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Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes.
Pang, Chi Nam Ignatius; Ballouz, Sara; Weissberger, Daniel; Thibaut, Loïc M; Hamey, Joshua J; Gillis, Jesse; Wilkins, Marc R; Hart-Smith, Gene.
Afiliación
  • Pang CNI; Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia.
  • Ballouz S; Garvan Institute of Medical Research, Darlinghurst, Sydney, New South Wales, Australia.
  • Weissberger D; School of Chemistry, University of New South Wales, Sydney, New South Wales, Australia.
  • Thibaut LM; School of Mathematics and Statistics, University of New South Wales, Sydney, New South Wales, Australia.
  • Hamey JJ; Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia.
  • Gillis J; Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Woodbury, New York, USA.
  • Wilkins MR; Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia.
  • Hart-Smith G; Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales, Australia; Department of Molecular Sciences, Macquarie University, Sydney, New South Wales, Australia. Electronic address: gene.hart-smith@mq.edu.au.
Mol Cell Proteomics ; 19(11): 1876-1895, 2020 11.
Article en En | MEDLINE | ID: mdl-32817346
Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies - Spearman and Kendall correlations - and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric-Euclidean distance-delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.
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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Espectrometría de Masas / Proteoma / Proteínas de Saccharomyces cerevisiae / Proteómica / Fraccionamiento Químico Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Mol Cell Proteomics Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA Año: 2020 Tipo del documento: Article País de afiliación: Australia

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Espectrometría de Masas / Proteoma / Proteínas de Saccharomyces cerevisiae / Proteómica / Fraccionamiento Químico Tipo de estudio: Guideline / Prognostic_studies Límite: Humans Idioma: En Revista: Mol Cell Proteomics Asunto de la revista: BIOLOGIA MOLECULAR / BIOQUIMICA Año: 2020 Tipo del documento: Article País de afiliación: Australia