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Alarcon-Gil, J.

Publications and source records attributed to Alarcon-Gil, J..

2 recordsLinked to original sources

Astrocyte-neuron mitochondrial transfer via mitoEVs supports neuronal energy metabolism and is impaired in early Alzheimer's disease

BackgroundMitochondrial dysfunction is an early and central feature of Alzheimers disease (AD). In particular, intercellular mitochondrial transfer has emerged as a mechanism of neuronal support in brain injury and neurodegeneration. However, pathways governing astrocyte-to-neuron transfer and its role in AD pathogenesis remain unknown. MethodsUsing the AppNL-G-F knock-in AD model, we combined high-resolution 4D live-cell imaging with quantitative fluorescence-based reporters to assess synaptic function and mitochondrial network dynamics in neurons and astrocytes. Direct and extracellular vesicle (EV)-restricted neuron-astrocyte co-culture systems were used to investigate bidirectional mitochondrial transfer. We performed the first in-depth structural, proteomic, and functional characterization of astrocyte-derived mitochondrial extracellular vesicles (mitoEVs) using cryo-electron microscopy, quantitative mass spectrometry, and bioenergetic analyses to define their cargo composition and metabolic effects. ResultsWe identified cell-type-specific mitochondrial remodeling in early AD, with compartmentalized synaptic energy deficits in neurons and hyperdynamic, less interconnected, yet metabolically preserved networks in astrocytes, preceding global bioenergetic decline. Bidirectional mitochondrial transfer between astrocytes and neurons, also at axonal terminals, was mediated by specialized mitoEVs but significantly reduced in the AppNL-G-Fmodel. Comprehensive proteomic and functional profiling revealed that WT astrocyte-derived mitoEVs are enriched in inner membrane and matrix proteins, supporting oxidative phosphorylation, lipid and amino acid metabolism, and redox homeostasis. In contrast, AppNL-G-F mitoEVs are selectively depleted of respiratory and fatty acid oxidation components and exhibit impaired respiration with reduced Complex IV activity. Functionally, WT mitoEVs promote mobilization of abnormal accumulation of lipid droplets in AppNL-G-Fneurons, restore fatty acid oxidation, and increase neuronal bioenergetics, including at the synapses. In contrast, disease-derived mitoEVs fail to engage these pathways. ConclusionsTogether, these findings identify mitoEV-mediated mitochondrial transfer as a glia-to-neuron metabolic pathway compromised in early AD and reveal a coordinated role for oxidative phosphorylation and fatty acid oxidation in supporting synaptic energy homeostasis.

neuroscience↗

fluxTrAM: Integration of tracer-based metabolomics data into atomically resolved genome-scale metabolic networks for metabolic flux analysis

Quantitative inference of intracellular reaction rates is essential for characterising metabolic phenotypes. The classical experimental method for measuring metabolic fluxes makes use of stable-isotope tracing of metabolites through the metabolic network, followed by mass spectrometry analysis. The most common 13C-based metabolic flux analysis requires multidisciplinary knowledge in analytical chemistry, cell biology, and mathematical modelling, as well as the use of multiple independent tools for handling mass spectrometry data. Besides, flux analysis is usually carried out within a small network to validate a specific biological hypothesis. To overcome interdisciplinary barriers and extend flux interpretation towards a genome-scale level, we developed fluxTrAM, a semi-automated pipeline for processing tracer- based metabolomics data and integrating it with atomically resolved genome-scale metabolic networks to enable flux predictions at genome-scale. fluxTrAM integrates different software packages inside and outside of the COBRA Toolbox v3.4 for the generation of metabolite structure and reaction databases for a genome-scale model, labelled mass spectrometry data processing into standardised mass isotopologue distribution data (MID), and metabolic flux analysis. To demonstrate the utility of this pipeline, we generated 13C-labeled metabolomics data on an in vitro human induced pluripotent stem cell (iPSC)-derived dopaminergic neuronal culture and processed 13C-labeled MID datasets. In parallel, we generated a cheminformatic database of standardised and context-specific metabolite structures, and atom-mapped reactions for a genome-scale dopaminergic neuronal metabolic model. MID data could be exported into established flux inference software for conventional flux inference on a core model scale. It could also be integrated into the atomically resolved metabolic model for flux inference at genome-scale using moiety fluxomics method. The core model flux solution and moiety flux solution were then compared to two additional flux solutions predicted via flux balance analysis and entropic flux balance analysis. The extensive computational flux analysis and comparison helped to better evaluate the obtained flux feasibility of the neuron-specific genome-scale model and suggested new tracer-based metabolomics experiments with novel labeling configurations, such as labelling a moiety within the thymidine metabolite. Overall, fluxTrAM enables the automation of labelled liquid chromatography (LC)-mass spectrometry (MS) data processing into MID datasets and atom mapping for any given genome-scale metabolic model. It contributes to the standardisation and high throughput of metabolic flux analysis at genome- scale.

systems biology↗