基于等质量肽段末端标记策略的质谱鉴定新算法

等质量肽段末端标记(Isobaric peptide termini labeling,IPTL)是一种使用轻、重同位素分别对肽段的C端和N端进行等重标记的技术.在对使用这种标记技术得到的数据进行一级谱分析时,由于肽段的质量相同,不会增加样本的复杂性,而在处理二级谱的数据时,可利用成对的b、y离子进行分析.本研究利用IPTL方法得到的实验数据设计了一种新的打分算法:全部离子打分算法(All ions scoring algorithm,AISA).AISA在对数据进行处理时,可以同时得到定性和定量信息.在Q-Exactive HeLa和Human-HCC-HL数据集上的蛋白定量覆盖率分别达到99%和100%.在Q-Exactive HeLa 2D RPLC数据集上,AISA算法鉴定到的PSM、唯一肽段和蛋白质分别比Morpheus高15%、26%和22%.在Human-HCC-HL数据集上,AISA算法鉴定到的PSM、唯一肽段和蛋白质分别比Morpheus高24%、39%和27%.在Q-Exactive HeLa和Human-HCC-HL数据集上蛋白质定量比值的平均值非常接近1,分别为1.18和0.90;在0.5~2.0区间内的定量比值分别为91%和94%.

Novel Algorithm for Identification and Quantification of Proteins Based on Strategy of Isobaric Peptide Termini Labelling

Isobaric peptide termini labeling ( IPTL) is a technology which uses light and heavy isotopes to label C-terminus and N-terminus of peptides. As the masses of labeled peptides are equivalent, the complexity of sample is low when analyzing MS data produced by this technology. Besides, paired b and y ions are helpful while analyzing MS/MS data in this kind of experiments. On the basis of this, a novel scoring algorithm, all ions scoring algorithm (AISA), has been designed for IPTL experiments. The information of quantification and qualification can be acquired at the same time using AISA. On Q-Exactive HeLa 2D RPLC dataset, peptide spectrum matches ( PSMs) , distinct peptides and protein groups identified by AISA are 15%, 26%and 22% higher than Morpheus. On human-HCC-HL dataset, PSMs, distinct peptides and protein groups identified by AISA are 24%, 39% and 27% higher than Morpheus. Quantification ratio on Q-Exactive HeLa and human-HCC-HL datasets are 1. 18 and 0. 90, respectively, which are very close to 1. Besides, quantification ratios between 0. 5 and 2. 0 are 91% and 94%, respectively.