Highly selective isolation of unknown mutations in diverse DNA fragments: Toward new multiplex screening in cancer

Cancer research would greatly benefit from technologies that allow simultan eous screening of several unknown gene mutations. Lack of such methods curr ently hampers the large-scale detection of genetic alterations in complex D NA samples. We present a novel mismatch-rapture methodology for the highly efficient isolation and amplification of mutation-containing DNA from diver se nucleic acid fragments of unknown sequence. To demonstrate the potential of this method, heteroduplexes with a single A/G mismatch are formed via c ross-hybridization of mutant C(T-->G) and wild-type DNA-fragment population s. Aldehydes are uniquely introduced at the position of mismatched adenines via the Escherichia coli glycosylase, MutY, Subsequent treatment with a bi otinylated hydroxylamine results in highly specific and covalent biotinylat ion of the site of mismatch. For PCR amplification synthetic Linkers are th en Ligated to the DNA fragments, Biotinylated DNA is then isolated and PCR amplified. Mutation-containing DNA fragments can subsequently be sequenced to identify type and position of mutation. This method correctly detects a single T-->G transversion introduced into a 7-kb plasmid containing full-le ngth cDNA from the p53 gene, In the presence of a high excess wild-type DNA (1:1000 mutant:normal plasmids) or in the presence of diverse DNA fragment sizes, the DNA fragments containing the mutation are readily detectable an d can be isolated and amplified, The present Aldehyde-Linker-Based Ultrasen sitive Mismatch Scanning has a current limit of detection of one base subst itution in 7 Mb of DNA and increases the Limit for unknown mutation scannin g by two to three orders of magnitude. Homozygous and heterozygous p53 regi ons (G-->T, exon 4) from genomic DNA are also examined, and correct identif ication of mutations is demonstrated. This method should allow large-scale detection of genetic alterations in cancer samples without any assumption a s to the genes of interest.