Characterizing microglia activation: a spatial statistics approach to maximize information extraction

Abstract Microglia play an important role in the pathology of CNS disorders, however, there remains significant uncertainty about the neuroprotective/degenerative role of these cells due to a lack of techniques to adequately assess their complex behaviour in response to injury. Advancing microscopy...

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Autores principales:	Benjamin M. Davis, Manual Salinas-Navarro, M. Francesca Cordeiro, Lieve Moons, Lies De Groef
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c34719e8eca940e2b3b207e7b76f5dc6
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spelling	oai:doaj.org-article:c34719e8eca940e2b3b207e7b76f5dc62021-12-02T16:06:14ZCharacterizing microglia activation: a spatial statistics approach to maximize information extraction10.1038/s41598-017-01747-82045-2322https://doaj.org/article/c34719e8eca940e2b3b207e7b76f5dc62017-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-01747-8https://doaj.org/toc/2045-2322Abstract Microglia play an important role in the pathology of CNS disorders, however, there remains significant uncertainty about the neuroprotective/degenerative role of these cells due to a lack of techniques to adequately assess their complex behaviour in response to injury. Advancing microscopy techniques, transgenic lines and well-characterized molecular markers, have made histological assessment of microglia populations more accessible. However, there is a distinct lack of tools to adequately extract information from these images to fully characterise microglia behaviour. This, combined with growing economic pressures and the ethical need to minimise the use of laboratory animals, led us to develop tools to maximise the amount of information obtained. This study describes a novel approach, combining image analysis with spatial statistical techniques. In addition to monitoring morphological parameters and global changes in microglia density, nearest neighbour distance, and regularity index, we used cluster analyses based on changes in soma size and roundness to yield novel insights into the behaviour of different microglia phenotypes in a murine optic nerve injury model. These methods should be considered a generic tool to quantitatively assess microglia activation, to profile phenotypic changes into microglia subpopulations, and to map spatial distributions in virtually every CNS region and disease state.Benjamin M. DavisManual Salinas-NavarroM. Francesca CordeiroLieve MoonsLies De GroefNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-12 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Benjamin M. Davis Manual Salinas-Navarro M. Francesca Cordeiro Lieve Moons Lies De Groef Characterizing microglia activation: a spatial statistics approach to maximize information extraction
description	Abstract Microglia play an important role in the pathology of CNS disorders, however, there remains significant uncertainty about the neuroprotective/degenerative role of these cells due to a lack of techniques to adequately assess their complex behaviour in response to injury. Advancing microscopy techniques, transgenic lines and well-characterized molecular markers, have made histological assessment of microglia populations more accessible. However, there is a distinct lack of tools to adequately extract information from these images to fully characterise microglia behaviour. This, combined with growing economic pressures and the ethical need to minimise the use of laboratory animals, led us to develop tools to maximise the amount of information obtained. This study describes a novel approach, combining image analysis with spatial statistical techniques. In addition to monitoring morphological parameters and global changes in microglia density, nearest neighbour distance, and regularity index, we used cluster analyses based on changes in soma size and roundness to yield novel insights into the behaviour of different microglia phenotypes in a murine optic nerve injury model. These methods should be considered a generic tool to quantitatively assess microglia activation, to profile phenotypic changes into microglia subpopulations, and to map spatial distributions in virtually every CNS region and disease state.
format	article
author	Benjamin M. Davis Manual Salinas-Navarro M. Francesca Cordeiro Lieve Moons Lies De Groef
author_facet	Benjamin M. Davis Manual Salinas-Navarro M. Francesca Cordeiro Lieve Moons Lies De Groef
author_sort	Benjamin M. Davis
title	Characterizing microglia activation: a spatial statistics approach to maximize information extraction
title_short	Characterizing microglia activation: a spatial statistics approach to maximize information extraction
title_full	Characterizing microglia activation: a spatial statistics approach to maximize information extraction
title_fullStr	Characterizing microglia activation: a spatial statistics approach to maximize information extraction
title_full_unstemmed	Characterizing microglia activation: a spatial statistics approach to maximize information extraction
title_sort	characterizing microglia activation: a spatial statistics approach to maximize information extraction
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/c34719e8eca940e2b3b207e7b76f5dc6
work_keys_str_mv	AT benjaminmdavis characterizingmicrogliaactivationaspatialstatisticsapproachtomaximizeinformationextraction AT manualsalinasnavarro characterizingmicrogliaactivationaspatialstatisticsapproachtomaximizeinformationextraction AT mfrancescacordeiro characterizingmicrogliaactivationaspatialstatisticsapproachtomaximizeinformationextraction AT lievemoons characterizingmicrogliaactivationaspatialstatisticsapproachtomaximizeinformationextraction AT liesdegroef characterizingmicrogliaactivationaspatialstatisticsapproachtomaximizeinformationextraction
_version_	1718385113271631872

Characterizing microglia activation: a spatial statistics approach to maximize information extraction

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