一种适用于质谱分析的简化胶内酶解方法

在常规方法的基础上,设计了一种适于质谱分析的简化胶内酶解方法。改进的步骤包括:(1)通过加大洗涤所用超纯水量、延长涡混时间来强化凝胶洗涤的环节;(2)加入酸化处理来提高胰蛋白酶的活性;(3)在预酶解时不加CaCl_2,减少了酶的自切作用;(4)省略了蛋白质样品脱盐、脱SDS的步骤;(5)直接吸取酶解液进行质谱分析。系统比较该简化酶解法和最新报道的一种酶解方法的质谱鉴定效果,简化法能有效减少酶解后肽段的损失,增加质谱数据库搜索的信息量,得到更可靠的蛋白质鉴定结果。     

温和过甲酸氧化辅助酶解结合液质联用技术鉴定大鼠大脑皮层质膜蛋白质

由于膜蛋白质尤其是内在膜蛋白的强疏水性,分析和鉴定质膜蛋白质仍然是以质谱为基础的蛋白质组学的方法中的一个难点.过甲酸氧化是一种应用广泛的打开二硫键的方法,温和的过甲酸试剂能完全的将半胱氨酸转化为半胱磺酸,将甲硫氨酸转化为甲硫氨酸砜,从而使目的蛋白更易溶于水介质.采用蔗糖密度梯度离心法纯化得到大鼠大脑皮层质膜,提取的质膜蛋白质经温和过甲酸氧化处理后经胰酶酶解消化得到肽段,利用LC-MS/MS对所得肽段进行质谱分析,采集的原始数据用Mascot软件进行库搜寻鉴定.此方法是研究质膜蛋白质的新方法,温和过甲酸氧化显示出很好的氧化效果却避免其它不利于鉴定的副反应.从大鼠大脑皮层膜提取物共鉴定出220种蛋白质,其中73种为整合膜蛋白,证明对质膜蛋白质直接进行温和过甲酸氧化然后酶解的方法辅助酶解可以有效的鉴定质膜蛋白质.     

基于质谱和生物信息学分析的小菜蛾蛋白质鉴定

本研究以非模式昆虫小菜蛾Plutella xylostella为材料, 对比2, 3, 4龄幼虫的蛋白质组双向电泳图谱, 得到24个蛋白质差异点, 从中选取了编号为1111的差异表达蛋白质点进行质谱鉴定和生物信息学分析. 采用胶内酶解的多肽进行MALDI-TOF/TOF分析, 获得该点的肽质量指纹图谱（PMF）及串联质谱（MS/MS）图谱。将获得的PMF分别用MASCOT和ProFound等常用软件在NCBInr的Metazoa蛋白质数据库进行搜索, 匹配结果不理想. 进一步用PMF+MS/MS谱图搜索NCBInr的Metazoa蛋白质数据库, 以及小菜蛾EST数据库。 在NCBInr库中匹配结果为拟暗果蝇Drosophila pseudoobscura中的一种假定蛋白GA18218-PA, 而用EST库搜索的结果为家蚕Bombyx mori的ATP合酶的亚基。为验证搜索结果, 将该蛋白质点进行磺基异硫氰酸苯酯（SPITC）化学衍生后de novo测序, 最后确认该点可能为ATP合酶的一个亚基。最后着重讨论了蛋白质的质谱鉴定与生物信息学分析的联合使用, 希望据此选择出最适合于非模式昆虫蛋白质组学鉴定的方法。     

大鼠海马的表达蛋白质组学实验研究

目的：用蛋白质组学方法初步分析大鼠海马蛋白质的表达。方法：提取大鼠海马蛋白质样品后,用双向凝胶电泳对其分离,经考马斯亮蓝染色后,产生大鼠海马蛋白质双向凝胶电泳图谱。从凝胶上切割分离的蛋白质,经胰蛋白酶胶内酶解,通过基质辅助激光解吸／电离飞行时间质谱（MALDI-TOF-MS）对酶解后的肽段进行分析。根据肽段质谱数据,经数据库（NCBI）检索,对蛋白质进行鉴定。结果：鉴定了37种具有明确功能的蛋白质,它们分别属于代谢酶、细胞骨架蛋白、热休克蛋白、抗氧化蛋白、信号传导蛋白、蛋白酶体相关蛋白、神经元特异蛋白及神经胶质蛋白。另外,鉴定了3种未知功能蛋白。结论：为建立大鼠海马蛋白质组数据库提供必要的资料,为在大鼠模型上研究神经疾病发病机理奠定基础。     

大腹园蛛(Araneus ventricosus)粗毒双向电泳及质谱分析

以大腹园蛛粗毒为材料,用固相pH梯度等电聚焦IPG(immobilized pH gradient)和SDS-PAGE(sodium dodecyl sulfate polyacrylamide gel electrophoresis)获得蛋白质组双向电泳图谱,经Bio-Rad公司的PDQUEST软件进行图像分析,检测到500个左右的蛋白质点．对其图谱的部分蛋白质点酶解后使用Micromass公司的ESI-Q-TOF进行了鉴定．得到了质量较好的MS／MS数据．然后将其在MS-Fit中的genepeptide数据库和Mascot的Swissprot中进行搜索从而对蛋白质点进行鉴定．目前初步获得5个组分的鉴定结果．     

串联质谱数据的从头解析与蛋白质的数据库搜索鉴定

蛋白质的鉴定是蛋白质组学研究中必不可少的一步。用串联质谱 (tandemmassspectrometry ,MS/MS)可以进行多肽的从头测序 (denovosequencing) ,并搜索数据库以鉴定蛋白质。用图论以及真实谱 理论谱联配 (alignment)的方法对串联质谱得到的多肽图谱进行从头解析 ,得到了可靠的多肽序列 ,并应用到数据库搜索中鉴定了相应的蛋白质。同时 ,还用统计的方法对SwissProt以及TrEMBL蛋白质数据库进行了详细的分析。结果表明 ,3个四肽或者 2个五肽或者 1个八肽一般可以唯一地确定一个蛋白质     

长双歧杆菌BBMN68 可溶性蛋白质图谱的建立

为了建立长双歧杆菌BBMN68蛋白质图谱,采用双向电泳的方法建立了2-D参考图谱,通过MALDI-TOF/MS质谱鉴定和数据库搜索,鉴定到206个蛋白质(占长双歧杆菌BBMN68基因预测总蛋白的11.4%)。通过2-D胶分析,共有800±15(对数期)和800±20(稳定期)个蛋白质,其中282个蛋白点成功鉴定,代表206个不同的蛋白质。另外,分析了实验鉴定蛋白质的等电点和分子量,蛋白功能,密码子偏好性,蛋白质疏水性以及蛋白质细胞定位的分析。研究结果为长双歧杆菌的比较蛋白质组学研究提供了参考图谱和蛋白质基础信息数据。     

多维色谱-串联质谱联用技术分离和鉴定小鼠肝脏质膜蛋白质

采用自动在线纳流多维液相色谱 串联质谱联用的方法分离和鉴定蔗糖密度梯度离心法分离和富集的小鼠肝脏质膜蛋白质 .以强阳离子交换柱为第一相 ,反相柱为第二相 ,在两相之间连接一预柱脱盐和浓缩肽段 .用含去污剂的溶剂提取细胞质膜中的蛋白质 ,获得的质膜蛋白质经酶解和适当的酸化后通过离子交换柱吸附 ,分别用 10个不同浓度的乙酸铵盐溶液进行分段洗脱 .洗脱物经预柱脱盐和浓缩后进入毛细管反相柱进行反相分离 ,分离后的肽段直接进入质谱仪离子源进行一级和二级质谱分析 .质谱仪采得的数据经计算机处理后用Mascot软件进行蛋白质数据库搜寻 ,共鉴定出 12 6种蛋白质 ,其中 4 1种为膜蛋白 ,包括与膜相关的蛋白质和具有多个跨膜区的整合膜蛋白 ,为建立质膜蛋白质组学研究的适宜方法和质膜蛋白质数据库提供了有价值的基础性研究资料 .     

MALDI-TOF MS技术在侵袭性丝状真菌快速鉴定中的应用

目的 探索不同培养基、不同培养时间和不同蛋白质提取方法对侵袭性丝状真菌质谱鉴定准确率的影响,旨在提高基质辅助激光解析电离飞行时间质谱技术鉴定侵袭性丝状真菌的准确率。方法 采用分子生物学方法为金标准,同时运用基质辅助激光解析电离飞行时间质谱技术对所收集临床丝状真菌进行鉴定。根据分子生物学的鉴定结果,去除VITEK-MS v3.0数据库中没有的菌株,其余菌株接种在沙氏葡萄糖琼脂(SDA)、马铃薯葡萄糖琼脂(PDA)和察氏培养基(CA)3种不同的培养基中,采用2种不同的蛋白质提取方法(甲酸乙腈法和磁珠法),获得了不同培养时间点(2、3、5、7和9 d)的特异性质谱指纹图谱。结果 不同丝状真菌蛋白质提取方法进行比较,甲酸乙腈法总鉴定准确率为79.8%,磁珠法总鉴定准确率为77.5%,2种丝状真菌蛋白质提取方法的质谱鉴定准确率差异无统计学意义(χ²=1.040,P=0.308)。不同培养基进行比较,SDA培养基总鉴定准确率为90.7%,PDA培养基总鉴定准确率为81.4%,CA培养基总鉴定准确率为67.4%,3种不同培养基的丝状真菌质谱鉴定准确率差异有统计学意义(χ     

固相化学辅助MALDI-TOF质谱源后衰变技术对2D-胶银染蛋白质点的鉴定

利用O 甲基异脲氢硫酸 (O methylisoureahydrogensulfate)修饰 2D 胶上胰蛋白酶原位酶切后产生的Lys 肽 ,使其具有Arg 肽的特性 ,提高质谱测定的灵敏度 ,然后用化学试剂 3 磺酸丙酸N 羟基琥珀酰胺酯 ( 3 sulfopropionicacidNHS ester)修饰Lys 肽及Arg 肽 ,修饰的产物在进行PSD测序时能得到单一的y 离子系列 ,有利于蛋白质酶解片段序列的从头解析 ,为 2D 胶上蛋白质点的准确鉴定提供有力的依据 ;该方法应用于鼻咽癌细胞 2D胶银染蛋白质点的鉴定取得可靠结果     

Effect of cleavage enzyme, search algorithm and decoy database on mass spectrometric identification of wheat gluten proteins

While tandem mass spectrometry (MS/MS) is routinely used to identify proteins from complex mixtures, certain types of proteins present unique challenges for MS/MS analyses. The major wheat gluten proteins, gliadins and glutenins, are particularly difficult to distinguish by MS/MS. Each of these groups contains many individual proteins with similar sequences that include repetitive motifs rich in proline and glutamine. These proteins have few cleavable tryptic sites, often resulting in only one or two tryptic peptides that may not provide sufficient information for identification. Additionally, there are less than 14,000 complete protein sequences from wheat in the current NCBInr release. In this paper, MS/MS methods were optimized for the identification of the wheat gluten proteins. Chymotrypsin and thermolysin as well as trypsin were used to digest the proteins and the collision energy was adjusted to improve fragmentation of chymotryptic and thermolytic peptides. Specialized databases were constructed that included protein sequences derived from contigs from several assemblies of wheat expressed sequence tags (ESTs), including contigs assembled from ESTs of the cultivar under study. Two different search algorithms were used to interrogate the database and the results were analyzed and displayed using a commercially available software package (Scaffold). We examined the effect of protein database content and size on the false discovery rate. We found that as database size increased above 30,000 sequences there was a decrease in the number of proteins identified. Also, the type of decoy database influenced the number of proteins identified. Using three enzymes, two search algorithms and a specialized database allowed us to greatly increase the number of detected peptides and distinguish proteins within each gluten protein group.     

Analysing proteomic data

The rapid growth of proteomics has been made possible by the development of reproducible 2D gels and biological mass spectrometry. However, despite technical improvements 2D gels are still less than perfectly reproducible and gels have to be aligned so spots for identical proteins appear in the same place. Gels can be warped by a variety of techniques to make them concordant. When gels are manipulated to improve registration, information is lost, so direct methods for gel registration which make use of all available data for spot matching are preferable to indirect ones. In order to identify proteins from gel spots a property or combination of properties that are unique to that protein are required. These can then be used to search databases for possible matches. Molecular mass, pI, amino acid composition and short sequence tags can all be used in database searches. Currently the method of choice for protein identification is mass spectrometry. Proteins are eluted from the gels and cleaved with specific endoproteases to produce a series of peptides of different molecular mass. In peptide mass fingerprinting, the peptide profile of the unknown protein is compared with theoretical peptide libraries generated from sequences in the different databases. Tandem mass spectroscopy (MS/MS) generates short amino acid sequence tags for the individual peptides. These partial sequences combined with the original peptide masses are then used for database searching, greatly improving specificity. Increasingly protein identification from MS/MS data is being fully or partially automated. When working with organisms, which do not have sequenced genomes (the case with most helminths), protein identification by database searching becomes problematical. A number of approaches to cross species protein identification have been suggested, but if the organism being studied is only distantly related to any organism with a sequenced genome then the likelihood of protein identification remains small. The dynamic nature of the proteome means that there really is no such thing as a single representative proteome and a complete set of metadata (data about the data) is going to be required if the full potential of database mining is to be realised in the future.     

蛋白质组学中新蛋白质鉴定的研究方法和策略

当前,基于生物质谱进行蛋白质鉴定的技术已经成为蛋白质组学研究的支撑技术之一.产生的数据主要使用数据库搜索的方法进行处理,这种方法的一大缺陷是不能鉴定数据库中未包含的蛋白质,因此如何充分利用质谱数据对蛋白质组研究的意义很大,而新蛋白质鉴定更是其中一个重要的内容.新蛋白质鉴定是蛋白质鉴定的一个方面,新蛋白质的定义按照序列和功能的已知程度分为3个层次;以蛋白质鉴定的方法为基础,目前新蛋白质鉴定的方法可分为denovo测序和相似序列搜索结合的方法以及搜索EST、基因组等核酸数据库的方法2大类;两者各有利弊.存在各自的问题和相应处理的策略.不同的研究者可以根据具体目的应用和发展不同的鉴定方法,同时新蛋白质的鉴定也将随着蛋白质组学研究的发展而更加完善.     

Optimization and use of peptide mass measurement accuracy in shotgun proteomics

Mass spectrometers that provide high mass accuracy such as FT-ICR instruments are increasingly used in proteomic studies. Although the importance of accurately determined molecular masses for the identification of biomolecules is generally accepted, its role in the analysis of shotgun proteomic data has not been thoroughly studied. To gain insight into this role, we used a hybrid linear quadrupole ion trap/FT-ICR (LTQ FT) mass spectrometer for LC-MS/MS analysis of a highly complex peptide mixture derived from a fraction of the yeast proteome. We applied three data-dependent MS/MS acquisition methods. The FT-ICR part of the hybrid mass spectrometer was either not exploited, used only for survey MS scans, or also used for acquiring selected ion monitoring scans to optimize mass accuracy. MS/MS data were assigned with the SEQUEST algorithm, and peptide identifications were validated by estimating the number of incorrect assignments using the composite target/decoy database search strategy. We developed a simple mass calibration strategy exploiting polydimethylcyclosiloxane background ions as calibrant ions. This strategy allowed us to substantially improve mass accuracy without reducing the number of MS/MS spectra acquired in an LC-MS/MS run. The benefits of high mass accuracy were greatest for assigning MS/MS spectra with low signal-to-noise ratios and for assigning phosphopeptides. Confident peptide identification rates from these data sets could be doubled by the use of mass accuracy information. It was also shown that improving mass accuracy at a cost to the MS/MS acquisition rate substantially lowered the sensitivity of LC-MS/MS analyses. The use of FT-ICR selected ion monitoring scans to maximize mass accuracy reduced the number of protein identifications by 40%.     

Result-driven strategies for protein identification and quantitation--a way to optimize experimental design and derive reliable results

Uni- or multidimensional microcapillary liquid chromatography (microLC) matrix-assisted laser desorption/ionization (MALDI) tandem mass spectrometry (MS/MS) approaches have gained significant attention for quantifying and identifying proteins in complex biological samples. The off-line coupling of microLC with MS quantitation and MS/MS identification methods makes new result-dependent workflows possible. A relational database is used to store the results from multiple high performance liquid chromatography runs, including information about MALDI plate positions, and both peptide and protein quantitations, and identifications. Unlike electrospray methodology, where all the decisions about which peptide to fragment, must be made during peptide fractionations, in the MALDI experiments the samples are effectively "frozen in time". Therefore, additional MS and MS/MS spectra can be acquired, to promote more accurate quantitation or additional identifications until reliable results are derived that meet experimental design criteria. In the case of what can be designated the expression-dependent workflow, quantitation can be detached from identification and only peak pairs with biological relevant expression changes can be selected for further MS/MS analyses. Alternatively, additional MS/MS data can be acquired to confirm tentative peptide mass fingerprint hits in what is designated a search result-dependent workflow. In the MS data-dependent workflow, the goal is to collect as many meaningful spectra as possible by judiciously adjusting the acquisition parameters based on characteristics of the parent masses. This level of sophistication requires the development of innovative algorithms for these three result-dependent workflows that make MS and MS/MS analysis more efficient and also add confidence to experimental results.     

CHOMPER: a bioinformatic tool for rapid validation of tandem mass spectrometry search results associated with high-throughput proteomic strategies

Current efforts aimed at developing high-throughput proteomics focus on increasing the speed of protein identification. Although improvements in sample separation, enrichment, automated handling, mass spectrometric analysis, as well as data reduction and database interrogation strategies have done much to increase the quality, quantity and efficiency of data collection, significant bottlenecks still exist. Various separation techniques have been coupled with tandem mass spectrometric (MS/MS) approaches to allow a quicker analysis of complex mixtures of proteins, especially where a high number of unambiguous protein identifications are the exception, rather than the rule. MS/MS is required to provide structural / amino acid sequence information on a peptide and thus allow protein identity to be inferred from individual peptides. Currently these spectra need to be manually validated because: (a) the potential of false positive matches i.e., protein not in database, and (b) observed fragmentation trends may not be incorporated into current MS/MS search algorithms. This validation represents a significant bottleneck associated with high-throughput proteomic strategies. We have developed CHOMPER, a software program which reduces the time required to both visualize and confirm MS/MS search results and generate post-analysis reports and protein summary tables. CHOMPER extracts the identification information from SEQUEST MS/MS search result files, reproduces both the peptide and protein identification summaries, provides a more interactive visualization of the MS/MS spectra and facilitates the direct submission of manually validated identifications to a database.     

Peptide reranking with protein-peptide correspondence and precursor peak intensity information

Searching tandem mass spectra against a protein database has been a mainstream method for peptide identification. Improving peptide identification results by ranking true Peptide-Spectrum Matches (PSMs) over their false counterparts leads to the development of various reranking algorithms. In peptide reranking, discriminative information is essential to distinguish true PSMs from false PSMs. Generally, most peptide reranking methods obtain discriminative information directly from database search scores or by training machine learning models. Information in the protein database and MS1 spectra (i.e., single stage MS spectra) is ignored. In this paper, we propose to use information in the protein database and MS1 spectra to rerank peptide identification results. To quantitatively analyze their effects to peptide reranking results, three peptide reranking methods are proposed: PPMRanker, PPIRanker, and MIRanker. PPMRanker only uses Protein-Peptide Map (PPM) information from the protein database, PPIRanker only uses Precursor Peak Intensity (PPI) information, and MIRanker employs both PPM information and PPI information. According to our experiments on a standard protein mixture data set, a human data set and a mouse data set, PPMRanker and MIRanker achieve better peptide reranking results than PetideProphet, PeptideProphet+NSP (number of sibling peptides) and a score regularization method SRPI. The source codes of PPMRanker, PPIRanker, and MIRanker, and all supplementary documents are available at our website: http://bioinformatics.ust.hk/pepreranking/. Alternatively, these documents can also be downloaded from: http://sourceforge.net/projects/pepreranking/.     

目标?鄄诱饵库搜索策略在蛋白质组质谱鉴定和质控中的应用及研究进展

基于串联质谱的蛋白质组研究会产生海量的质谱数据,这些数据通常使用数据库搜索引擎进行鉴定分析,并根据肽段谱图匹配(PSM)反推真实的样品蛋白质．对于高通量蛋白质组数据的处理,其鉴定结果的可信是后续分析应用的前提,因此对鉴定结果的质量控制尤为重要,而基于目标-诱饵库(target-decoy)搜索策略的质量控制是目前应用最为广泛的方法．本文首先介绍了基于目标-诱饵库搜索策略搜库和质量控制的实施流程,然后综述了基于目标-诱饵库搜索策略的质量控制工具,并提出了目标-诱饵库搜索策略的不足及改善方法,最后对目标-诱饵库搜索策略进行了总结与展望．     

Pepitome: evaluating improved spectral library search for identification complementarity and quality assessment

Spectral libraries have emerged as a viable alternative to protein sequence databases for peptide identification. These libraries contain previously detected peptide sequences and their corresponding tandem mass spectra (MS/MS). Search engines can then identify peptides by comparing experimental MS/MS scans to those in the library. Many of these algorithms employ the dot product score for measuring the quality of a spectrum-spectrum match (SSM). This scoring system does not offer a clear statistical interpretation and ignores fragment ion m/z discrepancies in the scoring. We developed a new spectral library search engine, Pepitome, which employs statistical systems for scoring SSMs. Pepitome outperformed the leading library search tool, SpectraST, when analyzing data sets acquired on three different mass spectrometry platforms. We characterized the reliability of spectral library searches by confirming shotgun proteomics identifications through RNA-Seq data. Applying spectral library and database searches on the same sample revealed their complementary nature. Pepitome identifications enabled the automation of quality analysis and quality control (QA/QC) for shotgun proteomics data acquisition pipelines.     

A nonparametric model for quality control of database search results in shotgun proteomics

Background  

Analysis of complex samples with tandem mass spectrometry (MS/MS) has become routine in proteomic research. However, validation of database search results creates a bottleneck in MS/MS data processing. Recently, methods based on a randomized database have become popular for quality control of database search results. However, a consequent problem is the ignorance of how to combine different database search scores to improve the sensitivity of randomized database methods.