Biology subjects

Di Bella, D.

Publications and source records attributed to Di Bella, D..

4 recordsLinked to original sources

bioRxiv2025

Mathematical modelling of mutant glycoprotein fate in the ER

BackgroundThe endoplasmic reticulum (ER) coordinates glycoprotein quality control through competing pathways: ER quality control (ERQC) and ER-associated degradation (ERAD). The fate of a glycoprotein is tied to its N-glycan(s) structure, which serves as a "molecular barcode" for quality control. In particular, modulation of ERQC/ERAD can increase leakage of responsive (i.e., non-inactive) glycoprotein mutants that remain misfolded yet retain biological activity once outside the ER. Rescue of secretion of such mutants is a promising therapeutic strategy for the therapy of congenital rare disease due to a missense mutation in a secreted glycoprotein gene, but the relative merits of UGGT vs. EDEM inhibition to release a mutant from the ER remain to be explored. MethodsAn ordinary differential equation (ODE) framework ("ER Glycoprotein Outcome", ERGO) evaluates time-dependent ER concentrations of 13 N-glycospecies of a single mutant glycoprotein (G1M9, G1M8B, G1M8C, G1M7BC, M9, M8A, M8B, M8C, M7AB, M7AC, M7BC, M6, M5) within the ER lumen, under a set of chosen hypotheses. All reactions follow mass-action kinetics with ER enzymes/lectins kinetic constants and concentrations as fixed parameters. The ODE system is solved in Python with adaptive Runge-Kutta integration. Simulations initialise from a single glycoform (M9, 1 {micro}M) and track glycoform distributions over [~]28 h. Starting glycoform concentrations and overall time can be customised. Given the lack of comprehensive kinetic data in the literature, parameter values reflect educated guesses, rather than measured constants. ResultsFour simulation scenarios explore the dynamics of ERQC vs ERAD: (A) baseline scenario with all enzymes active; (B) UGGT inhibition, which abolishes re-glucosylation, disrupts CNX/CRT cycles, and accelerates substrate flux toward ERAD-prone glycoforms; (C) inhibition of all ER mannosidases, preventing trimming-dependent ERAD commitment and prolonging ER retention of early glycoforms; (D) combined UGGT and ER mannosidases inhibition, mimicking experimental rescue of misfolded substrates by blockade of both glucosylation-driven ER retention and trimming-driven degradation signals. We further quantify the rate of CNX/CRT engagement ( carousel rides) by combining analytical estimates with Monte Carlo-style simulations of individual mutant glycoprotein fates.

bioinformatics↗

bioRxiv2025

DEK::NUP214 acts as an XPO1-dependent transcriptional activator of essential leukemia genes

The t(6;9)(p22.3;q34.1) translocation/DEK::NUP214 fusion protein defines a distinct subgroup of younger AML patients classified as a separate disease entity by the World Health Organization. DEK is a nuclear factor with multifunctional roles, including gene regulation, while its fusion partner, NUP214, plays a pivotal role in nuclear export by interacting with transport receptors such as XPO1. However, the precise mechanism by which DEK::NUP214 drives leukemia remains unclear. A comprehensive multi-omics comparison of 57 AML primary samples (including whole genome sequencing, targeted sequencing, transcriptomics, and drug screening with > 500 compounds) revealed that t(6;9) cases display a selective response to XPO1 inhibitors (Selinexor & Eltanexor) and a distinct transcriptomic signature characterized by the overexpression of FOXC1 and HOX genes that are key leukemia mediators. CUT&RUN experiments demonstrated the direct binding of DEK::NUP214 to the promoters of FOXC1 and HOXA/B clusters. Strikingly, the expression of these genes and the binding of DEK::NUP214 to their regulatory regions were selectively reduced upon XPO1 inhibition in t(6;9) cells. Altogether, these results identified a novel function of DEK::NUP214 as an XPO1-dependent transcriptional activator of key leukemia drivers and provide a rationale to explore the use of XPO1 inhibitors in this patient population.

cancer biology↗

bioRxiv2024

Neuronal-class specific molecular cues drive differential myelination in the neocortex

In the neocortex, oligodendrocytes produce distinct amounts of myelin in each cortical layer and along the axons of individual neuron types. Here we present a comprehensive single-cell molecular map of mouse cortical oligodendrocytes across different cortical layers and stages of myelination, spanning the initiation of cortical myelination into adulthood. We apply this dataset to show that neuron-class specific signals drive oligodendrocyte maturation and differential myelination across cortical layers. We find that each layer contains a similar compendium of oligodendrocyte classes, indicating that oligodendrocyte heterogeneity cannot explain layer-specific myelination. To evaluate whether neuronal diversity drives differential myelination across cortical layers, we generated a predicted ligand-receptor interactome between projection neuron types and oligodendrocyte states, across cortical layers and time. In vivo functional testing identified Fgf18, Ncam1, and Rspo3 as novel, neuron-derived pro-myelinating signals. Our results highlight neuron-class-dependent control of myelin distribution in the neocortex.

neuroscience↗

bioRxiv2020

Sensitive spatial genome wide expression profiling at cellular resolution

The precise spatial localization of molecular signals within tissues richly informs the mechanisms of tissue formation and function. Previously, we developed Slide-seq, a technology which enables transcriptome-wide measurements with 10-micron spatial resolution. Here, we report new modifications to Slide-seq library generation, bead synthesis, and array indexing that markedly improve the mRNA capture sensitivity of the technology, approaching the efficiency of droplet-based single-cell RNAseq techniques. We demonstrate how this modified protocol, which we have termed Slide-seqV2, can be used effectively in biological contexts where high detection sensitivity is important. First, we deploy Slide-seqV2 to identify new dendritically localized mRNAs in the mouse hippocampus. Second, we integrate the spatial information of Slide-seq data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex. The combination of near-cellular resolution and high transcript detection will enable broad utility of Slide-seq across many experimental contexts.

genomics↗