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Rasool, O.

Publications and source records attributed to Rasool, O..

6 recordsLinked to original sources

Genetic Disruption at the CIP2A Locus Modulates T Cell Responses and Attenuates Experimental Autoimmune Encephalomyelitis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system (CNS) driven by pathogenic T cell-mediated inflammation. Fingolimod (FTY720), an approved therapy for MS, is an established activator of protein phosphatase 2A (PP2A). However the contribution of PP2A in autoimmune neuroinflammation remains incompletely understood. Here, we addressed this question using experimental autoimmune encephalomyelitis (EAE), a murine model of MS, in mice carrying a genetic disruption of the locus encoding cancerous inhibitor of protein phosphatase 2A (CIP2A), an endogenous inhibitor of PP2A. Mice with disruption of the CIP2A locus, the knock out (KO) mice, exhibited attenuated EAE severity compared with wild-type (WT) controls. Histological and flow-cytometric analyses revealed markedly reduced infiltration of mononuclear cells, including CD4 and CD4CXCR6 encephalitogenic T cells, in the CNS of diseased KO mice. Reduced numbers of these T cell populations were also observed in peripheral lymphoid organs of the Cip2a-deficient mice during EAE, while T cell abundance was comparable under steady-state conditions, suggesting impaired activation-induced expansion rather than altered homeostasis or migration. Single-cell RNA sequencing of CNS and lymph node immune cells revealed changes in cell-type abundance and gene expression. Notably, Il17a expression was reduced in CNS CD8+ T cells and showed a similar trend in {gamma}{delta} T cells. Together, our findings reveal that genetic disruption at the CIP2A locus attenuates EAE, possibly by limiting the expansion and accumulation of encephalitogenic T cell populations in CNS. These results identify the CIP2A locus as a previously unrecognized regulator of T cell-driven autoimmune neuroinflammation and provide new insights into mechanisms that restrain pathogenic T cell responses during EAE.

immunology↗

HIC1 interacts with FOXP3 multi-protein complex: a novel mechanism to regulate human regulatory T cell differentiation and function

Transcriptional repressor, hypermethylated in cancer 1 (HIC1) participates in a range of important biological processes, such as tumor repression, immune suppression, embryonic development and epigenetic gene regulation. Further to these, we previously demonstrated that HIC1 provides a significant contribution to the function and development of regulatory T (Treg) cells. However, the mechanism by which it regulates these processes was not apparent. To address this question, we used affinity-purification mass spectrometry to characterize the HIC1 Interactome in human Treg cells. Altogether 61 high-confidence interactors were identified, including IKZF3, which is a key transcription factor in the development of Treg cells. The biological processes associated with these interacting proteins include protein transport, mRNA processing, non-coding (ncRNA) transcription and RNA metabolism. The results revealed that HIC1 is part of a FOXP3-RUNX1-CBFB protein complex that regulates Treg signature genes thus improving our understanding of HIC1 function during early Treg cell differentiation. HighlightsO_LISystematic characterization of HIC1 interactome in regulatory T cells by Affinity Purification-Mass Spectrometry C_LIO_LIHIC1 binds to the RUNX1 promoter and regulates its expression C_LIO_LIHIC1-a part of FOXP3-RUNX1-CBFB transcriptional complex C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=37 SRC="FIGDIR/small/540505v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@1fcb119org.highwire.dtl.DTLVardef@cf1397org.highwire.dtl.DTLVardef@10f512forg.highwire.dtl.DTLVardef@9ae94e_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

Permutation-based significance analysis reduces the type 1 error rate in bisulfite sequencing data analysis of human umbilical cord blood samples

BackgroundDNA methylation patterns are largely established in-utero and might mediate the impacts of in-utero conditions on later health outcomes. Associations between perinatal DNA methylation marks and pregnancy-related variables, such as maternal age and gestational weight gain, have been earlier studied with methylation microarrays, which typically cover less than 2 % of human CpG sites. To detect such associations outside these regions, we chose the bisulfite sequencing approach. MethodsWe collected and curated all available clinical data on 200 newborn infants; whose umbilical cord blood samples were analyzed with the reduced representation bisulfite sequencing (RRBS) method. A generalized linear mixed effects model was fit for each high coverage CpG site, followed by spatial and multiple testing adjustment of P values to identify differentially methylated cytosines (DMCs) and regions (DMRs) associated with clinical variables such as maternal age, mode of delivery, and birth weight. Type 1 error rate was then evaluated with a permutation analysis. ResultsWe discovered a strong inflation of spatially adjusted P values through the permutation analysis, which we then applied for empirical type 1 error control. Based on empirically estimated significance thresholds, very little differential methylation was associated with any of the studied clinical variables, other than sex. With this analysis workflow, the sex-associated differentially methylated regions were highly reproducible across studies, technologies, and statistical models. ConclusionsThe inflation of P values was caused by a common method for spatial adjustment and DMR detection, implemented in tools comb-p and RADMeth. With standard significance thresholds, type 1 error rates were high with both these implementations, across alternative parameter settings and analysis strategies. We conclude that comb-p and RADMeth are convenient methods for the detection of differentially methylated regions, but the statistical significance should either be determined empirically or before the spatial adjustment. Our RRBS data analysis workflow is available in https://github.com/EssiLaajala/RRBS_workflow.

bioinformatics↗

Mapping Interactome Networks of FOSL1 and FOSL2 in Human Th17 Cells

Dysregulated function of Th17 cells has implications in immunodeficiencies and autoimmune disorders. Th17 cell-differentiation is orchestrated by a complex network of transcription factors, including several members of the activator protein (AP-1) family. Among these, FOSL1 and FOSL2 influence the effector responses of Th17 cells. However, the molecular mechanisms underlying these functions are unclear, owing to the poorly characterized protein interaction networks of these factors. Here, we establish the first interactomes of FOSL1 and FOSL2 in human Th17 cells, using affinity purification-mass spectrometry analysis. In addition to the known JUN proteins, we identified several novel binding partners of FOSL1 and FOSL2. Gene ontology analysis found a major fraction of these interactors to be associated with RNA binding activity, which suggests new mechanistic links. Intriguingly, 29 proteins were found to share interactions with FOSL1 and FOSL2, and these included key regulators of Th17-fate. We further validated the binding partners identified in this study by using parallel reaction monitoring targeted mass-spectrometry and other methods. Our study provides key insights into the interaction-based signaling mechanisms of FOSL factors that potentially govern Th17 cell-differentiation and associated pathologies.

immunology↗

The AP-1 factors FOSL1 and FOSL2 co-regulate human Th17 responses

Th17 cells protect mucosal barriers, but their aberrant activity can cause autoimmunity. Molecular networks dictating human Th17 function are largely unexplored, and this hinders disease-studies. Here, we investigated the roles of the AP-1 factors, FOSL1 and FOSL2, in inducing human Th17 responses. Transient knockdown and over-expression strategies found the two proteins to inhibit Th17-cell identity, while revealing a distinct cooperativity between their functions. Strikingly, FOSL1 plays different roles in human and mouse and FOSL-mediated Th17 regulation is opposed by the AP-1 factor, BATF. Genome-wide occupancy analysis demonstrated the co-localization of FOSL1, FOSL2 and BATF in the vicinity of key Th17 genes. The functional interplay among these factors is possibly governed by sharing interactions with a common set of lineage-associated proteins. We further discovered that the genomic binding sites of these factors harbour a large number of disease-linked SNPs, many of which alter the ability of a given factor to bind DNA. Our findings thus provide crucial insights into the transcriptional regulation of human Th17 function and associated pathologies. ONE SENTENCE SUMMARYFOSL1- and FOSL2-mediated transcription during early human Th17 differentiation

immunology↗

Quantitative analysis and genome-scale modeling of human CD4+ T-cell differentiation reveals subset-specific regulation of glycosphingolipid pathways

T-cells are sentinels of adaptive cell-mediated immune responses. T-cell activation, proliferation and differentiation involves metabolic reprogramming involving the interplay of genes, proteins and metabolites. Here, we aim to understand the metabolic pathways involved in the activation and functional differentiation of human CD4+ T-cell subsets (Th1, Th2, Th17 and iTregs). We combined genome-scale metabolic modeling, gene expression data, targeted and non-targeted lipidomics experiments, together with in vitro gene knockdown experiments and showed that human CD4+ T-cells undergo specific metabolic changes during activation and functional differentiation. In addition, we identified and confirmed the importance of ceramide and glycosphingolipid synthesis pathways in Th17 differentiation and effector functions. Finally, through in vitro gene knockdown experiments, we substantiated the requirement of serine palmitoyl transferase (SPT), a de novo sphingolipid pathway in the expression of proinflammatory cytokine (IL17A and IL17F) by Th17 cells. Our findings may provide a comprehensive resource for identifying CD4+ T-cell-specific targets for their selective manipulation under disease conditions, particularly, diseases characterized by an imbalance of Treg / Th17 cells. Our data also suggest a role for elevated levels of ceramides in conditions comorbid with these diseases, e.g., obesity and insulin resistance.

immunology↗