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ISPTM: an Iterative Search Algorithm for Systematic Identification of Post-translational Modifications from Complex Proteome Mixtures

机译:ISPTM:一种用于从复杂蛋白质组混合物中系统识别翻译后修饰的迭代搜索算法

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摘要

Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search. The performance of the ISPTM approach was evaluated on mixtures of 70 synthetic peptides with known modifications, on an 18-protein standard mixture with unknown modifications and on real, complex biological samples of mouse nuclear matrix proteins with unknown modifications. ISPTM revealed that many chemical PTMs were introduced by urea and iodoacetamide during sample preparation and many biological PTMs, including dimethylation of arginine and lysine, were significantly activated by Adriamycin treatment in NM associated proteins. ISPTM increased the MS/MS spectral identification rate substantially, displayed significantly better sensitivity for systematic PTM identification than the conventional all-in-one search approach and offered PTM identification results that were complementary to InsPecT and MODa, both of which are established PTM identification algorithms. In summary, ISPTM is a new and powerful tool for unbiased identification of many different PTMs with high confidence from complex proteome mixtures.
机译:从复杂蛋白质组混合物的串联质谱数据中鉴定蛋白质翻译后修饰(PTM)是一项极富挑战性的任务。在这里,我们提出了一种新的策略,称为用于标识PTM的迭代搜索(ISPTM),以应对这一挑战。 ISPTM方法包括不进行变量修改的基本搜索,然后在每次搜索中使用少量PTM(通常是两个)进行迭代搜索。 ISPTM方法的性能是在70种具有已知修饰的合成肽的混合物,在18种蛋白质具有未知修饰的标准混合物上以及在具有复杂修饰的小鼠核基质蛋白的真实,复杂生物学样品上进行评估的。 ISPTM显示,在样品制备过程中,尿素和碘乙酰胺引入了许多化学PTM,并且在NM相关蛋白中,阿霉素处理可显着激活许多生物PTM,包括精氨酸和赖氨酸的二甲基化。 ISPTM大大提高了MS / MS频谱识别率,与常规的多合一搜索方法相比,对系统PTM识别显示出显着更好的灵敏度,并提供了与InsPecT和MODa互补的PTM识别结果,这两种方法都是已建立的PTM识别算法。总之,ISPTM是一种新的强大工具,可以从复杂的蛋白质组混合物中高度可信地无偏识别许多不同的PTM。

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