Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS.
|Nr||61 (Research article)|
|Authors||Rosenberger, George; Liu, Yansheng; Röst, Hannes; Ludwig, Christina; Buil, Alfonso; Bensimon, Ariel; Soste, Martin; Spector, Tim; Dermitzakis, Emmanouil; Collins, Ben; Malmström, Lars; Aebersold, Ruedi|
|Title||Inference and quantification of peptidoforms in large sample cohorts by SWATH-MS.|
|Journal||Nat Biotechnol (2017) 35(8) 781-788|
|Citations||75 citations (journal impact: 41.67)|
|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.|