Biology subjects

Danese, A.

Publications and source records attributed to Danese, A..

8 recordsLinked to original sources

bioRxiv2026

Human cerebral assembloids as a model to study the interaction of glioblastoma with resident glial cells

Glioblastoma (GB) is a highly invasive brain cancer characterized by extensive peritumoral glial reactivity. Although GB infiltration and recurrence remain major therapeutic challenges, the contribution of GB-induced gliosis to tumor progression is poorly understood. To investigate glia-GB interactions, we developed human iPSC-derived cerebral forebrain assembloids containing innate microglia and macroglia and transplanted them with GB cells. The model recapitulates key tumor features observed in patients, including distinct tumor regions, reactive gliosis, and altered tissue stiffness. Single-cell RNA sequencing revealed an unexpected enrichment of extracellular vesicles (EVs) in peritumoral reactive glia, which we validated in patient samples. EV inhibition impaired formation of the peritumoral niche, whereas EVs from GB-containing assembloids induced glial reactivity in GB-free assembloids. Furthermore, the modularity of our system enables incorporation of additional niche components, such as monocytes, allowing investigation of the monocyte-glia-tumor axis and providing a powerful platform to dissect mechanisms regulating the GB microenvironment.

neuroscience↗

bioRxiv2026

Antagonizing niche signals regulate the emergence of postnatal neural stem cells and allow enlargement of their pool

Adult neural stem cells (aNSCs) of the lateral ventricular sub-ventricular zone (V-SVZ) are set aside during embryogenesis from a pool of slowly dividing neural stem/progenitor cells (NSPCs) residing in the lateral ganglionic eminence (LGE). The time of aNSCs specification coincides with the peak of embryonic neurogenesis, raising the question of which mechanisms allow only a subpopulation of NSPCs to retain stem cell identity while others proceed to divide and differentiate into neurons. To address this, we isolated rapidly and slowly dividing NSPCs from the mouse LGE at mid-neurogenesis, when aNSCs are specified, and profiled the transcriptome at the single cell level. We find that slowly dividing NSPCs constitute a heterogeneous population encompassing both radial glia cells (RGCs) and intermediate progenitors (IPs) and characterized by different gene signatures. Focusing on RGCs, we show that slowly and rapidly dividing RGCs differentially express genes involved in the formation - such as Lamb2 - or degradation - such as Mmp15 - of the extracellular matrix (ECM), pointing to opposite niche-remodelling strategies as a potential mechanism of fate determination. In vivo perturbation of Lamb2 and Mmp15 affects the seeding and maintenance of NSCs in an opposing manner, with knockdown of Mmp15 increasing the NSC pool as also shown by single-cell RNA-sequencing. These findings suggest that opposite ECM remodelling by slowly and rapidly dividing RGCs constitutes a novel cross-regulatory niche-level mechanism regulating aNSCs emergence, opening new avenues for regulating their numbers and thereby long-term maintenance of the brains regenerative potential.

developmental biology↗

bioRxiv2026

Cell free-mtDNA release drives pyroptosis and inflammation in cell models carrying the mitochondrial m.3243A>G pathogenic variant

Mitochondrial Encephalopathy, Lactic Acidosis, and Stroke-like episodes (MELAS) syndrome is primarily caused by the heteroplasmic m.3243A>G/MT-TL1 pathogenic variant. Patients exhibit elevated circulating cell-free mtDNA (cf-mtDNA) in plasma, which acts as a damage-associated molecular pattern. Using patient-derived fibroblasts and neuronal progenitors, as well as transmitochondrial cytoplasmic hybrids (cybrids), we show that mutant cells release higher levels of cf-mtDNA than wild-type controls, demonstrating that the m.3243A>G pathogenic variant drives mtDNA release. Mechanistically, increased mitochondrial oxidative stress promotes mtDNA oxidation and fragmentation, leading to Ca2+ overload and subsequent mtDNA extrusion. This, in turn, triggers inflammasome activation and pyroptosis, resulting in the secretion of pro-inflammatory cytokines and the activation of innate immune pathways. Pharmacological inhibition of the Mitochondrial Calcium Uniporter (MCU) or Voltage-Dependent Anion Channel (VDAC) reduced mtDNA release, confirming their involvement. Overall, our findings reveal a previously unrecognized mechanism in MELAS linking mitochondrial dysfunction to innate immune activation, with potential implications for therapeutic intervention.

cell biology↗

bioRxiv2025

Geometry aware graph attention networks to explain single-cell chromatin state and gene expression

High-throughput measurements that profile the transcriptome or the epigenome of single-cells are becoming a common way to study cell identity. These data are high dimensional, sparse and non linear. Here we present SEAGALL (Single-cell Explainable Geometry-Aware Graph Attention Learning pipeLine), a hypothesis free method to extract biologically relevant features from single-cell experiments based on geometry regularised autoencoders (GRAE) and explainable graph attention networks (GAT). We use a GRAE to embed the data into a latent space preserving the data geometry and we construct a cell-to-cell graph computing distances in the GRAE bottleneck. Exploiting the attention mechanism to dynamically learn the relevant edges, we use GATs to classify the cells and we explain the predictions of the model with XAI methods to unravel the features which are driving cell identity beyond marker genes. We apply our method to data sets from scRNA-seq, scATAC-seq and scChIP-seq experiments. SEAGALL can extract cell type specific and stable signatures which not only differ from the ones found in classical linear approaches but are less biassed by coverage and high expression.

bioinformatics↗

bioRxiv2024

SLAM-seq reveals independent contributions of RNA processing and stability to gene expression in African trypanosomes

Gene expression is a multi-step process that converts DNA-encoded information into proteins, involving RNA transcription, maturation, degradation, and translation. While transcriptional control is a major regulator of protein levels, the role of post-transcriptional processes such as RNA processing and degradation is less well understood due to the challenge of measuring their contributions individually. To address this challenge, we investigated the control of gene expression in Trypanosoma brucei, a unicellular parasite assumed to lack transcriptional control. Instead, mRNA levels in T. brucei are controlled by post-transcriptional processes, which enabled us to disentangle the contribution of both processes to total mRNA levels. In this study, we developed an efficient metabolic RNA labeling approach and combined ultra-short metabolic labeling with transient transcriptome sequencing (TT-seq) to confirm the long-standing assumption that RNA polymerase II transcription is unregulated in T. brucei. In addition, we established thiol (SH)-linked alkylation for metabolic sequencing of RNA (SLAM-seq) to globally quantify RNA processing rates and half-lives. Our data, combined with scRNA-seq data, indicate that RNA processing and stability independently affect total mRNA levels and contribute to the variability seen between individual cells in African trypanosomes.

molecular biology↗

bioRxiv2023

The Wolfram-like variant WFS1E864K destabilizes MAM and compromises autophagy and mitophagy in human and mice.

Dominant variants in WFS1, a gene coding for the mitochondria-associated endoplasmic reticulum (ER) membrane (MAM) resident protein Wolframin, have been associated with Wolfram-like syndrome (WLS). In vitro and in vivo, WFS1 loss results in reduced ER to mitochondria calcium (Ca2+) transfer, mitochondrial dysfunction, and enhanced autophagy and mitophagy. However, in WLS pathological context, whether the mutant protein triggers the same cellular processes is unknown. Here, we show that, in human fibroblasts and murine neuronal cultures, WLS protein WFS1E864K leads to decreases in mitochondria bioenergetics and Ca2+ uptake, deregulation of the mitochondrial quality system mechanisms, and alteration of the autophagic flux. Moreover, in the Wfs1E864K mouse, these alterations are concomitant with a decrease of MAM number. These findings reveal pathophysiological similarities between WS and WLS, highlighting the importance of WFS1 for MAMs integrity and functionality. It may open new treatment perspectives, until now non-existent, for patients with WLS.

neuroscience↗

bioRxiv2020

Benchmarking atlas-level data integration in single-cell genomics

Cell atlases often include samples that span locations, labs, and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration. Choosing a data integration method is a challenge due to the difficulty of defining integration success. Here, we benchmark 38 method and preprocessing combinations on 77 batches of gene expression, chromatin accessibility, and simulation data from 23 publications, altogether representing >1.2 million cells distributed in nine atlas-level integration tasks. Our integration tasks span several common sources of variation such as individuals, species, and experimental labs. We evaluate methods according to scalability, usability, and their ability to remove batch effects while retaining biological variation. Using 14 evaluation metrics, we find that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, BBKNN, Scanorama, and scVI perform well, particularly on complex integration tasks; Seurat v3 performs well on simpler tasks with distinct biological signals; and methods that prioritize batch removal perform best for ATAC-seq data integration. Our freely available reproducible python module can be used to identify optimal data integration methods for new data, benchmark new methods, and improve method development.

bioinformatics↗

bioRxiv2019

epiScanpy: integrated single-cell epigenomic analysis

Epigenetic single-cell measurements reveal a layer of regulatory information not accessible to single-cell transcriptomics, however single-cell-omics analysis tools mainly focus on gene expression data. To address this issue, we present epiScanpy, a computational framework for the analysis of single-cell DNA methylation and single-cell ATAC-seq data. EpiScanpy makes the many existing RNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities. We introduce and compare multiple feature space constructions for epigenetic data and show the feasibility of common clustering, dimension reduction and trajectory learning techniques. We benchmark epiScanpy by interrogating different single-cell brain mouse atlases of DNA methylation, ATAC-seq and transcriptomics. We find that differentially methylated and differentially open markers between cell clusters enrich transcriptome-based cell type labels by orthogonal epigenetic information.

bioinformatics↗