首页> 外文期刊>Analytical chemistry >Practical Implementation of 2D HPLC Scheme with Accurate Peptide Retention Prediction in Both Dimensions for High-Throughput Bottom-Up Proteomics
【24h】

Practical Implementation of 2D HPLC Scheme with Accurate Peptide Retention Prediction in Both Dimensions for High-Throughput Bottom-Up Proteomics

机译:高通量自下而上蛋白质组学在二维中具有精确肽保留预测的二维HPLC方案的实际实现

获取原文
获取原文并翻译 | 示例
       

摘要

We describe the practical implementation of a new RP (pH 10 - pH 2) 2D HPLC-ESI/MS scheme for large-scale bottom-up analysis in proteomics. When compared to the common SCX-RP approach, it provides a higher separation efficiency in the first dimension and increases the number of identified peptides/proteins. We also employed the methodology of our sequence-specific retention calculator (SSRCalc) and developed peptide retention prediction algorithms for both LC dimensions. A diverse set of approx10 000 tryptic peptides from the soluble protein fraction of whole NK-type cells gave retention time versus hydrophobicity correlations, with R~(2) values of 0.95 for pH 10 and 0.945 for pH 2 (formic acid) separation modes. The superior separation efficiency and the ability to use retention prediction to filter out false-positive MS/MS identifications gives promise that this approach will be a method of choice for large-scale proteomics analyses in the future. Finally, the "semi-orthogonal" separation selectivity permits the concatenation of fractions in the first dimension of separation before the final LC-ESI MS step, effectively cutting the analysis time in half, while resulting in a minimal reduction in protein identification.
机译:我们描述了蛋白质组学中大规模自下而上分析的新RP(pH 10-pH 2)2D HPLC-ESI / MS方案的实际实施。与普通的SCX-RP方法相比,它在第一维方向上提供了更高的分离效率,并增加了已鉴定肽/蛋白质的数量。我们还采用了序列特异性保留计算器(SSRCalc)的方法,并针对两个LC维度开发了肽保留预测算法。来自整个NK型细胞的可溶性蛋白质部分的大约10000种胰蛋白酶肽的多样化集合给出了保留时间与疏水性的相关性,pH 10的R〜(2)值为0.95,pH 2(甲酸)的R〜(2)值为0.945。出色的分离效率和使用保留预测功能过滤掉假阳性MS / MS鉴定的能力,使该方法有望在将来成为大规模蛋白质组学分析的一种选择方法。最后,“半正交”分离选择性允许在最后的LC-ESI MS步骤之前在分离的第一维中级分级联,从而有效地将分析时间缩短了一半,同时使蛋白质鉴定的减少降至最低。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号