High-efficiency identification of genes by functional analysis from a retroviral cDNA expression library. - Wong, B Y (1994)
Retroviral gene transfer efficiently delivers genes of interest stably into target cells, and expression cDNA cloning has been shown to be highly successful. Considering these two advantages, we now report a method by which one can identify genes stimulating cell growth through functional analysis. The first step requires the construction of a retroviral cDNA expression library and the optimization of transfection of vector DNA into virus packaging cells. The second step involves the cocultivation of target cells with libraries of retrovirus-producing cells, resulting in the amplification of target cells transduced with a gene(s) stimulating cell growth. Under standardized conditions of transfection, we detected an average of 4,000 independent clones per dish, among which expression of a retroviral beta-galactosidase gene at an abundance of 0.2% could be detected. Next, we demonstrated the augmentation of the sensitivity of the assay by retroviral infection and functional analysis. We did this by cocultivating factor-dependent (FD) cells with dishes of GP/E cells transfected with plasmids containing various molar ratios of pN2-IL3 DNA and retroviral library cDNA and by determining the highest dilution of pN2-IL3 which still resulted in the conversion of FD cells to factor independence. The retroviral interleukin-3 gene at an abundance as low as 0.001% could be detected. Indeed, we were able to detect from FD cells the development of factor-independent colonies with different phenotypes after retroviral transfer of cDNAs from an immortalized hemopoietic stem cell line. Thus, the combination of a standardized high-efficiency DNA transfection and retrovirus-mediated gene transfer should facilitate the identification of genes capable of conferring to target FD cells a detectable new function or phenotype. By scaling up the size of the experiment realistically during screening, the assay can detect cDNA at an abundance of lower than 0.0001%.