Kathy Call

We described previously the isolation of a Saccharomyces cerevisiae 3-methyladenine (3-MeAde) DNA glycosylase repair gene (MAG) by its expression in glycosylase-deficient Escherichia coli alkA tag mutant cells and its ability to rescue these cells from the toxic effects of alkylating agents. Here we extend this cross-species functional complementation approach to the isolation of a full-length human 3-MeAde DNA glycosylase cDNA that rescues alkA tag E. coli from killing by methyl methanesulfonate, and we have mapped the gene to human chromosome 16. The cloned cDNA, expressed from the pBR322 beta-lactamase promoter, contains an 894-base-pair open reading frame encoding a 32,894-Da protein able to release 3-MeAde, but not 7-methylguanine, from alkylated DNA. Surprisingly, the predicted human protein does not share significant amino acid sequence homology with the bacterial AlkA and Tag glycosylases or the yeast MAG glycosylase, but it does share extensive amino acid sequence homology with a rat 3-MeAde DNA glycosylase and significant DNA sequence homology with genes from several mammalian species. The cloning of a human 3-MeAde DNA glycosylase cDNA represents a key step in generating 3-MeAde repair-deficient cells and the determination of the in vivo role of this DNA repair enzyme in protecting against the toxic and carcinogenic effects of alkylating agents.

A supervised classification scheme for analyzing microarray expression data, based on the k-nearest-neighbor method coupled to noise-reduction filters, has been used to find genes involved in the osteogenic pathway of the mouse C2C12 cell line studied here as a model for in vivo osteogenesis. The scheme uses as input a training set embodying expert biological knowledge, and provides internal estimates of its own misclassification errors, which furthermore enables systematic optimization of the classifier parameters. On the basis of the C2C12-generated expression data set with 34,130 expression profiles across 2 time courses, each comprised of 6 points, and a training set containing known members of the osteogenic, myoblastic, and adipocytic pathways, 176 new genes in addition to 28 originally in the training set are selected as relevant to osteogenesis. For this selection, the estimated sensitivity is 42% and the posterior false-positive rate (fraction of candidates that are spurious) is 12%. The corresponding sensitivity and false-positive rate for detection of myoblastic genes are 9% and 31%, respectively, and only 4% and approximately 100%, respectively, for adipocytic genes, in accordance with an experimental design that predominantly stimulated the osteogenic pathway. Validation of this selection is provided by examining expression of the genes in an independent biological assay involving mouse calvaria (skull bone) primary cell cultures, in which a large fraction of the 176 genes are seen to be strongly regulated, as well as by case-by-case analysis of the genes on the basis of expert domain knowledge. The methodology should be generalizable to any situation in which enough a priori biological knowledge exists to define a training set.