New targeted approaches for the quantification of data-independent acquisition mass spectrometry. Bruderer, R., Sondermann, J., Tsou, C., Barrantes-Freer, A., Stadelmann, C., Nesvizhskii, A. I., Schmidt, M., Reiter, L., & Gomez-Varela, D. Proteomics, May, 2017. doi abstract bibtex 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.
@article{bruderer_new_2017,
title = {New targeted approaches for the quantification of data-independent acquisition mass spectrometry.},
volume = {17},
copyright = {(c) 2017 WILEY-VCH Verlag GmbH \& Co. KGaA, Weinheim.},
issn = {1615-9861 1615-9853},
doi = {10.1002/pmic.201700021},
abstract = {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.},
language = {eng},
number = {9},
journal = {Proteomics},
author = {Bruderer, Roland and Sondermann, Julia and Tsou, Chih-Chiang and Barrantes-Freer, Alonso and Stadelmann, Christine and Nesvizhskii, Alexey I. and Schmidt, Manuela and Reiter, Lukas and Gomez-Varela, David},
month = may,
year = {2017},
pmid = {28319648},
pmcid = {PMC5870755},
keywords = {*Software, Animals, Computational Biology/*methods, Data-independent acquisition, Humans, Mass Spectrometry/*methods, Mice, Peptide Library, Prefrontal Cortex/*metabolism, Proteome/*analysis, Proteomics/*methods, Spectral libraries, Spinal Cord/*metabolism}
}
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