Parnell Laurence D, Schueller Christine M E
US Department of Agriculture, Nutrition and Genomics Laboratory, Jean Mayer Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA.
Methods Mol Biol. 2010;641:101-22. doi: 10.1007/978-1-60761-711-2_7.
Proteomics-based biomarker discovery studies usually entail the isolation of peptide fragments from candidate biomarkers of interest. Detection of such peptides from biological or clinical samples and identification of the corresponding full-length protein and the gene encoding that protein provide the means to gather a wealth of information. This information, termed annotation because it is attached to the gene or protein sequence under study, describes relationships to human disease, cytogenetic map position, protein domains, protein-protein and small molecule interactions, tissues or cell types in which the gene is expressed, as well as several other aspects of gene and protein function. Bioinformatics tools are employed and genome databases are mined to retrieve this information. Coupled with extensive gene and protein annotation, detected peptides are better placed in a biological context with respect to the health status of the subject. Examples of the status include cancers (bladder, kidney), metabolic disorders (diabetes and kidney function), and the nutritional state of the subject.
基于蛋白质组学的生物标志物发现研究通常需要从感兴趣的候选生物标志物中分离肽片段。从生物或临床样本中检测此类肽,并鉴定相应的全长蛋白质以及编码该蛋白质的基因,提供了收集大量信息的方法。这些信息,由于它附着在所研究的基因或蛋白质序列上而被称为注释,描述了与人类疾病、细胞遗传图谱位置、蛋白质结构域、蛋白质-蛋白质和小分子相互作用、基因表达所在的组织或细胞类型以及基因和蛋白质功能的其他几个方面的关系。利用生物信息学工具并挖掘基因组数据库来检索这些信息。结合广泛的基因和蛋白质注释,检测到的肽在受试者健康状况的生物学背景下能得到更好的定位。这种状况的例子包括癌症(膀胱癌、肾癌)、代谢紊乱(糖尿病和肾功能)以及受试者的营养状况。