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利用广谱特异性蛋白酶加速蛋白质组学研究。

Accelerating Proteomics Using Broad Specificity Proteases.

机构信息

Manitoba Centre for Proteomics and Systems Biology, Health Science Centre, Winnipeg, Manitoba R3E 3P4, Canada.

Department of Biochemistry and Medical Genetics, University of Manitoba, Winnipeg, Manitoba R3E 0J9, Canada.

出版信息

J Proteome Res. 2024 Apr 5;23(4):1360-1369. doi: 10.1021/acs.jproteome.3c00852. Epub 2024 Mar 8.

Abstract

Trypsin is the gold-standard protease in bottom-up proteomics, but many sequence stretches of the proteome are inaccessible to trypsin and standard LC-MS approaches. Thus, multienzyme strategies are used to maximize sequence coverage in post-translational modification profiling. We present fast and robust SP3- and STRAP-based protocols for the broad-specificity proteases subtilisin, proteinase K, and thermolysin. All three enzymes are remarkably fast, producing near-complete digests in 1-5 min, and cost 200-1000× less than proteomics-grade trypsin. Using FragPipe resolved a major challenge by drastically reducing the duration of the required "unspecific" searches. In-depth analyses of proteinase K, subtilisin, and thermolysin Jurkat digests identified 7374, 8178, and 8753 unique proteins with average sequence coverages of 21, 29, and 37%, including 10,000s of amino acids not reported in PeptideAtlas' >2400 experiments. While we could not identify distinct cleavage patterns, machine learning could distinguish true protease products from random cleavages, potentially enabling the prediction of cleavage products. Finally, proteinase K, subtilisin, and thermolysin enabled label-free quantitation of 3111, 3659, and 4196 unique Jurkat proteins, which in our hands is comparable to trypsin. Our data demonstrate that broad-specificity proteases enable quantitative proteomics of uncharted areas of the proteome. Their fast kinetics may allow "on-the-fly" digestion of samples in the future.

摘要

胰蛋白酶是底部向上蛋白质组学的金标准蛋白酶,但许多蛋白质组的序列片段无法被胰蛋白酶和标准 LC-MS 方法所触及。因此,多酶策略被用于在后翻译修饰分析中最大限度地提高序列覆盖度。我们提出了基于 SP3 和 STRAP 的快速而稳健的广谱蛋白酶枯草杆菌蛋白酶、蛋白酶 K 和胰凝乳蛋白酶的方案。这三种酶都非常快,在 1-5 分钟内产生近乎完全的消化,成本比蛋白质组学级别的胰蛋白酶低 200-1000 倍。使用 FragPipe 解决了一个主要挑战,通过大大缩短所需“非特异性”搜索的时间来实现。对蛋白酶 K、枯草杆菌蛋白酶和胰凝乳蛋白酶 Jurkat 消化物的深入分析确定了 7374、8178 和 8753 个独特的蛋白质,平均序列覆盖率分别为 21%、29%和 37%,包括肽Atlas 报道的 >2400 次实验中未报道的 10000 多个氨基酸。虽然我们无法识别出不同的切割模式,但机器学习可以区分真实的蛋白酶产物和随机切割,这可能使预测切割产物成为可能。最后,蛋白酶 K、枯草杆菌蛋白酶和胰凝乳蛋白酶能够对 3111、3659 和 4196 个独特的 Jurkat 蛋白进行无标记定量,在我们的实验中,这与胰蛋白酶相当。我们的数据表明,广谱蛋白酶能够对蛋白质组中未被探索的区域进行定量蛋白质组学研究。它们的快速动力学可能允许在未来对样品进行“实时”消化。

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