Tajai · Free radical biology & medicine 2018 · In vitro gene-editing and mutagenesis assay · n=?

An engineered cell line lacking OGG1 and MUTYH glycosylases implicates the accumulation of genomic 8-oxoguanine as the basis for paraquat mutagenicity.

Cited 20 times in the scientific literature.

Level 5 - mechanism / opinion, no new human data

In vitro bench study using an engineered animal cell line without human subjects (CEBM Level 5).

PubMed 29289706 · doi:10.1016/j.freeradbiomed.2017.12.035 · record verified 2026-08-29

What was done

Researchers used CRISPR-Cas9 to knock out 8-oxoguanine DNA glycosylase (OGG1) and MUTYH glycosylase in Chinese hamster ovary-derived AS52 cells containing an integrated bacterial gpt reporter gene. They exposed the resulting double-knockout (DKO) cells and parental wild-type AS52 cells to low doses of the herbicide paraquat, comparing toxicity, reactive oxygen species generation, DNA double-strand breaks, genomic 8-oxoguanine accumulation, mutation induction, and the effect of antioxidant co-treatment.

What was found

The abstract reports directional findings without numerical values. DKO cells showed greater sensitivity to paraquat toxicity than wild-type cells, accompanied by higher levels of reactive oxygen species and increased DNA double-strand breaks. DKO cells also accumulated more genomic 8-oxoguanine and exhibited higher mutation levels. Co-treatment with an antioxidant reduced both cellular reactive oxygen species and paraquat-induced mutagenesis.

Why it matters

The findings show that genomic 8-oxoguanine accumulation mediates paraquat-induced mutagenesis and that OGG1 and MUTYH provide essential protection against this damage. The engineered DKO cell model provides an assay system to detect and quantify mutagenesis from weak oxidative genotoxicants.

Limits

The study is entirely in vitro using a non-human, transformed cell line (CHO-derived AS52), limiting direct generalizability to intact mammalian tissues or human exposure. The abstract provides no exact quantitative values, sample sizes, dose-response metrics, or statistical confidence intervals.

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