Journal article
TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies
Journal of proteome research, Vol.22(2), pp.311-322
02/03/2023
DOI: 10.1021/acs.jproteome.2c00173
PMCID: PMC10066879
PMID: 36165806
Abstract
In spite of its central role in biology and disease, protein turnover is a largely understudied aspect of most proteomic studies due to the complexity of computational workflows that analyze in vivo turnover rates. To address this need, we developed a new computational tool, TurnoveR, to accurately calculate protein turnover rates from mass spectrometric analysis of metabolic labeling experiments in Skyline, a free and open-source proteomics software platform. TurnoveR is a straightforward graphical interface that enables seamless integration of protein turnover analysis into a traditional proteomics workflow in Skyline, allowing users to take advantage of the advanced and flexible data visualization and curation features built into the software. The computational pipeline of TurnoveR performs critical steps to determine protein turnover rates, including isotopologue demultiplexing, precursor-pool correction, statistical analysis, and generation of data reports and visualizations. This workflow is compatible with many mass spectrometric platforms and recapitulates turnover rates and differential changes in turnover rates between treatment groups calculated in previous studies. We expect that the addition of TurnoveR to the widely used Skyline proteomics software will facilitate wider utilization of protein turnover analysis in highly relevant biological models, including aging, neurodegeneration, and skeletal muscle atrophy.
Details
- Title: Subtitle
- TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies
- Creators
- Nathan Basisty - Buck Institute for Research on AgingNicholas Shulman - University of WashingtonCameron Wehrfritz - Buck Institute for Research on AgingAlexandra N Marsh - University of WashingtonSamah Shah - Buck Institute for Research on AgingJacob Rose - Buck Institute for Research on AgingScott Ebert - Mayo ClinicMatthew Miller - University of IowaDao-Fu Dai - University of IowaPeter S Rabinovitch - University of WashingtonChristopher M Adams - Mayo ClinicMichael J MacCoss - University of WashingtonBrendan MacLean - University of WashingtonBirgit Schilling - Buck Institute for Research on Aging
- Resource Type
- Journal article
- Publication Details
- Journal of proteome research, Vol.22(2), pp.311-322
- DOI
- 10.1021/acs.jproteome.2c00173
- PMID
- 36165806
- PMCID
- PMC10066879
- NLM abbreviation
- J Proteome Res
- ISSN
- 1535-3893
- eISSN
- 1535-3907
- Grant note
- DOI: 10.13039/100000049, name: National Institute on Aging, award: 5P30 AG013280, K99 AG065484, R01 AG060637, U01 AG060906; DOI: 10.13039/100000069, name: National Institute of Arthritis and Musculoskeletal and Skin Diseases, award: R01 AR071762; DOI: 10.13039/100000179, name: Office of the Director, award: S10 OD016281; DOI: 10.13039/100000057, name: National Institute of General Medical Sciences, award: P41 GM103533, R24 GM141156
- Language
- English
- Electronic publication date
- 09/27/2022
- Date published
- 02/03/2023
- Academic Unit
- Pathology; Iowa Neuroscience Institute; Radiation Oncology; Internal Medicine
- Record Identifier
- 9984302595102771
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