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Baccino-Calace, M.

Publications and source records attributed to Baccino-Calace, M..

4 recordsLinked to original sources

A Normative Model Reveals Functional Optimization of Synaptic Nano-Architecture

Super-resolution microscopy approaches have revealed that synaptic proteins are not randomly distributed within individual synapses. Rather, they form sub-synaptic clusters that may be coordinated between the synaptic compartments, thereby forming transsynaptic nanocolumns. However, the functional significance of this nano-architecture remains under debate. In particular, it is unclear whether the positions of synaptic proteins optimize a specific cost function. Here, we present a normative modeling framework that integrates synaptic nano-architecture imaged with STED and dSTORM microscopy with synaptic transmission recorded with electrophysiology at the Drosophila neuromuscular junction (NMJ). Model-based quantification showed that clusters of Unc13A, which likely demark presynaptic release sites, and postsynaptic glutamate receptors (GluRs) adopt aligned ring-like arrangements in individual synapses. We developed an analytical description of GluR activation relative to presynaptic release position, enabling to link super-resolution imaging data with recorded postsynaptic current amplitudes without relying on costly Markov chain Monte Carlo (MCMC) simulations. Our model predicts that glutamate released from a single vesicle spreads across the entire receptor population. Given this spread, the postsynaptic current amplitude is maximized when glutamate is released close to the active zone (AZ) center, in contradiction to the observed offset of Unc13A clusters. However, the observed relative positions of Unc13A and GluR clusters maximize the postsynaptic current amplitude and minimize the delay between vesicle release and receptor activation during multivesicular release. Hence, transsynaptically-aligned Unc13A-GluR rings optimize for multivesicular but not univesicular release. Given that multivesicular release is mainly observed during enhanced presynaptic release at the Drosophila NMJ, transsynaptic nano-architecture may be adapted to elevated presynaptic release states.

neuroscience↗

Deep learning-based synaptic event detection

Quantitative information about synaptic transmission is key to our understanding of neural function. Spontaneously occurring synaptic events carry fundamental information about synaptic function and plasticity. However, their stochastic nature and low signal-to-noise ratio present major challenges for the reliable and consistent analysis. Here, we introduce miniML, a supervised deep learning- based method for accurate classification and automated detection of spontaneous synaptic events. Comparative analysis using simulated ground-truth data shows that miniML outperforms existing event analysis methods in terms of both precision and recall. miniML enables precise detection and quantification of synaptic events in electrophysiological recordings. We demonstrate that the deep learning approach generalizes easily to diverse synaptic preparations, different electrophysiological and optical recording techniques, and across animal species. miniML provides not only a comprehensive and robust framework for automated, reliable, and standardized analysis of synaptic events, but also opens new avenues for high-throughput investigations of neural function and dysfunction.

neuroscience↗

The E3 ligase Thin controls homeostatic plasticity through neurotransmitter release repression

Synaptic proteins and synaptic transmission are under homeostatic control, but the relationship between these two processes remains enigmatic. Here, we systematically investigated the role of E3 ligases, key regulators of protein degradation-mediated proteostasis, in presynaptic homeostatic plasticity (PHP). An electrophysiology-based genetic screen of 157 E3 ligase-encoding genes at the Drosophila neuromuscular junction identified thin, an ortholog of human tripartite motif-containing 32 (TRIM32), a gene implicated in several neural disorders, including Autism Spectrum Disorder and schizophrenia. We demonstrate that thin functions presynaptically during rapid and sustained PHP. Presynaptic thin negatively regulates neurotransmitter release under baseline conditions by limiting the number of release-ready vesicles, independent of gross morphological defects. We provide genetic evidence that thin controls release through dysbindin, a schizophrenia-susceptibility gene required for PHP. Thin and Dysbindin localize in close proximity within presynaptic boutons, and Thin degrades Dysbindin in vitro. Thus, the E3 ligase Thin links protein degradation-dependent proteostasis of Dysbindin to homeostatic regulation of neurotransmitter release.

neuroscience↗

Compartment and cell type-{-}specific hypoxia responses in the developing Drosophila brain

Environmental factors such as the availability of oxygen are instructive cues to regulate stem cell maintenance and differentiation. We used a genetically encoded biosensor to monitor the hypoxic state of neural cells in the larval brain of Drosophila. The biosensor reveals brain compartment and cell type specific levels of hypoxia. The values correlate with differential tracheolation that is observed throughout development between the central brain and the optic lobe. Neural stem cells in both compartments show the strongest hypoxia response while intermediate progenitors, neurons and glial cells reveal weaker responses. We demonstrate that the distance between a cell and the next closest tracheole is a good predictor of the hypoxic state for that cell. Our model concludes that oxygen availability is the major factor controlling the hypoxia response in the developing Drosophila brain but cell intrinsic and cell-type specific factors contribute to modulate the response in an unexpected manner.

developmental biology↗