Quantitation, networking, and function of protein phosphorylation in plant cell

Lin Zhu*, Ning Li

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

7 Citations (Scopus)

Abstract

Protein phosphorylation is one of the most important post-translational modifications (PTMs) as it participates in regulating various cellular processes and biological functions. It is therefore crucial to identify phosphorylated proteins to construct a phosphor-relay network, and eventually to understand the underlying molecular regulatory mechanism in response to both internal and external stimuli. The changes in phosphorylation status at these novel phosphosites can be accurately measured using a 15N-stable isotopic labeling in Arabidopsis (SILIA) quantitative proteomic approach in a high-throughput manner. One of the unique characteristics of the SILIA quantitative phosphoproteomic approach is the preservation of native PTM status on protein during the entire peptide preparation procedure. Evolved from SILIA is another quantitative PTM proteomic approach, AQUIP (absolute quantitation of isoforms of post-translationally modified proteins), which was developed by combining the advantages of targeted proteomics with SILIA. Bioinformatics-based phosphorylation site prediction coupled with an MS-based in vitro kinase assay is an additional way to extend the capability of phosphosite identification from the total cellular protein. The combined use of SILIA and AQUIP provides a novel strategy for molecular systems biological study and for investigation of in vivo biological functions of these phosphoprotein isoforms and combinatorial codes of PTMs.

Original languageEnglish
Article number302
Number of pages7
JournalFrontiers in Plant Science
Volume3
DOIs
Publication statusPublished - 8 Jan 2013

Scopus Subject Areas

  • Plant Science

User-Defined Keywords

  • AQUIP
  • Cell signaling and regulation
  • Mass spectrometry-based interactomics
  • Plant
  • Post-translational modification
  • Quantitative proteomics
  • SILIA

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