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Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus
Biomolecular 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 method...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10607852/ https://www.ncbi.nlm.nih.gov/pubmed/37894933 http://dx.doi.org/10.3390/ijms242015253 |
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author | Etibor, Temitope Akhigbe O’Riain, Aidan Alenquer, Marta Diwo, Christian Vale-Costa, Sílvia Amorim, Maria João |
author_facet | Etibor, Temitope Akhigbe O’Riain, Aidan Alenquer, Marta Diwo, Christian Vale-Costa, Sílvia Amorim, Maria João |
author_sort | Etibor, Temitope Akhigbe |
collection | PubMed |
description | Biomolecular 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. |
format | Online Article Text |
id | pubmed-10607852 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-106078522023-10-28 Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus Etibor, Temitope Akhigbe O’Riain, Aidan Alenquer, Marta Diwo, Christian Vale-Costa, Sílvia Amorim, Maria João Int J Mol Sci Article Biomolecular 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. MDPI 2023-10-17 /pmc/articles/PMC10607852/ /pubmed/37894933 http://dx.doi.org/10.3390/ijms242015253 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Etibor, Temitope Akhigbe O’Riain, Aidan Alenquer, Marta Diwo, Christian Vale-Costa, Sílvia Amorim, Maria João Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus |
title | Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus |
title_full | Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus |
title_fullStr | Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus |
title_full_unstemmed | Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus |
title_short | Challenges in Imaging Analyses of Biomolecular Condensates in Cells Infected with Influenza A Virus |
title_sort | challenges in imaging analyses of biomolecular condensates in cells infected with influenza a virus |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10607852/ https://www.ncbi.nlm.nih.gov/pubmed/37894933 http://dx.doi.org/10.3390/ijms242015253 |
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