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Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics
The insect cell-baculovirus expression vector system (IC-BEVS) has been widely used to produce recombinant protein at high titers, including complex virus-like particles (VPLs). However, cell-to-cell variability upon infection is yet one of the least understood phenomena in virology, and little is k...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025388/ https://www.ncbi.nlm.nih.gov/pubmed/36949887 http://dx.doi.org/10.3389/fbioe.2023.1143255 |
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author | Silvano, Marco Virgolini, Nikolaus Correia, Ricardo Clarke, Colin Isidro, Inês A. Alves, Paula M. Roldão, António |
author_facet | Silvano, Marco Virgolini, Nikolaus Correia, Ricardo Clarke, Colin Isidro, Inês A. Alves, Paula M. Roldão, António |
author_sort | Silvano, Marco |
collection | PubMed |
description | The insect cell-baculovirus expression vector system (IC-BEVS) has been widely used to produce recombinant protein at high titers, including complex virus-like particles (VPLs). However, cell-to-cell variability upon infection is yet one of the least understood phenomena in virology, and little is known about its impact on production of therapeutic proteins. This study aimed at dissecting insect cell population heterogeneity during production of influenza VLPs in IC-BEVS using single-cell RNA-seq (scRNA-seq). High Five cell population was shown to be heterogeneous even before infection, with cell cycle being one of the factors contributing for this variation. In addition, infected insect cells were clustered according to the timing and level of baculovirus genes expression, with each cluster reporting similar influenza VLPs transgenes (i.e., hemagglutinin and M1) transcript counts. Trajectory analysis enabled to track infection progression throughout pseudotime. Specific pathways such as translation machinery, protein folding, sorting and degradation, endocytosis and energy metabolism were identified as being those which vary the most during insect cell infection and production of Influenza VLPs. Overall, this study lays the ground for the application of scRNA-seq in IC-BEVS processes to isolate relevant biological mechanisms during recombinant protein expression towards its further optimization. |
format | Online Article Text |
id | pubmed-10025388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100253882023-03-21 Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics Silvano, Marco Virgolini, Nikolaus Correia, Ricardo Clarke, Colin Isidro, Inês A. Alves, Paula M. Roldão, António Front Bioeng Biotechnol Bioengineering and Biotechnology The insect cell-baculovirus expression vector system (IC-BEVS) has been widely used to produce recombinant protein at high titers, including complex virus-like particles (VPLs). However, cell-to-cell variability upon infection is yet one of the least understood phenomena in virology, and little is known about its impact on production of therapeutic proteins. This study aimed at dissecting insect cell population heterogeneity during production of influenza VLPs in IC-BEVS using single-cell RNA-seq (scRNA-seq). High Five cell population was shown to be heterogeneous even before infection, with cell cycle being one of the factors contributing for this variation. In addition, infected insect cells were clustered according to the timing and level of baculovirus genes expression, with each cluster reporting similar influenza VLPs transgenes (i.e., hemagglutinin and M1) transcript counts. Trajectory analysis enabled to track infection progression throughout pseudotime. Specific pathways such as translation machinery, protein folding, sorting and degradation, endocytosis and energy metabolism were identified as being those which vary the most during insect cell infection and production of Influenza VLPs. Overall, this study lays the ground for the application of scRNA-seq in IC-BEVS processes to isolate relevant biological mechanisms during recombinant protein expression towards its further optimization. Frontiers Media S.A. 2023-03-06 /pmc/articles/PMC10025388/ /pubmed/36949887 http://dx.doi.org/10.3389/fbioe.2023.1143255 Text en Copyright © 2023 Silvano, Virgolini, Correia, Clarke, Isidro, Alves and Roldão. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Bioengineering and Biotechnology Silvano, Marco Virgolini, Nikolaus Correia, Ricardo Clarke, Colin Isidro, Inês A. Alves, Paula M. Roldão, António Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics |
title | Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics |
title_full | Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics |
title_fullStr | Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics |
title_full_unstemmed | Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics |
title_short | Dissecting insect cell heterogeneity during influenza VLP production using single-cell transcriptomics |
title_sort | dissecting insect cell heterogeneity during influenza vlp production using single-cell transcriptomics |
topic | Bioengineering and Biotechnology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10025388/ https://www.ncbi.nlm.nih.gov/pubmed/36949887 http://dx.doi.org/10.3389/fbioe.2023.1143255 |
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