Mechanisms of mutagenesis in hot spots causing cancer

描述（由申请方提供）：这些研究的长期目标是使用两种微生物模型系统来确定应激引发的基因转录和超螺旋增加激活基因突变率的机制。这些突变发生在已知导致癌症的相同种类的二级结构中。我们实验室的最新证据表明，在微生物和人类中，转录驱动DNA超螺旋，从而产生具有易受突变影响的未配对碱基的茎环结构（SLS）。应激因子也可以直接影响负超螺旋，导致更多的SLS和更高的突变率。在我们的E.大肠杆菌模型系统，我们将确定转录，超螺旋和突变频率的影响，获得证据的存在预测的SLS在转录和非转录链，并修改序列的SLS检查预测的影响突变率。 在我们的S.在酿酒酵母模型系统中，我们将研究各种环境应激因素对p53癌基因特异性高变碱基回复率的影响。利用DNA折叠程序和一种新的计算机算法，我们已经定位了DNA SLS中的致癌碱基，并成功地预测了它们的突变指数（MI）。我们希望通过酵母质粒模型来验证我们预测突变频率的方法，并促进我们对导致突变的变量的理解。例如，我们将在相同的SLS中比较p53超变和对照碱基中的已知结构、MI和正向（野生型到突变型）突变频率与反向（突变型到野生型）突变频率。我们将比较转录、超螺旋和应激因子对SLS中MI和位置不同的碱基突变频率的影响：可以比较已知致癌物对SLS相同脆弱位置中不同碱基的回复率的影响，以澄清1）碱基本身与2）碱基位置在确定突变频率中的相对重要性。这些调查应提供新的见解诱变和致癌机制。

DESCRIPTION (provided by applicant): The long-term goal of these investigations is to use two microbial model systems to determine the mechanisms by which gene transcription and supercoiling triggered by stress increase mutation rates specifically in the activated genes. These mutations occur in the same kinds of secondary structures known to cause cancer. Recent evidence from our laboratory suggests that, in both microbes and man, transcription drives DNA supercoiling which creates stem-loop structures (SLS) with unpaired bases vulnerable to mutations. Stressors can also affect negative supercoiling directly, resulting in more SLS and higher mutation rates. In our E. coli model system we will determine the effects of stress on transcription, supercoiling, and mutation frequency, obtain evidence for the existence of predicted SLS in both transcribed and non-transcribed strands, and modify sequences in SLS to examine predicted effects on mutation rates. In our S. cerevisiae model system, we will examine the effects of various kinds of environmental stressors on reversion rates of specific hypermutable bases of the p53 cancer gene. Using a DNA folding program and a new computer algorithm we have localized cancer-causing bases in DNA SLS and successfully predicted their mutability indexes (MIs). With the yeast-plasmid model we hope to verify our method for predicting mutation frequencies and advance our understanding of the variables that cause mutations. For example, we will compare known structures, MIs and forward (wild to mutant) mutation frequencies inp53 hypermutable and control bases to those of the backward (mutant to wild) mutations, in the same SLS. We will compare the effects of transcription, supercoiling, and stressors on mutation frequencies of bases that differ in MIs and locations in SLS: The effects of known carcinogens on reversion rates of different bases in the same vulnerable position of a SLS can be compared, to clarify the relative importance of 1) the base per se, vs 2) the location of the base in determining mutation frequencies. These investigations should provide new insights into the mechanisms of mutagenesis and carcinogenesis.