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A phenomics approach for antiviral drug discovery
BACKGROUND: The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to fo...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325993/ https://www.ncbi.nlm.nih.gov/pubmed/34334126 http://dx.doi.org/10.1186/s12915-021-01086-1 |
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author | Rietdijk, Jonne Tampere, Marianna Pettke, Aleksandra Georgiev, Polina Lapins, Maris Warpman-Berglund, Ulrika Spjuth, Ola Puumalainen, Marjo-Riitta Carreras-Puigvert, Jordi |
author_facet | Rietdijk, Jonne Tampere, Marianna Pettke, Aleksandra Georgiev, Polina Lapins, Maris Warpman-Berglund, Ulrika Spjuth, Ola Puumalainen, Marjo-Riitta Carreras-Puigvert, Jordi |
author_sort | Rietdijk, Jonne |
collection | PubMed |
description | BACKGROUND: The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates. Here we present a method able to assess the general health of host cells based on morphological profiling, for untargeted phenotypic drug screening against viral infections. RESULTS: We combine Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that this methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. CONCLUSIONS: The phenomics approach presented here, which makes use of a modified Cell Painting protocol by incorporating an anti-virus antibody stain, can be used for the unbiased morphological profiling of virus infection on host cells. The method can identify antiviral reference compounds, as well as novel antivirals, demonstrating its suitability to be implemented as a strategy for antiviral drug repurposing and drug discovery. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01086-1. |
format | Online Article Text |
id | pubmed-8325993 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83259932021-08-02 A phenomics approach for antiviral drug discovery Rietdijk, Jonne Tampere, Marianna Pettke, Aleksandra Georgiev, Polina Lapins, Maris Warpman-Berglund, Ulrika Spjuth, Ola Puumalainen, Marjo-Riitta Carreras-Puigvert, Jordi BMC Biol Methodology Article BACKGROUND: The emergence and continued global spread of the current COVID-19 pandemic has highlighted the need for methods to identify novel or repurposed therapeutic drugs in a fast and effective way. Despite the availability of methods for the discovery of antiviral drugs, the majority tend to focus on the effects of such drugs on a given virus, its constituent proteins, or enzymatic activity, often neglecting the consequences on host cells. This may lead to partial assessment of the efficacy of the tested anti-viral compounds, as potential toxicity impacting the overall physiology of host cells may mask the effects of both viral infection and drug candidates. Here we present a method able to assess the general health of host cells based on morphological profiling, for untargeted phenotypic drug screening against viral infections. RESULTS: We combine Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties. We show that this methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state. CONCLUSIONS: The phenomics approach presented here, which makes use of a modified Cell Painting protocol by incorporating an anti-virus antibody stain, can be used for the unbiased morphological profiling of virus infection on host cells. The method can identify antiviral reference compounds, as well as novel antivirals, demonstrating its suitability to be implemented as a strategy for antiviral drug repurposing and drug discovery. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-021-01086-1. BioMed Central 2021-08-02 /pmc/articles/PMC8325993/ /pubmed/34334126 http://dx.doi.org/10.1186/s12915-021-01086-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Methodology Article Rietdijk, Jonne Tampere, Marianna Pettke, Aleksandra Georgiev, Polina Lapins, Maris Warpman-Berglund, Ulrika Spjuth, Ola Puumalainen, Marjo-Riitta Carreras-Puigvert, Jordi A phenomics approach for antiviral drug discovery |
title | A phenomics approach for antiviral drug discovery |
title_full | A phenomics approach for antiviral drug discovery |
title_fullStr | A phenomics approach for antiviral drug discovery |
title_full_unstemmed | A phenomics approach for antiviral drug discovery |
title_short | A phenomics approach for antiviral drug discovery |
title_sort | phenomics approach for antiviral drug discovery |
topic | Methodology Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8325993/ https://www.ncbi.nlm.nih.gov/pubmed/34334126 http://dx.doi.org/10.1186/s12915-021-01086-1 |
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