Creation of mice bearing a partial duplication of HPRT gene marked with a GFP gene and detection of revertant cells in situ as GFP-positive somatic cells

Abstract

It is becoming clear that apparently normal somatic cells accumulate mutations. Such accumulations or propagations of mutant cells are thought to be related to certain diseases such as cancer. To better understand the nature of somatic mutations, we developed a mouse model that enables in vivo detection of rare genetically altered cells via GFP positive cells. The mouse model carries a partial duplication of 3' portion of X-chromosomal HPRT gene and a GFP gene at the end of the last exon. In addition, although HPRT gene expression was thought ubiquitous, the expression level was found insufficient in vivo to make the revertant cells detectable by GFP positivity. To overcome the problem, we replaced the natural HPRT-gene promoter with a CAG promoter. In such animals, termed HPRT-dup-GFP mouse, losing one duplicated segment by crossover between the two sister chromatids or within a single molecule of DNA reactivates gene function, producing hybrid HPRT-GFP proteins which, in turn, cause the revertant cells to be detected as GFP-positive cells in various tissues. Frequencies of green mutant cells were measured using fixed and frozen sections (liver and pancreas), fixed whole mount (small intestine), or by means of flow cytometry (unfixed splenocytes). The results showed that the frequencies varied extensively among individuals as well as among tissues. X-ray exposure (3 Gy) increased the frequency moderately (~2 times) in the liver and small intestine. Further, in two animals out of 278 examined, some solid tissues showed too many GFP-positive cells to score (termed extreme jackpot mutation). Present results illustrated a complex nature of somatic mutations occurring in vivo. While the HPRT-dup-GFP mouse may have a potential for detecting tissue-specific environmental mutagens, large inter-individual variations of mutant cell frequency cause the results unstable and hence have to be reduced. This future challenge will likely involve lowering the background mutation frequency, thus reducing inter-individual variation.