Similar Datasets
Project description:The aim of this study was to investigate the transciptional mechanisms governed by FOSL1, FOSL2 and BATF for regulation of human Th17 cell-function. FOSL factors were transiently perturbed using RNAi (KD) and over-expression (OE) strategies, whereas BATF was perturbed using RNAi only. RNA-seq was then performed to determine their global transciptional targets.
2022-04-12 | GSE174809 | GEO
Project description:The aim of this study was to investigate the transciptional mechanisms governed by FOSL1, FOSL2 and BATF for regulation of human Th17 cell-function. To determine the genome-wide binding sites of these factors, ChIP-seq analysis was performed using in vitro derived Th17 cells at 72h of polarization.
2022-04-12 | GSE174810 | GEO
Project description:Th17 cells are essential for protection against extracellular pathogens, but their aberrant activity can cause autoimmunity. Molecular mechanisms that dictate Th17 cell-differentiation have been extensively studied using mouse models. However, species-specific differences underscore the need to validate these findings in human. Here, we characterized the human-specific roles of three AP-1 transcription factors, FOSL1, FOSL2 and BATF, during early stages of Th17 differentiation. Our results demonstrate that FOSL1 and FOSL2 co-repress Th17 fate-specification, whereas BATF promotes the Th17 lineage. Strikingly, FOSL1 was found to play different roles in human and mouse. Genome-wide binding analysis indicated that FOSL1, FOSL2 and BATF share occupancy over regulatory regions of genes involved in Th17 lineage commitment. These AP-1 factors also share their protein interacting partners, which suggests mechanisms for their functional interplay. Our study further reveals that the genomic binding sites of FOSL1, FOSL2 and BATF harbour hundreds of autoimmune disease-linked SNPs. We show that many of these SNPs alter the ability of these transcription factors to bind DNA. Our findings thus provide critical insights into AP-1-mediated regulation of human Th17-fate and associated pathologies.
| S-EPMC9122603 | biostudies-literature
Project description:Global gene-regulatory targets and Genome-wide binding sites of FOSL1, FOSL2 and BATF in human Th17 cells
| PRJNA734773 | ENA
Project description: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 the latter, FOSL1 and FOSL2 modulate the effector functions of Th17 cells. However, the molecular mechanisms underlying these effects are unclear, owing to the poorly characterized protein interaction networks of FOSL 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 significant 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 proteins that potentially govern Th17 cell differentiation and associated pathologies.
| S-EPMC8482465 | biostudies-literature
Project description:Global gene-regulatory targets of FOSL1, FOSL2 and BATF in human Th17 cells [RNA-seq]
| PRJNA731665 | ENA
Project description:Genome-wide binding sites of FOSL1, FOSL2 and BATF in human Th17 cells [ChIP-seq]
| PRJNA731664 | ENA
Project description:The differentiation of Th17 cells is controlled by a complex network of transcription factors (TFs), including FOS and JUN proteins of the AP-1 family. The FOS-like proteins, FOSL1 and FOSL2 have recently been reported to control Th17 responses. The molecular mechanisms dictating their roles, however, are unclear. Moreover, although the functions of AP-1 TFs are largely governed by their protein-protein interactions, these are also poorly characterized in this milieu. Using affinity purification in combination with mass-spectrometry we established the first interactomes of FOSL1 and FOSL2 in human Th17 cells. In addition to their known interactions with JUN proteins, our analysis identified several novel binding partners of FOSL factors. Gene ontology analysis revealed RNA binding was enriched as the major functionality for FOSL1 and FOSL2 associated proteins, thereby suggesting possible mechanistic links that have not been studied before. Intriguingly, 29 interactors were found to be shared between FOSL1 and FOSL2, which included crucial regulators of Th17-fate. These findings, including unique and shared interactions, were validated using parallel reaction monitoring targeted mass-spectrometry (PRM-MS), with additional measurements with other laboratory methods. Overall, this study provides key insights into interaction-based signalling mechanisms of FOSL1 and FOSL2, which potentially control Th17 cell-development and associated pathologies.
2021-11-02 | PXD025729 | Pride
Project description:Although cis-regulatory binding sites (CRBSs) are at least as important as the coding sequences in a genome, our general understanding of them in most sequenced genomes is very limited due to the lack of efficient and accurate experimental and computational methods for their characterization, which has largely hindered our understanding of many important biological processes. In this article, we describe a novel algorithm for genome-wide de novo prediction of CRBSs with high accuracy. We designed our algorithm to circumvent three identified difficulties for CRBS prediction using comparative genomics principles based on a new method for the selection of reference genomes, a new metric for measuring the similarity of CRBSs, and a new graph clustering procedure. When operon structures are correctly predicted, our algorithm can predict 81% of known individual binding sites belonging to 94% of known cis-regulatory motifs in the Escherichia coli K12 genome, while achieving high prediction specificity. Our algorithm has also achieved similar prediction accuracy in the Bacillus subtilis genome, suggesting that it is very robust, and thus can be applied to any other sequenced prokaryotic genome. When compared with the prior state-of-the-art algorithms, our algorithm outperforms them in both prediction sensitivity and specificity.
| S-EPMC2691844 | biostudies-other
Project description:The transcription regulatory system of Mycobacterium tuberculosis (M. tb) remains incompletely understood. In this study, we have applied the eGLECLUBS algorithm to a group of related prokaryotic genomes for de novo genome-wide prediction of cis-regulatory binding sites (CRBSs) in M. tb H37Rv. The top 250 clusters from our prediction recovered 83.3% (50/60) of all known CRBSs in extracted inter-operonic sequences of this strain. We further demonstrated that the integration of our prediction results with the ChIP-Seq datasets is very effective in identifying true binding sites of TFs. Using electrophoretic mobility shift assays and real-time RT-PCR, we experimentally verified our prediction of CRBSs for Rv0081, an important transcription factor thought to be involved in regulation of M. tb under hypoxia.
| S-EPMC4757040 | biostudies-literature