Your browser doesn't support javascript.
loading
Benchmarking accuracy and precision of intensity-based absolute quantification of protein abundances in Saccharomyces cerevisiae.
Sánchez, Benjamín J; Lahtvee, Petri-Jaan; Campbell, Kate; Kasvandik, Sergo; Yu, Rosemary; Domenzain, Iván; Zelezniak, Aleksej; Nielsen, Jens.
Afiliação
  • Sánchez BJ; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
  • Lahtvee PJ; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden.
  • Campbell K; Institute of Technology, University of Tartu, Tartu, Estonia.
  • Kasvandik S; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
  • Yu R; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden.
  • Domenzain I; Institute of Technology, University of Tartu, Tartu, Estonia.
  • Zelezniak A; Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden.
  • Nielsen J; Novo Nordisk Foundation Center for Biosustainability, Chalmers University of Technology, Gothenburg, Sweden.
Proteomics ; 21(6): e2000093, 2021 03.
Article em En | MEDLINE | ID: mdl-33452728
ABSTRACT
Protein quantification via label-free mass spectrometry (MS) has become an increasingly popular method for predicting genome-wide absolute protein abundances. A known caveat of this approach, however, is the poor technical reproducibility, that is, how consistent predictions are when the same sample is measured repeatedly. Here, we measured proteomics data for Saccharomyces cerevisiae with both biological and inter-batch technical triplicates, to analyze both accuracy and precision of protein quantification via MS. Moreover, we analyzed how these metrics vary when applying different methods for converting MS intensities to absolute protein abundances. We demonstrate that our simple normalization and rescaling approach can perform as accurately, yet more precisely, than methods which rely on external standards. Additionally, we show that inter-batch reproducibility is worse than biological reproducibility for all evaluated methods. These results offer a new benchmark for assessing MS data quality for protein quantification, while also underscoring current limitations in this approach.
Assuntos
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saccharomyces cerevisiae / Benchmarking Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Saccharomyces cerevisiae / Benchmarking Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article