---
OA_place: publisher
_id: '12378'
abstract:
- lang: eng
  text: "Environmental cues influence the highly dynamic morphology of microglia.
    Strategies to \r\ncharacterize these changes usually involve user-selected morphometric
    features, which \r\npreclude the identification of a spectrum of context-dependent
    morphological phenotypes. \r\nHere, we develop MorphOMICs, a topological data
    analysis approach, which enables semi\x02automatic mapping of microglial morphology
    into an atlas of cue-dependent phenotypes,\r\novercomes feature-selection bias
    and minimizes biological variability. \r\nFirst, with MorphOMICs we derive the
    morphological spectrum of microglia across seven \r\nbrain regions during postnatal
    development and in two distinct Alzheimer’s disease \r\ndegeneration mouse models.
    We uncover region-specific and sexually dimorphic\r\nmorphological trajectories,
    with females showing an earlier morphological shift than males in \r\nthe degenerating
    brain. Overall, we demonstrate that both long primary- and short terminal \r\nprocesses
    provide distinct insights to morphological phenotypes. Moreover, using machine
    \r\nlearning to map novel condition on the spectrum, we observe that microglia
    morphologies \r\nreflect a dose-dependent adaptation upon ketamine anesthesia
    and do not recover to control \r\nmorphologies.\r\nNext, we took advantage of
    MorphOMICs to build a high-resolution and layer-specific map of \r\nmicroglial
    morphological spectrum in the retina, covering postnatal development and rd10
    \r\ndegeneration. Here, following photoreceptor death, microglia assume an early
    development\x02like morphology. Finally, we map microglial morphology following
    optic nerve crush on the \r\nretinal spectrum and observe a layer- and sex-dependent
    response. \r\nOverall, MorphOMICs opens a new perspective to analyze microglial
    morphology across \r\nmultiple conditions, and provides a novel tool to characterize
    microglial morphology beyond \r\nthe traditionally dichotomized view of microglia."
acknowledged_ssus:
- _id: PreCl
- _id: Bio
- _id: ScienComp
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Gloria
  full_name: Colombo, Gloria
  id: 3483CF6C-F248-11E8-B48F-1D18A9856A87
  last_name: Colombo
  orcid: 0000-0001-9434-8902
citation:
  ama: Colombo G. MorphOMICs, a tool for mapping microglial morphology, reveals brain
    region- and sex-dependent phenotypes. 2022. doi:<a href="https://doi.org/10.15479/at:ista:12378">10.15479/at:ista:12378</a>
  apa: Colombo, G. (2022). <i>MorphOMICs, a tool for mapping microglial morphology,
    reveals brain region- and sex-dependent phenotypes</i>. Institute of Science and
    Technology Austria. <a href="https://doi.org/10.15479/at:ista:12378">https://doi.org/10.15479/at:ista:12378</a>
  chicago: Colombo, Gloria. “MorphOMICs, a Tool for Mapping Microglial Morphology,
    Reveals Brain Region- and Sex-Dependent Phenotypes.” Institute of Science and
    Technology Austria, 2022. <a href="https://doi.org/10.15479/at:ista:12378">https://doi.org/10.15479/at:ista:12378</a>.
  ieee: G. Colombo, “MorphOMICs, a tool for mapping microglial morphology, reveals
    brain region- and sex-dependent phenotypes,” Institute of Science and Technology
    Austria, 2022.
  ista: Colombo G. 2022. MorphOMICs, a tool for mapping microglial morphology, reveals
    brain region- and sex-dependent phenotypes. Institute of Science and Technology
    Austria.
  mla: Colombo, Gloria. <i>MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals
    Brain Region- and Sex-Dependent Phenotypes</i>. Institute of Science and Technology
    Austria, 2022, doi:<a href="https://doi.org/10.15479/at:ista:12378">10.15479/at:ista:12378</a>.
  short: G. Colombo, MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals
    Brain Region- and Sex-Dependent Phenotypes, Institute of Science and Technology
    Austria, 2022.
corr_author: '1'
date_created: 2023-01-25T14:27:43Z
date_published: 2022-11-11T00:00:00Z
date_updated: 2026-04-07T14:29:41Z
day: '11'
ddc:
- '570'
degree_awarded: PhD
department:
- _id: GradSch
- _id: SaSi
doi: 10.15479/at:ista:12378
ec_funded: 1
file:
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  creator: cchlebak
  date_created: 2023-01-25T14:31:32Z
  date_updated: 2023-04-12T22:30:03Z
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  file_name: Gloria_Colombo_Thesis.docx
  file_size: 23890382
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  date_updated: 2023-04-12T22:30:03Z
  embargo: 2023-04-11
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file_date_updated: 2023-04-12T22:30:03Z
has_accepted_license: '1'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '11'
oa: 1
oa_version: Published Version
page: '142'
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  issn:
  - 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
  record:
  - id: '12244'
    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Sandra
  full_name: Siegert, Sandra
  id: 36ACD32E-F248-11E8-B48F-1D18A9856A87
  last_name: Siegert
  orcid: 0000-0001-8635-0877
title: MorphOMICs, a tool for mapping microglial morphology, reveals brain region-
  and sex-dependent phenotypes
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: dissertation
user_id: ba8df636-2132-11f1-aed0-ed93e2281fdd
year: '2022'
...