MIC-MAC: An automated pipeline for high-throughput characterization and classification of three-dimensional microglia morphologies in mouse and human postmortem brain samples.


Journal

Glia
ISSN: 1098-1136
Titre abrégé: Glia
Pays: United States
ID NLM: 8806785

Informations de publication

Date de publication:
08 2019
Historique:
received: 17 12 2018
revised: 21 02 2019
accepted: 29 03 2019
pubmed: 16 4 2019
medline: 11 2 2020
entrez: 16 4 2019
Statut: ppublish

Résumé

The phenotypic changes of microglia in brain diseases are particularly diverse and their role in disease progression, beneficial, or detrimental, is still elusive. High-throughput molecular approaches such as single-cell RNA-sequencing can now resolve the high heterogeneity in microglia population for a specific physiological condition, however, the relation between the different microglial signatures and their surrounding brain microenvironment is barely understood. Thus, better tools to characterize the phenotypic variations of microglia in situ are needed, particularly for human brain postmortem samples analysis. To address this challenge, we developed MIC-MAC, a Microglia and Immune Cells Morphologies Analyser and Classifier pipeline that semiautomatically segments, extracts, and classifies all microglia and immune cells labeled in large three-dimensional (3D) confocal image stacks of mouse and human brain samples. Our imaging-based approach enables automatic 3D-morphology characterization and classification of thousands of individual microglia in situ and revealed species- and disease-specific morphological phenotypes in mouse aging, human Alzheimer's disease, and dementia with Lewy Bodie's samples. MIC-MAC is a precision diagnostic tool that allows a rapid, unbiased, and large-scale analysis of microglia morphological states in mouse models and patient brain samples.

Identifiants

pubmed: 30983036
doi: 10.1002/glia.23623
pmc: PMC6617786
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1496-1509

Subventions

Organisme : National Biomedical Computation Resource (NIH)
ID : NIH P41 GM103426
Pays : International

Informations de copyright

© 2019 The Authors. Glia published by Wiley Periodicals, Inc.

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Auteurs

Luis Salamanca (L)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.
Swiss Data Science Center, ETH Zürich, Zürich, Switzerland.

Naguib Mechawar (N)

Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, Quebec, Canada.

Keith K Murai (KK)

Centre for Research in Neuroscience, Department of Neurology and Neurosurgery, The Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, Quebec, Canada.

Rudi Balling (R)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.

David S Bouvier (DS)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.

Alexander Skupin (A)

Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.
National Biomedical Computation Resource, University California San Diego, La Jolla, California.

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