Proteomics analysis of human amniotic fluid
Proteomics analysis of human amniotic fluid
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DOI：
10.1074/mcp.m700090-mcp200
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发表时间：
2007-08-01
影响因子：
7
通讯作者：
Diamandis, Eleftherios P.
中科院分区：
文献类型：
--
作者：
Cho, Chan-Kyung J.;Shan, Shannon J.;Diamandis, Eleftherios P.
羊水是一种动态的复杂混合物，反映了发育中胎儿的生理状态。在这项研究中，人类羊水（AF）蛋白质组的16-18周的正常妊娠的轮廓和分析，以探讨这种液体的组成和功能。由于AF的复杂性，我们使用了三种不同的分割策略来提供更大的覆盖范围。使用两种类型的二维LC/MS/MS以及LCSDSPAGE-LC-MS/MS平台。通过三种分馏方法之一，然后通过常见的反相LC-MS/MS步骤，对来自携带染色体正常胎儿的女性的16个胎龄为16至18周的AF样本进行分析。Mascot和Global Proteome Machine引擎用于搜索国际蛋白质索引人类数据库以进行肽序列鉴定。通过Scaffold软件的PeptideProphet将两个引擎的结果组合生成蛋白质列表。将所有鉴定的蛋白质组合以产生包含1，026个独特基因匹配或842个非冗余蛋白质的AF蛋白质组。该列表包括大多数目前使用的妊娠相关病理条件的生物标志物，如早产，羊膜内感染和胎儿染色体异常。AF蛋白质组的亚细胞定位，组织表达，功能和网络进行了分析，通过各种生物信息学工具。这些数据将有助于更好地了解羊水功能，并发现新的生物标志物产前诊断胎儿异常。
Amniotic fluid is a dynamic and complex mixture that reflects the physiological status of the developing fetus. In this study, the human amniotic fluid (AF) proteome of a 16-18-week normal pregnancy was profiled and analyzed to investigate the composition and functions of this fluid. Due to the complexity of AF, we utilized three different fractionation strategies to provide greater coverage. Two types of two-dimensional LC/MS/MS as well as an LCSDSPAGE-LC-MS/MS platform were used. A total of 16 AF samples between gestational ages of 16 and 18 weeks from women carrying chromosomally normal fetuses were analyzed by one of the three fractionation methods followed by a common reverse phase LC-MS/MS step. Mascot and The Global Proteome Machine engines were used to search the International Protein Index human database for peptide sequence identification. The list of proteins was generated by combining the results of both engines through the PeptideProphet of Scaffold software. All identified proteins were combined to generate the AF proteome comprising 1,026 unique gene matches or 842 non-redundant proteins. This list includes most of the currently used biomarkers for pregnancy-associated pathologic conditions such as preterm delivery, intra-amniotic infection, and chromosomal anomalies of the fetus. The subcellular localization, tissue expression, functions, and networks of the AF proteome were analyzed by various bioinformatic tools. These data will contribute to the better understanding of amniotic fluid function and to the discovery of novel biomarkers for prenatal diagnosis of fetal abnormalities.