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).

Plant phenotyping relevance

Arabidopsisの細胞内オルガネラ量という植物状態を、標的プロテオミクスと計算推定で定量する手法を開発・検証し、オンラインツールとして提供しているため、測定法が中心である。

Code and data availability

The paper deposits its own shotgun proteomics raw data (whole plant and CSC samples) in PRIDE (PXD005408), its SRM organelle-marker transitions in PeptideAtlas (PASS00906), and integrates its MMAP analysis tool (NPAS + HC-marker based organelle abundance estimation) into the public SUBA4 web interface at suba.live. All