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Quantifying Homologous Proteins and Proteoforms.

Dmitry Malioutov1, Tianchi Chen2, Edoardo Airoldi3

  • 1From the ‡T. J. Watson IBM Research Center, 1101 Kitchawan Road, Yorktown Heights, NY 10598.

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Summary
This summary is machine-generated.

A new method, HIquant, quantifies proteoform stoichiometry using mass spectrometry, overcoming peptide biases. This approach accurately measures proteoform levels, crucial for understanding distinct biological functions.

Keywords:
AlgorithmsBioinformaticsBioinformatics SoftwareMass SpectrometryMathematical Modeling

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Area of Science:

  • Proteomics
  • Biochemistry
  • Molecular Biology

Background:

  • Proteoforms, arising from alternative splicing, post-translational modifications (PTM), or paralogous genes, possess distinct biological functions.
  • Existing bottom-up mass spectrometry (MS) methods for proteoform quantification are hindered by peptide-specific biases.

Purpose of the Study:

  • To develop and implement a first-principles model (HIquant) for unbiased quantification of proteoform stoichiometries.
  • To characterize the conditions under which MS data enable proteoform stoichiometry inference using HIquant.
  • To derive an algorithm for optimal proteoform stoichiometry inference.

Main Methods:

  • Development of the HIquant first-principles model for proteoform stoichiometry quantification.
  • Characterization of MS data requirements for inferring proteoform stoichiometries.
  • Derivation of an algorithm for optimal inference of proteoform stoichiometries.
  • Application of the algorithm to benchmark experimental systems: spiked-in alkylated proteoforms and endogenous histone 3 PTM proteoforms.

Main Results:

  • HIquant accurately infers proteoform stoichiometries, overcoming peptide-specific biases inherent in traditional MS methods.
  • Benchmarking with known ratios of alkylated proteoforms and endogenous histone 3 PTM proteoforms showed relative errors of 5-15% for simple proteoforms and 20-30% for complex proteoforms.
  • The developed algorithm enables optimal inference of proteoform stoichiometries from MS data.

Conclusions:

  • HIquant provides a robust and accurate method for quantifying proteoform stoichiometries without relying on external standards.
  • The method is applicable to both simple and complex proteoforms, advancing the field of quantitative proteomics.
  • Accessible via a web server, HIquant facilitates broader adoption and application in biological research.