Mass fingerprinting of complex mixtures: protein inference from high-resolution peptide masses and predicted retention times.
J Proteome Res
; 12(12): 5730-41, 2013 Dec 06.
Article
en En
| MEDLINE
| ID: mdl-24074221
ABSTRACT
In typical shotgun experiments, the mass spectrometer records the masses of a large set of ionized analytes but fragments only a fraction of them. In the subsequent analyses, normally only the fragmented ions are used to compile a set of peptide identifications, while the unfragmented ones are disregarded. In this work, we show how the unfragmented ions, here denoted MS1-features, can be used to increase the confidence of the proteins identified in shotgun experiments. Specifically, we propose the usage of in silico mass tags, where the observed MS1-features are matched against de novo predicted masses and retention times for all peptides derived from a sequence database. We present a statistical model to assign protein-level probabilities based on the MS1-features and combine this data with the fragmentation spectra. Our approach was evaluated for two triplicate data sets from yeast and human, respectively, leading to up to 7% more protein identifications at a fixed protein-level false discovery rate of 1%. The additional protein identifications were validated both in the context of the mass spectrometry data and by examining their estimated transcript levels generated using RNA-Seq. The proposed method is reproducible, straightforward to apply, and can even be used to reanalyze and increase the yield of existing data sets.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Fragmentos de Péptidos
/
Proteínas
/
Modelos Estadísticos
/
Mezclas Complejas
/
Espectrometría de Masas en Tándem
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
J Proteome Res
Asunto de la revista:
BIOQUIMICA
Año:
2013
Tipo del documento:
Article
País de afiliación:
Suecia