摘要
目的 分析肝细胞癌患者与正常人血清双向凝胶电泳的差异蛋白质 ,寻找肝癌早期血清学诊断的可能指标。方法 固相 pH梯度双向凝胶电泳分离肝细胞癌患者及正常人血清总蛋白。银染显色 ,PDQuest 2DE软件分析 ,对差异蛋白质点用基质辅助激光解吸电离飞行时间质谱 (MALDI TOF MS)测定其胶内酶解后的肽质指纹图谱 ,用PepIdent软件查询SWISS PROT数据库。 结果 获得了重复性较好的双向电泳银染图谱。图像分析检测 3块胶平均匹配的点数占平均蛋白点数的匹配率是 70 2 %。等电聚焦方向的平均偏差为 (1 0 2± 0 2 2 )mm ,十二烷基硫酸钠 聚丙烯酰胺凝胶电泳 (SDS PAGE)方向的平均偏差为 (0 97± 0 14 )mm。将 2 3个差异点进行胶内原位酶解 质谱指纹图分析 ,获得 15张肽质指纹图 ,查询数据库进行了初步鉴定。结论 固相 pH梯度双向凝胶电泳分离人血清总蛋白获得重复性较好的结果 ,但仍需进一步探索如何去除高丰度已知蛋白及脂类等物质的方法 ,以便得到分辨率更高的双向电泳银染图谱。MALDI TOF
Objective To analyze the proteomic components of the sera from the patients with hepatocellular carcinomas (HCC), in search of the diagnostic markers of HCC. Methods Immobilized pH gradient two-dimensional polyacrylamide gel electrophoresis (2DE), silver staining, PDQuest 2DE analysis software, peptide mass fingerprint based on matrix-assisted laser desorption/ionization time of flying mass spectrometry (MALDI-TOF-MS) and SWISS-PROT database searching, were used to separate and identify the proteome of the sera from the patients with HCC. Results The 2DE images were analysed by PDQuest 2DE software. The average matching rate was 70.2%. In IEF direction, the average deviation was (1.02±0.22) mm, in SDS-PAGE direction, the deviation was (0.97±0.14) mm. The twenty-three different protein spots were incised from silver staining gel and digested in-gel by TPCK trypsin. 15 peptide mass fingerprints (PMF) maps were obtained by MOLDI-TOF-MS. The typical peptide masses were searched in the SWISS-PROT database using PeptIdent software. Conclusions Good reproducibility could be obtained by applying immobilized pH gradient two-dimensional polyacrylamide gel electrophoresis (2DE) to separate and identify the proteome in serum. There is still the problem of efficiently removing a higher level of proteins and lipids from the serum. Identification by MOLDI-TOF-MS peptide mass fingerprint provides useful information for screening diagnostic markers of human HCC.
出处
《中华病理学杂志》
CAS
CSCD
北大核心
2003年第4期333-336,共4页
Chinese Journal of Pathology
基金
国家自然科学基金资助项目 (3 0 0 70 847)