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Web-Based Software for Rapid Top-Down Proteomic Identification of Protein Biomarkers, with Implications for Bacterial Identification

机译:基于网络的软件,可用于蛋白质生物标志物的快速自上而下的蛋白质组学鉴定,对细菌鉴定具有一定的意义

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We have developed web-based software for the rapid identification of protein biomarkers of bacterial microorganisms. Proteins from bacterial cell lysates were ionized by matrix-assisted laser desorption ionization (MALDI), mass isolated, and fragmented using a tandem time of flight (TOF-TOF) mass spectrometer. The sequence-specific fragment ions generated were compared to a database of in silico fragment ions derived from bacterial protein sequences whose molecular weights are the same as the nominal molecular weights of the protein biomarkers. A simple peak-matching and scoring algorithm was developed to compare tandem mass spectrometry (MS-MS) fragment ions to in silico fragment ions. In addition, a probability-based significance-testing algorithm (P value), developed previously by other researchers, was incorporated into the software for the purpose of comparison. The speed and accuracy of the software were tested by identification of 10 protein biomarkers from three Campylobacter strains that had been identified previously by bottom-up proteomics techniques. Protein biomarkers were identified using (i) their peak-matching scores and/or P values from a comparison of MS-MS fragment ions with all possible in silico N and C terminus fragment ions (i.e., ions a, b, b-18, y, y-17, and y-18), (ii) their peak-matching scores and/or P values from a comparison of MS-MS fragment ions to residue-specific in silico fragment ions (i.e., in silico fragment ions resulting from polypeptide backbone fragmentation adjacent to specific residues [aspartic acid, glutamic acid, proline, etc.]), and (iii) fragment ion error analysis, which distinguished the systematic fragment ion error of a correct identification (caused by calibration drift of the second TOF mass analyzer) from the random fragment ion error of an incorrect identification.
机译:我们已经开发了基于Web的软件,可以快速识别细菌微生物的蛋白质生物标记。来自细菌细胞裂解物的蛋白质通过基质辅助激光解吸电离(MALDI)进行电离,进行质量分离,并使用串联飞行时间(TOF-TOF)质谱仪进行片段化。将产生的序列特异性片段离子与来源于细菌蛋白质序列的计算机芯片片段离子数据库进行比较,所述细菌蛋白质序列的分子量与蛋白质生物标志物的标称分子量相同。开发了一种简单的峰匹配和评分算法,以比较串联质谱(MS-MS)碎片离子与计算机碎片离子。此外,出于比较的目的,将由其他研究人员先前开发的基于概率的显着性检验算法(P值)并入了该软件。通过从先前通过自下而上的蛋白质组学技术鉴定的三个弯曲杆菌菌株中鉴定10种蛋白质生物标记物,测试了该软件的速度和准确性。通过比较MS-MS碎片离子与所有可能的计算机N和C末端碎片离子(即离子a,b,b-18, y,y-17和y-18),(ii)通过比较MS-MS碎片离子与残基特异性的in silico碎片离子(即得到的in silico碎片离子)的峰匹配分数和/或P值(与特定残基[天冬氨酸,谷氨酸,脯氨酸等]相邻的多肽骨架断裂)产生的,以及(iii)碎片离子误差分析,可区分正确鉴定的系统碎片离子误差(由第二个样品的校正漂移引起) TOF质量分析仪)从随机碎片离子错误中鉴定出错误。

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