Raucci Giuseppe, Gabrielli Meri, Novelli Sabrina, Picariello Gianluca, Collins Stephen H
Menarini Biotech, Via Tito Speri 10, 00040 Pomezia, RM, Italy.
J Mass Spectrom. 2005 Apr;40(4):475-88. doi: 10.1002/jms.817.
We describe CHASE, a novel algorithm for automated de novo sequencing based on the mass spectrometric (MS) fragmentation analysis of tryptic peptides. This algorithm is used for protein identification from sequence similarity criteria and consists of four steps: (1) derivatization of tryptic peptides at the N-terminus with a negatively charged reagent; (2) post-source decay (PSD) fragmentation analysis of peptides; (3) interpretation of the mass peaks with the CHASE algorithm and reconstruction of the amino acid sequence; (4) transfer of these data to software for protein identifications based on sequence homology (Basic Local Alignment Search Tool, BLAST). This procedure deduced the correct amino acid sequence of tryptic peptide samples and also was able to deduce the correct sequence from difficult mass patterns and identify the amino acid sequence. This allows complete automation of the process starting from MS fragmentation of complex peptide mixtures at low concentration (e.g. from silver-stained gel bands) to identification of the protein. We also show that if PSD data are collected in a single spectrum (instead of the segmented mode offered by conventional matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) instrumentation), the complete workflow from MS-PSD data acquisition to similarity-based identification can be completely automated. This strategy may be applied to proteomic studies for protein identification based on automated de novo sequencing instead of MS or tandem MS patterns. We describe the Charge Assisted Sequencing Engine (CHASE) algorithm, the working protocol, the performance of the algorithm on spectra from MALDI-TOFMS and the data comparison between a TOF and a TOF-TOF instrument.
我们描述了CHASE,一种基于胰蛋白酶肽段质谱(MS)碎裂分析的新型自动从头测序算法。该算法用于根据序列相似性标准进行蛋白质鉴定,包括四个步骤:(1)用带负电荷的试剂对胰蛋白酶肽段的N端进行衍生化;(2)对肽段进行源后衰变(PSD)碎裂分析;(3)用CHASE算法解释质谱峰并重建氨基酸序列;(4)将这些数据传输到基于序列同源性的蛋白质鉴定软件(基本局部比对搜索工具,BLAST)。该程序推导了胰蛋白酶肽段样品的正确氨基酸序列,并且还能够从复杂的质谱图中推导正确的序列并鉴定氨基酸序列。这使得从低浓度复杂肽混合物的MS碎裂(例如从银染凝胶条带)到蛋白质鉴定的过程能够完全自动化。我们还表明,如果在单个光谱中收集PSD数据(而不是传统基质辅助激光解吸/电离飞行时间(MALDI-TOF)仪器提供的分段模式),从MS-PSD数据采集到基于相似性的鉴定的完整工作流程可以完全自动化。该策略可应用于蛋白质组学研究,用于基于自动从头测序而不是MS或串联MS模式的蛋白质鉴定。我们描述了电荷辅助测序引擎(CHASE)算法、工作方案、该算法在MALDI-TOFMS光谱上的性能以及TOF和TOF-TOF仪器之间的数据比较。