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通过磁珠辅助、自动化样品处理及基质辅助激光解吸电离飞行时间质谱法进行血清肽谱分析。

Serum peptide profiling by magnetic particle-assisted, automated sample processing and MALDI-TOF mass spectrometry.

作者信息

Villanueva Josep, Philip John, Entenberg David, Chaparro Carlos A, Tanwar Meena K, Holland Eric C, Tempst Paul

机构信息

Protein Center, Molecular Biology Program, Memorial Sloan-Kettering Cancer Center, New York, New York 10021, USA.

出版信息

Anal Chem. 2004 Mar 15;76(6):1560-70. doi: 10.1021/ac0352171.

Abstract

Human serum contains a complex array of proteolytically derived peptides (serum peptidome) that may provide a correlate of biological events occurring in the entire organism; for instance, as a diagnostic for solid tumors (Petricoin, E. F.; Ardekani, A. M.; Hitt, B. A.; Levine, P. J.; Fusaro, V. A.; Steinberg, S. M.; Mills, G. B.; Simone, C.; Fishman, D. A.; Kohn, E. C.; Liotta, L. Lancet 2002, 359, 572-577). Here, we describe a novel, automated technology platform for the simultaneous measurement of serum peptides that is simple, scalable, and generates highly reproducible patterns. Peptides are captured and concentrated using reversed-phase (RP) batch processing in a magnetic particle-based format, automated on a liquid handling robot, and followed by a MALDI TOF mass spectrometric readout. The protocol is based on a detailed investigation of serum handling, RP ligand and eluant selection, small-volume robotics design, an optimized spectral acquisition program, and consistent peak extraction plus binning across a study set. The improved sensitivity and resolution allowed detection of 400 polypeptides (0.8-15-kDa range) in a single droplet (approximately 50 microL) of serum, and almost 2000 unique peptides in larger sample sets, which can then be analyzed using common microarray data analysis software. A pilot study indicated that sera from brain tumor patients can be distinguished from controls based on a pattern of 274 peptide masses. This, in turn, served to create a learning algorithm that correctly predicted 96.4% of the samples as either normal or diseased.

摘要

人血清中含有一系列复杂的经蛋白水解产生的肽(血清肽组),这些肽可能与整个机体中发生的生物学事件相关;例如,可作为实体瘤的诊断标志物(佩特里科因,E.F.;阿德卡尼,A.M.;希特,B.A.;莱文,P.J.;富萨罗,V.A.;斯坦伯格,S.M.;米尔斯,G.B.;西蒙内,C.;菲什曼,D.A.;科恩,E.C.;利奥塔,L.《柳叶刀》2002年,第359卷,572 - 577页)。在此,我们描述了一种用于同时测量血清肽的新型自动化技术平台,该平台操作简单、可扩展,且能产生高度可重复的图谱。肽通过基于磁珠的反相(RP)批量处理进行捕获和浓缩,在液体处理机器人上实现自动化操作,随后进行基质辅助激光解吸电离飞行时间(MALDI TOF)质谱读出。该方案基于对血清处理、RP配体和洗脱液选择、小体积机器人设计、优化的光谱采集程序以及整个研究集的一致峰提取和分箱的详细研究。灵敏度和分辨率的提高使得在一滴(约50微升)血清中能够检测到400种多肽(0.8 - 15千道尔顿范围),在更大的样本集中可检测到近2000种独特的肽,然后可使用常见的微阵列数据分析软件进行分析。一项初步研究表明,根据274个肽质量的图谱可将脑肿瘤患者的血清与对照血清区分开来。这进而用于创建一种学习算法,该算法能正确预测96.4%的样本为正常或患病样本。

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