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Related Experiment Video

Updated: Jul 20, 2026

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Published on: August 28, 2021

Profiling human brain proteome by multi-dimensional separations coupled with MS.

Young Mok Park¹, Jin Young Kim, Kyung-Hoon Kwon

¹Proteomics Team, Korea Basic Science Institute, Daejeon, Republic of Korea.

|August 24, 2006

Summary

Researchers identified 1533 human brain proteins using advanced multi-dimensional separation and mass spectrometry. This proteomic analysis reveals the brain

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Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

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Last Updated: Jul 20, 2026

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Quantitative Proteomics Workflow using Multiple Reaction Monitoring Based Detection of Proteins from Human Brain Tissue

Published on: August 28, 2021

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification

Published on: November 15, 2017

Area of Science:

Proteomics
Neuroscience
Biochemistry

Background:

The human brain proteome is highly complex.
Previous proteomic studies faced limitations in identifying a comprehensive protein set.

Purpose of the Study:

To develop and apply a multi-dimensional strategy for extensive human brain proteome analysis.
To identify and classify proteins within the human temporal lobe.

Main Methods:

Sample fractionation of human temporal lobe proteins into cytoplasmic/nucleoplasmic, membrane/structural, and DNA-binding fractions.
One-dimensional SDS-PAGE separation followed by trypsin digestion and peptide analysis using RP-LC/ESI-MS/MS on an LTQ spectrometer.
Protein identification via SEQUEST search against the IPI database, validated by reversed sequence searching and Protein Hit Score filtering.

Main Results:

Identification of 1533 distinct proteins from the human brain proteome.
Classification of identified proteins based on cellular component distribution.
Determination that 24% of the identified proteins are membrane proteins.

Conclusions:

A multi-step fractionation strategy is effective for high-throughput proteomic characterization of complex biological samples like the human brain.
This approach enhances the depth and breadth of protein identification in proteomic studies.
The findings provide a significant catalog of human brain proteins and their cellular localization.