Development of a versatile high-throughput mutagenesis assay with multiplexed short-read NGS using DNA-barcoded <i>supF</i> shuttle vector library amplified in <i>E. coli</i>.
Hidehiko KawaiRen IwataShungo EbiRyusei SugiharaShogo MasudaChiho FujiwaraShingo KimuraHiroyuki KamiyaPublished in: eLife (2022)
A forward mutagenesis assay using the <i>supF</i> gene has been widely employed for the last several decades in studies addressing mutation frequencies and mutation spectra associated with various intrinsic and environmental mutagens. In this study, by using a <i>supF</i> shuttle vector and non-SOS-induced <i>Escherichia coli</i> with short-read next-generation sequencing (NGS) technology, we present an advanced method for the study of mutations, which is simple, versatile, and cost-effective. We demonstrate the performance of our newly developed assay via pilot experiments with ultraviolet (UV) irradiation, the results from which emerge more relevant than expected. The NGS data obtained from samples of the indicator <i>E. coli</i> grown on titer plates provides mutation frequency and spectrum data, and uncovers obscure mutations that cannot be detected by a conventional <i>supF</i> assay. Furthermore, a very small amount of NGS data from selection plates reveals the almost full spectrum of mutations in each specimen and offers us a novel insight into the mechanisms of mutagenesis, despite them being considered already well known. We believe that the method presented here will contribute to future opportunities for research on mutagenesis, DNA repair, and cancer.
Keyphrases
- high throughput
- escherichia coli
- crispr cas
- dna repair
- electronic health record
- single molecule
- single cell
- big data
- circulating tumor
- copy number
- genome wide
- endothelial cells
- randomized controlled trial
- machine learning
- gene expression
- high glucose
- study protocol
- current status
- oxidative stress
- young adults
- risk assessment
- diabetic rats
- multidrug resistant
- biofilm formation
- transcription factor
- pseudomonas aeruginosa
- data analysis
- nucleic acid