Biology subjects

Pereira, J. B.

Publications and source records attributed to Pereira, J. B..

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

Quantitative Multicolored Deep Imaging of Human Bones Reveals a Composite Osteo-Sinusoidal Niche for Mesenchymal Stromal Cells.

Human bone marrow mesenchymal stromal/stem cells (BM-MSCs) are widely utilized in clinical trials and tissue engineering; however, their native microenvironment remains poorly understood. Here, we introduced a tissue-clearing protocol for human bones and integrated it with simultaneous mRNA and protein detection. Using this protocol, named DeepBone, we spatially mapped BM-MSCs relative to key bone microenvironment components, including human blood capillaries, adipocytes, sinusoids, and bony trabeculae. Quantitative analysis revealed that the native microenvironment of human BM-MSCs in young bone is enriched in vasculature, sinusoids, bone matrix, and adipocytes. In contrast, in aged bone, BM-MSCs showed no preferential association with bone or adipocytes. Proliferative BM-MSCs were predominantly found along blood vessels. Moreover, we identified a specialized microenvironment for BM-MCs in young bone, characterized by sinusoids coiled around trabeculae and enriched by R-type vessels. These findings provide novel insights into the native niches of BM-MSCs, offering a foundation for the development of tissue-engineering strategies that mimic their physiological context.

cell biology↗

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

Medial temporal atrophy in preclinical dementia: visual and automated assessment during six year follow-up

AO_SCPLOWBSTRACTC_SCPLOWMedial temporal lobe (MTL) atrophy is an important morphological marker of many dementias and is closely related to cognitive decline. In this study we aimed to characterize longitudinal progression of MTL atrophy in 93 individuals with subjective cognitive decline and mild cognitive impairment followed up over six years, and to assess if clinical rating scales are able to detect these changes. All MRI images were visually rated according to Scheltens scale of medial temporal atrophy (MTA) by two neuroradiologists and AVRA, a software for automated MTA ratings. The images were also segmented using FreeSurfers longitudinal pipeline in order to compare the MTA ratings to volumes of the hippocampi and inferior lateral ventricles. We found that MTL atrophy rates increased with CSF biomarker abnormality, used to define preclinical stages of Alzheimers Disease. Both AVRAs and the radiologists MTA ratings showed a similar longitudinal trajectory as the subcortical volumes, suggesting that visual rating scales provide a valid alternative to automatic segmentations. While the MTA scores from each radiologist showed strong correlations to subcortical volumes, the inter-rater agreement was low. We conclude that the main limitation of quantifying MTL atrophy with visual ratings in clinics is the subjectiveness of the assessment.

neuroscience↗

bioRxiv2019

Fully Bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression

Tau pathology and regional brain atrophy are the closest correlate of cognitive decline in Alzheimers disease (AD). Understanding heterogeneity and longitudinal progression of brain atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that: 1) incorporates whole brain data, 2) leverages unequal visits per individual, 3) compares clusters with a control group, 4) allows to study confounding effects, 5) provides clusters visualization, 6) measures clustering uncertainty, all these simultaneously. We used amyloid-{beta} positive AD and negative healthy subjects, three longitudinal sMRI scans (cortical thickness and subcortical volume) over two years. We found 3 distinct longitudinal AD brain atrophy patterns: a typical diffuse pattern (n=34, 47.2%), and 2 atypical patterns: Minimal atrophy (n=23 31.9%) and Hippocampal sparing (n=9, 12.5%). We also identified outliers (n=3, 4.2%) and observations with uncertain classification (n=3, 4.2%). The clusters differed not only in regional distributions of atrophy at baseline, but also longitudinal atrophy progression, age at AD onset, and cognitive decline. A framework for the longitudinal assessment of variability in cohorts with several neuroimaging measures was successfully developed. We believe this framework may aid in disentangling distinct subtypes of AD from disease staging.

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↗