Biology subjects

Medina-Rivera, A.

Publications and source records attributed to Medina-Rivera, A..

4 recordsLinked to original sources

bioRxiv2025

Gene expression profiling of dendritic cell tolerance dysfunction in women with Systemic lupus erythematosus

Dendritic cells (DCs) are central regulators of immune tolerance, and disturbances in their phenotype and function contribute to the breakdown of self-tolerance in systemic lupus erythematosus (SLE). Tolerogenic DCs (tolDCs), which suppress autoreactive responses and promote peripheral tolerance, are a promising therapeutic focus in autoimmune diseases. Here, we analyzed the transcriptional profiles of in vitro generated DCs derived from monocytes of individuals with SLE and healthy controls to identify disease-specific disruptions in tolerance associated pathways. Interferon stimulated genes (ISGs) emerged as dominant markers across all cellular contexts, with monocytes exhibiting the most substantial enrichment; key ISGs (IFI27, IFI44L, USP18, IFI6) acted as central hubs in regulatory networks, underscoring their diagnostic and pathogenic significance. In tolDCs from SLE donors, lipid metabolism pathways were selectively altered, suggesting impaired synthesis of pro-resolving lipid mediators. Additionally, diminished IL10RA expression and dysregulated IRF4 activity in SLE moDCs indicated intrinsic defects in IL-10 mediated tolerogenic differentiation. Together, these findings suggest that interferon driven transcriptional rewiring, impaired IL-10 signaling, and aberrant lipid metabolic programming converge to compromise DCs tolerogenic capacity in SLE. This highlights key mechanistic pathways that could be targeted to restore immune tolerance and reduce chronic inflammation.

immunology↗

bioRxiv2023

Logical model of human tolerogenic dendritic cells and their participation in autoimmune disease

Tolerogenic dendritic cells (tolDC) regulate the immune response, several clinical trials focused on autoimmune diseases use tolDC to promote immune tolerance response and Treg activation. Here we built a logical model for the tolerization cellular process of dendritic cells using IL10. By combining literature knowledge, microarray gene expression, and key tolDC markers, we ensembled a logical model that describes the obtention of tolDC using the IL10 signaling cascade that spawns the most tolerogenic phenotype. The model uses IL10 as input and the signaling cascade that trigger seven transcription factors (TFs), three previously known TFs in the IL10 response (STAT3, NFKB, STAT6), and four were incorporated based on our gene expression analysis (IRF8, TCF7L2, CEBPB, and TFCP2L1). Using our model, we generated mutants in-silico and identified that even when IL10 is present the single mutants for TCF7L2, IRF8, TFCP2L1, and STAT3 were not able to reach a tolDC stable state, highlighting the relevance of these TFs in the process. The current model sets a precedent that will help in the development of tolDC for future applications.

bioinformatics↗

bioRxiv2020

Logical modeling of dendritic cells in vitro differentiation from human monocytes unravels novel transcriptional regulatory interactions

Dendritic cells are the major specialized antigen-presenting cells, thereby connecting innate and adaptive immunity. Because of their role in establishing adaptive immunity, they have been used as targets for immunotherapy. Monocytes can differentiate into dendritic cells in vitro in the presence of colony-stimulating factor 2 (CSF2) and interleukin 4 (IL4), activating four signalling pathways (MAPK, JAK/STAT, NFKB, and PI3K). However, the transcriptional regulation responsible for dendritic cell differentiation from monocytes (moDCs) remains unknown. By curating scientific literature on moDCs differentiation, we established a preliminary logical model that helped us identify missing information for the activation of genes responsible for this differentiation, including missing targets for key transcription factors (TFs). Using ChIP-seq and RNA-seq data from the Blueprint consortium, we defined active and inactive promoters, together with differentially expressed genes in monocytes, moDCs, and macrophages (which correspond to an alternative cell fate). We then used this functional genomic information to predict novel targets for the identified TFs. We established a second logical model integrating this information, which enabled us to recapitulate the main established facts regarding moDCs differentiation. Prospectively, the resulting model should be useful to develop novel immunotherapies based on moDCs regulatory network.

immunology↗

bioRxiv2019

RSAT Var-tools: an accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding

Gene regulatory regions contain short and degenerated DNA sites recognized by transcription factors (TFs). When such regions harbor SNPs, the DNA motifs where TFs bind may be affected, thereby altering the transcriptional regulation of the target genes. Such regulatory SNPs have been implicated as causal variants in GWAS studies. In this study, we describe the application of the programs Var-tools designed to predict regulatory variants, and present four case studies to illustrate their usage and applications. In brief, Var-tools facilitate i) obtaining variation information, ii) interconversion of variation file formats, iii) retrieval of sequences surrounding variants, and iv) calculating the change on predicted TF affinity scores between alleles, using motif scanning approaches. Notably, the tools support the analysis of haplotypes. The tools are included within the well-maintained suite Regulatory Sequence Analysis Tools (RSAT, http://rsat.eu), and accessible through a web interface that currently enables analysis of five metazoa and ten plant genomes. Vart-tools can also be used in command-line with any locally-installed Ensembl genome. Users can input personal collections of variants and motifs, providing flexibility in the analysis.

bioinformatics↗