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Nat Biotechnol. 2017 Aug;35(8):781-788. doi: 10.1038/nbt.3908. Epub 2017 Jun 12.

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

Author information

1
Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland.
2
PhD Program in Systems Biology, University of Zurich and ETH Zurich, Zurich, Switzerland.
3
Department of Genetics, Stanford University, Stanford, California, USA.
4
Bavarian Biomolecular Mass Spectrometry Center (BayBioMS), Technical University Munich, Freising, Germany.
5
Research Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Roskilde, Denmark.
6
Department of Biology, Institute of Biochemistry, ETH Zurich, Zurich, Switzerland.
7
Department of Twin Research and Genetic Epidemiology, King's College London, St Thomas' Hospital Campus, London, UK.
8
Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland.
9
S3IT, University of Zurich, Zurich, Switzerland.
10
Faculty of Science, University of Zurich, Zurich, Switzerland.

Abstract

Consistent detection and quantification of protein post-translational modifications (PTMs) across sample cohorts is a prerequisite for functional analysis of biological processes. Data-independent acquisition (DIA) is a bottom-up mass spectrometry approach that provides complete information on precursor and fragment ions. However, owing to the convoluted structure of DIA data sets, confident, systematic identification and quantification of peptidoforms has remained challenging. Here, we present inference of peptidoforms (IPF), a fully automated algorithm that uses spectral libraries to query, validate and quantify peptidoforms in DIA data sets. The method was developed on data acquired by the DIA method SWATH-MS and benchmarked using a synthetic phosphopeptide reference data set and phosphopeptide-enriched samples. IPF reduced false site-localization by more than sevenfold compared with previous approaches, while recovering 85.4% of the true signals. Using IPF, we quantified peptidoforms in DIA data acquired from >200 samples of blood plasma of a human twin cohort and assessed the contribution of heritable, environmental and longitudinal effects on their PTMs.

PMID:
28604659
PMCID:
PMC5593115
DOI:
10.1038/nbt.3908
[Indexed for MEDLINE]
Free PMC Article

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