Biology subjects

Alcoforado Diniz, J.

Publications and source records attributed to Alcoforado Diniz, J..

4 recordsLinked to original sources

bioRxiv2026

The Genetic Discovery (GeDi) resource: Deep characterization of a multi-ancestry panel of human reference iPSCs for functional genomic studies

Human induced pluripotent stem cells (iPSCs) are essential tools for disease modelling, drug discovery, and functional genomics, yet the field remains anchored to a small number of reference lines, limiting our understanding of how genetic background shapes cellular phenotypes across human populations. Here we describe the Genetic Discovery iPSC panel (GeDi), eight clonal iPSC lines reprogrammed from male and female donors that broadly span global human population diversity. Ancestry analysis confirmed that each line's genetic profile is concordant with donor self-reported ancestry. All GeDi lines are pluripotent and passed comprehensive quality control, demonstrating Sendai virus clearance, intact p53 pathway integrity, reproducible proliferative capacity, and compatibility with standardized genome editing workflows. Transcriptome profiling across five differentiated lineages covered 80% of annotated protein-coding genes and revealed stable donor-intrinsic variability in gene expression within each lineage. Haplotype-resolved genome assemblies were used to catalog structural variants and regions of absence of heterozygosity invisible to short-read sequencing. Whole-genome methylation analysis confirmed successful epigenetic reprogramming, catalogued the status of imprinted loci and captured the early dynamics of erosion of X chromosome inactivation (XCI) in female lines. The GeDi panel is available from The Jackson Laboratory as a quality-controlled resource designed to support functional genomic studies across varied genetic backgrounds.

cell biology↗

bioRxiv2026

Distinct senescent β-cell senotypes differentially drive islet aging and dysfunction

Biological aging greatly impacts the bodys ability to handle glucose, and represents a major risk factor the development and progression of type 2 diabetes (T2D). Nonetheless, despite advances in cellular senescence research and the development of new senolytic therapies, the heterogeneity of cellular senescence in the human endocrine pancreas, as well as its roles in normal aging, remains to be elucidated at the single-cell level. Here, we performed single-cell-resolved spatial proteomics and transcriptomics on intact pancreas from 26 donors (ages 20-80) and multiplexed single-cell RNA sequencing and functional assays on dispersed islets from 14 donors (ages 34-69). We identify two discrete SnC subpopulations distinguished by relative expression of CDKN1A and CDKN2A. CDKN1A senescent cells (SnCs) exhibit loss of {beta}-cell identity, impaired insulin secretion, and a proinflammatory SASP associated with increased islet immune infiltration. In contrast, CDKN2A SnCs retain transcriptional identity and functional competence, with lower inflammatory signaling. Together, these findings identify heterogeneous and functionally divergent senotypes in the human pancreas, distinguishing an adaptive (CDKN2A) from a maladaptive (CDKN1A) senescence program, thus providing a mechanism-guided framework for senescence-targeted therapies in T2D.

cell biology↗

bioRxiv2026

DIANNE: Segmentation-Free Localization of Histology Differential Attributes

Pathologist-guided distinctions within histology and spatial omic images provide insights into health and disease, with digital pathology leveraging artificial intelligence to automate such assessments. To train computational models, current digital pathology methods rely on upfront manual annotations, which are time-consuming to generate. Pre-annotation is poorly suited to investigating novel spatial behaviors--a major need driven by advances in spatial profiling--for which annotation criteria and data needs will be uncertain. To address these challenges, we present DIANNE, a digital pathology annotation support and discovery approach for rapid training and inference of spatial differential attributes, enabled by train-time Positive Class Mixup Augmentation. DIANNE can compute foundation model-derived segmentation-free localization of differential classifiers across whole slide H&E images within seconds on a workstation, enabling interactive investigation of spatial niches. Predictive models can be re-trained in real-time in response to patch or regional annotation changes, clarifying determinative biological attributes across slides from only a few dozen annotated patches. We demonstrate the effectiveness of DIANNE for tumor detection, artifact identification, and exploration of pancreatic, fetal membranes and kidney tissue structures. DIANNE also provides analogous capabilities for IHC, multiplex immunofluorescence, and registered spatial transcriptomic+H&E images. DIANNE is implemented in a Jupyter toolkit, enabling rapid development of high-resolution classifiers from weakly-supervised training. DIANNE provides a practical system to quantitatively understand known and novel spatial phenotypes.

pathology↗

bioRxiv2021

Functional study of Leishmania braziliensis protein arginine methyltransferases (PRMTs) reveals that PRMT1 and PRMT5 are required for macrophage infection

In trypanosomatids, regulation of gene expression occurs mainly at the posttranscriptional level, and RNA-binding proteins (RBPs) are key players in determining the fates of transcripts. RBPs are major targets of protein arginine methyltransferases (PRMTs), which posttranslationally regulate the RNA-binding capacity and other macromolecular interactions of RBPs by transferring methyl groups to protein arginine residues. Herein, we present the results of a study that functionally characterized the five predicted PRMTs in Leishmania braziliensis by gene knockout and endogenous protein HA tagging using CRISPR/Cas9 gene editing. We report that arginine methylation profiles vary among Leishmania species and that target protein methylation changes across different L. braziliensis life cycle stages, with higher PRMT expression in the promastigote stages than in the axenic amastigote stage. Knockout of some of the L. braziliensis PRMTs led to significant changes in global arginine methylation patterns without affecting promastigote axenic growth. Deletion of either PRMT1 or PRMT3 disrupted most type I PRMT activity, resulting in a global increase in monomethyl arginine (MMA) levels, which is mainly catalyzed by PRMT7. Putative targets and/or PRMT-interacting proteins were identified by coimmunoprecipitation using HA-tagged PRMTs, revealing a network of target RBPs and suggesting functional interactions between them and a relevant participation in epigenetic control of gene expression. Finally, we demonstrate that L. braziliensis PRMT1 and PRMT5 are required for efficient macrophage infection in vitro, and that in the absence of PRMT1 and PRMT5, axenic amastigote proliferation is impaired. The results indicate that arginine methylation is modulated across life cycle stages in L. braziliensis and show possible functional overlap and cooperation among the different PRMTs in targeting proteins. Overall, our data suggest important regulatory roles of these proteins throughout the L. braziliensis life cycle, showing that arginine methylation is important for parasite-host cell interactions.

molecular biology↗