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

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

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

In: Plant Journal, Vol. 92, No. 6, 2017, p. 1202-1217.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Hooper, CM, Stevens, TJ, Saukkonen, A, Castleden, IR, Singh, P, Mann, GW, Fabre, B, Ito, J, Deery, MJ, Lilley, KS, Petzold, CJ, Millar, AH, Heazlewood, JL & Parsons, HT 2017, 'Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples', Plant Journal, vol. 92, no. 6, pp. 1202-1217. https://doi.org/10.1111/tpj.13743

APA

Hooper, C. M., Stevens, T. J., Saukkonen, A., Castleden, I. R., Singh, P., Mann, G. W., Fabre, B., Ito, J., Deery, M. J., Lilley, K. S., Petzold, C. J., Millar, A. H., Heazlewood, J. L., & Parsons, H. T. (2017). Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples. Plant Journal, 92(6), 1202-1217. https://doi.org/10.1111/tpj.13743

Vancouver

Hooper CM, Stevens TJ, Saukkonen A, Castleden IR, Singh P, Mann GW et al. Multiple marker abundance profiling: combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples. Plant Journal. 2017;92(6):1202-1217. https://doi.org/10.1111/tpj.13743

Author

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 Tempé. / Multiple marker abundance profiling : combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples. In: Plant Journal. 2017 ; Vol. 92, No. 6. pp. 1202-1217.

Bibtex

@article{446721386a9f49dbba5a62bb294cdd9b,
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).",
author = "Hooper, {Cornelia M.} and Stevens, {Tim J.} and Anna Saukkonen and Castleden, {Ian R.} and Pragya Singh and Mann, {Gregory W.} and Bertrand Fabre and Jun Ito and Deery, {Michael J} and Lilley, {Kathryn S.} and Petzold, {Christopher J.} and Millar, {A. Harvey} and Heazlewood, {Joshua L.} and Parsons, {Harriet Temp{\'e}}",
note = "{\textcopyright} 2017 The Authors The Plant Journal {\textcopyright} 2017 John Wiley & Sons Ltd.",
year = "2017",
doi = "10.1111/tpj.13743",
language = "English",
volume = "92",
pages = "1202--1217",
journal = "Plant Journal",
issn = "0960-7412",
publisher = "Wiley-Blackwell",
number = "6",

}

RIS

TY - JOUR

T1 - Multiple marker abundance profiling

T2 - combining selected reaction monitoring and data-dependent acquisition for rapid estimation of organelle abundance in subcellular samples

AU - Hooper, Cornelia M.

AU - Stevens, Tim J.

AU - Saukkonen, Anna

AU - Castleden, Ian R.

AU - Singh, Pragya

AU - Mann, Gregory W.

AU - Fabre, Bertrand

AU - Ito, Jun

AU - Deery, Michael J

AU - Lilley, Kathryn S.

AU - Petzold, Christopher J.

AU - Millar, A. Harvey

AU - Heazlewood, Joshua L.

AU - Parsons, Harriet Tempé

N1 - © 2017 The Authors The Plant Journal © 2017 John Wiley & Sons Ltd.

PY - 2017

Y1 - 2017

N2 - 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).

AB - 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).

U2 - 10.1111/tpj.13743

DO - 10.1111/tpj.13743

M3 - Journal article

C2 - 29024340

VL - 92

SP - 1202

EP - 1217

JO - Plant Journal

JF - Plant Journal

SN - 0960-7412

IS - 6

ER -

ID: 195464995