A collaborative study evaluating the detection of virus-infected cells by transcriptomic high-throughput sequencing
10 affiliations
- 1GSK, Wavre, Belgium
- 2Division of Viral Products, Office of Vaccines Research and Review, Center for Biologics Evaluation and Review, U.S. Food and Drug Administration, Silver Spring, Maryland, USA
- 3GSK, Rixensart, Belgium
- 4PathoQuest, Paris, France
- 5Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
- 6Sanofi, Toronto, Ontario, Canada
- 7Graduate School of Science, Technology, and Innovation, Kobe University, Kobe, Japan
- 8EMD Serono RBM S.p.A. Istituto di Ricerche Biomediche A. Marxer, Colleretto Giacosa, Italy
- 9Analytical Research and Development, Microbiology Strategy and Testing Department, Biotherapeutics Pharm. Sci., Pfizer Inc., Andover, Massachusetts, USA
- 10Machine Learning and Computational Sciences, Discovery & Early Development Department, Medicine Design, Pfizer Inc., Cambridge, Massachusetts, USA
Abstract
High-throughput sequencing (HTS) is an agnostic virus detection technology that can replace or supplement the conventional adventitious virus assays used for safety testing of biologics. Transcriptomic HTS is particularly suitable for the detection of replicating viruses. We have evaluated the sensitivity of virus detection by transcriptomic HTS using targeted and non-targeted bioinformatics analysis of infected cells spiked into a background of uninfected cells, mimicking material representing a test sample from product manufacturing. Eight laboratories tested a mix of Raji cells (expressing Epstein-Barr virus [EBV] RNAs without virus production) and EBV-negative Ramos cells at ratios ranging from 0.5 to 0.00005. Seven laboratories performed the analysis using different HTS protocols, while the eighth laboratory quantified EBV RNA recovery in all extracted samples by quantifying EBNA-1 by RT-ddPCR assay. All participants detected EBV transcripts at a 0.001 ratio with the targeted analysis and a 0.01 ratio with the non-targeted analysis (i.e., one infected cell in 100 uninfected cells), with four laboratories achieving detection at the 0.0001 ratio for both analysis. The results of the spiking studies demonstrated the capabilities of transcriptomic HTS for adventitious virus detection in cell lines used for the production of biologics, and highlight that optimization in the workflow can improve HTS virus detection.IMPORTANCEHigh-throughput sequencing (HTS) is currently recognized as a powerful technology for broad virus detection. While HTS can be considered an alternative method to replace or supplement the conventional adventitious virus detection assays for testing biologics, its routine implementation has been challenging due to the complexities of the HTS workflow, including the matrix of the test sample, selection of HTS methodology (viromic, genomic, or transcriptomic), and variability in the protocols (from sample preparation to bioinformatic analysis). The study demonstrated the performance and capabilities of the transcriptomic HTS approach for the detection of virus-infected cells using different workflows presented by seven laboratories. The study indicated that regardless of the protocol used, all participants detected viral RNA at the 0.01 ratio; however, certain HTS protocols demonstrated better sensitivity of viral detection.
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BibTeX
@article{deneyer2026collaborative,
title = {{A collaborative study evaluating the detection of virus-infected cells by transcriptomic high-throughput sequencing}},
author = {Noémie Deneyer and Pei-Ju Chin and Guillaume Bayon-Vicente and Pascale Beurdeley and Megan H. Cleveland and Anne-Sophie Colinet and Stéphane Cruveiller and Marc Eloit and Shanaz Gilchrist and Noriko Hashiba and Christophe Lambert and Antonio Lembo and Ka-Wai Leong and Brandye Micheals and Sandrine Moreira and Reiko Nakashima and Simone Olgiati and Nasrin Salehi and Qinyu Sun and Kazuhisa Uchida and Olivier Vandeputte and Yuzhe Yuan and Keisuke Yusa and Valeria Maria Zanda and Arifa S. Khan},
journal = {Microbiology Spectrum},
year = {2026},
month = sep,
doi = {10.1128/spectrum.00066-26},
url = {https://doi.org/10.1128/spectrum.00066-26},
note = {CC BY},
}
RIS
TY - JOUR
TI - A collaborative study evaluating the detection of virus-infected cells by transcriptomic high-throughput sequencing
AU - Noémie Deneyer
AU - Pei-Ju Chin
AU - Guillaume Bayon-Vicente
AU - Pascale Beurdeley
AU - Megan H. Cleveland
AU - Anne-Sophie Colinet
AU - Stéphane Cruveiller
AU - Marc Eloit
AU - Shanaz Gilchrist
AU - Noriko Hashiba
AU - Christophe Lambert
AU - Antonio Lembo
AU - Ka-Wai Leong
AU - Brandye Micheals
AU - Sandrine Moreira
AU - Reiko Nakashima
AU - Simone Olgiati
AU - Nasrin Salehi
AU - Qinyu Sun
AU - Kazuhisa Uchida
AU - Olivier Vandeputte
AU - Yuzhe Yuan
AU - Keisuke Yusa
AU - Valeria Maria Zanda
AU - Arifa S. Khan
PY - 2026
DA - 2026/09/22
JO - Microbiology Spectrum
DO - 10.1128/spectrum.00066-26
UR - https://doi.org/10.1128/spectrum.00066-26
AB - High-throughput sequencing (HTS) is an agnostic virus detection technology that can replace or supplement the conventional adventitious virus assays used for safety testing of biologics. Transcriptomic HTS is particularly suitable for the detection of replicating viruses. We have evaluated the sensitivity of virus detection by transcriptomic HTS using targeted and non-targeted bioinformatics analysis of infected cells spiked into a background of uninfected cells, mimicking material representing a test sample from product manufacturing. Eight laboratories tested a mix of Raji cells (expressing Epstein-Barr virus [EBV] RNAs without virus production) and EBV-negative Ramos cells at ratios ranging from 0.5 to 0.00005. Seven laboratories performed the analysis using different HTS protocols, while the eighth laboratory quantified EBV RNA recovery in all extracted samples by quantifying EBNA-1 by RT-ddPCR assay. All participants detected EBV transcripts at a 0.001 ratio with the targeted analysis and a 0.01 ratio with the non-targeted analysis (i.e., one infected cell in 100 uninfected cells), with four laboratories achieving detection at the 0.0001 ratio for both analysis. The results of the spiking studies demonstrated the capabilities of transcriptomic HTS for adventitious virus detection in cell lines used for the production of biologics, and highlight that optimization in the workflow can improve HTS virus detection.IMPORTANCEHigh-throughput sequencing (HTS) is currently recognized as a powerful technology for broad virus detection. While HTS can be considered an alternative method to replace or supplement the conventional adventitious virus detection assays for testing biologics, its routine implementation has been challenging due to the complexities of the HTS workflow, including the matrix of the test sample, selection of HTS methodology (viromic, genomic, or transcriptomic), and variability in the protocols (from sample preparation to bioinformatic analysis). The study demonstrated the performance and capabilities of the transcriptomic HTS approach for the detection of virus-infected cells using different workflows presented by seven laboratories. The study indicated that regardless of the protocol used, all participants detected viral RNA at the 0.01 ratio; however, certain HTS protocols demonstrated better sensitivity of viral detection.
SN - 2165-0497
ER -