State Key Laboratory of Proteomics, Beijing Institute of Radiation Medicine, National Engineering Research Center for Protein Drugs, No. 33, Life Science Park Road, Changping District, Beijing, 102206, China.
Rapid Commun Mass Spectrom. 2012 Aug 30;26(16):1875-86. doi: 10.1002/rcm.6293.
Chimera spectra make it challenging to identify proteins in complex mixtures by LC/MS/MS. Approximately half of the spectra collected are chimera spectra even when high-resolution tandem mass spectrometry is used. Chimera spectra are generated from the co-fragmentation of different co-elute peptides, and it is often difficult to distinguish monoisotopic precursors of these peptides from each other.
In this paper, we propose a peak intensity ratio-based monoisotopic peak determination algorithm (PIRMD) to distinguish different monoisotopic precursors of chimera spectra. Monoisotopic peaks in non-overlapping clusters are detected by the edge features of the isotopic peak intensity ratios. For multiple overlapping clusters grouped as one cluster, monoisotopic peaks can be detected by an advanced estimation of the similarity between the estimated and the experimental isotopic distribution based on the isotopic peak intensity ratios.
High-resolution mass spectrometric datasets acquired from mixtures of 30 synthetic peptides and mixtures of 18 proteins were used to evaluate the efficiency and accuracy of PIRMD. The results indicate that PIRMD can recognize monoisotopic precursors from the chimera spectra containing non-overlapping and overlapping isotopic clusters. Compared to several published algorithms, PIRMD identifies approximately 2 ~ 14% more spectra and has fewer false positives.
The results on standard datasets and actual samples demonstrated that PIRMD could notably improve the successful identification rates of the spectra by identifying more chimera spectra, and of the identified spectra, approximately 25% are chimera spectra. This novel algorithm will help to interpret spectra produced by shotgun strategy in proteomics.
嵌合体谱使通过 LC/MS/MS 对复杂混合物中的蛋白质进行鉴定变得具有挑战性。即使使用高分辨率串联质谱,也有约一半收集的谱是嵌合体谱。嵌合体谱是由不同共洗脱肽的共碎裂产生的,通常很难将这些肽的单一同位素前体彼此区分开来。
在本文中,我们提出了一种基于峰强度比的单一同位素峰确定算法(PIRMD),以区分嵌合体谱的不同单一同位素前体。通过同位素峰强度比的边缘特征检测非重叠峰簇中的单一同位素峰。对于分组为一个簇的多个重叠峰簇,可以通过基于同位素峰强度比的估计和实验同位素分布之间的相似性的高级估计来检测单一同位素峰。
使用从 30 种合成肽混合物和 18 种蛋白质混合物获得的高分辨率质谱数据集来评估 PIRMD 的效率和准确性。结果表明,PIRMD 可以识别包含非重叠和重叠同位素簇的嵌合体谱中的单一同位素前体。与几个已发表的算法相比,PIRMD 可以识别约 2%至 14%更多的谱,并且假阳性更少。
在标准数据集和实际样本上的结果表明,PIRMD 可以通过识别更多的嵌合体谱来显著提高谱的成功识别率,并且在已识别的谱中,约 25%是嵌合体谱。这种新算法将有助于解释蛋白质组学中使用鸟枪法产生的谱。