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Lahesmaa, R.

Publications and source records attributed to Lahesmaa, R..

10 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↗

Satb1 integrates cohesin mediated genome organization and transcriptional regulation during T cell development

Three-dimensional (3D) genome folding, which is highly cell type-specific, plays a crucial role in orchestrating spatiotemporal gene expression. Although factors such as CTCF have been extensively studied in the hierarchical regulation of 3D chromatin organization, the mechanisms driving dynamic genome folding during T cell fate transitions remain incompletely defined. In this study, we reveal that Satb1, a chromatin organizer enriched in the T cell lineage, co-occupies genomic regions with the cohesin complex and Ctcf in double-positive (DP) thymocytes, where chromatin interactions are notably increased. We show that Satb1 physically interacts with the cohesin subunit Smc1a, and its deletion results in aberrant Smc1a binding and reduced chromatin contacts at sites co-occupied by Satb1 and cohesin. In both DP and immature CD4 single-positive (SP) T cells, Satb1 is essential for proper T cell activation and cytokine signaling. At the Cd3 locus, Satb1 and cohesin collaboratively regulate gene expression, with Satb1 loss leading to disrupted Smc1a occupancy and compromised chromatin interactions. Furthermore, Satb1 shows in vitro properties consistent with liquid-liquid phase separation, and disease-associated mutations impair these properties. Together, our findings uncover a molecular mechanism in which Satb1 facilitates chromatin looping through direct interaction with the cohesin complex and its ability to form nuclear condensates, thereby governing transcriptional regulation during T cell development.

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↗

Protein Interactome of the Cancerous Inhibitor of Protein Phosphatase 2A (CIP2A) in Th17 Cells

Cancerous inhibitor of protein phosphatase 2A (CIP2A) is involved in immune response, cancer progression, and in Alzheimers disease. However, an understanding of the mechanistic basis of its function in this wide spectrum of physiological and pathological processes is limited due to its poorly characterized interaction networks. Here we present the first systematic characterization of the CIP2A interactome by affinity-purification mass spectrometry combined with validation by selected reaction monitoring targeted mass spectrometry (SRM-MS) analysis in Th17 cells. In addition to the known regulatory subunit of protein phosphatase PP2A, the catalytic subunit of protein PP2A was found to be interacting with CIP2A. Furthermore, the regulatory (PPP1R18, and PPP1R12A) and catalytic (PPP1CA) subunits of phosphatase PP1 were identified among the top novel CIP2A interactors. Evaluation of the ontologies associated with the proteins in this interactome revealed that they were linked with RNA metabolic processing and splicing, protein traffic, cytoskeleton regulation and ubiquitin-mediated protein degradation processes. Taken together, this network of protein-protein interactions will be important for understanding and further exploring the biological processes and mechanisms regulated by CIP2A both in physiological and pathological conditions.\n\nHighlights{blacksquare} The first characterisation of the CIP2A interactome in Th17 cells.\n{blacksquare}Key interactions were validated by targeted SRM-MS proteomics, western blot and confocal microscopy.\n{blacksquare}Pathway analysis of the interactome revealed interrelationships with proteins across a broad range of processes, in particular associated with mRNA processing.

systems biology↗

LonGP: an additive Gaussian process regression model for longitudinal study designs

MotivationBiomedical research typically involves longitudinal study designs where samples from individuals are measured repeatedly over time and the goal is to identify risk factors (covariates) that are associated with an outcome value. General linear mixed effect models have become the standard workhorse for statistical analysis of data from longitudinal study designs. However, analysis of longitudinal data can be complicated for both practical and theoretical reasons, including difficulties in modelling, correlated outcome values, functional (time-varying) covariates, nonlinear effects, and model inference.\n\nResultsWe present LonGP, an additive Gaussian process regression model for analysis of experimental data from longitudinal study designs. LonGP implements a flexible, non-parametric modelling framework that solves commonly faced challenges in longitudinal data analysis. In addition to inheriting all standard features of Gaussian processes, LonGP can model time-varying random effects and non-stationary signals, incorporate multiple kernel learning, and provide interpretable results for the effects of individual covariates and their interactions. We develop an accurate Bayesian inference and model selection method, and implement an efficient model search algorithm for our additive Gaussian process model. We demonstrate LonGPs performance and accuracy by analysing various simulated and real longitudinal -omics datasets. Our work is accompanied by a versatile software implementation.\n\nAvailabilityLonGP software tool is available at http://research.cs.aalto.fi/csb/software/longp/.\n\nContactlu.cheng.ac@gmail.com, harri.lahdesmaki@aalto.fi

bioinformatics↗

An unbiased reconstruction of the T helper cell type 2 differentiation network

T helper type 2 (Th2) cells are important regulators of our adaptive immune response, particularly the response against parasites, and have relevance for auto-immunity as well as tumour progression. This classic T helper type has been studied intensively, but not systematically. Using newly developed, genome-wide retroviral CRISPR knock-out (KO) technology, combined with RNA-seq, ATAC-seq and ChIP-seq, we have dissected the regulatory circuitry governing differentiation in these cells. During Th2 activation/differentiation approximately 4000 genes are perturbed, with at least 200 genes specifically associated with the Th2 program in mouse and human. We confirm previously known Th2 driver genes and have discovered several novel genes, including transcription factors, metabolic genes and potential receptors/cytokines, critical for Th2 function. Our study provides an atlas for, but not limited to, the Th2 regulatory network, pinpointing the key players of Th2 differentiation.

immunology↗