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

TitleMIC-MAC: An automated pipeline for high-throughput characterization and classification of three-dimensional microglia morphologies in mouse and human postmortem brain samples.
Publication TypeJournal Article
Year of Publication2019
AuthorsSalamanca L, Mechawar N, Murai KK, Balling R, Bouvier DS, Skupin A
JournalGlia
Volume67
Issue8
Pagination1496-1509
Date Published2019 Aug
ISSN1098-1136
Abstract

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.

DOI10.1002/glia.23623
Alternate JournalGlia
PubMed ID30983036
PubMed Central IDPMC6617786
Grant List / / Auguste et Simone Prévot foundation award /
C14/BM/7975668/CaSCAD / / Fonds National de la Recherche Luxembourg /
/ / Luxembourgish Espoir-en-Tête Rotary Club award /
NIH P41 GM103426 / / National Biomedical Computation Resource (NIH) /

  • Douglas Hospital
  • Dobell Pavillion
  • Brain imaging centre