Cagney Gerard, Park Stephen, Chung Clement, Tong Bianca, O'Dushlaine Colm, Shields Denis C, Emili Andrew
Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland.
J Proteome Res. 2005 Sep-Oct;4(5):1757-67. doi: 10.1021/pr0500354.
Profiling of tissues and cell types through systematic characterization of expressed genes or proteins shows promise as a basic research tool, and has potential applications in disease diagnosis and classification. We used multidimensional protein identification protein identification technology (MudPIT) to analyze proteomes for enriched nuclear extracts of eight human tissues: brain, heart, liver, lung, muscle, pancreas, spleen, and testis. We show that the method is approximately 80% reproducible. We address issues of relative abundance, tissue-specificity, and selectivity, and the significance of proteins whose expression does not correlate with that of the corresponding mRNA. Surprisingly, most proteins are detected in a single tissue. These proteins tend to fulfill specialist (and potentially tissue-specific) functions compared to proteins expressed in two or more tissues.
通过对表达的基因或蛋白质进行系统表征来分析组织和细胞类型，显示出作为一种基础研究工具的潜力，并在疾病诊断和分类中具有潜在应用。我们使用多维蛋白质鉴定技术（MudPIT）来分析八种人类组织（脑、心脏、肝脏、肺、肌肉、胰腺、脾脏和睾丸）富集核提取物的蛋白质组。我们表明该方法的重现性约为80%。我们探讨了相对丰度、组织特异性和选择性问题，以及表达与相应mRNA不相关的蛋白质的意义。令人惊讶的是，大多数蛋白质在单一组织中被检测到。与在两种或更多组织中表达的蛋白质相比，这些蛋白质倾向于履行专门（且可能是组织特异性）的功能。
