A phenomics approach for antiviral drug discovery.
Antiviral
Cell Painting
Drug discovery
Morphological profiling
Phenomics
Journal
BMC biology
ISSN: 1741-7007
Titre abrégé: BMC Biol
Pays: England
ID NLM: 101190720
Informations de publication
Date de publication:
02 08 2021
02 08 2021
Historique:
received:
10
03
2021
accepted:
08
07
2021
entrez:
2
8
2021
pubmed:
3
8
2021
medline:
10
8
2021
Statut:
epublish
Résumé
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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 34334126
doi: 10.1186/s12915-021-01086-1
pii: 10.1186/s12915-021-01086-1
pmc: PMC8325993
doi:
Substances chimiques
Antiviral Agents
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
156Subventions
Organisme : Knut och Alice Wallenbergs Stiftelse
ID : KAW 2020.0182
Organisme : Vetenskapsrådet
ID : 2017-05631
Organisme : Vetenskapsrådet
ID : 2020-03731
Organisme : Svenska Forskningsrådet Formas
ID : 2018-00924
Organisme : H2020 Marie Skłodowska-Curie Actions
ID : 722729
Organisme : Stiftelsen för Strategisk Forskning
ID : FID15-0010
Informations de copyright
© 2021. The Author(s).
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