Cell line bias in virus research: implications for viral propagation and biological interpretation

TL;DR

This paper highlights how over-reliance on a few cell lines in virus research can lead to biased results and calls for a more diverse and data-driven approach to improve accuracy.

Contribution

The paper introduces a data-driven strategy for cell line selection in virology to reduce bias and improve modeling of host-virus interactions.

Findings

A small number of cell lines are disproportionately used in virology research.

Underutilized cell lines from diverse tissues can also support viral propagation.

Molecular databases and diverse cell line panels are recommended to improve reproducibility.

Abstract

Cell lines are essential tools in virology for propagating viruses for characterization studies. However, reliance on a few historically popular lines—such as Vero, BHK-21, and MDCK—can introduce bias and obscure important aspects of viral biology, such as entry mechanisms and replication dynamics. A review of over 6,000 publications revealed that a small number of cell lines are used disproportionately, often due to historical precedence and general permissiveness for viral infection. Gene expression analysis showed that while these lines are enriched for pro-viral process genes, many underutilized cell lines from diverse tissue types also exhibit similar profiles. This review calls for a more strategic, molecularly informed approach to cell line selection, including the development of molecular databases for non-human cell lines, identification of virologically relevant traits, and broader use of biologically diverse panels. Such a data-driven strategy is especially vital for studying emerging and zoonotic viruses, where accurate modeling of host–virus interactions is important. Expanding and refining cell line use will improve reproducibility and yield more accurate insights into viral pathogenesis.

Figures