葡萄基因组中KUP蛋白的生物信息学分析

植物钾(K+)转运体蛋白在K+的跨膜运输中起重要作用,进而维持植物体正常生长和代谢活动.本研究中,通过隐马尔科夫模型(HMM)和葡萄蛋白质库搜索,共找到18个葡萄钾转运体蛋白(VvKUPs).利用生物信息学方法,我们对葡萄家族12条KUP蛋白序列的系统发生和KUP基因组定位进行分析,然后对其氨基酸组成成分、理化性质以及二级结构进行预测和分析,同时还分析了葡萄与拟南芥、水稻和杨树的KUP基因家族之间的联系.基因组定位结果发现其分布在至少9条染色体上.二级结构预测结果发现不同成员间氨基酸数目、氨基酸序列间的疏水性存在一定的差异;α-螺旋和无规则卷曲为主要二级结构组成部分.基因结构分析表明,KUP基因家族成员分别含有7～10个内含子.葡萄KUP蛋白的亚细胞定位分析表明VvKUP主要定位于膜结构上.电子表达图谱分析结果表明:12条KUP基因有对应的EST序列,其中的11条KUP有相应的电子表达谱,并主要在花、果实、花序和花蕾等组织部位表达.     

In silico assessment of chemical mutagenesis in comparison with results of Salmonella microsome assay on 909 chemicals

Genotoxicity is one of the important endpoints for risk assessment of environmental chemicals. Many short-term assays to evaluate genotoxicity have been developed and some of them are being used routinely. Although these assays can generally be completed within a short period, their throughput is not sufficient to assess the huge number of chemicals, which exist in our living environment without information on their safety. We have evaluated three commercially available in silico systems, i.e., DEREK, MultiCASE, and ADMEWorks, to assess chemical genotoxicity. We applied these systems to the 703 chemicals that had been evaluated by the Salmonella/microsome assay from CGX database published by Kirkland et al. [1]. We also applied these systems to the 206 existing chemicals in Japan that were recently evaluated using the Salmonella/microsome assay under GLP compliance (ECJ database). Sensitivity (the proportion of the positive in Salmonella/microsome assay correctly identified by the in silico system), specificity (the proportion of the negative in Salmonella/microsome assay correctly identified) and concordance (the proportion of correct identifications of the positive and the negative in Salmonella/microsome assay) were increased when we combined the three in silico systems to make a final decision in mutagenicity, and accordingly we concluded that in silico evaluation could be optimized by combining the evaluations from different systems. We also investigated whether there was any correlation between the Salmonella/microsome assay result and the molecular weight of the chemicals: high molecular weight (>3000) chemicals tended to give negative results. We propose a decision tree to assess chemical genotoxicity using a combination of the three in silico systems after pre-selection according to their molecular weight.