Biology subjects

Torre, D.

Publications and source records attributed to Torre, D..

8 recordsLinked to original sources

bioRxiv2026

Integrated metabolic and proteostatic profiling reveals remodeling of proteolytic pathways associated with redox-bioenergetic dysfunction in a PAHenu2 mouse model of phenylketonuria

Phenylketonuria (PKU) is a genetic metabolic disorder caused by the lack of functional phenylalanine hydroxylase (PAH). Elevated levels of phenylalanine (Phe) are known to be neurotoxic; however, the molecular mechanisms underlying Phes effects remain elusive. This study investigates the impact of PKU on proteostasis, redox balance, and metabolism in BTBR PAHenu2 mice, a severe disease animal model. Combined proteomics and metabolomics revealed impaired redox homeostasis in the brain and disrupted mitochondrial energy metabolism (ATP and TCA intermediates). The dysregulation was further supported by decreased levels of ATP, reduced glutathione (GSH), cysteine, and reduced catalase activity. Western blot analyses revealed substantial remodeling of protein degradation systems: the 19S regulatory (Rpt1) subunit and 26S proteasome content and activity were significantly increased, and ubiquitinated protein levels were elevated, indicating protein turnover and activation of the ubiquitin-proteasome system. Autophagy was also activated, as evidenced by a reduced LC3-II/LC3-I ratio, decreased p62 levels, unchanged ATG5 levels, and increased HSPA8 protein expression. By contrast, UPR markers remained stable despite an increase in the oxidized-to-reduced PDI ratio, suggesting a localized shift without activation of a full ER stress response. In parallel, systemic alterations were assessed in whole blood. Indeed, GSH, cysteine, ATP and ADP were decreased in PKU, whereas NADPH increased. These changes were accompanied by reduced activities of GSH reductase and GSH peroxidase, thereby confirming metabolic and redox disruption. Collectively, these findings indicate that PKU is associated with activation of protein degradation pathways as an adaptive response to cellular stress combined with redox imbalance and energy dysregulation. Highlights- Proteasome complex levels and activity were upregulated in PAHenu2 mouse brains - Autophagy was also enhanced in PAHenu2 mouse brains - Despite increased PDI oxidation, the Unfolded Protein Response was not activated - Redox and energy metabolism were disrupted in both brain and blood

molecular biology↗

bioRxiv2026

A Genetically Engineered Human Organoid Model Reveals Distinct Genetic and Epigenetic Barriers of Lineage Plasticity in Early PDAC Transformation

The lack of accurate, human-based models recapitulating early-stage pancreatic ductal adenocarcinoma (PDAC) has hindered therapeutic development. Using pluripotent stem cell-derived pancreatic progenitor organoids, we established a human PDAC model that faithfully reproduces the genetic, epigenetic, and transcriptomic trajectory of tumor initiation and progression in vitro, validated against clinical datasets and histopathology. We demonstrate that CDKN2A loss, nearly universal in patients but dispensable in mouse models, is essential for neoplastic transformation when combined with KRAS and TP53 mutations, while SMAD4 loss promotes tumor progression. Multi-omics profiling reveals epigenetic repression of pancreatic lineage program during PDAC initiation, alongside oncogenic AP-1-driven chromatin remodeling. Notably, we identify TET1 suppression as a mechanistic link between oncogenic ERK signaling and the hypermethylation and silencing of essential pancreatic transcription factors. This model captures the genetic and epigenetic determinants of human PDAC, reveals antagonism between oncogenic and lineage restriction programs, and supports TET-based lineage restoration as a promising early intervention strategy for high-risk individuals.

cancer biology↗

bioRxiv2021

A LINCS microenvironment perturbation resource for integrative assessment of ligand-mediated molecular and phenotypic responses

The phenotype of a cell and its underlying molecular state is strongly influenced by extracellular signals, including growth factors, hormones, and extracellular matrix. While these signals are normally tightly controlled, their dysregulation leads to phenotypic and molecular states associated with diverse diseases. To develop a detailed understanding of the linkage between molecular and phenotypic changes, we generated a comprehensive dataset that catalogs the transcriptional, proteomic, epigenomic and phenotypic responses of MCF10A mammary epithelial cells after exposure to the ligands EGF, HGF, OSM, IFNG, TGFB and BMP2. Systematic assessment of the molecular and cellular phenotypes induced by these ligands comprise the LINCS Microenvironment (ME) perturbation dataset, which has been curated and made publicly available for community-wide analysis and development of novel computational methods (synapse.org/LINCS_MCF10A). In illustrative analyses, we demonstrate how this dataset can be used to discover functionally related molecular features linked to specific cellular phenotypes.

systems biology↗

bioRxiv2021

PPARdelta signaling activation improves metabolic and contractile maturation of human pluripotent stem cell-derived cardiomyocytes.

Pluripotent stem cell-derived cardiomyocytes (PSC-CMs) provide an unprecedented opportunity to study human heart development and disease. A major caveat however is that they remain functionally and structurally immature in culture, limiting their potential for disease modeling and regenerative approaches. Here, we address the question of how different metabolic pathways can be modulated in order to induce efficient hPSC-CM maturation. We show that PPAR signaling acts in an isoform-specific manner to balance glycolysis and fatty acid oxidation (FAO). PPARD activation or inhibition results in efficient respective up- or down-regulation of the gene regulatory networks underlying FAO in hPSC-CMs. PPARD induction further increases mitochondrial and peroxisome content, enhances mitochondrial cristae formation and augments FAO flux. Lastly PPARD activation results in enhanced myofibril organization and improved contractility. Transient lactate exposure, commonly used in hPSC-CM purification protocols, induces an independent program of cardiac maturation, but when combined with PPARD activation equally results in a metabolic switch to FAO. In summary, we identify multiple axes of metabolic modifications of hPSC-CMs and a role for PPARD signaling in inducing the metabolic switch to FAO in hPSC-CMs. Our findings provide new and easily implemented opportunities to generate mature hPSC-CMs for disease modeling and regenerative therapy.

cell biology↗

bioRxiv2019

PKMYT1 is a computationally predicted target for kidney cancer

Protein Kinase Membrane Associated Tyrosine/Threonine 1 (PKMYT1) is an understudied member of the serine/threonine protein kinase family. PKMYT1 is listed as a dark kinase according to the Illuminating the Druggable Genome (IDG) target development level classification. Using a combination of bioinformatics tools that we developed, we predict that targeting PKMYT1 is potentially beneficial for treating kidney cancer.

bioinformatics↗

bioRxiv2019

FAIRshake: toolkit to evaluate the findability, accessibility, interoperability, and reusability of research digital resources

As more datasets, tools, workflows, APIs, and other digital resources are produced by the research community, it is becoming increasingly difficult to harmonize and organize these efforts for maximal synergistic integrated utilization. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have prompted many stakeholders to consider strategies for tackling this challenge by making these digital resources follow common standards and best practices so that they can become more integrated and organized. Faced with the question of how to make digital resources more FAIR, it has become imperative to measure what it means to be FAIR. The diversity of resources, communities, and stakeholders have different goals and use cases and this makes assessment of FAIRness particularly challenging. To begin resolving this challenge, the FAIRshake toolkit was developed to enable the establishment of community-driven FAIR metrics and rubrics paired with manual, semi- and fully-automated FAIR assessment capabilities. The FAIRshake toolkit contains a database that lists registered digital resources, with their associated metrics, rubrics, and assessments. The FAIRshake toolkit also has a browser extension and a bookmarklet that enables viewing and submitting assessments from any website. The FAIR assessment results are visualized as an insignia that can be viewed on the FAIRshake website, or embedded within hosting websites. Using FAIRshake, a variety of bioinformatics tools, datasets listed on dbGaP, APIs registered in SmartAPI, workflows in Dockstore, and other biomedical digital resources were manually and automatically assessed for FAIRness. In each case, the assessments revealed room for improvement, which prompted enhancements that significantly upgraded FAIRness scores of several digital resources.

bioinformatics↗

bioRxiv2018

BioJupies: Automated Generation of Interactive Notebooks for RNA-seq Data Analysis in the Cloud

Interactive notebooks can make bioinformatics data analyses more transparent, accessible and reusable. However, creating notebooks requires computer programming expertise. Here we introduce BioJupies, a web server that enables automated creation, storage, and deployment of Jupyter Notebooks containing RNA-seq data analyses. Through an intuitive interface, novice users can rapidly generate tailored reports to analyze and visualize their own raw sequencing files, their gene expression tables, or fetch data from >5,500 published studies containing >250,000 preprocessed RNA-seq samples. Generated notebooks have executable code of the entire pipeline, rich narrative text, interactive data visualizations, and differential expression and enrichment analyses. The notebooks are permanently stored in the cloud and made available online through a persistent URL. The notebooks are downloadable, customizable, and can run within a Docker container. By providing an intuitive user interface for notebook generation for RNA-seq data analysis, starting from the raw reads, all the way to a complete interactive and reproducible report, BioJupies is a useful resource for experimental and computational biologists. BioJupies is freely available as a web-based application from: http://biojupies.cloud and as a Chrome extension from the Chrome Web Store.

bioinformatics↗

bioRxiv2017

Massive Mining of Publicly Available RNA-seq Data from Human and Mouse

RNA-sequencing (RNA-seq) is currently the leading technology for genome-wide transcript quantification. While the volume of RNA-seq data is rapidly increasing, the currently publicly available RNA-seq data is provided mostly in raw form, with small portions processed non- uniformly. This is mainly because the computational demand, particularly for the alignment step, is a significant barrier for global and integrative retrospective analyses. To address this challenge, we developed all RNA-seq and ChIP-seq sample and signature search (ARCHS4), a web resource that makes the majority of previously published RNA-seq data from human and mouse freely available at the gene count level. Such uniformly processed data enables easy integration for downstream analyses. For developing the ARCHS4 resource, all available FASTQ files from RNA-seq experiments were retrieved from the Gene Expression Omnibus (GEO) and aligned using a cloud-based infrastructure. In total 137,792 samples are accessible through ARCHS4 with 72,363 mouse and 65,429 human samples. Through efficient use of cloud resources and dockerized deployment of the sequencing pipeline, the alignment cost per sample is reduced to less than one cent. ARCHS4 is updated automatically by adding newly published samples to the database as they become available. Additionally, the ARCHS4 web interface provides intuitive exploration of the processed data through querying tools, interactive visualization, and gene landing pages that provide average expression across cell lines and tissues, top co-expressed genes, and predicted biological functions and protein-protein interactions for each gene based on prior knowledge combined with co-expression. Benchmarking the quality of these predictions, co-expression correlation data created from ARCHS4 outperforms co-expression data created from other major gene expression data repositories such as GTEx and CCLE.\n\nARCHS4 is freely accessible at: http://amp.pharm.mssm.edu/archs4

bioinformatics↗