Evidence map›Paper›PMID 30629668›Full record

ArticlePloS one2019

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

Cord C Uphoff, Claudia Pommerenke, Sabine A Denkmann, Hans G Drexler

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.6field-weighted citation impact, top 11% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Kmerator Suite: design of specificNAR genomics and bioinformatics · 2021
    Article
  8. Article
  9. Article
  10. The LL-100 Cell Lines Panel: Tool for Molecular Leukemia-Lymphoma Research.International journal of molecular sciences · 2020
    Review
  11. Review
  12. What human sperm RNA-Seq tells us about the microbiome.Journal of assisted reproduction and genetics · 2020
    Article
  13. Article
  14. Article
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Cord C UphoffDepartment of Human and Animal Cell Lines, Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.ORCID 0000-0002-7813-3191
Claudia PommerenkeDepartment of Human and Animal Cell Lines, Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.
Sabine A DenkmannDepartment of Human and Animal Cell Lines, Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.
Hans G DrexlerDepartment of Human and Animal Cell Lines, Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Braunschweig, Germany.
Leibniz Institute DSMZ – German Collection of Microorganisms and Cell Cultures · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

AnimalsCattleCell LineComputational BiologyGenome, ViralHigh-Throughput Nucleotide SequencingHumansQuality ControlSequence Analysis, RNA

Identifiers

PMID30629668
PMCPMC6328144
OpenAlexW2909793383

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.