Biology subjects

Fresno, C.

Publications and source records attributed to Fresno, C..

3 recordsLinked to original sources

bioRxiv2025

MICOMWeb: a website for microbial community metabolic modeling of the human gut

SummaryMICOMWeb is a user-friendly website for easy microbial community metabolic modeling of the human gut. This website tackles three constraints when generating in silico metagenome-scale metabolic models: (i) the prior Python user knowledge for metabolic modeling using flux balance analysis with MICOM Python package, (ii) predefined and user-defined diets to generate ad hoc metabolic models, and (iii) the high- throughput computational infrastructure required to obtain the simulated growth and metabolic exchange fluxes, using real abundance from metagenomic shotgun or 16S amplicon sequencing; we present MICOMWebs features to easily run in silico experiments as a functional hypothesis generator for experimental validation on previously published data. Availability and ImplementationMICOMWeb is freely accessible for academic purposes at https://micomweb.c3.unam.mx.

systems biology↗

bioRxiv2019

Higher-order chromatin organization defines PR and PAX2 binding to regulate endometrial cancer cell gene expression

Estrogen (E2) and Progesterone (Pg), via their specific receptors (ER and PR respectively), are major determinants in the development and progression of endometrial malignancies. Here, we have studied how E2 and the synthetic progestin R5020 affect genomic functions in Ishikawa endometrial cancer cells. Using ChIPseq in cells exposed to the corresponding hormones, we identified cell specific binding sites for ER (ERbs) and PR (PRbs), which mostly correspond to independent sites but both adjacent to sites bound by PAX2. Analysis of long-range interactions by Hi-C showed enrichment of regions co-bound by PR and PAX2 inside TADs that contain differentially progestin-regulated genes. These regions, which we call "progestin control regions" (PgCRs), exhibit an open chromatin state prior to the exposure to the hormone. Our observations suggest that endometrial response to progestins in differentiated endometrial tumor cells results in part from binding of PR together with partner transcription factors to PgCRs, compartmentalizing hormone-independent open chromatin.

genomics↗

bioRxiv2018

Loss of Trans Regulation in Breast Cancer Molecular Subtypes

Breast carcinomas are characterized by anomalous gene regulatory programs. As is well known, gene expression programs are able to shape phenotypes. Hence, the understanding of gene co-expression may shed light on the underlying mechanisms behind the transcriptional regulatory programs affecting tumor development and evolution. For instance, in breast cancer, there is a clear loss of inter-chromosomal (trans-) co-expression, compared with healthy tissue. At the same time cis- (intra-chromosomal) interactions are favored in breast tumors. In order to have a deeper understanding of regulatory phenomena in cancer, here, we constructed Gene Co-expression Networks by using 848 RNA-seq whole-genome samples corresponding to the four breast cancer molecular subtypes, as well as healthy tissue. We quantify the cis-/trans- co-expression imbalance in all phenotypes. Additionally, we measured the association between co-expression and physical distance between genes, and characterized the proportion of intra/inter-cytoband interactions per phenotype. We confirmed loss of trans- co-expression in all molecular subtypes. We also observed that gene cisco-expression decays abruptly with distance in all tumors in contrast with healthy tissue. We observed co-expressed gene hotspots, that tend to be connected at cytoband regions, and coincide accurately with already known copy number altered regions, such as Chr17q12, or Chr8q24.3 for all subtypes. Our methodology recovered different alterations already reported for specific breast cancer subtypes, showing how co-expression network approaches might help to capture distinct events that modify the cell regulatory program.

systems biology↗