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Abstract

Top-down proteomics, the analysis of intact proteins in their endogenous form, preserves valuable information about post-translation modifications, isoforms and proteolytic processing. The quality of top-down liquid chromatography–tandem MS (LC-MS/MS) data sets is rapidly increasing on account of advances in instrumentation and sample-processing protocols. However, top-down mass spectra are substantially more complex than conventional bottom-up data. New algorithms and software tools for confident proteoform identification and quantification are needed. Here we present Informed-Proteomics, an open-source software suite for top-down proteomics analysis that consists of an LC-MS feature-finding algorithm, a database search algorithm, and an interactive results viewer. We compare our tool with several other popular tools using human-in-mouse xenograft luminal and basal breast tumor samples that are known to have significant differences in protein abundance based on bottom-up analysis.

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Change history

  • 13 June 2018

    In the version of this article initially published, the authors erroneously reported the search mode that was used for ProSightPC 3.0 in the Online Methods and in Supplementary Table 3.  The results presented in Fig. 5 were obtained with 'absolute mass' search mode, not 'biomarker discovery' search mode. The 'biomarker discovery' search mode of ProSightPC 3.0 looks for subsequences of those contained in the annotated proteoform database (e.g., truncated forms from degradation and/or cleavage). This search mode is expected to generate similar numbers of identifications as Informed-Proteomics, but is also expected to take dramatically longer (~480 CPU hours). Unfortunately, because of these heavy computational requirements, the authors were unable to complete an analysis using this search mode. They chose to use 'absolute mass' mode to illustrate the effect of search mode and database choice on the results. 'Absolute mass' mode is the most restrictive of the search modes illustrated in Fig. 5, as it searches only for proteoforms explicitly listed in the proteoform database within a user-defined mass tolerance.  In addition, in the supplementary information originally published online, Supplementary Table 3 incorrectly stated that ProSightPC v3.0 was used in 'biomarker discovery' mode. 'Absolute mass' mode was the mode actually used in this comparison. These errors have been corrected in the HTML and PDF versions of this article and in the associated supplementary information.

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Acknowledgements

Portions of this work were supported by the NIH National Institute of General Medical Sciences grant GM103493 (R.D.S.), the National Cancer Institute Clinical Proteomic Tumor Analysis Consortium (CPTAC) grant U24CA160019 (R.D.S.), the National Institute of Allergy and Infectious Diseases NIH/DHHS through interagency agreement Y1-A1-8401-01 (J. Adkins, PNNL), and the U.S. Department of Energy (DOE) Office of Science and Office of Biological and Environmental Research, under the Pan-omics program (R.D.S.). L.P.T., N.T., M.Z., and J.B.S. were supported as part of the “High Resolution and Mass Accuracy Capability” development project at the Environmental Molecular Science Laboratory (EMSL), a U.S. DOE national scientific user facility at Pacific Northwest National Laboratory (PNNL) in Richland, Washington. Battelle operates PNNL for the DOE under contract DE-AC05-76RLO01830.

Author information

Author notes

    • Sangtae Kim

    Present address: Illumina Inc., San Diego, California, USA.

Affiliations

  1. Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, USA.

    • Jungkap Park
    • , Paul D Piehowski
    • , Christopher Wilkins
    • , Joshua Mendoza
    • , Grant M Fujimoto
    • , Bryson C Gibbons
    • , Yufeng Shen
    • , Anil K Shukla
    • , Ronald J Moore
    • , Tao Liu
    • , Vladislav A Petyuk
    • , Richard D Smith
    • , Samuel H Payne
    •  & Sangtae Kim
  2. Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington, USA.

    • Mowei Zhou
    • , Jared B Shaw
    • , Nikola Tolić
    •  & Ljiljana Paša-Tolić

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Contributions

J.P., P.D.P., S.H.P., and S.K. designed and executed the study. J.P., C.W., J.M., G.M.F., B.C.G., and S.K. implemented algorithms in software. T.L. contributed samples. P.D.P., Y.S., A.K.S., R.J.M. performed LC-MS/MS experiments. J.P., P.D.P., J.B.S., V.A.P., M.Z., T.L., and N.T. analyzed data. L.P.-T. and R.D.S. provided technical leadership and oversight. J.P., P.D.P., and S.K. contributed to writing the manuscript with input from all authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Samuel H Payne or Sangtae Kim.

Integrated supplementary information

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–9 and Supplementary Tables 1–3.

  2. 2.

    Reporting Summary

    Life Sciences Reporting Summary.

  3. 3.

    Supplementary Protocol

    MSPathFinder Tutorial.

Zip files

  1. 1.

    Supplementary Software

    Informed-Proteomics software suite.

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DOI

https://doi.org/10.1038/nmeth.4388

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