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Updated: Jul 30, 2025

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

Published on: September 28, 2013

Label-Free Quantitative Proteomics in Plant.

Ruonan Wang^1,2, Peijun Zhou^1,2, Yilin Pan^1,2

¹State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China.

Methods in Molecular Biology (Clifton, N.J.)

|May 11, 2023

Summary

This summary is machine-generated.

Label-free quantitation (LFQ) proteomics quantifies protein levels using peptide intensity from mass spectrometry. This protocol details LFQ for plant research, including studies on plant iron homeostasis.

Keywords:

Label-free quantitation Mass spectra Plant Proteomics

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Last Updated: Jul 30, 2025

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

Metabolic Labeling and Membrane Fractionation for Comparative Proteomic Analysis of Arabidopsis thaliana Suspension Cell Cultures

Published on: September 28, 2013

mRNA Interactome Capture from Plant Protoplasts

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Published on: July 28, 2017

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

A Simple Fractionated Extraction Method for the Comprehensive Analysis of Metabolites, Lipids, and Proteins from a Single Sample

Published on: June 1, 2017

Area of Science:

Proteomics
Plant Biology
Biochemistry

Background:

Label-free quantitation (LFQ) proteomics is crucial for determining relative protein abundance across samples.
LFQ relies on extracting peptide (precursor) intensity at the MS¹ (mass spectrum 1) level.
Standard LFQ protocols require adaptation for specific biological systems like plants.

Purpose of the Study:

To describe an optimized LFQ proteomics experimental protocol tailored for plant research.
To provide a methodological framework for investigating plant protein expression, exemplified by plant iron homeostasis.

Main Methods:

Individual scanning of plant samples using an advanced mass spectrometer.
Extraction of chromatographic features from each analytical run.
Generation of consensus patterns across multiple experimental runs for accurate quantification.

Main Results:

The described protocol enables robust relative protein quantification in plant samples.
Successful application demonstrated for studying plant iron homeostasis.

Conclusions:

The adapted LFQ protocol is effective for plant proteomics studies.
This methodology facilitates deeper understanding of plant biological processes at the proteome level.