人卵巢癌耐药细胞株的比较蛋白质组分析

本文采用高分辨二维凝胶电泳分离技术对人卵巢癌细胞株COC1及其耐药细胞株COC1/DDP中的蛋白质进行分离和差异表达分析, 应用基质辅助激光解吸电离-飞行时间质谱对酶解多肽进行测定[即测定蛋白质的肽质量指纹图(Peptide mass fingerprinting, PMF)], 并通过相应的数据库搜索来鉴定蛋白质. 为获得更准确的检索结果, 采用串联质谱技术对各肽段进行氨基酸测序, 并应用IPI-HUMAN数据库对上述检索结果进一步加以确认.      

溶菌酶基质辅助激光解吸电离-串联飞行时间质谱分析中的不常见修饰及脱水反应

利用基质辅助激光解吸电离-串联飞行时间质谱(MALDI-TOF/TOF)分析了溶菌酶标准蛋白,在常规搜库条件下鉴定到6个独立肽段,Mascot得分420,鉴定覆盖率为54%。此外,经人工解析发现,肽段IVSDG-DGMNAWVAWR(98→112)在样品处理过程中发生了天冬酰胺脱氨化、天冬酰胺脱氨化+甲硫氨酸氧化、天冬酰胺脱氨化+甲硫氨酸氧化+色氨酸氧化等修饰,在激光解吸电离过程中发生脱水反应,脱水位点是脱氨后形成的第103位天冬氨酸。此外,还发现了部分肽段的丙酰胺化修饰。本研究表明,选择一级质谱中的极低丰度离子进行串联质谱分析和利用人工解析方法分析数据库未匹配数据,有可能发现一些特殊的蛋白质修饰,可增加数据利用度和分析结果的确定性。     

肽质量指纹谱鉴定蛋白质时生物信息学分析条件的优化

为了优化肽质量指纹谱(peptide mass fingerprint,PMF)鉴定蛋白质的生物信息学分析条件。将牛碳酸酐酶2(carbonic anhydrase-2,CAH2)和人热休克蛋白70s(Hsp70s)进行2-DE分离、酶解,肽段经过MALDI-TOFMS分析得到PMF数据。选择Swissprot、MSDB、NCBInr、Random等数据库和MASCOT与MS-Fit搜索引擎,以牛CAH2为模型优化搜索参数,结果表明:Swissprot是适合做蛋白PMF分析的数据库;主要参数最佳设置为:漏切位点数为1个,肽质量容错数为±1Da,同时肽质量类型选择平均分子质量比单同位素质量更便于候选蛋白的筛选。最后用人Hsp70s蛋白的PMF数据检验优化条件,结果表明,所选择的数据库及参数是可靠的。     

新闻

肽质量指纹图谱法（PMF）是获得蛋白质结构信息和鉴定蛋白质的常用方法。蛋白质的酶解是蛋白-质组学研究中蛋白质分析的关键步骤,将蛋白分解成肽段,然后用基质辅助激光解析电离飞行时间质谱（MALDI-TOF-Ms）或液相色谱电喷雾质谱（LC-ESI-MS）分析多肽混合物,获得肽质量指纹图谱。由于传统的溶液酶解方法耗时（12h以上）,建立高效快速的蛋白酶解新技术具有重要意义。     

一种可用于评估肽质量指纹谱数据的方法——反转错位数据库

反转数据库常被用于估算大规模蛋白质组研究中串联质谱搜索数据库结果的可靠性。然而,对于经典的且现在依然在产出的肽质量指纹谱的数据,这种方法并不适用。为解决该问题,构建了另外一种随机数据库,称为反转错位数据库。这种数据库是在反转数据库的基础上,将序列中的K和R及其后的氨基酸交换位置(对于胰蛋白酶切割的结果)获得。这种处理避免了某些肽段因前后胰蛋白酶酶切位点氨基酸相同而在序列反转后质量依然不变,导致肽质量指纹谱法无法区分的问题。通过串联质谱和肽质量指纹谱测试数据的搜索结果,证明了这种方法同时适用于串联质谱和肽质量指纹谱的数据。这种方法扩大了经典反转数据库的适用范围,将对评估和整合串联质谱和肽质量指纹谱的数据具有重要意义。     

高分辨飞行时间质谱在蛋白质组学相对定量分析中的应用

利用TripleTOF 5600高分辨质谱仪分析牛血清白蛋白等3种蛋白质标准品,研究了质谱离子强度与蛋白质样品相对含量的相关性。蛋白质标准品用胰酶酶切后,稀释成1~1024 fmol/7μL的系列溶液,考察在1~1024 fmol 上样量情况下,肽段的前体离子计数( cps)、蛋白质全部肽段的离子计数之和以及被检出肽段数目与上样量的相关性,以及相同样品在3次平行实验之间这些数值的变化幅度。结果表明。被检出肽段数目与上样量正相关,当cps超过1000时,所有肽段离子强度之和与上样量呈线性关系,但是用最灵敏肽段的离子强度表示更为准确。3次测量同一肽段的最高离子强度通常不会超过最低强度的1.5倍,提示当不同样品中同一蛋白的离子强度相差3倍以上是判断不同样品中相同蛋白质的含量具有差异的可靠阈值。本研究提供了一种利用高分辨率和高扫描速度蛋白质组组学定性数据进行半定量分析的方法,简便、快速,可为相关生物学和医学研究提供参考。     

液相等电聚焦技术结合液相色谱-质谱联用技术分析鼠肝全蛋白

利用液相等电聚焦预分离技术结合液相色谱-质谱(LTQ-Orbitrap)联用技术,研究了C57小鼠肝脏的蛋白质表达谱.质谱分析结果采用Max Quant1.4.1.2软件搜索数据库,共鉴定出3474个蛋白(2个以上唯一肽段).用DAVID在线工具、GO分类工具和IPA软件对鉴定蛋白进行生物信息学分析,单独发现832个新蛋白.研究结果表明,通过基于等电点和亲疏水性的两维分离,提高了质谱鉴定蛋白数,可以鉴定出更多低丰度蛋白.     

基于非特异性蛋白酶连续酶解的蛋白质全序列测定方法

对蛋白质全序列进行测定,有助于分析蛋白质的结构,揭示蛋白质的生物学功能.针对目前基于质谱的蛋白质测序流程中使用特异性蛋白酶酶解产生的肽段种类少、重叠度低、序列拼接困难等问题,发展了一种基于非特异性蛋白酶连续酶解的蛋白质全序列测定方法.构建了连续酶解装置,并使用多种非特异性蛋白酶对蛋白质进行连续酶解.利用非特异性蛋白酶酶解位点的非特异性、不同的酶解时间以及不同种类蛋白酶酶解产生肽段的互补性,提高蛋白质酶解肽段的种类和重叠度,并发展了蛋白质序列拼接算法对液相色谱质谱联用(LC-MS/MS)和从头测序获得的肽段序列进行拼接.将此方法应用于牛血清白蛋白和单克隆抗体赫赛汀的全序列测定,在不考虑亮氨酸和异亮氨酸的情况下,对牛血清白蛋白和赫赛汀轻链的测序准确度达到100%,赫赛汀重链的测序准确度为99.7%.     

固定化酶微升反应器与MALDI-TOF MS联用技术用于蛋白质肽谱研究

以甲基丙烯酸缩水甘油酯新型复合纤维素膜为介质固定化胰蛋白酶, 与传统微球固定化酶反应器相比, 提高了分子扩散传质性能. 设计并制成固定化酶微升反应器, 并与基体辅助激光解吸电离飞行时间质谱(MALDI-TOF MS)联用应用于蛋白质的肽谱分析. 将所获得的肽质谱图用于蛋白质数据库检索, 可以确定各肽段在蛋白质中的位置. 这种方法尤其适用于高灵敏度和微量生物样品的快速分析, 可以在皮摩尔的水平上对蛋白质的结构进行鉴定.     

规模化蛋白质生物质谱鉴定中肽段氨基端环化修饰现象

对蛋白质样品制备中引入的氨基酸残基的一种现象--蛋白质酶切肽段氨基端的环化修饰现象的初步研究结果显示,很多以谷氨酰胺(Q)或氨乙酰化修饰的半胱氨酸(CAM_C)残基起始的肽段会发生氨基端的环化修饰,且修饰反应不完全,在同一样本中修饰与非修饰两种状态常同时存在,并且环化修饰后的肽段的反相色谱保留时间发生延迟.在数据库检索时添加环化修饰,可以提高蛋白质的鉴定成功率.本研究结果为大规模的蛋白质质谱数据解析提供了有价值的参考.     

A novel approach for protein identification from complex cell proteome using modified peptide mass fingerprinting algorithm

A unique peptide based search algorithm for identification of protein mixture using PMF is proposed. The proposed search algorithm utilizes binary search and heapsort programs to generate frequency chart depicting the unique peptides corresponding to all proteins in a proteome. The use of binary search program significantly reduces the time for frequency chart preparation to ～2 s for a proteome comprising ～23 000 proteins. The algorithm was applied to a three‐protein mixture identification, host cell protein (HCP) analysis, and a simulation‐generated data set. It was found that the algorithm could identify at least one unique peptide of a protein even in the presence of fourfold higher concentration of another protein. In addition, two HCPs that are known to be difficult to remove were missed by MS/MS approach and were exclusively identified using the presented algorithm. Thus, the proposed algorithm when used along with standard proteomic approaches present avenues for enhanced protein identification efficiency, particularly for applications such as HCP analysis in biopharmaceutical research, where identification of low‐abundance proteins are generally not achieved due to dynamic range limitations between the target product and HCPs.     

Improved peptide mass fingerprinting matches via optimized sample preparation in MALDI mass spectrometry

Peptide mass fingerprinting (PMF) is a powerful technique in which experimentally measured m/z values of peptides resulting from a protein digest form the basis for a characteristic fingerprint of the intact protein. Due to its propensity to generate singly charged ions, along with its relative insensitivity to salts and buffers, matrix-assisted laser desorption and ionization (MALDI)-time-of-flight mass spectrometry (TOFMS) is the MS method of choice for PMF. The qualitative features of the mass spectrum can be selectively tuned by employing different methods to prepare the protein digest and matrix for MALDI-TOFMS. The selective tuning of MALDI mass spectra in order to optimize PMF is addressed here. Bovine serum albumin, carbonic anhydrase, cytochrome c, hemoglobin alpha- and beta-chain, and myoglobin were digested with trypsin and then analyzed by MALDI-TOFMS. 2,5-dihydroxybenzoic acid (DHB) and alpha-cyano-4-hydroxycinnamic acid (CHCA) were prepared using six different sample preparation methods: dried droplet, application of protein digest on MALDI plate followed by addition of matrix, dried droplet with vacuum drying, overlayer, sandwich, and dried droplet with heating. Improved results were obtained for the matrix alpha-cyano-4-hydroxycinnamic acid using a modification of the died droplet method in which the MALDI plate was heated to 80 °C prior to matrix application, which is supported by observations from scanning electron microscopy. Although each protein was found to have a different optimum sample preparation method for PMF, in general higher sequence coverage for PMF was obtained using DHB. The best PMF results were obtained when all of the mass spectral data for a particular protein digest was convolved together.     

Interpretation of mass spectrometry data for high-throughput proteomics

Recent developments in proteomics have revealed a bottleneck in bioinformatics: high-quality interpretation of acquired MS data. The ability to generate thousands of MS spectra per day, and the demand for this, makes manual methods inadequate for analysis and underlines the need to transfer the advanced capabilities of an expert human user into sophisticated MS interpretation algorithms. The identification rate in current high-throughput proteomics studies is not only a matter of instrumentation. We present software for high-throughput PMF identification, which enables robust and confident protein identification at higher rates. This has been achieved by automated calibration, peak rejection, and use of a meta search approach which employs various PMF search engines. The automatic calibration consists of a dynamic, spectral information-dependent algorithm, which combines various known calibration methods and iteratively establishes an optimised calibration. The peak rejection algorithm filters signals that are unrelated to the analysed protein by use of automatically generated and dataset-dependent exclusion lists. In the "meta search" several known PMF search engines are triggered and their results are merged by use of a meta score. The significance of the meta score was assessed by simulation of PMF identification with 10,000 artificial spectra resembling a data situation close to the measured dataset. By means of this simulation the meta score is linked to expectation values as a statistical measure. The presented software is part of the proteome database ProteinScape which links the information derived from MS data to other relevant proteomics data. We demonstrate the performance of the presented system with MS data from 1891 PMF spectra. As a result of automatic calibration and peak rejection the identification rate increased from 6% to 44%.Abbreviations 2-DE Two-dimensional gel electrophoresis - MALDI Matrix-assisted laser desorption ionisation - PMF Peptide mass fingerprinting - MS Mass spectrometry - TOF Time of flight     

Development and assessment of scoring functions for protein identification using PMF data

PMF is one of the major methods for protein identification using the MS technology. It is faster and cheaper than MS/MS. Although PMF does not differentiate trypsin-digested peptides of identical mass, which makes it less informative than MS/MS, current computational methods for PMF have the potential to improve its detection accuracy by better use of the information content in PMF spectra. We developed a number of new probability-based scoring functions for PMF protein identification based on the MOWSE algorithm. We considered a detailed distribution of matching masses in a protein database and peak intensity, as well as the likelihood of peptide matches to be close to each other in a protein sequence. Our computational methods are assessed and compared with other methods using PMF data of 52 gel spots of known protein standards. The comparison shows that our new scoring schemes have higher or comparable accuracies for protein identification in comparison to the existing methods. Our software is freely available upon request. The scoring functions can be easily incorporated into other proteomics software packages.     

HPTLC/DESI-MS imaging of tryptic protein digests separated in two dimensions

Desorption electrospray ionization mass spectrometry (DESI-MS) was demonstrated as a method to detect and identify peptides from two-dimensional separations of cytochrome c and myoglobin tryptic digests on ProteoChrom HPTLC Cellulose sheets. Data-dependent tandem mass spectra were acquired during lane scans across the TLC plates. Peptides and the corresponding proteins were identified using a protein database search software. Two-dimensional distributions of identified peptides were mapped for each separated protein digest. Sequence coverages for cytochrome c and myoglobin were 81 and 74%, respectively. These compared well with those determined using the more standard HPLC/ESI-MS/MS approach (89 and 84%, respectively). Preliminary results show that use of more sensitive instrumentation has the potential for improved detection of peptides with low R(f) values and improvement in sequence coverage. However, less multiple charging and more sodiation were seen in HPTLC/DESI-MS spectra relative to HPLC/ESI-MS spectra, which can affect peptide identification by MS/MS. Methods to increase multiple charging and reduce the extent of sodiation are currently under investigation.     

Improved protein identification efficiency by mass spectrometry using N-terminal chemical derivatization of peptides from Angiostrongylus costaricensis, a nematode with unknown genome

Matrix-assisted laser desorption ionization (MALDI), Peptide Mass Fingerprinting (PMF) and MALDI-MS/MS ion search (using MASCOT) have become the preferred methods for high-throughput identification of proteins. Unfortunately, PMF can be ambiguous, mainly when the genome of the organism under investigation is unknown and the quality of spectra generated is poor and does not allow confident identification. The post-source decay (PSD) fragmentation of singly charged tryptic peptide ions generated by MALDI-TOF/TOF typically results in low fragmentation efficiency and/or complex spectra, including backbone fragmentation ions (series b and y), internal fragmentation etc. Interpreting these data either manually and/or using de novo sequencing software can frequently be a challenge. To overcome this limitation when studying the proteome of adult Angiostrongylus costaricensis, a nematode with unknown genome, we have used chemical N-terminal derivatization of the tryptic peptides with 4-sulfophenyl isothiocyanate (SPITC) prior to MALDI-TOF/TOF MS. This methodology has recently been reported to enhance the quality of MALDI-TOF/TOF-PSD data, allowing the obtainment of complete sequence of most of the peptides and thus facilitating de novo peptide sequencing. Our approach, consisting of SPITC derivatization along with manual spectra interpretation and Blast analysis, was able to positively identify 76% of analyzed samples, whereas MASCOT analysis of derivatized samples, MASCOT analysis of nonderivatized samples and PMF of nonderivatized samples yielded only 35, 41 and 12% positive identifications, respectively. Moreover, de novo sequencing of SPITC modified peptides resulted in protein sequences not available in NCBInr database paving the way to the discovery of new protein molecules.     

Improved protein identification efficiency by mass spectrometry using N-terminal chemical derivatization of peptides from Angiostrongylus costaricensis, a nematode with unknown genome

Matrix-assisted laser desorption ionization (MALDI), Peptide Mass Fingerprinting (PMF) and MALDI-MS/MS ion search (using MASCOT) have become the preferred methods for high-throughput identification of proteins. Unfortunately, PMF can be ambiguous, mainly when the genome of the organism under investigation is unknown and the quality of spectra generated is poor and does not allow confident identification. The post-source decay (PSD) fragmentation of singly charged tryptic peptide ions generated by MALDI-TOF/TOF typically results in low fragmentation efficiency and/or complex spectra, including backbone fragmentation ions (series b and y), internal fragmentation etc. Interpreting these data either manually and/or using de novo sequencing software can frequently be a challenge. To overcome this limitation when studying the proteome of adult Angiostrongylus costaricensis, a nematode with unknown genome, we have used chemical N-terminal derivatization of the tryptic peptides with 4-sulfophenyl isothiocyanate (SPITC) prior to MALDI-TOF/TOF MS. This methodology has recently been reported to enhance the quality of MALDI-TOF/TOF-PSD data, allowing the obtainment of complete sequence of most of the peptides and thus facilitating de novo peptide sequencing. Our approach, consisting of SPITC derivatization along with manual spectra interpretation and Blast analysis, was able to positively identify 76% of analyzed samples, whereas MASCOT analysis of derivatized samples, MASCOT analysis of nonderivatized samples and PMF of nonderivatized samples yielded only 35, 41 and 12% positive identifications, respectively. Moreover, de novo sequencing of SPITC modified peptides resulted in protein sequences not available in NCBInr database paving the way to the discovery of new protein molecules.     

Spectral quality assessment and application for gel-based matrix-assisted laser desorption ionization-time of flight tandem mass spectrometer

Gel-based matrix-assisted laser desorption ionization-time of flight tandem mass spectrometer (MALDI TOF/TOF MS) is one of the dominant methods of current proteomics, utilizing both peptide mass fingerprinting (PMF) and peptide fragment fingerprinting (PFF) for protein identification on a spot-to-spot basis. However, the unique impact of the quality of the corresponding mass spectrometry spectra remains largely unreported, and has motivated the development and use of an automatic spectra-assessment method. In this study, a multi-variant regression approach has been utilized to assess spectral quality for both PMF and PFF spectra obtained from MALDI TOF/TOF MS. The assessment index has been applied to investigations of MASCOT search results. Systematic examination of two large-scale sets of human liver tissue data has proved that spectral quality was a key factor in significant matching. Based on large-scale investigations on individual PMF search, individual PFF search and their combination, respectively, the filtering of bad quality spectra or spots proves to be an efficient way to improve search efficiency of all search modes in MASCOT. Meanwhile, a validation method based on score differences between normal and decoy (reverse or random) database searches is proposed to precisely define the positive matches. Further analysis showed that spectral quality assessment was also efficient in representing the quality of 2-DE gel spots and promoted the discovery of potential post-translation modifications.