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Criscuolo, L.

Publications and source records attributed to Criscuolo, L..

2 recordsLinked to original sources

Isolation and characterization of synaptic structures from human neural organoids

Human neural organoids (NOs) provide a powerful platform for investigating synaptic development and dysfunction during early neurodevelopment. However, methodologies for isolating functional synaptic structures from these models remain limited. Here, we present a differential centrifugation protocol enabling the enrichment of growth cone particles (GCPs) and immature synaptosomes from air-liquid interface cerebral organoids (ALI-COs) at distinct developmental stages (day 90 and 150). Notably, the method avoids density gradients, requires minimal starting material while maintaining reproducibility across human and murine tissues. Quantitative proteomic profiling revealed significant enrichment of growth cone markers (e.g. GAP43) and classical synaptosomal proteins (e.g. PCLO, BSN, SYN1). Transmission electron microscopy (TEM) confirmed the presence of membrane-enclosed GCPs with fibrous content and mitochondria in day 90 isolates, and immature synaptosomes containing synaptic vesicles on day 150. Functional viability of both types of synaptic structures was demonstrated through KCl-induced depolarization, which triggered phosphorylation changes in growth cone proteins (GAP43, MARCKS, MARCKSL1), cytoskeletal regulators (DCLK1, SHTN1, MARK4, MAP1B) and protein kinases (CAMK2G, PRKCE) in day 90 GCPs, as well as classical synaptic vesicle cycle proteins (SYN1, DNM1, RPH3A) at day 150. Overall, this study establishes a centrifugation-based protocol for isolating growth cones and immature synapses from human organoids, capturing key stages of synaptic development and enabling scalable, patient-compatible models to study synaptic function and dysfunction in neurodevelopmental and neurodegenerative disorders.

neuroscience↗

Multi-omic analysis of guided and unguided forebrain organoids reveal differences in cellular composition and metabolic profiles

Neural organoids are invaluable model systems for studying neurodevelopment and neurological diseases. For this purpose, reproducible differentiation protocols are needed that minimize inter-organoid variability whilst generating neural organoids that physiologically resemble the brain area of interest. Currently, two main approaches are used: guided, where the differentiation towards neuroectoderm and subsequently specific CNS regions is driven by applying extrinsic signalling molecules, and unguided, where the intrinsic capability of pluripotent stem cells to generate neuroectoderm without external signalling is promoted. Despite the importance for the field, the resulting differences between these models have not been directly investigated. To obtain an unbiased comparison, we performed a multi-omic analysis of forebrain organoids generated using a guided and unguided approach focusing on proteomic, lipidomic and metabolomic differences. Furthermore, we characterised differences in phosphorylation and sialylation states of proteins, two key post-translational modifications (PTMs) in neurodevelopment, and performed single cell transcriptomics (scRNAseq). The multi-omic analysis revealed considerable differences in neuronal-, synaptic and glial content, indicating that guided forebrain organoids contain a larger proportion of neurons, including GABAergic interneurons, and synapses whereas unguided organoids contain significantly more GFAP+ cells and choroid plexus. Furthermore, substantial differences in mitochondrial- and metabolic profiles were identified, pointing to increased levels of oxidative phosphorylation and fatty acid {beta}-oxidation in unguided forebrain organoids and a higher reliance on glycolysis in guided forebrain organoids. Overall, our study comprises a thorough description of the multi-omic differences arising when generating guided and unguided forebrain organoids and provide an important resource for the organoid field studying neurodevelopment and -disease.

neuroscience↗