Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, Macquarie University, Macquarie Park, NSW 2109, Australia.
Australian Proteome Analysis Facility (APAF), Department of Molecular Sciences, Faculty of Science and Engineering, Macquarie University, Macquarie Park, NSW 2109, Australia.
J Proteome Res. 2021 May 7;20(5):2374-2389. doi: 10.1021/acs.jproteome.0c00898. Epub 2021 Mar 22.
Credible detection and quantification of low abundance proteins from human blood plasma is a major challenge in precision medicine biomarker discovery when using mass spectrometry (MS). In this proof-of-concept study, we employed a mixture of selected recombinant proteins in DDA libraries to subsequently identify (not quantify) cancer-associated low abundance plasma proteins using SWATH/DIA. The exemplar DDA recombinant protein spectral library (rPSL) was derived from tryptic digestion of 36 recombinant human proteins that had been previously implicated as possible cancer biomarkers from both our own and other studies. The rPSL was then used to identify proteins from nondepleted colorectal cancer (CRC) EDTA plasmas by SWATH-MS. Most (32/36) of the proteins used in the rPSL were reliably identified from CRC plasma samples, including 8 proteins (i.e., BTC, CXCL10, IL1B, IL6, ITGB6, TGFα, TNF, TP53) not previously detected using high-stringency protein inference MS according to PeptideAtlas. The rPSL SWATH-MS protocol was compared to DDA-MS using MARS-depleted and postdigestion peptide fractionated plasmas (here referred to as a human plasma DDA library). Of the 32 proteins identified using rPSL SWATH, only 12 could be identified using DDA-MS. The 20 additional proteins exclusively identified using the rPSL SWATH approach were almost exclusively lower abundance (i.e., <10 ng/mL) proteins. To mitigate justified FDR concerns, and to replicate a more typical library creation approach, the DDA rPSL library was merged with a human plasma DDA library and SWATH identification repeated using such a merged library. The majority (33/36) of the low abundance plasma proteins added from the rPSL were still able to be identified using such a merged library when high-stringency HPP Guidelines v3.0 protein inference criteria were applied to our data set. The MS data set has been deposited to ProteomeXchange Consortium via the PRIDE partner repository (PXD022361).
可信地检测和定量来自人血浆的低丰度蛋白质是精准医学生物标志物发现中使用质谱(MS)的主要挑战。在这项概念验证研究中,我们使用选定的重组蛋白混合物在 DDA 文库中,随后使用 SWATH/DIA 来鉴定(而不是定量)与癌症相关的低丰度血浆蛋白。示例 DDA 重组蛋白光谱文库(rPSL)源自 36 种重组人蛋白的胰蛋白酶消化物,这些蛋白先前已被我们自己和其他研究确定为可能的癌症生物标志物。然后,rPSL 被用于通过 SWATH-MS 鉴定非耗竭结直肠癌(CRC)EDTA 血浆中的蛋白质。rPSL 中使用的大多数(36/36)蛋白都可以从 CRC 血浆样本中可靠地鉴定出来,包括 8 种蛋白(即 BTC、CXCL10、IL1B、IL6、ITGB6、TGFα、TNF、TP53),根据 PeptideAtlas,它们之前未使用高严格性蛋白推断 MS 检测到。rPSL SWATH-MS 方案与使用 MARS 耗尽和消化后肽分馏的血浆(此处称为人类血浆 DDA 文库)的 DDA-MS 进行了比较。在使用 rPSL SWATH 鉴定的 32 种蛋白中,只有 12 种可以使用 DDA-MS 鉴定。仅使用 rPSL SWATH 方法鉴定的 20 种额外蛋白几乎都是低丰度(即 <10ng/mL)蛋白。为了减轻合理的 FDR 问题,并复制更典型的文库创建方法,将 DDA rPSL 文库与人类血浆 DDA 文库合并,并使用此类合并文库重复进行 SWATH 鉴定。当将严格的 HPP 指南 v3.0 蛋白推断标准应用于我们的数据集中时,从 rPSL 添加的大多数(33/36)低丰度血浆蛋白仍可以使用此类合并文库进行鉴定。MS 数据集已通过 PRIDE 合作伙伴存储库(PXD022361)递交给 ProteomeXchange 联盟。