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使用线性离子阱质谱进行MRM筛选/生物标志物发现:人类癌症特异性肽库

MRM screening/biomarker discovery with linear ion trap MS: a library of human cancer-specific peptides.

作者信息

Yang Xu, Lazar Iulia M

机构信息

Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.

出版信息

BMC Cancer. 2009 Mar 27;9:96. doi: 10.1186/1471-2407-9-96.

Abstract

BACKGROUND

The discovery of novel protein biomarkers is essential in the clinical setting to enable early disease diagnosis and increase survivability rates. To facilitate differential expression analysis and biomarker discovery, a variety of tandem mass spectrometry (MS/MS)-based protein profiling techniques have been developed. For achieving sensitive detection and accurate quantitation, targeted MS screening approaches, such as multiple reaction monitoring (MRM), have been implemented.

METHODS

MCF-7 breast cancer protein cellular extracts were analyzed by 2D-strong cation exchange (SCX)/reversed phase liquid chromatography (RPLC) separations interfaced to linear ion trap MS detection. MS data were interpreted with the Sequest-based Bioworks software (Thermo Electron). In-house developed Perl-scripts were used to calculate the spectral counts and the representative fragment ions for each peptide.

RESULTS

In this work, we report on the generation of a library of 9,677 peptides (p < 0.001), representing approximately 1,572 proteins from human breast cancer cells, that can be used for MRM/MS-based biomarker screening studies. For each protein, the library provides the number and sequence of detectable peptides, the charge state, the spectral count, the molecular weight, the parameters that characterize the quality of the tandem mass spectrum (p-value, DeltaM, Xcorr, DeltaCn, Sp, no. of matching a, b, y ions in the spectrum), the retention time, and the top 10 most intense product ions that correspond to a given peptide. Only proteins identified by at least two spectral counts are listed. The experimental distribution of protein frequencies, as a function of molecular weight, closely matched the theoretical distribution of proteins in the human proteome, as provided in the SwissProt database. The amino acid sequence coverage of the identified proteins ranged from 0.04% to 98.3%. The highest-abundance proteins in the cellular extract had a molecular weight (MW)<50,000.

CONCLUSION

Preliminary experiments have demonstrated that putative biomarkers, that are not detectable by conventional data dependent MS acquisition methods in complex un-fractionated samples, can be reliable identified with the information provided in this library. Based on the spectral count, the quality of a tandem mass spectrum and the m/z values for a parent peptide and its most abundant daughter ions, MRM conditions can be selected to enable the detection of target peptides and proteins.

摘要

背景

新型蛋白质生物标志物的发现对于临床环境至关重要,有助于早期疾病诊断并提高生存率。为了促进差异表达分析和生物标志物发现,已开发了多种基于串联质谱(MS/MS)的蛋白质谱分析技术。为实现灵敏检测和准确定量,已采用了靶向MS筛选方法,如多反应监测(MRM)。

方法

通过二维强阳离子交换(SCX)/反相液相色谱(RPLC)分离与线性离子阱MS检测联用,对MCF-7乳腺癌蛋白质细胞提取物进行分析。MS数据用基于Sequest的Bioworks软件(赛默飞世尔科技)进行解释。使用内部开发的Perl脚本计算每个肽段的谱图计数和代表性碎片离子。

结果

在本研究中,我们报告了一个包含9677个肽段(p < 0.001)的文库的生成,这些肽段代表了来自人乳腺癌细胞的约1572种蛋白质,可用于基于MRM/MS的生物标志物筛选研究。对于每种蛋白质,该文库提供了可检测肽段的数量和序列、电荷状态、谱图计数、分子量、表征串联质谱质量的参数(p值、DeltaM、Xcorr、DeltaCn、Sp、谱图中匹配的a、b、y离子数量)、保留时间以及对应给定肽段的前10个最强产物离子。仅列出通过至少两个谱图计数鉴定的蛋白质。蛋白质频率的实验分布作为分子量的函数,与SwissProt数据库中提供的人类蛋白质组中蛋白质的理论分布密切匹配。鉴定出的蛋白质的氨基酸序列覆盖率范围为0.04%至98.3%。细胞提取物中丰度最高的蛋白质分子量(MW)<50,000。

结论

初步实验表明,在复杂的未分级样品中,传统的数据依赖型MS采集方法无法检测到的假定生物标志物,可通过该文库提供的信息可靠地鉴定出来。基于谱图计数、串联质谱的质量以及母肽及其最丰富子离子的m/z值,可以选择MRM条件以实现对目标肽段和蛋白质的检测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d6f/2670839/2376e2ed5f8d/1471-2407-9-96-1.jpg

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