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dc.contributor.authorColombo, Gloria
dc.contributor.authorCubero, Ryan John A
dc.contributor.authorKanari, Lida
dc.contributor.authorVenturino, Alessandro
dc.contributor.authorSchulz, Rouven
dc.contributor.authorScolamiero, Martina
dc.contributor.authorAgerberg, Jens
dc.contributor.authorMathys, Hansruedi
dc.contributor.authorTsai, Li-Huei
dc.contributor.authorChachólski, Wojciech
dc.contributor.authorHess, Kathryn
dc.contributor.authorSiegert, Sandra
dc.date.accessioned2023-04-04T17:56:05Z
dc.date.available2023-04-04T17:56:05Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/1721.1/150410
dc.description.abstract<jats:title>Abstract</jats:title><jats:p>Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes and overcomes feature-selection biases and biological variability. We extract spatially heterogeneous and sexually dimorphic morphological phenotypes for seven adult mouse brain regions. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration mouse models, with females showing a faster morphological shift in affected brain regions. Remarkably, microglia morphologies reflect an adaptation upon repeated exposure to ketamine anesthesia and do not recover to control morphologies. Finally, we demonstrate that both long primary processes and short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs opens a new perspective to characterize microglial morphology.</jats:p>en_US
dc.language.isoen
dc.publisherSpringer Science and Business Media LLCen_US
dc.relation.isversionof10.1038/S41593-022-01167-6en_US
dc.rightsCreative Commons Attribution 4.0 International licenseen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceNatureen_US
dc.titleA tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypesen_US
dc.typeArticleen_US
dc.identifier.citationColombo, Gloria, Cubero, Ryan John A, Kanari, Lida, Venturino, Alessandro, Schulz, Rouven et al. 2022. "A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes." Nature Neuroscience, 25 (10).
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.relation.journalNature Neuroscienceen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2023-04-04T17:48:07Z
dspace.orderedauthorsColombo, G; Cubero, RJA; Kanari, L; Venturino, A; Schulz, R; Scolamiero, M; Agerberg, J; Mathys, H; Tsai, L-H; Chachólski, W; Hess, K; Siegert, Sen_US
dspace.date.submission2023-04-04T17:48:26Z
mit.journal.volume25en_US
mit.journal.issue10en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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