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Related Concept Videos

Proteomics01:33

Proteomics

7.5K
A proteome is the entire set of proteins that a cell type produces. We can study proteomes using the knowledge of genomes because genes code for mRNAs, and the mRNAs encode proteins. Although mRNA analysis is a step in the right direction, not all mRNAs are translated into proteins.
Proteomics is the study of proteomes' function. It involves the large-scale systematic study of the proteome to denote the protein complement expressed by a genome. Scientist Mark Wilkins coined the term...
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Related Experiment Video

Updated: Apr 30, 2026

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

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Applying label-free quantitation to top down proteomics.

Ioanna Ntai1, Kyunggon Kim, Ryan T Fellers

  • 1Departments of Chemistry, Molecular Biosciences and the Proteomics Center of Excellence , 2145 N. Sheridan Road, Evanston, Illinois 60208, United States.

Analytical Chemistry
|May 9, 2014
PubMed
Summary
This summary is machine-generated.

This study presents a new method for quantitative analysis of whole protein forms (proteoforms) in complex biological systems. The robust pipeline identifies over 100 proteoform changes, advancing discovery proteomics.

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Area of Science:

  • Proteomics
  • Biochemistry
  • Molecular Biology

Background:

  • Quantitative analysis of whole protein forms (proteoforms) is crucial for understanding biological complexity.
  • Existing methods often focus on peptides, limiting proteoform-level insights.

Purpose of the Study:

  • To develop and validate a robust pipeline for the identification and quantitative analysis of proteoforms <30 kDa in discovery mode.
  • To apply this pipeline to study the effects of histone deacetylase deletion on proteoforms in S. cerevisiae.

Main Methods:

  • Development of a label-free, top-down proteomics pipeline for proteoform identification and quantification.
  • Utilizing a hierarchical linear model tailored to study design for statistical analysis.
  • Input of ~100-400 µg total protein per biological replicate.

Main Results:

  • Successful identification and stringent scoring of abundance changes in proteoforms <30 kDa.
  • Detection of over 100 proteoform changes in WT vs Δrpd3 mutant yeast.
  • Validation of findings through observation of histone H4 and H2B hyperacetylation.

Conclusions:

  • The developed pipeline is a critical advance for label-free, top-down proteomics in discovery mode.
  • This approach enables hypothesis testing on the link between whole proteoforms and complex phenotypes.
  • Proteoform-level analysis offers deeper insights into cell and disease biology than peptide-centric methods.