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Screening human cell lines for viral infections applying RNA-Seq data analysis

Monitoring viral infections of cell cultures is largely neglected although the viruses may have an impact on the physiology of cells and may constitute a biohazard regarding laboratory safety and safety of bioactive agents produced by cell cultures. PCR, immunological assays, and enzyme activity tes...

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Detalles Bibliográficos
Autores principales: Uphoff, Cord C., Pommerenke, Claudia, Denkmann, Sabine A., Drexler, Hans G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328144/
https://www.ncbi.nlm.nih.gov/pubmed/30629668
http://dx.doi.org/10.1371/journal.pone.0210404
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author Uphoff, Cord C.
Pommerenke, Claudia
Denkmann, Sabine A.
Drexler, Hans G.
author_facet Uphoff, Cord C.
Pommerenke, Claudia
Denkmann, Sabine A.
Drexler, Hans G.
author_sort Uphoff, Cord C.
collection PubMed
description Monitoring viral infections of cell cultures is largely neglected although the viruses may have an impact on the physiology of cells and may constitute a biohazard regarding laboratory safety and safety of bioactive agents produced by cell cultures. PCR, immunological assays, and enzyme activity tests represent common methods to detect virus infections. We have screened more than 300 Cancer Cell Line Encyclopedia RNA sequencing and 60 whole exome sequencing human cell lines data sets for specific viral sequences and general viral nucleotide and protein sequence assessment applying the Taxonomer bioinformatics tool developed by IDbyDNA. The results were compared with our previous findings from virus specific PCR analyses. Both, the results obtained from the direct alignment method and the Taxonomer alignment method revealed a complete concordance with the PCR results: twenty cell lines were found to be infected with five virus species. Taxonomer further uncovered a bovine polyomavirus infection in the breast cancer cell line SK-BR-3 most likely introduced by contaminated fetal bovine serum. RNA-Seq data sets were more sensitive for virus detection although a significant proportion of cell lines revealed low numbers of virus specific alignments attributable to low level nucleotide contamination during RNA preparation or sequencing procedure. Low quality reads leading to Taxonomer false positive results can be eliminated by trimming the sequence data before analysis. One further important result is that no viruses were detected that had never been shown to occur in cell cultures. The results prove that the currently applied testing of cell cultures is adequate for the detection of contamination and for the risk assessment of cell cultures. The results emphasize that next generation sequencing is an efficient tool to determine the viral infection status of human cells.
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spelling pubmed-63281442019-02-01 Screening human cell lines for viral infections applying RNA-Seq data analysis Uphoff, Cord C. Pommerenke, Claudia Denkmann, Sabine A. Drexler, Hans G. PLoS One Research Article Monitoring viral infections of cell cultures is largely neglected although the viruses may have an impact on the physiology of cells and may constitute a biohazard regarding laboratory safety and safety of bioactive agents produced by cell cultures. PCR, immunological assays, and enzyme activity tests represent common methods to detect virus infections. We have screened more than 300 Cancer Cell Line Encyclopedia RNA sequencing and 60 whole exome sequencing human cell lines data sets for specific viral sequences and general viral nucleotide and protein sequence assessment applying the Taxonomer bioinformatics tool developed by IDbyDNA. The results were compared with our previous findings from virus specific PCR analyses. Both, the results obtained from the direct alignment method and the Taxonomer alignment method revealed a complete concordance with the PCR results: twenty cell lines were found to be infected with five virus species. Taxonomer further uncovered a bovine polyomavirus infection in the breast cancer cell line SK-BR-3 most likely introduced by contaminated fetal bovine serum. RNA-Seq data sets were more sensitive for virus detection although a significant proportion of cell lines revealed low numbers of virus specific alignments attributable to low level nucleotide contamination during RNA preparation or sequencing procedure. Low quality reads leading to Taxonomer false positive results can be eliminated by trimming the sequence data before analysis. One further important result is that no viruses were detected that had never been shown to occur in cell cultures. The results prove that the currently applied testing of cell cultures is adequate for the detection of contamination and for the risk assessment of cell cultures. The results emphasize that next generation sequencing is an efficient tool to determine the viral infection status of human cells. Public Library of Science 2019-01-10 /pmc/articles/PMC6328144/ /pubmed/30629668 http://dx.doi.org/10.1371/journal.pone.0210404 Text en © 2019 Uphoff et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Uphoff, Cord C.
Pommerenke, Claudia
Denkmann, Sabine A.
Drexler, Hans G.
Screening human cell lines for viral infections applying RNA-Seq data analysis
title Screening human cell lines for viral infections applying RNA-Seq data analysis
title_full Screening human cell lines for viral infections applying RNA-Seq data analysis
title_fullStr Screening human cell lines for viral infections applying RNA-Seq data analysis
title_full_unstemmed Screening human cell lines for viral infections applying RNA-Seq data analysis
title_short Screening human cell lines for viral infections applying RNA-Seq data analysis
title_sort screening human cell lines for viral infections applying rna-seq data analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6328144/
https://www.ncbi.nlm.nih.gov/pubmed/30629668
http://dx.doi.org/10.1371/journal.pone.0210404
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