Ndassa Yasmine M, Orsi Chris, Marto Jarrod A, Chen She, Ross Mark M
Biophysics Program, Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA.
J Proteome Res. 2006 Oct;5(10):2789-99. doi: 10.1021/pr0602803.
Dysregulated protein phosphorylation is a primary culprit in multiple physiopathological states. Hence, although analysis of signaling cascades on a proteome-wide scale would provide significant insight into both normal and aberrant cellular function, such studies are simultaneously limited by sheer biological complexity and concentration dynamic range. In principle, immobilized metal affinity chromatography (IMAC) represents an ideal enrichment method for phosphoproteomics. However, anecdotal evidence suggests that this technique is not widely and successfully applied beyond analysis of simple standards, gel bands, and targeted protein immunoprecipitations. Here, we report significant improvements in IMAC-based methodology for enrichment of phosphopeptides from complex biological mixtures. Moreover, we provide detailed explanation for key variables that in our hands most influenced the outcome of these experiments. Our results indicate 5- to 10-fold improvement in recovery of singly- and multiply phosphorylated peptide standards in addition to significant improvement in the number of high-confidence phosphopeptide sequence assignments from global analysis of cellular lysate. In addition, we quantitatively track phosphopeptide recovery as a function of phosphorylation state, and provide guidance for impedance-matching IMAC column capacity with anticipated phosphopeptide content of complex mixtures. Finally, we demonstrate that our improved methodology provides for identification of phosphopeptide distributions that closely mimic physiological conditions.
蛋白质磷酸化失调是多种生理病理状态的主要罪魁祸首。因此，尽管在蛋白质组范围内分析信号级联反应将为正常和异常细胞功能提供重要见解，但此类研究同时受到生物学复杂性和浓度动态范围的限制。原则上，固定化金属亲和色谱法（IMAC）是磷酸化蛋白质组学的理想富集方法。然而，有传闻证据表明，除了简单标准品、凝胶条带和靶向蛋白质免疫沉淀分析之外，该技术并未得到广泛且成功的应用。在此，我们报告了基于IMAC的方法在从复杂生物混合物中富集磷酸肽方面的重大改进。此外，我们对在我们手中对这些实验结果影响最大的关键变量提供了详细解释。我们的结果表明，单磷酸化和多磷酸化肽标准品的回收率提高了5至10倍，同时从细胞裂解物的全局分析中获得的高可信度磷酸肽序列分配数量也有显著提高。此外，我们定量跟踪磷酸肽回收率作为磷酸化状态的函数，并为使IMAC柱容量与复杂混合物中预期的磷酸肽含量进行阻抗匹配提供指导。最后，我们证明我们改进的方法能够识别出紧密模拟生理条件的磷酸肽分布。
