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Challenges in imaging analyses of biomolecular condensates in cells infected with influenza A virus

dc.contributor.authorEtibor, Temitope Akhigbe
dc.contributor.authorO’Riain, Aidan
dc.contributor.authorAlenquer, Marta
dc.contributor.authorDiwo, Christian
dc.contributor.authorVale-Costa, Sílvia
dc.contributor.authorAmorim, Maria João
dc.date.accessioned2023-10-31T11:07:18Z
dc.date.available2023-10-31T11:07:18Z
dc.date.issued2023
dc.description.abstractBiomolecular condensates are crucial compartments within cells, relying on their material properties for function. They form and persist through weak, transient interactions, often undetectable by classical biochemical approaches. Hence, microscopy-based techniques have been the most reliable methods to detail the molecular mechanisms controlling their formation, material properties, and alterations, including dissolution or phase transitions due to cellular manipulation and disease, and to search for novel therapeutic strategies targeting biomolecular condensates. However, technical challenges in microscopy-based analysis persist. This paper discusses imaging, data acquisition, and analytical methodologies’ advantages, challenges, and limitations in determining biophysical parameters explaining biomolecular condensate formation, dissolution, and phase transitions. In addition, we mention how machine learning is increasingly important for efficient image analysis, teaching programs what a condensate should resemble, aiding in the correlation and interpretation of information from diverse data sources. Influenza A virus forms liquid viral inclusions in the infected cell cytosol that serve as model biomolecular condensates for this study. Our previous work showcased the possibility of hardening these liquid inclusions, potentially leading to novel antiviral strategies. This was established using a framework involving live cell imaging to measure dynamics, internal rearrangement capacity, coalescence, and relaxation time. Additionally, we integrated thermodynamic characteristics by analysing fixed images through Z-projections. The aforementioned paper laid the foundation for this subsequent technical paper, which explores how different modalities in data acquisition and processing impact the robustness of results to detect bona fide phase transitions by measuring thermodynamic traits in fixed cells. Using solely this approach would greatly simplify screening pipelines. For this, we tested how single focal plane images, Z-projections, or volumetric analyses of images stained with antibodies or live tagged proteins altered the quantification of thermodynamic measurements. Customizing methodologies for different biomolecular condensates through advanced bioimaging significantly contributes to biological research and potential therapeutic advancements.
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.doi10.3390/ijms242015253pt_PT
dc.identifier.eid85175276088
dc.identifier.issn1661-6596
dc.identifier.pmcPMC10607852
dc.identifier.pmid37894933
dc.identifier.urihttp://hdl.handle.net/10400.14/42937
dc.identifier.wos001095361300001
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectBiomolecular condensatespt_PT
dc.subjectImagingpt_PT
dc.subjectVirologypt_PT
dc.subjectInfluenza A viruspt_PT
dc.titleChallenges in imaging analyses of biomolecular condensates in cells infected with influenza A viruspt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.issue20pt_PT
oaire.citation.titleInternational Journal of Molecular Sciencespt_PT
oaire.citation.volume24pt_PT
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT

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