New targeted approaches for the quantification of data-independent acquisition mass spectrometry
New targeted approaches for the quantification of data-independent acquisition mass spectrometry
复制标题
DOI：
10.1002/pmic.201700021
复制
发表时间：
2017-05-01
期刊：
影响因子：
3.4
通讯作者：
Gomez-Varela, David
中科院分区：
文献类型：
--
作者：
Bruderer, Roland;Sondermann, Julia;Gomez-Varela, David
在过去的几年里，使用数据独立采集（DIA）方法对复杂蛋白质样品进行可重复和精确的定量已经增加。由DIA分析产生的蛋白质信息存储在数字蛋白质图谱（DIA图谱）中，其可以通过使用在与DIA图谱的生成相同的样品物种上生成的特定或可生物利用的肽光谱文库以靶向方式进行查询。某些难以获得的人体组织的有限可用性（即，脑）以及使用在可变实验条件下产生的光谱库的注意事项限制了DIA的潜力。因此，DIA工作流程将受益于高质量和扩展的光谱库，这些光谱库可以在不需要使用有价值的样本进行库生产的情况下生成。我们在这里描述了两种新的有针对性的方法，使用经典的数据依赖性采集库（不是专门为DIA构建的）或特设小鼠光谱库，这使得人类大脑DIA数据集的分析成为可能。我们的结果与最广泛的人体光谱库和最先进的非靶向方法的比较支持使用这些新策略来改善未来的DIA分析工作。
The use of data-independent acquisition (DIA) approaches for the reproducible and precise quantification of complex protein samples has increased in the last years. The protein information arising from DIA analysis is stored in digital protein maps (DIA maps) that can be interrogated in a targeted way by using ad hoc or publically available peptide spectral libraries generated on the same sample species as for the generation of the DIA maps. The restricted availability of certain difficult-to-obtain human tissues (i.e., brain) together with the caveats of using spectral libraries generated under variable experimental conditions limits the potential of DIA. Therefore, DIA workflows would benefit from high-quality and extended spectral libraries that could be generated without the need of using valuable samples for library production. We describe here two new targeted approaches, using either classical data-dependent acquisition repositories (not specifically built for DIA) or ad hoc mouse spectral libraries, which enable the profiling of human brain DIA data set. The comparison of our results to both the most extended publically available human spectral library and to a state-of-the-art untargeted method supports the use of these new strategies to improve future DIA profiling efforts.