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Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry

Author

Listed:
  • Brian C. Searle

    (University of Washington
    Proteome Software)

  • Lindsay K. Pino

    (University of Washington)

  • Jarrett D. Egertson

    (University of Washington)

  • Ying S. Ting

    (University of Washington)

  • Robert T. Lawrence

    (University of Washington)

  • Brendan X. MacLean

    (University of Washington)

  • Judit Villén

    (University of Washington)

  • Michael J. MacCoss

    (University of Washington)

Abstract

Data independent acquisition (DIA) mass spectrometry is a powerful technique that is improving the reproducibility and throughput of proteomics studies. Here, we introduce an experimental workflow that uses this technique to construct chromatogram libraries that capture fragment ion chromatographic peak shape and retention time for every detectable peptide in a proteomics experiment. These coordinates calibrate protein databases or spectrum libraries to a specific mass spectrometer and chromatography setup, facilitating DIA-only pipelines and the reuse of global resource libraries. We also present EncyclopeDIA, a software tool for generating and searching chromatogram libraries, and demonstrate the performance of our workflow by quantifying proteins in human and yeast cells. We find that by exploiting calibrated retention time and fragmentation specificity in chromatogram libraries, EncyclopeDIA can detect 20–25% more peptides from DIA experiments than with data dependent acquisition-based spectrum libraries alone.

Suggested Citation

  • Brian C. Searle & Lindsay K. Pino & Jarrett D. Egertson & Ying S. Ting & Robert T. Lawrence & Brendan X. MacLean & Judit Villén & Michael J. MacCoss, 2018. "Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry," Nature Communications, Nature, vol. 9(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-07454-w
    DOI: 10.1038/s41467-018-07454-w
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    Cited by:

    1. Fengchao Yu & Guo Ci Teo & Andy T. Kong & Klemens Fröhlich & Ginny Xiaohe Li & Vadim Demichev & Alexey I. Nesvizhskii, 2023. "Analysis of DIA proteomics data using MSFragger-DIA and FragPipe computational platform," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    2. Digant Nayak & Dongwen Lv & Yaxia Yuan & Peiyi Zhang & Wanyi Hu & Anindita Nayak & Eliza A. Ruben & Zongyang Lv & Patrick Sung & Robert Hromas & Guangrong Zheng & Daohong Zhou & Shaun K. Olsen, 2024. "Development and crystal structures of a potent second-generation dual degrader of BCL-2 and BCL-xL," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    3. Marziah Hashimi & T. Andrew Sebrell & Jodi F. Hedges & Deann Snyder & Katrina N. Lyon & Stephanie D. Byrum & Samuel G. Mackintosh & Dan Crowley & Michelle D. Cherne & David Skwarchuk & Amanda Robison , 2023. "Antiviral responses in a Jamaican fruit bat intestinal organoid model of SARS-CoV-2 infection," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    4. Rafaela Muniz de Queiroz & Gizem Efe & Asja Guzman & Naoko Hashimoto & Yusuke Kawashima & Tomoaki Tanaka & Anil K. Rustgi & Carol Prives, 2024. "Mdm2 requires Sprouty4 to regulate focal adhesion formation and metastasis independent of p53," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    5. Klemens Fröhlich & Eva Brombacher & Matthias Fahrner & Daniel Vogele & Lucas Kook & Niko Pinter & Peter Bronsert & Sylvia Timme-Bronsert & Alexander Schmidt & Katja Bärenfaller & Clemens Kreutz & Oliv, 2022. "Benchmarking of analysis strategies for data-independent acquisition proteomics using a large-scale dataset comprising inter-patient heterogeneity," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    6. Masaji Sakaguchi & Shota Okagawa & Yuma Okubo & Yuri Otsuka & Kazuki Fukuda & Motoyuki Igata & Tatsuya Kondo & Yoshifumi Sato & Tatsuya Yoshizawa & Takaichi Fukuda & Kazuya Yamagata & Weikang Cai & Yu, 2022. "Phosphatase protector alpha4 (α4) is involved in adipocyte maintenance and mitochondrial homeostasis through regulation of insulin signaling," Nature Communications, Nature, vol. 13(1), pages 1-19, December.
    7. Zhi Huang & Gennifer E. Merrihew & Eric B. Larson & Jea Park & Deanna Plubell & Edward J. Fox & Kathleen S. Montine & Caitlin S. Latimer & C. Dirk Keene & James Y. Zou & Michael J. MacCoss & Thomas J., 2023. "Brain proteomic analysis implicates actin filament processes and injury response in resilience to Alzheimer’s disease," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    8. Valdemaras Petrosius & Pedro Aragon-Fernandez & Nil Üresin & Gergo Kovacs & Teeradon Phlairaharn & Benjamin Furtwängler & Jeff Op De Beeck & Sarah L. Skovbakke & Steffen Goletz & Simon Francis Thomsen, 2023. "Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    9. Ray Sajulga & Caleb Easterly & Michael Riffle & Bart Mesuere & Thilo Muth & Subina Mehta & Praveen Kumar & James Johnson & Bjoern Andreas Gruening & Henning Schiebenhoefer & Carolin A Kolmeder & Steph, 2020. "Survey of metaproteomics software tools for functional microbiome analysis," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-20, November.

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