Biology subjects

Garcia-Sotelo, J. S.

Publications and source records attributed to Garcia-Sotelo, J. S..

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

A Golden Standard for Transcription Factor-Gene Regulatory Interactions in Escherichia coli K-12: How reliable are they based on the methods supporting them?

Post-genomic implementations have expanded the experimental strategies to identify elements involved in the regulation of transcription initiation. As new methodologies emerge, a natural step is to compare their results with those from established methodologies, such as the classic methods of molecular biology used to characterize transcription factor binding sites, promoters, or transcription units. In the case of Escherichia coli K-12, the best-studied microorganism, for the last 30 years we have continuously gathered such knowledge from original scientific publications, and have organized it in two databases, RegulonDB and EcoCyc. Furthermore, since RegulonDB version 11.0 (1), we offer comprehensive datasets of binding sites from chromatin immunoprecipitation combined with sequencing (ChIP-seq), ChIP combined with exonuclease digestion and next-generation sequencing (ChIP-exo), genomic SELEX screening (gSELEX), and DNA affinity purification sequencing (DAP-seq) HT technologies, as well as additional datasets for transcription start sites, transcription units and RNA sequencing (RNA-seq) expression profiles. Here, we present for the first time an analysis of the sources of knowledge supporting the collection of transcriptional regulatory interactions (RIs) of E. coli K-12. An RI is formed by the transcription factor, its positive or negative effect on a promoter, a gene or transcription unit. We improved the evidence codes so that the specific methods are described, and we classified them into seven independent groups. This is the basis for our updated computation of confidence levels, weak, strong, or confirmed, for the collection of RIs. We compare the confidence levels of the RI collection before and after adding HT evidence illustrating how knowledge will change as more HT data and methods appear in the future. Users can generate subsets filtering out the method they want to benchmark and avoid circularity, or keep for instance only the confirmed interactions. The comparison of different HT methods with the available datasets indicate that ChIP-seq recovers the highest fraction (>70%) of binding sites present in RegulonDB followed by gSELEX, DAP-seq and ChIP-exo. There is no other genomic database that offers this comprehensive high-quality anatomy of evidence supporting a corpus of transcriptional regulatory interactions.

genomics↗

bioRxiv2019

PulmonDB: a curated lung disease gene expression database

Chronic Obstructive Pulmonary Disease (COPD) and Idiopathic Pulmonary Fibrosis (IPF) have contrasting clinical and pathological characteristics, and interesting whole-genome transcriptomic profiles. However, data from public repositories are difficult to reprocess and reanalyze. Here we present PulmonDB, a web-based database (http://pulmondb.liigh.unam.mx/) and R library that facilitates exploration of gene expression profiles for these diseases by integrating transcriptomic data and curated annotation from different sources. We demonstrated the value of this resource by presenting the expression of already well-known genes of COPD and IPF across multiple experiments and the results of two differential expression analyses in which we successfully identified differences and similarities. With this first version of PulmonDB, we create a new hypothesis and compare the two diseases from a transcriptomics perspective.

bioinformatics↗

bioRxiv2018

VCF/Plotein: A web application to facilitate the clinical interpretation of genetic and genomic variants from exome sequencing projects

PurposeTo create a user-friendly web application that allows researchers, medical professionals and patients to easily and securely view, filter and interact with human exome sequencing data in the Variant Call Format (VCF).\n\nMethodsWe have created VCF/Plotein, a web application written entirely in JavaScript using the Vue.js framework, available at http://vcfplotein.liigh.unam.mx. After a VCF is loaded, gene and variant information is extracted from Ensembl, and cross-referencing with external databases is performed via the Elasticsearch search engine. Support for application-based gene and variant filtering has also been implemented. Interactive graphs are created using the D3.js library. All data processing is done locally in the users CPU to ensure the security of patient data.\n\nResultsVCF/Plotein allows users to interactively view and filter VCF files without needing any bioinformatics knowledge. A number of features make it especially suited for the medical community, such as its speed, security, the ability to filter by disease or gene function, and the ease with which information may be shared with collaborators/co-workers.\n\nConclusionVCF/Plotein is a novel web application that allows users to easily and interactively filter and display exome sequencing information, and that is especially suited for bench researchers, medical professionals and patients.

bioinformatics↗