Quantifying homologous proteins and proteoforms

TL;DR

This paper introduces HIquant, a first-principles model that accurately quantifies proteoform stoichiometries from mass spectrometry data, overcoming peptide-specific biases and enabling precise measurement of PTM occupancy.

Contribution

The paper presents HIquant, a novel computational method that infers proteoform stoichiometries directly from MS data without external standards, improving accuracy in proteoform quantification.

Findings

HIquant accurately quantifies fractional PTM occupancy.

The method works without external standards.

High accuracy demonstrated in histone modification analysis.

Abstract

Many proteoforms - arising from alternative splicing, post-translational modifications (PTMs), or paralogous genes - have distinct biological functions, such as histone PTM proteoforms. However, their quantification by existing bottom-up mass-spectrometry (MS) methods is undermined by peptide-specific biases. To avoid these biases, we developed and implemented a first-principles model (HIquant) for quantifying proteoform stoichiometries. We characterized when MS data allow inferring proteoform stoichiometries by HIquant, derived an algorithm for optimal inference, and demonstrated experimentally high accuracy in quantifying fractional PTM occupancy without using external standards, even in the challenging case of the histone modification code. HIquant server is implemented at: https://web.northeastern.edu/slavov/2014_HIquant/