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A flexible workflow for building spectral libraries from narrow window data independent acquisition mass spectrometry data

View ORCID ProfileLilian R. Heil, View ORCID ProfileWilliam E. Fondrie, Christopher D. McGann, View ORCID ProfileAlexander J. Federation, View ORCID ProfileWilliam S. Noble, View ORCID ProfileMichael J. MacCoss, View ORCID ProfileUri Keich
doi: https://doi.org/10.1101/2021.11.22.469568
Lilian R. Heil
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
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William E. Fondrie
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
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Christopher D. McGann
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
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Alexander J. Federation
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
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William S. Noble
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
2Paul G. Allen School for Computer Science and Engineering, University of Washington, Seattle, WA, USA
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  • For correspondence: william-noble@uw.edu maccoss@uw.edu uri.keich@sydney.edu.au
Michael J. MacCoss
1Department of Genome Sciences, University of Washington, Seattle, WA, USA
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  • For correspondence: william-noble@uw.edu maccoss@uw.edu uri.keich@sydney.edu.au
Uri Keich
3School of Mathematics and Statistics, University of Sydney, NSW, Australia
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  • For correspondence: william-noble@uw.edu maccoss@uw.edu uri.keich@sydney.edu.au
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Abstract

Advances in library-based methods for peptide detection from data independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.

Competing Interest Statement

The authors declare the following competing financial interest(s): The MacCoss Lab at the University of Washington has a sponsored research agreement with Thermo Fisher Scientific, the manufacturer of the instrumentation used in this research. M.J.M. is a paid consultant for Thermo Fisher Scientific.

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  • Corrected methods section

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted December 07, 2021.
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A flexible workflow for building spectral libraries from narrow window data independent acquisition mass spectrometry data
Lilian R. Heil, William E. Fondrie, Christopher D. McGann, Alexander J. Federation, William S. Noble, Michael J. MacCoss, Uri Keich
bioRxiv 2021.11.22.469568; doi: https://doi.org/10.1101/2021.11.22.469568
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A flexible workflow for building spectral libraries from narrow window data independent acquisition mass spectrometry data
Lilian R. Heil, William E. Fondrie, Christopher D. McGann, Alexander J. Federation, William S. Noble, Michael J. MacCoss, Uri Keich
bioRxiv 2021.11.22.469568; doi: https://doi.org/10.1101/2021.11.22.469568

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