Biology subjects

Mularoni, L.

Publications and source records attributed to Mularoni, L..

9 recordsLinked to original sources

bioRxiv2026

Mapping Uterine Remodeling from Pregnancy to a New Homeostatic State

Pregnancy drives uterine remodeling through rapid anatomical expansion and scar-free postpartum repair, yet how the organ reconstructs its cellular architecture after birth remains incompletely understood. Here, we present single-cell transcriptomic profiling of 698,631 cells derived from the whole mouse uterus across five distinct stages centered around parturition: Non-pregnant Control, late gestation (embryonic day 16.5), and postpartum days (PPD) 1, 7, and 30. We resolved 16 distinct cell lineages spanning epithelial, stromal, endothelial, and immune compartments. Although gross morphological involution occurs rapidly, with uterine horn length returning to baseline levels by PPD7, the underlying cellular architecture does not revert to its pre-pregnancy state. Tissue composition, transcriptional states, and intercellular signalling networks did not revert to their pre-pregnancy configurations. Instead, postpartum reconstruction proceeded through five sequential but overlapping transcriptional programs, with individual cells simultaneously extinguishing gestational programs and acquiring repair-associated states. By one month postpartum, the tissue adopts a reconfigured architecture that fails to fully reactivate the non-pregnant baseline, thus, establishing a novel homeostatic state. This work provides a foundation for delineating the specific organizational levels that fully recover following physiological injury versus those that establish new baseline set points.

cell biology↗

bioRxiv2025

Staufen2 modulates the temporal dynamics of human neurogenesis in vitro

RNA-binding proteins (RBPs) play a central role in post-transcriptional regulation during brain development, yet their specific functions in coordinating human neural lineage decisions remain poorly understood. Here, we investigate for the first time the role of the double-stranded RBP Staufen2 (STAU2) in human neurogenesis. Characterization of STAU2 knockout iPSC derived cells using scRNA-seq shows that loss of STAU2 disrupts neuroepithelial cell identity and accelerates neural differentiation by altering the activity of key transcription factors and driving early metabolic transitions. Additionally, STAU2 regulates the expression of miRNA host genes and alters miRNA-mediated post- transcriptional control in progenitor cells, which exerts additional effects on STAU2 regulated gene regulatory networks. These changes result in neural progenitor exhaustion, unstructured neural rosettes, and reduced organoid size. Together, our work uncovers a previously unrecognized role for STAU2 as a central regulator of early human neurogenesis, acting through both miRNA-mediated and transcriptional pathways to coordinate progenitor maintenance and neuronal fate specification.

molecular biology↗

bioRxiv2025

Astrocytic Ceruloplasmin Deficiency Triggers Iron Toxicity and Neurodegeneration in a LRRK2 Parkinson's Tri-Culture Model

Astrocytes and microglia carrying the LRRK2-G2019S mutation contribute to non-cell- autonomous dopaminergic neuron (DAn) degeneration in Parkinsons disease (PD), but the mechanisms underlying their interplay remain unclear. Here, we developed a novel induced pluripotent stem cell (iPSC)-derived tri-culture system comprising healthy DAn and either LRRK2-mutant or isogenic control iPSC-derived astrocytes and microglia. Using integrated functional assays and transcriptomic profiling, we found that mutant astrocytes adopt a hyperreactive state, driving microglial activation and subsequent DAn degeneration. Mechanistically, we identified a selective downregulation of ceruloplasmin (CP), a copper-dependent ferroxidase, in mutant astrocytes, leading to disrupted iron homeostasis with accumulation of Fe2+ and ROS. This iron dysregulation mediated both microglial reactivity and neurodegeneration. Notably, pharmacological restoration of CP re-established iron homeostasis, reduced microglial activation, and protected DAn from degeneration. Our findings uncover a novel astrocyte-microglia-neuron axis driving PD pathogenesis and showcase the power of our unique stem cell tri-culture platform for dissecting disease mechanisms and discovering therapeutic targets.

cell biology↗

bioRxiv2025

Targeting RhoA activity rejuvenates aged hematopoietic stem cells

Biomechanical alterations contribute to the decreased regenerative capacity of hematopoietic stem cells (HSCs) upon aging. RhoA is a key regulator of mechano-signaling but its role for mechanotransduction in stem cell aging has not been investigated yet. Here, we show that murine HSCs respond to increased nuclear envelope (NE) tension by inducing NE translocation of P-cPLA2, which cell intrinsically activates RhoA. Interestingly, aged HSCs experience physiologically higher intrinsic NE tension, associated with increased NE P-cPLA2 and RhoA activity. Reducing RhoA activity lowers NE tension in aged HSCs. Feature image analysis of HSC nuclei reveals that chromatin remodeling is associated to RhoA inhibition, which includes the restoration of youthful levels of the heterochromatin marker H3K9me2 and a decrease in chromatin accessibility and transcription at retrotransposons. Eventually, we demonstrate that RhoA inhibition upregulates Klf4 expression and transcriptional activity, improving aged HSCs regenerative capacity and lympho/myeloid skewing in vivo. Overall, our data support that an intrinsic mechano-signaling axis dependent on RhoA can be pharmacologically targeted to rejuvenate stem cell function upon aging.

cell biology↗

bioRxiv2024

A single-cell atlas of the murine pancreatic ductal tree identifies novel cell populations with potential implications in pancreas regeneration and exocrine pathogenesis.

Background and aimsPancreatic ducts form an intricate network of tubules that secrete bicarbonate and drive acinar secretions into the duodenum. This network is formed by centroacinar cells, terminal, intercalated, intracalated ducts, and the main pancreatic duct. Ductal heterogeneity at the single-cell level has been poorly characterized; therefore, our understanding of the role of ductal cells in pancreas regeneration and exocrine pathogenesis has been hampered by the limited knowledge and unexplained diversity within the ductal network. MethodsWe used scRNA-seq to comprehensively characterize mouse ductal heterogeneity at single-cell resolution of the entire ductal epithelium from centroacinar cells to the main duct. Moreover, we used organoid cultures, injury models and pancreatic tumor samples to interrogate the role of novel ductal populations in pancreas regeneration and exocrine pathogenesis. ResultsWe have identified the coexistence of 15 ductal populations within the healthy pancreas and characterized their organoid formation capacity and endocrine differentiation potential. Cluster isolation and subsequent culturing let us identify ductal cell populations with high organoid formation capacity and endocrine and exocrine differentiation potential in vitro, including Wnt-responsive-population, ciliated-population and FLRT3+ cells. Moreover, we have characterized the location of these novel ductal populations in healthy pancreas, chronic pancreatitis, and tumor samples, highlighting a putative role of WNT-responsive, IFN-responsive and EMT-populations in pancreatic exocrine pathogenesis as their expression increases in chronic pancreatitis and PanIN lesions. ConclusionsIn light of our discovery of previously unidentified ductal populations, we unmask the potential roles of specific ductal populations in pancreas regeneration and exocrine pathogenesis.

cell biology↗

bioRxiv2022

Methanol fixation is the method of choice for droplet-based single-cell transcriptomics of neural cells

Single-cell transcriptomics methods have become very popular to study the cellular composition of organs and tissues and characterize the expression profiles of the individual cells that compose them. The main critical step in single-cell transcriptomics is sample preparation. Several methods have been developed to preserve cells after sample dissociation to uncouple sample handling from library preparation. Yet, the suitability of these methods depends on the types of cells to be processed. In this project, we perform a systematic comparison of preservation methods for droplet-based single-cell RNA-seq (scRNA-seq) on neural and glial cells derived from induced pluripotent stem cells (iPSCs) and highlight their strengths and weaknesses. We compared the cellular composition and expression profile of single-cell suspensions from fresh NPCs with that of NPCs preserved with Dimethyl Sulfoxide (DMSO), Methanol, vivoPHIX and Acetil-methanol (ACME). Our results show that while DMSO provides the highest cell quality in terms of RNA molecules and genes detected per cell, it strongly affects the cellular composition and the expression profile of the resulting datasets. In contrast, methanol fixed samples display a cellular composition like that of fresh samples while providing a good cell quality and smaller expression biases. Taken together, our results show that methanol fixation is the method of choice for performing droplet-based single-cell transcriptomics experiments on neural cell populations.

genomics↗

bioRxiv2018

OncodriveCLUSTL: a sequence-based clustering method to identify cancerdrivers

SummaryThe identification of the genomic alterations driving tumorigenesis is one of the main goals in oncogenomics research. Given the evolutionary principles of cancer development, computational methods that detect signals of positive selection in the pattern of tumor mutations have been effectively applied in the search for cancer genes. One of these signals is the abnormal clustering of mutations, which has been shown to be complementary to other signals in the detection of driver genes. We have developed OncodriveCLUSTL, a new sequence-based clustering algorithm to detect significant clustering signals across genomic regions. OncodriveCLUSTL is based on a local background model derived from the simulation of mutations accounting for the composition of tri- or penta-nucleotide context substitutions observed in the cohort under study. Our method is able to identify known clusters and bona-fide cancer drivers across cohorts of tumor whole-exomes, outperforming the existing OncodriveCLUST algorithm and complementing other methods based on different signals of positive selection. We show that OncodriveCLUSTL may be applied to the analysis of non-coding genomic elements and non-human mutations data.\n\nAvailability and implementationOncodriveCLUSTL is available as an installable Python 3.5 package. The source code and running examples are freely available at https://bitbucket.org/bbglab/oncodriveclustl under GNU Affero General Public License.\n\nContactnuria.lopez@irbbarcelona.org

bioinformatics↗

bioRxiv2017

Discovery and characterization of coding and non-coding driver mutations in more than 2,500 whole cancer genomes

Discovery of cancer drivers has traditionally focused on the identification of protein-coding genes. Here we present a comprehensive analysis of putative cancer driver mutations in both protein-coding and non-coding genomic regions across >2,500 whole cancer genomes from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We developed a statistically rigorous strategy for combining significance levels from multiple driver discovery methods and demonstrate that the integrated results overcome limitations of individual methods. We combined this strategy with careful filtering and applied it to protein-coding genes, promoters, untranslated regions (UTRs), distal enhancers and non-coding RNAs. These analyses redefine the landscape of non-coding driver mutations in cancer genomes, confirming a few previously reported elements and raising doubts about others, while identifying novel candidate elements across 27 cancer types. Novel recurrent events were found in the promoters or 5UTRs of TP53, RFTN1, RNF34, and MTG2, in the 3UTRs of NFKBIZ and TOB1, and in the non-coding RNA RMRP. We provide evidence that the previously reported non-coding RNAs NEAT1 and MALAT1 may be subject to a localized mutational process. Perhaps the most striking finding is the relative paucity of point mutations driving cancer in non-coding genes and regulatory elements. Though we have limited power to discover infrequent non-coding drivers in individual cohorts, combined analysis of promoters of known cancer genes show little excess of mutations beyond TERT.

genomics↗

bioRxiv2017

The whole-genome panorama of cancer drivers

The advance of personalized cancer medicine requires the accurate identification of the mutations driving each patients tumor. However, to date, we have only been able to obtain partial insights into the contribution of genomic events to tumor development. Here, we design a comprehensive approach to identify the driver mutations in each patients tumor and obtain a whole-genome panorama of driver events across more than 2,500 tumors from 37 types of cancer. This panorama includes coding and non-coding point mutations, copy number alterations and other genomic rearrangements of somatic origin, and potentially predisposing germline variants. We demonstrate that genomic events are at the root of virtually all tumors, with each carrying on average 4.6 driver events. Most individual tumors harbor a unique combination of drivers, and we uncover the most frequent co-occurring driver events. Half of all cancer genes are affected by several types of driver mutations. In summary, the panorama described here provides answers to fundamental questions in cancer genomics and bridges the gap between cancer genomics and personalized cancer medicine.

cancer biology↗