The Optimized Workflow for Sample Preparation in LC-MS/MS-Based Urine Proteomics
The Optimized Workflow for Sample Preparation in LC-MS/MS-Based Urine Proteomics
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DOI：
10.3390/mps2020046
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发表时间：
2019-06-07
影响因子：
2.4
通讯作者：
Yamamoto T
中科院分区：
文献类型：
--
作者：
Saito S;Hirao Y;Quadery AF;Xu B;Elguoshy A;Fujinaka H;Koma S;Yamamoto K;Yamamoto T
样品条件是尿蛋白质组学稳定性和准确性的重要因素。然而，质谱分析中尿蛋白制备的一般方案尚未建立。在这里，我们提出了一个工作流程，优化样品制备的基础上，甲醇/氯仿（M/C）沉淀和溶液中的胰蛋白酶消化LC-MS/MS为基础的尿液蛋白质组学。通过M/C沉淀制备的尿蛋白显示约80%的蛋白回收率。与其他基于LC-MS/MS的尿蛋白质组学沉淀方法相比，样品显示出最多的鉴定蛋白质，平均超过1000个。为了进一步改进工作流程，将香精安排在蛋白溶解和胰蛋白酶消化步骤中用于提取尿蛋白。乙二胺四乙酸（EDTA）的加入显著增强了蛋白质的溶解，并促进了消化步骤中的胰蛋白酶活性，因为处理增加了具有较少遗漏切割位点的鉴定的蛋白质的数量。最终，通过组织良好的策略建立了基于LC-MS/MS的尿液蛋白质组学日常使用的优化工作流程。该工作流程将对基于尿液蛋白质组学方法的几个目标有很大的帮助，例如诊断和生物标志物发现。
The sample condition is an important factor in urine proteomics with stability and accuracy. However, a general protocol of urine protein preparation in mass spectrometry analysis has not yet been established. Here, we proposed a workflow for optimized sample preparation based on methanol/chloroform (M/C) precipitation and in-solution trypsin digestion in LC-MS/MS-based urine proteomics. The urine proteins prepared by M/C precipitation showed around 80% of the protein recovery rate. The samples showed the largest number of identified proteins, which were over 1000 on average compared with other precipitation methods in LC-MS/MS-based urine proteomics. For further improvement of the workflow, the essences were arranged in protein dissolving and trypsin digestion step for the extraction of urine proteins. Addition of Ethylene diamine tetraacetic acid (EDTA) dramatically enhanced the dissolution of protein and promoted the trypsin activity in the digestion step because the treatment increased the number of identified proteins with less missed cleavage sites. Eventually, an optimized workflow was established by a well-organized strategy for daily use in the LC-MS/MS-based urine proteomics. The workflow will be of great help for several aims based on urine proteomics approaches, such as diagnosis and biomarker discovery.
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影响因子：
3.8
作者：
Sigdel TK;Nicora CD;Hsieh SC;Dai H;Qian WJ;Camp DG 2nd;Sarwal MM
通讯作者：
Sarwal MM
DOI：
10.4137/bic.s17991
发表时间：
2014
期刊：
Biomarkers in cancer
影响因子：
--
作者：
Beretov J;Wasinger VC;Schwartz P;Graham PH;Li Y
通讯作者：
Li Y
影响因子：
3.7
作者：
Yang Z;Zhang L;Zhang Y;Zhang T;Feng Y;Lu X;Lan W;Wang J;Wu H;Cao C;Wang X
通讯作者：
Wang X
影响因子：
3.7
作者：
Lee MY;Huang CH;Kuo CJ;Lin CL;Lai WT;Chiou SH
通讯作者：
Chiou SH
影响因子：
7
作者：
Chen, Chien-Lun;Chung, Ting;Chen, Yi-Ting
通讯作者：
Chen, Yi-Ting