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Title: Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

Abstract

Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).

Authors:
 [1];  [2];  [3];  [1];  [4];  [4];  [3];  [4];  [3];  [3];  [4];  [1]; ORCiD logo [5]; ORCiD logo [6]
  1. Univ. of Western Australia, Perth, WA (Australia). ARC Centre of Excellence in Plant Energy Biology
  2. MRC Lab. of Molecular Biology, Cambridge (United Kingdom)
  3. Univ. of Cambridge (United Kingdom). Dept. of Biochemistry
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint BioEnergy Inst.
  5. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Joint BioEnergy Inst.; Univ. of Melbourne (Australia). School of BioSciences
  6. Univ. of Cambridge (United Kingdom). Dept. of Biochemistry; Copenhagen Univ. (Denmark). Plant and Environmental Sciences
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23); Australian Research Council (ARC)
OSTI Identifier:
1432223
Grant/Contract Number:  
AC02-05CH11231; CE140100008; FT13010123
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
The Plant Journal
Additional Journal Information:
Journal Volume: 92; Journal Issue: 6; Related Information: © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd; Journal ID: ISSN 0960-7412
Publisher:
Society for Experimental Biology
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Arabidopsis; organelles; tissues; protein abundance; shotgun proteomics; selected reaction monitoring

Citation Formats

Hooper, Cornelia M., Stevens, Tim J., Saukkonen, Anna, Castleden, Ian R., Singh, Pragya, Mann, Gregory W., Fabre, Bertrand, Ito, Jun, Deery, Michael J., Lilley, Kathryn S., Petzold, Christopher J., Millar, A. Harvey, Heazlewood, Joshua L., and Parsons, Harriet T. Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples. United States: N. p., 2017. Web. doi:10.1111/tpj.13743.
Hooper, Cornelia M., Stevens, Tim J., Saukkonen, Anna, Castleden, Ian R., Singh, Pragya, Mann, Gregory W., Fabre, Bertrand, Ito, Jun, Deery, Michael J., Lilley, Kathryn S., Petzold, Christopher J., Millar, A. Harvey, Heazlewood, Joshua L., & Parsons, Harriet T. Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples. United States. doi:10.1111/tpj.13743.
Hooper, Cornelia M., Stevens, Tim J., Saukkonen, Anna, Castleden, Ian R., Singh, Pragya, Mann, Gregory W., Fabre, Bertrand, Ito, Jun, Deery, Michael J., Lilley, Kathryn S., Petzold, Christopher J., Millar, A. Harvey, Heazlewood, Joshua L., and Parsons, Harriet T. Thu . "Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples". United States. doi:10.1111/tpj.13743. https://www.osti.gov/servlets/purl/1432223.
@article{osti_1432223,
title = {Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples},
author = {Hooper, Cornelia M. and Stevens, Tim J. and Saukkonen, Anna and Castleden, Ian R. and Singh, Pragya and Mann, Gregory W. and Fabre, Bertrand and Ito, Jun and Deery, Michael J. and Lilley, Kathryn S. and Petzold, Christopher J. and Millar, A. Harvey and Heazlewood, Joshua L. and Parsons, Harriet T.},
abstractNote = {Measuring changes in protein or organelle abundance in the cell is an essential, but challenging aspect of cell biology. Frequently-used methods for determining organelle abundance typically rely on detection of a very few marker proteins, so are unsatisfactory. In silico estimates of protein abundances from publicly available protein spectra can provide useful standard abundance values but contain only data from tissue proteomes, and are not coupled to organelle localization data. A new protein abundance score, the normalized protein abundance scale (NPAS), expands on the number of scored proteins and the scoring accuracy of lower-abundance proteins in Arabidopsis. NPAS was combined with subcellular protein localization data, facilitating quantitative estimations of organelle abundance during routine experimental procedures. A suite of targeted proteomics markers for subcellular compartment markers was developed, enabling independent verification of in silico estimates for relative organelle abundance. Estimation of relative organelle abundance was found to be reproducible and consistent over a range of tissues and growth conditions. In silico abundance estimations and localization data have been combined into an online tool, multiple marker abundance profiling, available in the SUBA4 toolbox (http://suba.live).},
doi = {10.1111/tpj.13743},
journal = {The Plant Journal},
number = 6,
volume = 92,
place = {United States},
year = {Thu Oct 12 00:00:00 EDT 2017},
month = {Thu Oct 12 00:00:00 EDT 2017}
}

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