Biology subjects

Mijalkov, M.

Publications and source records attributed to Mijalkov, M..

8 recordsLinked to original sources

bioRxiv2026

Brain mitovesicles undergo stage-specific remodelling during the progression of amyloid-β pathology

Mitochondrial dysfunction is an early feature of Alzheimer's disease that shows nonlinear changes as the disease progresses. However, how these changes are reflected in the mitochondrial material released by brain cells remains poorly understood. Mitovesicles are a recently described extracellular vesicle subpopulation of mitochondrial origin that provide a unique insight into mitochondrial alterations in the brain and could potentially show how nonlinear changes evolve across disease stages of amyloid-beta pathology. Here, we isolated forebrain-derived small extracellular vesicles and mitovesicles from wild-type and Amyloid precursor protein (App) knock-in (AppKI) mice, carrying familial AD mutations and progressively accumulating amyloid-beta plaques, at presymptomatic (2-month) and symptomatic (12-month) stages using high-resolution density gradient fractionation. Vesicle identity and composition were assessed by morphological, biophysical and quantitative proteomic analyses, and mitovesicle respiratory function was measured by extracellular flux analysis. We show that mitovesicles carry a distinct, predominantly mitochondrial inner membrane proteome that is remodelled by age and disease in a stage-specific manner. Compared with small extracellular vesicles, mitovesicle proteomic profiles captured disease progression more clearly, with symptomatic AppKI mice forming the most molecularly distinct group. At the presymptomatic stage, AppKI mitovesicles showed reduced mitochondrial protein representation, most notably of fatty acid {beta}-oxidation and lipid-metabolism proteins associated with astroglial and vascular signatures, preceding any detectable respiratory impairment. At the symptomatic stage this reversed: AppKI mitovesicles were enriched for oxidative phosphorylation, mitochondrial membrane and transporter proteins, yet showed reduced Complex IV-linked respiration, revealing a dissociation between mitochondrial cargo abundance and respiratory function. Selected cargo changes were not mirrored in whole-brain tissue, indicating selective remodelling of mitovesicle content. Comparison with mitovesicles from post-mortem human Alzheimer's disease frontotemporal cortex and hippocampus identified a conserved 62-protein mitovesicle core, dominated by oxidative phosphorylation subunits and mitochondrial carriers. In addition, 25 of these proteins were enriched in mitovesicles derived from Alzheimer's and AppKI forebrains, defining a conserved mitovesicular disease signature. Together, these findings establish forebrain-derived mitovesicles as a dynamically remodelled vesicle population that reflects progressive mitochondrial dysfunction in the Alzheimer's disease brain and provides a cross-species resource for future biomarker and mechanistic studies.

neuroscience↗

bioRxiv2026

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↗

bioRxiv2025

BRAPH 2: a flexible, open-source, reproducible, community-oriented, easy-to-use framework for network analyses in neurosciences

As network analyses in neuroscience continue to grow in both complexity and size, flexible methods are urgently needed to provide unbiased, reproducible insights into brain function. BRAPH 2 is a versatile, open-source framework that meets this challenge by offering streamlined workflows for advanced statistical models and deep learning in a community-oriented environment. Through its Genesis compiler, users can build specialized distributions with custom pipelines, ensuring flexibility and scalability across diverse research domains. These powerful capabilities will ensure reproducibility and accelerate discoveries in neuroscience.

neuroscience↗

bioRxiv2023

Linking structural and functional changes during aging using multilayer brain network analysis

Brain structure and function are intimately linked, however this association remains poorly understood of the complexity of this relationship has remained understudied. Healthy aging is characterized by heterogenous levels of structural integrity changes that influence functional network dynamics. Here, we used the multilayer brain network analysis on structural (diffusion tensor imaging) and functional (magnetoencephalography) data from the Cam-CAN database. We found that the level of similarity of connectivity patterns between brain structure and function in the parietal and temporal regions (alpha frequency band) was associated with cognitive performance in healthy older individuals. These results highlight the impact of structural connectivity changes on the reorganisation of functional connectivity associated with the preservation of cognitive function, and provide a mechanistic understanding of the concepts of brain maintenance and compensation with aging. Investigation of the link between structure and function could thus represent a new marker of individual variability, and of pathological changes.

neuroscience↗

bioRxiv2021

Directed brain connectivity identifies widespread functional network changes in Parkinson's disease

Parkinsons disease (PD) is a progressive neurodegenerative disorder characterized by topological changes in large-scale functional brain networks. These networks are commonly analysed using undirected correlations between the activation signals of brain regions. However, this approach suffers from an important drawback: it assumes that brain regions get activated at the same time, despite previous evidence showing that brain activation features causality, with signals being typically generated in one region and then propagated to other ones. Thus, in order to address this limitation, in this study we developed a new method to assess whole-brain directed functional connectivity in patients with PD and healthy controls using anti-symmetric delayed correlations, which capture better this underlying causality. To test the potential of this new method, we compared it to standard connectivity analyses based on undirected correlations. Our results show that whole-brain directed connectivity identifies widespread changes in the functional networks of PD patients compared to controls, in contrast to undirected methods. These changes are characterized by increased global efficiency, clustering and transitivity as well as lower modularity. In addition, changes in the directed connectivity patterns in the precuneus, thalamus and superior frontal gyrus were associated with motor, executive and memory deficits in PD patients. Altogether, these findings suggest that directional brain connectivity is more sensitive to functional network changes occurring in PD compared to standard methods. This opens new opportunities for the analysis of brain connectivity and the development of new brain connectivity markers to track PD progression.

neuroscience↗

bioRxiv2020

Dendritic spines are lost in clusters in patients with Alzheimers disease

Alzheimers disease (AD) is a progressive neurodegenerative disorder characterized by a deterioration of neuronal connectivity. The pathological accumulation of tau in neurons is one of the hallmarks of AD and has been connected to the loss of dendritic spines of pyramidal cells, which are the major targets of cortical excitatory synapses and key elements in memory storage. However, the detailed mechanisms underlying the loss of dendritic spines in individuals with AD are still unclear. Here, we used graph-theory approaches to compare the distribution of dendritic spines from neurons with and without tau pathology of AD individuals. We found that the presence of tau pathology determines the loss of dendritic spines in clusters, ruling out alternative models where spine loss occurs at random locations. Since memory storage has been associated with synaptic clusters, the present results provide a new insight into the mechanisms by which tau drives synaptic damage in AD, paving the way to memory deficits through alterations of spine organization.

neuroscience↗

bioRxiv2020

Age-related differences in network structure and dynamic synchrony of cognitive control

Cognitive trajectories vary greatly across older individuals, and the neural mechanisms underlying these differences remain poorly understood. Here, we propose a mechanistic framework of cognitive variability in older adults, linking the influence of white matter microstructure on fast and effective communications between brain regions. Using diffusion tensor imaging and electroencephalography, we show that individual differences in white matter network organization are associated with network clustering and efficiency in the alpha and high-gamma bands, and that functional network dynamics partly explain individual cognitive control performance in older adults. We show that older individuals with high versus low structural network clustering differ in task-related network dynamics and cognitive performance. These findings were corroborated by investigating magnetoencephalography networks in an independent dataset. This multimodal brain connectivity framework of individual differences provides a holistic account of how differences in white matter microstructure underlie age-related variability in dynamic network organization and cognitive performance.

neuroscience↗

bioRxiv2017

BRAPH: A Graph Theory Software for the Analysis of Brain Connectivity

The brain is a large-scale complex network whose workings rely on the interaction between its various regions. In the past few years, the organization of the human brain network has been studied extensively using concepts from graph theory, where the brain is represented as a set of nodes connected by edges. This representation of the brain as a connectome can be used to assess important measures that reflect its topological architecture. We have developed a freeware MatLab-based software (BRAPH - BRain Analysis using graPH theory) for connectivity analysis of brain networks derived from structural magnetic resonance imaging (MRI), functional MRI (fMRI), positron emission tomography (PET) and electroencephalogram (EEG) data. BRAPH allows building connectivity matrices, calculating global and local network measures, performing non-parametric permutations for group comparisons, assessing the modules in the network, and comparing the results to random networks. By contrast to other toolboxes, it allows performing longitudinal comparisons of the same patients across different points in time. Furthermore, even though a user-friendly interface is provided, the architecture of the program is modular (object-oriented) so that it can be easily expanded and customized. To demonstrate the abilities of BRAPH, we performed structural and functional graph theory analyses in two separate studies. In the first study, using MRI data, we assessed the differences in global and nodal network topology in healthy controls, patients with amnestic mild cognitive impairment, and patients with Alzheimers disease. In the second study, using resting-state fMRI data, we compared healthy controls and Parkinsons patients with mild cognitive impairment.

neuroscience↗