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Virus contaminations of cell cultures – A biotechnological view
Open accessAbstract
In contrast to contamination by microbes and mycoplasma, which can be relatively easily detected, viral contamination present a serious threat because of the difficulty in detecting some viruses and the lack of effective methods of treating infected cell cultures. While some viruses are capable of causing morphological changes to infected cells (e.g. cytopathic effect) which are detectable by microscopy some viral contaminations result in the integration of the viral genome as provirus, this causes no visual evidence, by means of modification of the cellular morphology. Virus production from such cell lines, are potentially dangerous for other cell cultures (in research labs)by cross contaminations, or for operators and patients (in the case of the production of injectable biologicals) because of potential infection. The only way to keep cell cultures for research, development, and the biotech industry virus-free is the prevention of such contaminations. Cell cultures can become contaminated by the following means: firstly, they may already be contaminated as primary cultures (because the source of the cells was already infected), secondly, they were contaminated due to the use of contaminated raw materials, or thirdly, they were contaminated via an animal passage. This overview describes the problems and risks associated with viral contaminations in animal cell culture, describes the origins of these contaminations as well as the most important virsuses associated with viral contaminations in cell culture. In addition, ways to prevent viral contaminations as well as measures undertaken to avoid and assess risks for viral contaminations as performed in the biotech industry are briefly described.
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“Animal-derived raw materials (ADRMs), especially serum, carry a relatively higher risk of being contaminated with virus and are thus being replaced where possible throughout the industry 1,9,13 .”
From Viral contamination in biologic manufacture and implications for emerging therapies (2020) · cites this paper as [1]
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“In the 20 th century several vaccine products were unintentionally contaminated with unwanted viruses during their production [1][2][3] .”
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“Viruses are of particular concern as they are often more difficult to detect than other microbial contaminants 1 .”
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Metadata
- Authors
- Merten, O.-W.
- Affiliations
- Genethon (France) (FR)
- Corresponding author
- Merten, O.-W.
- ORCID
- Merten, O.-W.
- Venue
- Cytotechnology
- Published
- 2002-06
- Volume
- 39
- Issue
- 2
- Pages
- 91-116
- ISSN
- 0920-9069 (ISSN-L)
- 1573-0778
- PMC
- PMC3463984
- OpenAlex
- W2153805979
- Cited by
- 133
- References
- 110
- Citations by year
- 2026: 8 · 2025: 6 · 2024: 10 · 2023: 9 · 2022: 13 · 2021: 12 · 2020: 14 · 2019: 10 · 2018: 7 · 2017: 4 · 2016: 4 · 2015: 3 · 2014: 9 · 2013: 5
- FWCI
- 0.23
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
- Locations
- Cytotechnology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Viral Infectious Diseases and Gene Expression in Insects
- Life Sciences › Immunology and Microbiology › Microbiology › Microbial infections and disease research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Virus-based gene therapy research
- Keywords
- viral contamination, cell culture contamination, animal cell culture, provirus integration, cytopathic effect, cross-contamination, animal passage, contamination prevention, risk assessment, biotechnology industry
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
