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DIA-Pipe: Identification and Quantification of Post-Translational Modifications using exclusively Data-Independent Acquisition

View ORCID ProfileJesse G. Meyer, Sushanth Mukkamalla, Alexandria K. D’Souza, Alexey I. Nesvizhskii, Bradford W. Gibson, View ORCID ProfileBirgit Schilling
doi: https://doi.org/10.1101/141382
Jesse G. Meyer
1Buck Institute for Research on Aging, Novato, CA, USA.
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Sushanth Mukkamalla
1Buck Institute for Research on Aging, Novato, CA, USA.
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Alexandria K. D’Souza
1Buck Institute for Research on Aging, Novato, CA, USA.
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Alexey I. Nesvizhskii
2Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.
3Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA.
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Bradford W. Gibson
1Buck Institute for Research on Aging, Novato, CA, USA.
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  • For correspondence: bgibson@buckinstitute.org bschilling@buckinstitute.org
Birgit Schilling
1Buck Institute for Research on Aging, Novato, CA, USA.
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  • ORCID record for Birgit Schilling
  • For correspondence: bgibson@buckinstitute.org bschilling@buckinstitute.org
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Abstract

Label-free quantification using data-independent acquisition (DIA) is a robust method for deep and accurate proteome quantification1,2. However, when lacking a pre-existing spectral library, as is often the case with studies of novel post-translational modifications (PTMs), samples are typically analyzed several times: one or more data dependent acquisitions (DDA) are used to generate a spectral library followed by DIA for quantification. This type of multi-injection analysis results in significant cost with regard to sample consumption and instrument time for each new PTM study, and may not be possible when sample amount is limiting and/or studies require a large number of biological replicates. Recently developed software (e.g. DIA-Umpire) has enabled combined peptide identification and quantification from a data-independent acquisition without any pre-existing spectral library3,4. Still, these tools are designed for protein level quantification. Here we demonstrate a software tool and workflow that extends DIA-Umpire to allow automated identification and quantification of PTM peptides from DIA. We accomplish this using a custom, open-source graphical user interface DIA-Pipe (https://github.com/jgmeyerucsd/PIQEDia/releases/tag/v0.1.2) (figure 1a).

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Posted May 25, 2017.
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DIA-Pipe: Identification and Quantification of Post-Translational Modifications using exclusively Data-Independent Acquisition
Jesse G. Meyer, Sushanth Mukkamalla, Alexandria K. D’Souza, Alexey I. Nesvizhskii, Bradford W. Gibson, Birgit Schilling
bioRxiv 141382; doi: https://doi.org/10.1101/141382
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DIA-Pipe: Identification and Quantification of Post-Translational Modifications using exclusively Data-Independent Acquisition
Jesse G. Meyer, Sushanth Mukkamalla, Alexandria K. D’Souza, Alexey I. Nesvizhskii, Bradford W. Gibson, Birgit Schilling
bioRxiv 141382; doi: https://doi.org/10.1101/141382

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