David Geffen School of Medicine, Department of Biological Chemistry, University of California Los Angeles, Los Angeles, California, USA; Molecular Biology Interdepartmental Graduate Program, University of California Los Angeles, Los Angeles, California, USA.
David Geffen School of Medicine, Department of Biological Chemistry, University of California Los Angeles, Los Angeles, California, USA.
Mol Cell Proteomics. 2021;20:100039. doi: 10.1074/mcp.RA120.002411. Epub 2021 Jan 19.
Deep proteome coverage in bottom-up proteomics requires peptide-level fractionation to simplify the complex peptide mixture before analysis by tandem mass spectrometry. By decreasing the number of coeluting precursor peptide ions, fractionation effectively reduces the complexity of the sample leading to higher sample coverage and reduced bias toward high-abundance precursors that are preferentially identified in data-dependent acquisition strategies. To achieve this goal, we report a bead-based off-line peptide fractionation method termed CIF or carboxylate-modified magnetic bead-based isopropanol gradient peptide fractionation. CIF is an extension of the SP3 (single-pot solid phase-enhanced sample preparation) strategy and provides an effective but complementary approach to other commonly used fractionation methods including strong cation exchange and reversed phase-based chromatography. We demonstrate that CIF is an effective offline separation strategy capable of increasing the depth of peptide analyte coverage both when used alone or as a second dimension of peptide fractionation in conjunction with high pH reversed phase. These features make it ideally suited for a wide range of proteomic applications including the affinity purification of low-abundance bait proteins.
在基于向下的蛋白质组学中，要实现深度蛋白质组覆盖，需要在串联质谱分析之前进行肽级分馏，以简化复杂的肽混合物。通过减少共洗脱前体肽离子的数量，分馏有效地降低了样品的复杂性，从而提高了样品的覆盖率，并减少了对在数据依赖型采集策略中优先鉴定的高丰度前体的偏向。为了实现这一目标，我们报告了一种基于珠子的离线肽分级方法，称为 CIF 或羧酸修饰的基于磁性珠的异丙醇梯度肽分级。CIF 是 SP3（单锅固相增强样品制备）策略的扩展，为其他常用的分级方法（包括强阳离子交换和基于反相的色谱法）提供了一种有效但互补的方法。我们证明 CIF 是一种有效的离线分离策略，无论是单独使用还是与高 pH 反相作为肽分级的第二维使用，都能够增加肽分析物覆盖的深度。这些特性使其非常适合广泛的蛋白质组学应用，包括低丰度诱饵蛋白的亲和纯化。
