Biology subjects

Barile, L.

Publications and source records attributed to Barile, L..

6 recordsLinked to original sources

bioRxiv2026

Plasmatic immune extracellular vesicle profiles identify prodromal and early stages of Parkinson's disease

Extracellular vesicles (EVs) hold promise as minimally invasive biomarkers for neurodegenerative proteinopathies, but disease- and stage-specific profiles remain unclear. For this study, we enrolled 378 participants across five centers and the MJFF-BioFIND cohort: 100 healthy controls [HC], 64 isolated REM sleep behavior disorder [iRBD], 41 DeNovo Parkinsons Disease [PD], 89 Late PD, 32 other Synucleinopathies, and 52 Tauopathies. All participants underwent clinical evaluation and blood collection. The 77 subjects from the BioFIND cohort also provided CSF samples. EV concentration and size were assessed by nanoparticle tracking analysis; flow cytometry quantified tetraspanins (CD9/CD63/CD81) and 37 surface markers. Multivariable logistic regression, receiver operating characteristic analyses (ROC), and repeated random forest (rRF) classifiers evaluated diagnostic utility. Late PD showed the highest EV concentrations compared to HC and other disease groups. Participants exhibited distinct EV surface immunophenotypes, with the iRBD group displaying the most extensive immune activation signature vs HC, followed by PD patients. Multivariate logistic regression analysis identified diagnostic marker panels: CD3/CD9/CD25/CD56 for iRBD, SSEA4 for Late PD, CD146/CD209 for Synucleinopathies, and CD8/CD45/CD62P for Tauopathies. ROC confirmed good discriminatory performance, with CD56 emerging as the strongest single predictor for iRBD vs HC, SSEA4 showing high sensitivity for Late PD, and marker combinations providing optimal balance for Synucleinopathy/Tauopathy classification vs HC. In the CSF BioFIND subset, Late PD EVs exhibited increased myeloid (CD1c), adhesion (CD29), activation (CD69), and epithelial (CD326) markers compared to HC. Among these, CD326 was independently associated with Late PD diagnosis. Machine learning classifiers using all 37 surface antigens achieved excellent training performance (91.7-94.3% accuracy for iRBD/Synucleinopathies vs HC) and maintained robust validation accuracy, particularly for iRBD (77.8%) and DeNovo PD (76.6%) vs HC. EV immuno-phenotyping reveals distinct signatures across the neurodegenerative proteinopathies spectrum, with the highest diagnostic utility for prodromal iRBD detection. Longitudinal validation and cell-of-origin refinement represent key next steps toward clinical translation.

neuroscience↗

bioRxiv2026

Circulating extracellular vesicles drive microglial senescence and neurodegeneration in Parkinson`s disease

BackgroundExtracellular vesicles (EV), secreted membrane particles involved in cell-to-cell communication, carry important information on immunity and its dysregulation. Recent studies have demonstrated the crucial role of peripheral and central inflammation in causing Parkinsons disease (PD), as well as the involvement of EV in mediating neuron-glial interactions during neurodegeneration. However, the underlying mechanism of plasmatic EV in PD pathogenesis remains unknown. MethodsEV were isolated from pool of plasma of PD patients and age- and sex-matched healthy controls (HC) using size-exclusion chromatography and characterized by nanoparticle tracking analysis, western blot, and transmission electron microscopy. SH-SY5Y neurons and HMC3 microglia cells were treated with EV, and their impact was evaluated using flow cytometry and immunofluorescence. Conditioned medium (CM) from EV-treated HMC3 cells was applied to SH-SY5Y neurons to determine indirect neurotoxic effects. Cytokine profiling and senescence-like features of EV-treated HMC3 cells were assessed. Unbiased proteomic analysis of PD-EV and HC-EV were further performed. ResultsPD-EV induced axonal degeneration and cell death in SH-SY5Y neurons and increased levels of TNF-, IL-1{beta}, IFN-{gamma}, IL-8, and CCL11, accompanied by the expression of p16INK4a in HMC3 cells, suggesting a proinflammatory, senescence-associated secretory phenotype (SASP). Enrichment pathway analysis revealed that these changes were mainly related to inflammatory and immune responses. Moreover, CM from PD-EV-HMC3 cells increased apoptotic cell death in SH-SY5Y neurons more than direct PD-EV. Notably, proteomic analysis of PD-EV showed higher expression of proteins involved in complement cascades, immune response, phagocytosis, and post translational protein translation, further supporting the potential of EV to induce inflammatory changes in PD. ConclusionsThis study demonstrates that plasmatic PD-EV contributes to neuronal degeneration by reducing neuronal integrity and indirectly by activating microglia through the secretion of pro-inflammatory, senescence-associated mediators. Circulating EV exerts a role in bridging peripheral inflammation with microglia, modulating neuroinflammatory events.

neuroscience↗

bioRxiv2024

A novel ionic model for matured and paced atrial-like hiPSC-CMs integrating IKur and IKCa currents

Human induced pluripotent stem cells-derived cardiomyocytes have revolutionized the field of regenerative medicine, offering unparalleled potential for in-vitro modeling of normal and pathological human cardiomyocytes. The ability to produce stem cardiac myocytes in abundance has opened new avenues for drug efficacy and safety testing, as well as the study of conditions such as atrial fibrillation, a familial cardiac disorder. The development of atrial fibrillation is influenced by ion channel mutations, genetic variants, and other risk factors. Stem cells derived cardiomyocytes hold promise in personalized medicine, as they share the genetic heritage of the donor. While mathematical models have focused on immature stem cardiomyocytes phenotypes, they have primarily relied on a system of stiff ordinary differential equations. Computational modeling of diseased tissue presents an opportunity to evaluate drugs in a patient-specific manner, thereby improving therapeutic targets and ablation techniques. Previous studies categorized cell phenotypes based on action potential morphology, yet classification criteria remains ambiguous. This work introduces the first atrial-specific in-silico model of stem cells ionic currents, leveraging experimental data provided by Altomare et al. It begins by summarizing the baseline electrophysiological model and mathematical descriptions of atrial-specific additional currents. Model parameter tuning was performed through automatic optimization techniques to ensure realistic action potential shape and expedite the parameter adjustment process. The resulting model was validated against rate dependence and atrial-specific ion current blocking data. In summary, the development of an atrial-specific in-silico model represents a significant step forward in understanding cardiac electrophysiology and the potential for personalized medicine in treating conditions like atrial fibrillation. This model offers new tools for drug evaluation, therapeutic improvement, and a deeper comprehension of cardiac phenotypes. Author summaryHuman induced pluripotent stem cells have revolutionized regenerative medicine since their discovery in 2006, leading to a Nobel Prize in 2012. This kind of pluripotent cells can give rise to different types of specific tissue cells, such as derived cardiomyocytes. Differentiated cardiac cells offer an unlimited supply for studying human heart cells in normal and disease conditions, aiding a patient-specific drug testing and helping to explore pathogenic mechanisms behind different cardiomyopathies, including atrial fibrillation. Atrial fibrillation is a common heart condition, and stem cells with the same genetic heritage as the donor, are ideal for patient-specific treatments. Recent advances have produced mathematical models for the ionic currents in cardiomyocytes derived from stem cells, focusing on immature forms and enabling virtual drug testing. However, previous models did not capture the atrial-specific characteristics. We decided to create and introduce by this study the first atrial-like in-silico model for these cells, using novel experimental data. Thus, we describe the baseline model and additional atrial-specific currents, we tune the model parameters using automatic optimization technique, and we validate the models accuracy in simulating atrial action potentials and ion current blockage. This research paves the way for better understanding and treating atrial fibrillation and other heart conditions.

bioengineering↗

bioRxiv2023

Addressing heterogeneity in direct analysis of Extracellular Vesicles and analogues using Membrane-Sensing Peptides as Pan-Affinity Probes

Extracellular vesicles (EVs), crucial mediators of cell-to-cell communication, hold immense potential for diagnostic applications due to their ability to enrich protein biomarkers in body fluids. However, challenges in isolating EVs from complex biological specimens hinder their widespread use. In this frame, integrated isolation-and-analysis workflows are the go-to strategy, most of which see the prevalence of immunoaffinity methods. Yet, the high heterogeneity of EVs poses challenges, as proposed ubiquitous markers are less homogenously prevalent than believed, raising concerns about the reliability of downstream biomarker discovery programs. This issue extends to the burgeoning field of engineered EV-mimetics and bio-nanoparticles, where conventional immune-affinity methods may lack applicability. Addressing these challenges, we introduce the use Membrane Sensing Peptides (MSP) as "universal" affinity ligands for both EVs and EV-analogues. Employing a streamlined process integrating on-bead capture and vesicle phenotyping through Single Molecule Array (SiMoA) technology, we showcase the application of MSP ligands in the integrated analysis of circulating EVs in blood derivatives, eliminating the need for prior EV isolation. Demonstrating the possible clinical translation of MSP technology, we directly detect an EV-associated epitope signature in serum and plasma samples, demonstrating its potential for distinguishing patients with myocardial infarction versus stable angina. At last, notably, MSP exhibits a unique capability to enable the analysis of tetraspanin-lacking Red Blood Cell derived EVs (RBC-EVs). Overall, unlike traditional antibody-based methods, MSP probes work agnostically, overcoming limitations associated with surface protein abundance or scarcity. This highlights the potential of MSP in advancing EV analysis for clinical diagnostics and beyond. Of note, this represents also the first-ever peptide-based application in SiMoA technology.

biochemistry↗

bioRxiv2023

Mitochondrial DNA released by senescent cells triggers immunosuppression in cancer

DNA is a potent damage-associated molecular pattern signaling that, once in the extracellular space, triggers the activation of the innate immune system. Here we find that senescent cells release mtDNA to both the cytosol and the extracellular space. In cells undergoing cellular senescence, the release of mtDNA precedes that of nuclear DNA resulting in the activation of the cGAS/STING pathway and establishment of cellular senescence. Intriguingly, by exploiting co-culture and in vivo cross-species experiments, we show that extracellular mtDNA released by senescent tumors cells is specifically captured by polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) in the tumor microenvironment (TME). Mechanistically we find that PMN-MDSCs uptake mtDNA to enhance their immunosuppressive ability. Pharmacological inhibition of mtDNA released from senescent tumor cells blocks the PMN-MDSCs immunosuppressive activity, improving the efficacy of therapy-induced senescence (TIS) in cancer. These results reveal the crucial role of mtDNA in initiating cellular senescence and immunosuppression independently of the SASP. Thus, targeting mtDNA release-mediated pathway may hold promise to reprogram the immune suppressive microenvironment in patients treated with chemotherapy.

cell biology↗

bioRxiv2022

Compositional profiling of extracellular vesicles/lipoproteins mixtures by AFM nanomechanical imaging

The widely overlapping physicochemical properties of lipoproteins (LPs) and extracellular vesicles (EVs) represents one of the main obstacles for the isolation and characterization of these pervasive biogenic lipid nanoparticles. We herein present the application of an atomic force microscopy (AFM)-based quantitative morphometry assay to the rapid nanomechanical screening of mixed LPs and EVs samples. The method can determine the diameter and the mechanical stiffness of hundreds of individual nanometric objects within few hours. The obtained diameters are in quantitative accord with those measured via cryo-electron microscopy (cryo-EM); the assignment of a specific nanomechanical readout to each object enables the simultaneous discrimination of co-isolated EVs and LPs even if they have overlapping size distributions. EVs and all classes of LPs are shown to be characterized by specific combinations of diameter and stiffness, thus making it possible to estimate their relative abundance in EV/LP mixed samples in terms of stoichiometric ratio, surface area and volume. As a side finding, we show how the mechanical behaviour of specific LP classes is correlated to distinctive structural features revealed by cryo-EM. To the best of our knowledge, these results represent the first systematic single-particle mechanical investigation of lipoproteins. The described approach is label-free, single-step and relatively quick to perform. Importantly, it can be used to analyze samples which prove very challenging to assess with several established techniques due to ensemble-averaging, low sensibility to small particles, or both, thus providing a very useful tool for quickly assessing the purity of EV/LP isolates including plasma- and serum-derived preparations.

biophysics↗