Biology subjects

Ramirez, R. N.

Publications and source records attributed to Ramirez, R. N..

4 recordsLinked to original sources

bioRxiv2023

Ladder-like multimerization of FoxP3 enables microsatellite recognition and DNA bridging

FoxP3 is a transcription factor (TF) essential for development of regulatory T cells (Tregs), a branch of T cells that suppress excessive inflammation and autoimmunity1-5. Molecular mechanisms of FoxP3, however, remain elusive. We here show that FoxP3 utilizes the Forkhead domain--a DNA binding domain (DBD) that is commonly thought to function as a monomer or dimer--to form a higher-order multimer upon binding to TnG repeat microsatellites. A cryo-electron microscopy structure of FoxP3 in complex with T3G repeats reveals a ladder-like architecture, where two double-stranded DNA molecules form the two "side rails" bridged by five pairs of FoxP3 molecules, with each pair forming a "rung". Each FoxP3 subunit occupies TGTTTGT within the repeats in the manner indistinguishable from that of FoxP3 bound to the Forkhead consensus motif (FKHM; TGTTTAC). Mutations in the "intra-rung" interface impair TnG repeat recognition, DNA bridging and cellular functions of FoxP3, all without affecting FKHM binding. FoxP3 can tolerate variable "inter-rung" spacings, explaining its broad specificity for TnG repeat-like sequences in vivo and in vitro. Both FoxP3 orthologs and paralogs show similar TnG repeat recognition and DNA bridging. These findings thus reveal a new mode of DNA recognition that involves TF homo-multimerization and DNA bridging, and further implicates microsatellites in transcriptional regulation and diseases.

biochemistry↗

bioRxiv2023

Uncovering the cis-regulatory program of early human B-cell commitment and its implications in the pathogenesis of B-cell acute lymphoblastic leukemia

Dysregulation of the early stages of B-cell lymphopoiesis, orchestrating the development of cellular immunity, may induce malignant transformations. Therefore, it is essential to characterize the gene regulatory network (GRN) driving B-cell lymphopoiesis in healthy individuals to uncover malignancy mechanisms. To this end, we generated a dataset that included paired human data for chromatin accessibility and gene expression in eight B-cell precursor stages, providing the first deep characterization of early B-cell lymphopoiesis, including the identification of regulatory elements and the reconstruction of the GRN. Using this data, we recapitulated well-known regulatory elements and revealed new regulons, such as ELK3, enriched in pro-B cells with a putative role in cell cycle progression. Moreover, a single-cell multi-omics analysis validated and enhanced the resolution of the regulatory landscape recovered by bulk data, revealing MYBL2 and ZNF367 as specific regulons of cycling cell states, and CEBPA associated with lymphoid multipotent progenitors (LMPPs). Importantly, this dataset enabled us to uncover B-cell acute lymphoblastic leukemia (B-ALL) triggers. We identified different cellular origins of malignant transformation depending on the B-ALL subtype, including the association of the ETV6-RUNX1 with pro-B cells and the increased expression of ELK3 in this ALL subtype. Overall, our dataset provides the most comprehensive atlas to date of early human B-cell regulation (B-rex; https://translationalbio.shinyapps.io/brex/), facilitating further understanding of B-cell differentiation in health and disease.

immunology↗

bioRxiv2021

FoxP3 associates with enhancer-promoter loopsto regulate Treg-specific gene expression

Gene expression programs are specified by higher-order chromatin structure and enhancer-promoter loops (EPL). T regulatory cells (Treg) identity is dominantly specified by the transcription factor FoxP3, whose mechanism of action is unclear. We applied proximity-ligation with chromatin immunoprecipitation (HiChIP) in Treg and closely related conventional CD4+ T cells (Tconv). EPL identified by H3K27Ac HiChIP showed a range of connection intensity, with some super-connected genes. TF-specific HiChIP showed that FoxP3 interacts with EPLs at a large number of genes, including some not differentially expressed in Treg vs Tconv, but enriched at the core Treg signature loci that it upregulates. FoxP3 association correlates with heightened H3H27Ac looping, as ascertained by analysis of FoxP3-deficient Treg-like cells. There was marked asymmetry in the loci where FoxP3 associated at the enhancer- or the promoter-side of EPLs, with enrichment for different transcriptional cofactors. FoxP3 EPL intensity distinguished gene clusters identified by single-cell ATAC-seq as co-varying between individual Tregs, supporting a direct transactivation model for FoxP3 in determining Treg identity. One Sentence SummaryFoxP3 is associated with enhancer-promoter loops in Treg cells, and correlates with heightened enhancer-promoter cross-talk

immunology↗

bioRxiv2019

STATegra: a comprehensive multi-omics dataset of B-cell differentiation in mouse

Multi-omics approaches use a diversity of high-throughput technologies to profile the different molecular layers of living cells. Ideally, the integration of this information should result in comprehensive systems models of cellular physiology and regulation. However, most multi-omics projects still include a limited number of molecular assays and there have been very few multi-omic studies that evaluate dynamic processes such as cellular growth, development and adaptation. Hence, we lack formal analysis methods and comprehensive multi-omics datasets that can be leveraged to develop true multi-layered models for dynamic cellular systems. Here we present the STATegra multi-omics dataset that combines measurements from up to 10 different omics technologies applied to the same biological system, namely the well-studied mouse pre-B-cell differentiation. STATegra includes high-throughput measurements of chromatin structure, gene expression, proteomics and metabolomics, and it is complemented with single-cell data. To our knowledge, the STATegra collection is the most diverse multi-omics dataset describing a dynamic biological system.

bioinformatics↗