Guo Xiaofeng, Trudgian David C, Lemoff Andrew, Yadavalli Sivaramakrishna, Mirzaei Hamid
From the ‡Department of Biochemistry, UT Southwestern Medical Center, Dallas, Texas 75390.
From the ‡Department of Biochemistry, UT Southwestern Medical Center, Dallas, Texas 75390
Mol Cell Proteomics. 2014 Jun;13(6):1573-84. doi: 10.1074/mcp.M113.035170. Epub 2014 Apr 2.
Bottom-up proteomics largely relies on tryptic peptides for protein identification and quantification. Tryptic digestion often provides limited coverage of protein sequence because of issues such as peptide length, ionization efficiency, and post-translational modification colocalization. Unfortunately, a region of interest in a protein, for example, because of proximity to an active site or the presence of important post-translational modifications, may not be covered by tryptic peptides. Detection limits, quantification accuracy, and isoform differentiation can also be improved with greater sequence coverage. Selected reaction monitoring (SRM) would also greatly benefit from being able to identify additional targetable sequences. In an attempt to improve protein sequence coverage and to target regions of proteins that do not generate useful tryptic peptides, we deployed a multiprotease strategy on the HeLa proteome. First, we used seven commercially available enzymes in single, double, and triple enzyme combinations. A total of 48 digests were performed. 5223 proteins were detected by analyzing the unfractionated cell lysate digest directly; with 42% mean sequence coverage. Additional strong-anion exchange fractionation of the most complementary digests permitted identification of over 3000 more proteins, with improved mean sequence coverage. We then constructed a web application (https://proteomics.swmed.edu/confetti) that allows the community to examine a target protein or protein isoform in order to discover the enzyme or combination of enzymes that would yield peptides spanning a certain region of interest in the sequence. Finally, we examined the use of nontryptic digests for SRM. From our strong-anion exchange fractionation data, we were able to identify three or more proteotypic SRM candidates within a single digest for 6056 genes. Surprisingly, in 25% of these cases the digest producing the most observable proteotypic peptides was neither trypsin nor Lys-C. SRM analysis of Asp-N versus tryptic peptides for eight proteins determined that Asp-N yielded higher signal in five of eight cases.
自下而上的蛋白质组学在很大程度上依赖胰蛋白酶肽段进行蛋白质鉴定和定量。由于肽段长度、电离效率和翻译后修饰共定位等问题，胰蛋白酶消化通常只能提供有限的蛋白质序列覆盖范围。不幸的是，蛋白质中感兴趣的区域，例如由于靠近活性位点或存在重要的翻译后修饰，可能无法被胰蛋白酶肽段覆盖。更高的序列覆盖度也可以提高检测限、定量准确性和异构体区分能力。如果能够识别更多可靶向的序列，选择反应监测（SRM）也将受益匪浅。为了提高蛋白质序列覆盖度并靶向那些不能产生有用胰蛋白酶肽段的蛋白质区域，我们在HeLa蛋白质组上采用了多蛋白酶策略。首先，我们使用了七种市售酶进行单酶、双酶和三酶组合消化。总共进行了48次消化。通过直接分析未分级的细胞裂解物消化产物，检测到了5223种蛋白质；平均序列覆盖度为42%。对最互补的消化产物进行额外的强阴离子交换分级分离，使得能够鉴定出3000多种更多的蛋白质，平均序列覆盖度得到了提高。然后，我们构建了一个网络应用程序（https://proteomics.swmed.edu/confetti），该程序允许研究群体检查目标蛋白质或蛋白质异构体，以发现能够产生跨越序列中特定感兴趣区域的肽段的酶或酶组合。最后，我们研究了非胰蛋白酶消化用于SRM的情况。从我们的强阴离子交换分级分离数据中，我们能够为6056个基因在单次消化中鉴定出三个或更多的蛋白质型SRM候选物。令人惊讶的是，在这些情况的25%中，产生最易观察到的蛋白质型肽段的消化酶既不是胰蛋白酶也不是Lys-C。对八种蛋白质进行Asp-N与胰蛋白酶肽段的SRM分析表明，在八种情况中的五种中，Asp-N产生了更高的信号。
