Cleaning up the masses: exclusion lists to reduce contamination with HPLC-MS/MS.
Cleaning up the masses: exclusion lists to reduce contamination with HPLC-MS/MS.
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DOI：
10.1016/j.jprot.2013.02.023
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发表时间：
2013-08-02
影响因子：
3.3
通讯作者：
Lamond AI
中科院分区：
文献类型：
--
作者：
Hodge K;Have ST;Hutton L;Lamond AI
在过去的五年中，质谱仪在速度、准确性和使用方面都有所提高。随着质谱仪鉴定越来越多的蛋白质的能力，不需要的肽（那些不是来自蛋白质样品的肽）的鉴定也增加了。大多数不受欢迎的污染物来源于实验室，来自使用者（例如头发和皮肤的角蛋白）或试剂（例如胰蛋白酶），这些都是制备分析样品所需的。我们发现，大量的MS仪器时间花费在从丰富的污染蛋白质测序肽。虽然完全消除非特异性蛋白质污染是不可行的，但可以减少这些污染物的测序。例如，排除列表可以提供质量列表，其可以用于指示质谱仪“忽略”列表中的不期望的污染物肽。我们凭经验产生的被发言排除列表的几个模式生物（智人，秀丽隐杆线虫，酿酒酵母和非洲爪蟾），利用超过500个质谱运行和累积分析这些数据的信息。在这里，我们表明，通过采用这些经验产生的列表，它是可能的，以减少所花费的时间分析污染肽在一个给定的样品，从而促进更有效的数据采集和分析。生物学意义考虑到质谱仪器的当前功效，利用来自约500次质谱运行的数据来生成be-spoke排除列表并优化数据采集是本手稿的意义。这篇文章是特刊的一部分，题为：蛋白质组学的新视野和应用[EuPA 2012]。我们研究了“污染”肽对MS采集时间的贡献。我们发现30-50%的时间浪费在污染肽测序上。我们测试了排除列表的应用是否会解决这个问题。从> 500次质谱分析运行中生成特定物质的排除列表。排除列表使覆盖率和异构体数据的分析更有效。
Mass spectrometry, in the past five years, has increased in speed, accuracy and use. With the ability of the mass spectrometers to identify increasing numbers of proteins the identification of undesirable peptides (those not from the protein sample) has also increased. Most undesirable contaminants originate in the laboratory and come from either the user (e.g. keratin from hair and skin), or from reagents (e.g. trypsin), that are required to prepare samples for analysis. We found that a significant amount of MS instrument time was spent sequencing peptides from abundant contaminant proteins. While completely eliminating non-specific protein contamination is not feasible, it is possible to reduce the sequencing of these contaminants. For example, exclusion lists can provide a list of masses that can be used to instruct the mass spectrometer to ‘ignore’ the undesired contaminant peptides in the list. We empirically generated be-spoke exclusion lists for several model organisms (Homo sapiens, Caenorhabditis elegans, Saccharomyces cerevisiae and Xenopus laevis), utilising information from over 500 mass spectrometry runs and cumulative analysis of these data. Here we show that by employing these empirically generated lists, it was possible to reduce the time spent analysing contaminating peptides in a given sample thereby facilitating more efficient data acquisition and analysis. Biological significance Given the current efficacy of the Mass Spectrometry instrumentation, the utilisation of data from ~500 mass spec runs to generate be-spoke exclusion lists and optimise data acquisition is the significance of this manuscript. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012]. We looked at the contribution of ‘contaminating’ peptides to MS acquisition time. We found that 30–50% of time was wasted on contaminant peptide sequencing. We tested whether the application of an exclusion list would solve this problem. Exclusion lists generated for specific species from > 500 mass spectrometry runs. Exclusion lists enabled more efficient analysis with coverage and isoform data.
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DOI：
10.1016/s1570-0232(02)00142-3
发表时间：
2002-06-15
影响因子：
3
作者：
Müller, C;Schäfer, P;Weinmann, W
通讯作者：
Weinmann, W
影响因子：
3.4
作者：
McQueen, Peter;Spicer, Vic;Krokhin, Oleg
通讯作者：
Krokhin, Oleg
影响因子：
3.4
作者：
Granvogl, Bernhard;Gruber, Patrick;Eichacker, Lutz Andreas
通讯作者：
Eichacker, Lutz Andreas
影响因子：
4.8
作者：
Johnson, RS;Davis, MT;Patterson, SD
通讯作者：
Patterson, SD
影响因子：
168.9
作者：
Petricoin, EF;Ardekani, AM;Liotta, LA
通讯作者：
Liotta, LA