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Peptide Identification Using Tandem Mass Spectrometry

Peptide Identification Using Tandem Mass Spectrometry

Tandem mass spectrometry, also known as MS/MS or MS2, is an analytical technique that employs two mass analyzers. Essentially it is a series of mass spectrometers that helps isolate a particular biomolecule and then helps study its chemical properties.
This technique helps gather information regarding the protein from which the peptide was obtained and to study the peptides’ amino acid sequence. Identifying peptides from a complex mixture is an important component of the growing field of...

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Simultaneous Affinity Enrichment of Two Post-Translational Modifications for Quantification and Site Localization

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Published on: February 27, 2020

Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS.

George Rosenberger^1,2, Yansheng Liu¹, Hannes L Röst^1,3

¹Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.

Nature Biotechnology

|June 13, 2017

Summary

This summary is machine-generated.

Accurate protein post-translational modification (PTM) quantification in large cohorts is crucial. A new algorithm, inference of peptidoforms (IPF), enhances PTM detection in complex mass spectrometry data, improving heritability studies.

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Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics

Semi-Quantitative Analysis of Peptidoglycan by Liquid Chromatography Mass Spectrometry and Bioinformatics

Published on: October 13, 2020

Area of Science:

Proteomics
Mass Spectrometry
Systems Biology

Background:

Consistent detection and quantification of protein post-translational modifications (PTMs) are essential for understanding biological processes.
Data-independent acquisition (DIA) mass spectrometry offers comprehensive data but presents challenges in systematic peptidoform identification and quantification.

Purpose of the Study:

To develop a fully automated algorithm for confident and systematic identification and quantification of peptidoforms in DIA datasets.
To improve the accuracy of PTM site localization and signal recovery in complex proteomic data.

Main Methods:

Development of the inference of peptidoforms (IPF) algorithm, utilizing spectral libraries for querying, validation, and quantification.
Benchmarking IPF using SWATH-MS DIA data, a synthetic phosphopeptide reference dataset, and phosphopeptide-enriched samples.

Main Results:

IPF significantly reduced false site-localization by over sevenfold compared to previous methods.
The algorithm successfully recovered 85.4% of true signals in benchmark datasets.
IPF was applied to quantify peptidoforms in over 200 human blood plasma samples from a twin cohort.

Conclusions:

IPF provides a robust and automated solution for peptidoform quantification in DIA mass spectrometry data.
The application of IPF in a human twin cohort enabled assessment of heritable, environmental, and longitudinal effects on PTMs.
This advancement facilitates deeper functional analysis of biological processes through improved PTM characterization.