Learning from Decoys to Improve the Sensitivity and Specificity of Proteomics Database Search Results

The statistical validation of database search results is a complex issue in bottom-up proteomics. The correct and incorrect peptide spectrum match (PSM) scores overlap significantly, making an accurate assessment of true peptide matches challenging. Since the complete separation between the true and false hits is practically never achieved, there is need for better methods and rescoring algorithms to improve upon the primary database search results. Here we describe the calibration and False Discovery Rate (FDR) estimation of database search scores through a dynamic FDR calculation method, FlexiFDR, which increases both the sensitivity and specificity of search results. Modelling a simple linear regression on the decoy hits for different charge states, the method maximized the number of true positives and reduced the number of false negatives in several standard datasets of varying complexity (18-mix, 49-mix, 200-mix) and few complex datasets (E. coli and Yeast) obtained from a wide variety of MS platforms. The net positive gain for correct spectral and peptide identifications was up to 14.81% and 6.2% respectively. The approach is applicable to different search methodologies- separate as well as concatenated database search, high mass accuracy, and semi-tryptic and modification searches. FlexiFDR was also applied to Mascot results and showed better performance than before. We have shown that appropriate threshold learnt from decoys, can be very effective in improving the database search results. FlexiFDR adapts itself to different instruments, data types and MS platforms. It learns from the decoy hits and sets a flexible threshold that automatically aligns itself to the underlying variables of data quality and size.     

线粒体蛋白质组学研究进展

总结近年来不同物种线粒体蛋白表达谱的构建及线粒体蛋白功能的研究。线粒体蛋白质组正处于迅速发展阶段,但是由于分离、鉴定等技术的局限,线粒体蛋白数据库仍然贫乏。     

水稻蛋白质组学研究

水稻是全球最重要的粮食作物之一,目前水稻基因组精细图谱已得到全面解析,运用以双向电泳和质谱分析为主的蛋白质组技术平台对水稻各种组织器官进行蛋白质组学研究也取得了诸多进展,对水稻蛋白质组研究背景,技术路线及取得的进展进行了介绍,并对水稻蛋白质组的发展作了展望。     

基于GEO数据库、TMT蛋白组学筛选绞股蓝对膀胱癌的蛋白靶点

绞股蓝(Gynostemma pentaphyllum)是传统的中药材,对于多种癌症具有显著的疗效.为筛选绞股蓝对膀胱癌的作用靶点,本研究将30只SPF级SD大鼠随机分为模型组、给药组和空白组,通过膀胱灌注N-甲基-N-亚硝基脲(MNU)建立膀胱癌模型并通过相同的方式进行膀胱灌注绞股蓝干预治疗,在第10周进行取材,通过H&E染色病理切片观察各组膀胱内肿瘤情况以明确药效.通过蛋白质组学串联质谱标签(TMT) 10重标记法检测各组膀胱组织的蛋白差异表达情况,结合GEO数据库中3组膀胱癌数据集对作用靶点进行筛选.结果 显示,绞股蓝反向调节膀胱癌335种蛋白质,其中包括55种上调和280种下调.GEO的3个膀胱癌表达谱中汇集的差异蛋白(DEGs)包含20种上调和50种下调.将GEO中DEGs与TMT蛋白质组学中膀胱癌趋势相同的蛋白进行汇集,结合绞股蓝反向调节数据,总共筛选获得了3个反向调节靶点,其中包括1种下调的靶点CNN1和2种上调的靶点KRT19、PCP4,并通过蛋白免疫印迹法进行验证.本研究结果表明,CNN1、KRT19和PCP4可能是绞股蓝治疗膀胱癌的潜在靶点,绞股蓝可能通过调节CNN1、KRT19和PCP4来抵抗膀胱癌,这为绞股蓝治疗膀胱癌提供分子机制依据.     

蛋白质组学研究技术及其进展

蛋白质组学是在后基因组时代出现的一个新的研究领域,它是对机体、组织或细胞的全部蛋白质的表达和功能模式进行研究。对蛋白质组的研究可以使我们更容易接近对生命过程的认识。本文对蛋白质组学研究所使用的主要技术例如二维凝胶电泳、质谱、酵母双杂交、蛋白质芯片、表面等离子共振和生物信息学等作一简要综述。     

The HUPO Proteomics Standards Initiative Meeting: Towards Common Standards for Exchanging Proteomics Data

The Proteomics Standards Initiative (PSI) aims to define community standards for data representation in proteomics and to facilitate data comparison, exchange and verification. Initially the fields of protein-protein interactions (PPI) and mass spectroscopy have been targeted and the inaugural meeting of the PSI addressed the questions of data storage and exchange in both of these areas. The PPI group rapidly reached consensus as to the minimum requirements for a data exchange model; an XML draft is now being produced. The mass spectroscopy group have achieved major advances in the definition of a required data model and working groups are currently taking these discussions further. A further meeting is planned in January 2003 to advance both these projects.     

蛋白质组学及其技术发展

蛋白质组学产生于20世纪90年代,发展至今已日趋成熟。蛋白质组学是以生物体的全部或部分蛋白为研究对象,研究它们在生命活动过程中的作用、功能。蛋白质组学较之前的基因组学对于生命现象的解释更直接、更准确,近年得到了快速发展,并受到世界各国学者的高度关注。我们简要综述了蛋白质组学及其技术,并简单概述了这项技术在生命科学领域的应用。     

The MetaCyc Database

MetaCyc is a metabolic-pathway database that describes 445 pathways and 1115 enzymes occurring in 158 organisms. MetaCyc is a review-level database in that a given entry in MetaCyc often integrates information from multiple literature sources. The pathways in MetaCyc were determined experimentally, and are labeled with the species in which they are known to occur based on literature references examined to date. MetaCyc contains extensive commentary and literature citations. Applications of MetaCyc include pathway analysis of genomes, metabolic engineering and biochemistry education. MetaCyc is queried using the Pathway Tools graphical user interface, which provides a wide variety of query operations and visualization tools. MetaCyc is available via the World Wide Web at http://ecocyc.org/ecocyc/metacyc.html, and is available for local installation as a binary program for the PC and the Sun workstation, and as a set of flatfiles. Contact metacyc-info@ai.sri.com for information on obtaining a local copy of MetaCyc.     

Interaction Proteomics

The term proteome is traditionally associated with the identification of a large number of proteins within complex mixtures originating from a given organelle, cell or even organism. Current proteome investigations are basically focused on two major areas, expression proteomics and functional proteomics. Both approaches rely on the fractionation of protein mixtures essentially by two-dimensional polyacrylamide gel electrophoresis (2D-gel) and the identification of individual protein bands by mass spectrometric techniques (2D-MS). Functional proteomics approaches are basically addressing two main targets, the elucidation of the biological function of unknown proteins and the definition of cellular mechanisms at the molecular level. In the cell many processes are governed not only by the relative abundance of proteins but also by rapid and transient regulation of activity, association and localization of proteins and protein complexes. The association of an unknown protein with partners belonging to a specific protein complex involved in a particular process would then be strongly suggestive of its biological function. The identification of interacting proteins in stable complexes in a cellular system is essentially achieved by affinity-based procedures. Different strategies relying on this simple concept have been developed and a brief overview of the main approaches presently used in functional proteomics studies is described.     

亚细胞蛋白质组学

蛋白质组研究应用了分辨蛋白分离技术、质谱法、生物信息学工具来鉴定生物体蛋白质性质。但由于高等真核细胞的复杂性 ,对其全部蛋白质组进行一步鉴定难于达到。为了分析细胞的全蛋白质组 ,目前提议以亚细胞蛋白质组作为切入点 ,即建立细胞的大分子结构 ,如亚细胞区室、细胞器、大分子结构和多蛋白复合物相应的蛋白质组 ,其优点是减少全细胞分析的复杂性 ,研究结果更具体。本文将介绍在亚细胞蛋白质组方面的已开展研究的概况。1 .细胞膜蛋白质组学在ＳＤＳ ＰＡＧＥ分析中 ,由于膜蛋白提取量少和 /或分辨率差而难以显示 ,这首先涉及膜蛋白自…     

蛋白质组学及其在神经科学中的应用

蛋白质组学这一概念从提出到现在已应用到生命科学许多领域.在中枢神经系统中,全脑以及许多脑区的蛋白质组数据库逐步建立,并且已经鉴定出了许多在神经系统疾病过程中起重要作用的蛋白.虽然神经系统蛋白质组学的研究尚处于起步阶段,但在阐明某些疾病的发病机制方面已取得长足发展.本文对蛋白质组学及其在神经科学中的研究进展作一综述.     

Viral Proteomics

Summary: Viruses have long been studied not only for their pathology and associated disease but also as model systems for molecular processes and as tools for identifying important cellular regulatory proteins and pathways. Recent advances in mass spectrometry methods coupled with the development of proteomic approaches have greatly facilitated the detection of virion components, protein interactions in infected cells, and virally induced changes in the cellular proteome, resulting in a more comprehensive understanding of viral infection. In addition, a rapidly increasing number of high-resolution structures for viral proteins have provided valuable information on the mechanism of action of these proteins as well as aided in the design and understanding of specific inhibitors that could be used in antiviral therapies. In this paper, we discuss proteomic studies conducted on all eukaryotic viruses and bacteriophages, covering virion composition, viral protein structures, virus-virus and virus-host protein interactions, and changes in the cellular proteome upon viral infection.     

数据挖掘在蛋白质组学研究中的应用

介绍蛋白质组学研究的背景;阐述数据挖掘的原理、方法,重点讲述数据挖掘技术在蛋白质组学研究中取得的新的进展。最后,对数据挖掘目前存在的问题作分析,并对它的发展的前景作展望。