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解决定量蛋白质组学中的蛋白酶偏倚问题。

Addressing the Protease Bias in Quantitative Proteomics.

机构信息

Science for Life Laboratory, KTH─Royal Institute of Technology, SE-171 65 Solna, Sweden.

Department of Protein Science, KTH─Royal Institute of Technology, SE-106 91 Stockholm, Sweden.

出版信息

J Proteome Res. 2022 Oct 7;21(10):2526-2534. doi: 10.1021/acs.jproteome.2c00491. Epub 2022 Aug 31.

Abstract

Protein quantification strategies using multiple proteases have been shown to deliver poor interprotease accuracy in label-free mass spectrometry experiments. By utilizing six different proteases with different cleavage sites, this study explores the protease bias and its effect on accuracy and precision by using recombinant protein standards. We established 557 SRM assays, using a recombinant protein standard resource, toward 10 proteins in human plasma and determined their concentration with multiple proteases. The quantified peptides of these plasma proteins spanned 3 orders of magnitude (0.02-70 μM). In total, 60 peptides were used for absolute quantification and the majority of the peptides showed high robustness. The retained reproducibility was achieved by quantifying plasma proteins using spiked stable isotope standard recombinant proteins in a targeted proteomics workflow.

摘要

使用多种蛋白酶进行蛋白质定量的策略已被证明在无标记质谱实验中会导致不同蛋白酶之间的准确性较差。本研究利用六种具有不同切割位点的不同蛋白酶,通过使用重组蛋白标准品来探索蛋白酶的偏倚及其对准确性和精密度的影响。我们使用重组蛋白标准资源建立了 557 个 SRM 测定方法,针对 10 个人血浆中的蛋白质,并使用多种蛋白酶测定它们的浓度。这些血浆蛋白质的定量肽跨越 3 个数量级(0.02-70 μM)。总共使用 60 个肽进行绝对定量,并且大多数肽显示出高稳健性。通过使用靶向蛋白质组学工作流程中的掺入稳定同位素标准重组蛋白来定量血浆蛋白质,可以实现可重现性的保留。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/68b3/9552229/0563b96bbed4/pr2c00491_0002.jpg

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