Biology subjects

Bonfanti, M.

Publications and source records attributed to Bonfanti, M..

9 recordsLinked to original sources

bioRxiv2026

Human basal radial glia morphotypes are transcriptionally distinct and exhibit different cell fate determination

Basal radial glia (bRG) are key neural progenitors driving human neocortical expansion. They exhibit remarkable morphological heterogeneity, yet the stability and functional significance of their distinct morphotypes remains unclear. Using human cortical brain organoids combined with long-term live imaging and morphology-resolved spatial transcriptomics (CellShape-seq), we show that bRG morphotypes display distinct morphodynamic behaviors, proliferative capacities and transcriptional profiles. While bifurcated bRG remodel extensively during mitosis to produce morphologically diverse progeny, multipolar cells are most morphologically flexible during interphase. Multipolar bRG further show the greatest proliferative capacity and the transcriptional signature related to progenitor state. Bifurcated bRG are least proliferative and are enriched for the multifunctional gene expression regulator YBX1. Pharmacological inhibition of YBX1 depletes bifurcated bRG, reduces neurogenesis, and promotes glial commitment. Our findings link progenitor morphology, gene expression and fate, providing a framework for understanding the cellular logic of human cortical development.

neuroscience↗

bioRxiv2025

Benchmarking cerebellar organoids to model autism spectrum disorder and human brain evolution

While cortical organoids have been used to model different facets of neurodevelopmental conditions and human brain evolution, cerebellar organoids have not yet featured so prominently in the same context, despite increasing evidence of this brain regions importance for cognition and behavior. Here, we provide a longitudinal characterization of cerebellar organoids benchmarked against human fetal data and identify at very early stages of development a significant number of dynamically expressed genes relevant for neurodevelopmental conditions such as autism and attention deficit hyperactivity disorders. Then, we model an ASD mutation impacting CHD8, showing both granule cell and oligodendrocyte lineages prominently affected, resulting in altered network activity in more mature organoids. Lastly, using CRISPR/Cas9 editing, we also model an evolution-relevant mutation in a regulatory region of the CADPS2 gene. We investigate the effect of the derived allele exclusive to Homo sapiens, identifying a rerouting of the CADPS2-expression in rhombic lip cells, coupled with a different sensitivity to hypoxia which in turn lead to a differential timing of granule cell differentiation. HIGHLIGHTSO_LILongitudinal characterization of cerebellar organoids uncovers disorder related genes especially at early stages of development C_LIO_LIMutation in CHD8 alter rhombic lip and oligodendrocytes differentiation via WNT pathway C_LIO_LIRerouting of CADPS2 expression, delaying differentiation and migration, in recent human evolution C_LI IN BRIEFAprile and colleagues longitudinally profiled cerebellar organoids, benchmarking them against a fetal human atlas and identified a highly dynamic expression of genes related to cognitive and behavioral disorders especially at early stages of differentiation. Organoids were used to model the impact of a high-penetrance mutation associated with autism spectrum disorder and a high-frequency derived allele in Homo sapiens predicted to have played a role in recent brain evolution.

neuroscience↗

bioRxiv2025

Glioblastoma stem cell morphotypes convey distinct cell states and clinically relevant functions

Glioblastoma (GBM) is an aggressive brain tumor and an unmet clinical need due to its invasiveness and therapy-resistance. These features are driven by glioblastoma stem cells (GSCs), which exhibit remarkable functional heterogeneity. However, GSC transcriptional profiling alone cannot predict clinically relevant behaviors. Here, we developed CellShape-seq, a spatial transcriptomics platform that integrates cell morphology with transcriptome. This identified three GSC morphoclasses corresponding to distinct transcriptomic states and functions: (1) nonpolar cells show differentiation and therapy sensitivity, (2) elongated cells are invasive, and (3) multipolar cells form intercellular networks. Importantly, chemoresistance is morphoclass-specific: elongated GSCs depend on YAP/TEAD1 signaling, while multipolar GSCs rely on gap junction-mediated networks. Targeting these vulnerabilities with specific inhibitors sensitized resistant GSC morphoclasses to temozolomide (TMZ) in patient-derived organoids. Our findings demonstrate that morphology provides critical insights into GSC behavior and establish a rationale for morphology-informed therapies to overcome resistance and improve outcomes in GBM. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=85 SRC="FIGDIR/small/644884v2_ufig1.gif" ALT="Figure 1"> View larger version (15K): org.highwire.dtl.DTLVardef@141e698org.highwire.dtl.DTLVardef@18a238corg.highwire.dtl.DTLVardef@23ef62org.highwire.dtl.DTLVardef@1390c07_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2023

Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution

The combination of brain organoid and single cell omic technologies holds transformative potential to dissect human neurobiology at high resolution and with mechanistic precision. Delivering this promise in the context of human neurodiversity, physiological and pathological alike, requires however a major leap in scalability, given the need for experimental designs that include multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we implemented and benchmarked complementary strategies to multiplex brain organoids. Following an extended longitudinal design with a uniquely informative set of timepoints, we pooled cells from different induced pluripotent stem cell lines either during organoids generation (upstream multiplexing in mosaic models) or before single cell-RNAseq library preparation (downstream multiplexing). We developed a new method, SCanSNP, and an aggregated call to deconvolve organoids cell identities, overcoming current criticalities in doublets prediction and low quality cells identification and improving accuracy over state of the art algorithms. Integrating single cell transcriptomes and analysing cell types across neurodevelopmental stages and multiplexing modalities, we validated the feasibility of both multiplexing methods in charting neurodevelopmental trajectories at high resolution, linking their specificity to genetic variation between individual lines. Together, this multiplexing suite of experimental and computational methods provides an enabling resource for disease modelling at scale and paves the way towards an in vitro epidemiology paradigm.

neuroscience↗

bioRxiv2023

Towards Reduced Order Models via Robust Proper Orthogonal Decomposition to Capture Personalised Aortic Haemodynamics

Data driven, reduced order modelling has shown promise in tackling the challenges associated with computational and experimental hemodynamic models. In this work, we explore the use of Reduced Order Models (ROMs) to capture the main flow features in a patient-specific dissected aorta. We apply Proper Orthogonal Decomposition (POD) and Robust Principle Component Analysis (RPCA) on in vitro, hemodynamic data acquired by Particle Image Velocimetry and compare the decomposed flows to those derived from Computational Fluid Dynamics (CFD) data for the same geometry and flow conditions. The flow is reconstructed using different numbers of POD modes and the flow features obtained throughout the cardiac cycle are compared to the original Full Order Models (FOMs). RPCA has been found to enhance the quality of PIV data and to capture most of the kinetic energy of the flow in just two modes similar to the numerical data that are free from measurement noise. The reconstruction errors differ along the cardiac cycle with diastolic flows requiring more modes for accurate reconstruction. In general, modes{Phi} 1-10 are found sufficient to represent the flow field. The results demonstrate that the coherent structures that characterise this aortic dissection flow are described by the first few POD modes suggesting that it is possible to represent the macroscale behaviour of aortic flow in a low-dimensional space; thus significantly simplifying the problem, and allowing for more computationally efficient flow simulations that can pave the way for translation of such models to the clinic.

bioengineering↗

bioRxiv2022

RAGE engagement by SARS-CoV-2 enables monocyte infection and underlies COVID-19 severity

The spread of SARS-CoV-2 has fueled the COVID-19 pandemic with its enduring medical and socioeconomic challenges due to subsequent waves and long-term consequences of great concern. Here we charted the molecular basis of COVID-19 pathogenesis, by analysing patients immune response at single-cell resolution across disease course and severity. This approach uncovered cell subpopulation-specific dysregulation in COVID-19 across disease course and severity and identified a severity-associated activation of the receptor for advanced glycation endproduct (RAGE) pathway in monocytes. In vitro experiments confirmed that monocytes bind the SARS-CoV-2 S1-RBD via RAGE and that RAGE-Spike interactions drive monocyte infection. Our results demonstrate that RAGE is a novel functional receptor of SARS-CoV-2 contributing to COVID-19 severity. One-Sentence SummaryMonocyte SARS-CoV-2 infection via the receptor for advanced glycation endproduct triggers severe COVID-19.

immunology↗

bioRxiv2021

A novel MRI-based data fusion methodology for efficient, personalised, compliant simulations of aortic haemodynamics

We present a novel, cost-efficient methodology to simulate aortic haemo-dynamics in a patient-specific, compliant aorta using an MRI data fusion process. Based on a previously-developed Moving Boundary Method, this technique circumvents the high computational cost and numerous structural modelling assumptions required by traditional Fluid-Structure Interaction techniques. Without the need for Computed Tomography (CT) data, the MRI images required to construct the simulation can be obtained during a single imaging session. Black Blood MR Angiography and 2D Cine-MRI data were used to reconstruct the luminal geometry and calibrate wall movement specifically to each region of the aorta. 4D-Flow MRI and non-invasive pressure measurements informed patient-specific inlet and outlet boundary conditions. Luminal area closely matched 2D Cine-MRI measurements with a mean error of less than 4.6% across the cardiac cycle, while physiological pressure and flow distributions were simulated to within 3.3% of patient-specific targets. Moderate agreement with 4D-Flow MRI velocity data was observed. Despite lower peak velocity, an equivalent rigid-wall simulation predicted a mean Time-Averaged Wall Shear Stress (TAWSS) 13% higher than the compliant simulation. The agreement observed between compliant simulation results and MRI data is testament to the accuracy and efficiency of this MRI-based simulation technique.

bioengineering↗

bioRxiv2021

Effective Computational Framework for Pre-Interventional Planning of Peripheral Arteriovenous Malformations with In Vivo and In Vitro Validation

PurposePeripheral arteriovenous malformations (pAVMs) are congenital lesions characterised by abnormal high-flow, low-resistance vascular connections - constituting the so-called nidus - between arteries and veins. The mainstay treatment typically involves the embolisation of the nidus with embolic and sclerosant agents, however the complexity of AVMs often leads to uncertain outcomes. This study aims at developing a simple, yet effective computational framework to aid the clinical decision making around the treatment of pAVMs. MethodsA computational model was developed to simulate the pre-, intra-, and post-intervention haemodynamics of an AVM. A porous medium of varying permeability was used to simulate the effect that the sclerosant has on the blood flow through the nidus. The computational model was informed by computed tomography (CT) scans and digital subtraction angiography (DSA) images, and the results were compared against clinical data and experimental results. ResultsThe computational model was able to simulate the blood flow through the AVM throughout the intervention and predict (direct and indirect) haemodynamic changes due to the embolisation. The simulated transport of the dye in the AVM was compared against DSA time-series obtained at different intervention stages, providing confidence in the results. Moreover, experimental data obtained via a mock circulatory system involving a patient specific 3D printed phantom of the same AVM provided further validation of the simulation results. ConclusionWe developed a simple computational framework to simulate AVM haemodynamics and predict the effects of the embolisation procedure. The developed model lays the foundation of a new, computationally driven treatment planning tool for AVM embolisation procedures.

bioengineering↗

bioRxiv2019

Patient-specific haemodynamic simulations of complex aortic dissections informed by commonly available clinical datasets

Patient-specific computational fluid-dynamics (CFD) can assist the clinical decision-making process for Type-B aortic dissection (AD) by providing detailed information on the complex intra-aortic haemodynamics. This study presents a new approach for the implementation of personalised CFD models using non-invasive, and oftentimes minimal, datasets commonly collected for AD monitoring. An innovative way to account for arterial compliance in rigid-wall simulations using a lumped capacitor is introduced, and a parameter estimation strategy for boundary conditions calibration is proposed. The approach was tested on three complex cases of AD, and the results were successfully compared against invasive blood pressure measurements. Haemodynamics results (e.g. intraluminal pressures, flow partition between the lumina, wall shear-stress based indices) provided information that could not be obtained using imaging alone, providing insight into the state of the disease. It was noted that small tears in the distal intimal flap induce disturbed flow in both lumina. Moreover, oscillatory pressures across the intimal flap were often observed in proximity to the tears in the abdominal region, which could indicate a risk of dynamic obstruction of the true lumen.\n\nThis study shows how combining commonly available clinical data with computational modelling can be a powerful tool to enhance clinical understanding of AD.

bioengineering↗