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Enhancing Data Reliability in TOMAHAQ for Large-Scale Protein Quantification.

Fang Liu1, Kratika Singhal1, Rowan Matney1

  • 1Vincent Coates Foundation Mass Spectrometry Laboratory, Stanford University, Stanford, CA, 94305, USA.

Proteomics
|February 8, 2020
PubMed
Summary
This summary is machine-generated.

The triggered by offset, multiplexed, accurate mass, high resolution, and absolute quantitation (TOMAHAQ) technique enhances proteomics assays. A new data correction strategy resolves interference from TMTzero reporter ions for improved quantification.

Keywords:
data normalizationtandem mass tagstargeted proteomicstriggered by offset, multiplexed, accurate mass, high resolution, and absolute quantitation

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Area of Science:

  • Proteomics
  • Mass Spectrometry
  • Quantitative Biology

Background:

  • Targeted proteomics assays face limitations in analytical scale and instrument utilization.
  • The TOMAHAQ technique was developed to improve both analytical scale and quantitative performance through peptide and sample multiplexing.

Purpose of the Study:

  • To discuss critical technical requirements and data analysis for TOMAHAQ implementation.
  • To address interference issues observed with TMTzero reporter ions in TOMAHAQ.
  • To propose a data correction strategy for reliable high-throughput quantification.

Main Methods:

  • Studied 185 target peptides across over 200 clinical plasma samples.
  • Investigated interference from TMTzero reporter ions in TOMAHAQ assays.
  • Developed a post-acquisition data correction strategy to deconvolute reporter ion superposition.

Main Results:

  • Observed significant interference from TMTzero reporter ions, which was unexpected.
  • Identified the source of interference as synthetic trigger peptides.
  • Demonstrated the effectiveness of the proposed data correction strategy in recovering reliable data.

Conclusions:

  • The TOMAHAQ technique shows promise for high-throughput quantification in proteomics.
  • Interference from TMTzero reporter ions can compromise data reliability.
  • A post-acquisition data correction strategy is essential for accurate TOMAHAQ implementation and unlocking its full potential.