4291) showed the consistent association evidence from both gene expression and methylation data, and 3 genes (TMEM55B, RNF40 and ALDOA) were confirmed in the meta-analysis of 7 GWAS samples and GEnetic Factors for OSteoporosis consortium (GEFOS-2) GWAS results. Secondly in network analysis we identified an interaction network module with 12 genes and 11 miRNAs including AKT1, STAT3, STAT5A, FLT3, hsa-mir-141 and hsa-mir-34a which have been associated with BMD in previous studies. This module revealed the crosstalk among miRNAs, mRNAs and DNA methylation and showed four potential regulatory patterns of gene expression to influence the BMD status, including regulation by gene methylation, by miRNA and its methylation, by transcription factors and co-regulation by miRNA and gene methylation. In conclusion, the integration of multiple layers of omics can yield more in-depth results than analysis of individual omics data respectively. Integrative analysis from transcriptomics and epigenomic data improves our ability to identify causal genetic factors, and more importantly uncover functional regulation pattern of multi-omics for osteoporosis etiology. 5 high hip BMD subjects and 5 low hip BMD subjects
Project description:Objective: In idiopathic inflammatory myopathies (IIM) infiltration of immune cells into muscle and upregulation of MHC-I expression implies increased antigen presentation and involvement of the proteasome system. To decipher the role of immunoproteasomes in myositis, we investigated individual cell types and muscle tissues and focused on possible immune triggers. Methods: Expression of constitutive (PSMB5, -6, -7) and corresponding immunoproteasomal subunits (PSMB8, -9, -10) was analyzed by real-time RT-PCR in muscle biopsies and sorted peripheral blood cells of patients with IIM, non-inflammatory myopathies (NIM) and healthy donors (HD). Protein analysis in muscle biopsies was performed by western blot. Affymetrix HG-U133 platform derived transcriptome data from biopsies of different muscle diseases and from immune cell types as well as monocyte stimulation experiments were used for validation, coregulation and coexpression analyses. Results: Real-time RT-PCR revealed significantly increased expression of immunoproteasomal subunits (PSMB8/-9/-10) in DC, monocytes and CD8+ T-cells in IIM. In muscle biopsies, the immunosubunits were elevated in IIM compared to NIM and exceeded levels of matched blood samples. Proteins of PSMB8 and -9 were found only in IIM but not NIM muscle biopsies. Reanalysis of 78 myositis and 20 healthy muscle transcriptomes confirmed these results and revealed involvement of the antigen processing and presentation pathway. Comparison with reference profiles of sorted immune cells and healthy muscle confirmed upregulation of PSMB8 and -9 in myositis biopsies beyond infiltration related changes. This upregulation correlated highest with STAT1, IRF1 and IFNM-NM-3 expression. Elevation of T-cell specific transcripts in active IIM muscles was accompanied by increased expression of DC and monocyte marker genes and thus reflects the cell type specific involvement observed in peripheral blood. Conclusions: Immunoproteasomes seem to indicate IIM activity and suggest that dominant involvement of antigen processing and presentation may qualify these diseases exemplarily for the evolving therapeutic concepts of immunoproteasome specific inhibition. Investigation of constitutive and immunoproteasomal subunit expression in muscle tissue of patients with inflammatory and non-inflammatory myopathies These transcriptomes were used as reference signatures of different immune cell types in order to estimate the contribution of immune cell transcripts to the muscle transcriptomes investigated in the datasets GSE2044, GSE3112, GSE5370, GSE39454, GSE3307, GSE13205, GSE10685.