Phenotypic clustering: a novel method for microglial morphology analysis

Detalhes bibliográficos
Autor(a) principal: Verdonk, Franck
Data de Publicação: 2016
Outros Autores: Roux, Pascal, Flamant, Patricia, Fiette, Laurence, Bozza, Fernando A., Simard, Sébastien, Lemaire, Marc, Plaud, Benoit, Shorte, Spencer L., Sharshar, Tarek, Chrétien, Fabrice, Danckaert, Anne
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da FIOCRUZ (ARCA)
Texto Completo: https://www.arca.fiocruz.br/handle/icict/32564
Resumo: Institut Pasteur. Infection and Epidemiology Department. Human Histopathology and Animal Models Unit. Paris, France / Air Liquide Santé International. World Business Line Healthcare. Medical R&D. Jouy-en-Josas, France / Paris Descartes University. Paris, France / TRIGGERSEP, F-CRIN Network, Toulouse, France.
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spelling Verdonk, FranckRoux, PascalFlamant, PatriciaFiette, LaurenceBozza, Fernando A.Simard, SébastienLemaire, MarcPlaud, BenoitShorte, Spencer L.Sharshar, TarekChrétien, FabriceDanckaert, Anne2019-04-17T21:03:14Z2019-04-17T21:03:14Z2016VERDONK, Franck et al. Phenotypic clustering: a novel method for microglial morphology analysis. Journal of Neuroinflammation, v. 13, p. 1-15, 2016.1742-2094https://www.arca.fiocruz.br/handle/icict/3256410.1186/s12974-016-0614-7engBMCPhenotypic clustering: a novel method for microglial morphology analysisinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleInstitut Pasteur. Infection and Epidemiology Department. Human Histopathology and Animal Models Unit. Paris, France / Air Liquide Santé International. World Business Line Healthcare. Medical R&D. Jouy-en-Josas, France / Paris Descartes University. Paris, France / TRIGGERSEP, F-CRIN Network, Toulouse, France.Institut Pasteur, Imagopole. CITech. Paris, France.Institut Pasteur. Infection and Epidemiology Department. Human Histopathology and Animal Models Unit. Paris, France.Institut Pasteur. Infection and Epidemiology Department. Human Histopathology and Animal Models Unit. Paris, France.Fundação Oswaldo Cruz. Instituto de Pesquisa Clínica Evandro Chagas. Rio de Janeiro, RJ, Brasil.Institut Pasteur, Imagopole. CITech. Paris, France.Air Liquide Santé International. World Business Line Healthcare. Medical R&D. Paris-Saclay Research Center. Jouy-en-Josas, France.Saint-Louis University Hospital of Paris. Department of Anaesthesiology and Surgical Intensive Care. Paris, France / Paris Diderot University, Paris, France.Institut Pasteur, Imagopole. CITech. Paris, France.Institut Pasteur. Infection and Epidemiology Department. Human Histopathology and Animal Models Unit. Paris, France / Raymond Poincare University Hospital. Department of Intensive Care. Garches, France / Versailles Saint Quentin University. Versailles, France / TRIGGERSEP, F-CRIN Networ. Toulouse, France.Institut Pasteur. Infection and Epidemiology Department. Human Histopathology and Animal Models Unit. Paris, France / Centre Hospitalier Sainte Anne. Laboratoire hospitalo-universitaire de Neuropathologie. Paris, France / Paris Descartes University. Paris, France / TRIGGERSEP, F-CRIN Networ. Toulouse, France.Institut Pasteur, Imagopole. CITech. Paris, France.Background: Microglial cells are tissue-resident macrophages of the central nervous system. They are extremely dynamic, sensitive to their microenvironment and present a characteristic complex and heterogeneous morphology and distribution within the brain tissue. Many experimental clues highlight a strong link between their morphology and their function in response to aggression. However, due to their complex “dendritic-like” aspect that constitutes the major pool of murine microglial cells and their dense network, precise and powerful morphological studies are not easy to realize and complicate correlation with molecular or clinical parameters. Methods: Using the knock-in mouse model CX3CR1GFP/+, we developed a 3D automated confocal tissue imaging system coupled with morphological modelling of many thousands of microglial cells revealing precise and quantitative assessment of major cell features: cell density, cell body area, cytoplasm area and number of primary, secondary and tertiary processes. We determined two morphological criteria that are the complexity index (CI) and the covered environment area (CEA) allowing an innovative approach lying in (i) an accurate and objective study of morphological changes in healthy or pathological condition, (ii) an in situ mapping of the microglial distribution in different neuroanatomical regions and (iii) a study of the clustering of numerous cells, allowing us to discriminate different sub-populations. Results: Our results on more than 20,000 cells by condition confirm at baseline a regional heterogeneity of the microglial distribution and phenotype that persists after induction of neuroinflammation by systemic injection of lipopolysaccharide (LPS). Using clustering analysis, we highlight that, at resting state, microglial cells are distributed in four microglial sub-populations defined by their CI and CEA with a regional pattern and a specific behaviour after challenge. Conclusions: Our results counteract the classical view of a homogenous regional resting state of the microglial cells within the brain. Microglial cells are distributed in different defined sub-populations that present specific behaviour after pathological challenge, allowing postulating for a cellular and functional specialization. Moreover, this new experimental approach will provide a support not only to neuropathological diagnosis but also to study microglial function in various disease models while reducing the number of animals needed to approach the international ethical statements.Microglial cell morphologyNeuroinflammationAutomated high-content analysisClusteringSub-population behaviourComplexity indexinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da FIOCRUZ (ARCA)instname:Fundação Oswaldo Cruz (FIOCRUZ)instacron:FIOCRUZLICENSElicense.txtlicense.txttext/plain; charset=utf-83104https://www.arca.fiocruz.br/bitstream/icict/32564/1/license.txt79178e5f2a0eb066867a274556814938MD51ORIGINALve_ Verdonk_Franck_etal_INI_2016.pdfve_ Verdonk_Franck_etal_INI_2016.pdfapplication/pdf2064033https://www.arca.fiocruz.br/bitstream/icict/32564/2/ve_%20Verdonk_Franck_etal_INI_2016.pdf5e95f29faa0422ef558eafdff303ba77MD52TEXTve_ Verdonk_Franck_etal_INI_2016.pdf.txtve_ 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dc.title.pt_BR.fl_str_mv Phenotypic clustering: a novel method for microglial morphology analysis
title Phenotypic clustering: a novel method for microglial morphology analysis
spellingShingle Phenotypic clustering: a novel method for microglial morphology analysis
Verdonk, Franck
Microglial cell morphology
Neuroinflammation
Automated high-content analysis
Clustering
Sub-population behaviour
Complexity index
title_short Phenotypic clustering: a novel method for microglial morphology analysis
title_full Phenotypic clustering: a novel method for microglial morphology analysis
title_fullStr Phenotypic clustering: a novel method for microglial morphology analysis
title_full_unstemmed Phenotypic clustering: a novel method for microglial morphology analysis
title_sort Phenotypic clustering: a novel method for microglial morphology analysis
author Verdonk, Franck
author_facet Verdonk, Franck
Roux, Pascal
Flamant, Patricia
Fiette, Laurence
Bozza, Fernando A.
Simard, Sébastien
Lemaire, Marc
Plaud, Benoit
Shorte, Spencer L.
Sharshar, Tarek
Chrétien, Fabrice
Danckaert, Anne
author_role author
author2 Roux, Pascal
Flamant, Patricia
Fiette, Laurence
Bozza, Fernando A.
Simard, Sébastien
Lemaire, Marc
Plaud, Benoit
Shorte, Spencer L.
Sharshar, Tarek
Chrétien, Fabrice
Danckaert, Anne
author2_role author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Verdonk, Franck
Roux, Pascal
Flamant, Patricia
Fiette, Laurence
Bozza, Fernando A.
Simard, Sébastien
Lemaire, Marc
Plaud, Benoit
Shorte, Spencer L.
Sharshar, Tarek
Chrétien, Fabrice
Danckaert, Anne
dc.subject.en.pt_BR.fl_str_mv Microglial cell morphology
Neuroinflammation
Automated high-content analysis
Clustering
Sub-population behaviour
Complexity index
topic Microglial cell morphology
Neuroinflammation
Automated high-content analysis
Clustering
Sub-population behaviour
Complexity index
description Institut Pasteur. Infection and Epidemiology Department. Human Histopathology and Animal Models Unit. Paris, France / Air Liquide Santé International. World Business Line Healthcare. Medical R&D. Jouy-en-Josas, France / Paris Descartes University. Paris, France / TRIGGERSEP, F-CRIN Network, Toulouse, France.
publishDate 2016
dc.date.issued.fl_str_mv 2016
dc.date.accessioned.fl_str_mv 2019-04-17T21:03:14Z
dc.date.available.fl_str_mv 2019-04-17T21:03:14Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.citation.fl_str_mv VERDONK, Franck et al. Phenotypic clustering: a novel method for microglial morphology analysis. Journal of Neuroinflammation, v. 13, p. 1-15, 2016.
dc.identifier.uri.fl_str_mv https://www.arca.fiocruz.br/handle/icict/32564
dc.identifier.issn.pt_BR.fl_str_mv 1742-2094
dc.identifier.doi.none.fl_str_mv 10.1186/s12974-016-0614-7
identifier_str_mv VERDONK, Franck et al. Phenotypic clustering: a novel method for microglial morphology analysis. Journal of Neuroinflammation, v. 13, p. 1-15, 2016.
1742-2094
10.1186/s12974-016-0614-7
url https://www.arca.fiocruz.br/handle/icict/32564
dc.language.iso.fl_str_mv eng
language eng
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dc.publisher.none.fl_str_mv BMC
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dc.source.none.fl_str_mv reponame:Repositório Institucional da FIOCRUZ (ARCA)
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instacron_str FIOCRUZ
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