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Set of Novel Automated Quantitative Microproteomics Protocols for Small Sample Amounts and Its Application to Kidney Tissue Substructures.
de Graaf, Erik Leonardus; Pellegrini, Davide; McDonnell, Liam A.
Afiliação
  • de Graaf EL; Fondazione Pisana per la Scienza ONLUS , Pisa 56121, Italy.
  • Pellegrini D; Fondazione Pisana per la Scienza ONLUS , Pisa 56121, Italy.
  • McDonnell LA; NEST, Scuola Normale Superiore , Pisa 56127, Italy.
J Proteome Res ; 15(12): 4722-4730, 2016 12 02.
Article em En | MEDLINE | ID: mdl-27809536
ABSTRACT
Here we assessed the ability of an automated sample preparation device equipped with disposable microcolumns to prepare mass-limited samples for high-sensitivity quantitative proteomics, using both label-free and isobaric labeling approaches. First, we compared peptide label-free quantification reproducibility for 1.5-150 µg of cell lysates and found that labware preconditioning was essential for reproducible quantification of <7.5 µg digest. Second, in-solution and on-column tandem mass tag (TMT) labeling protocols were compared and optimized for 1 µg of sample. Surprisingly, standard methods for in-solution and on-column labeling showed poor TMT labeling (50-85%); however, novel optimized and automated protocols restored efficient labeling to >98%. Third, compared with a single long gradient experiment, a simple robotized high-pH fractionation protocol using only 6 µg of starting material doubled the number of unique peptides and increased proteome coverage 1.43-fold. To facilitate the analysis of heterogeneous tissue samples, such as those obtained from laser capture microdissection, a modified BCA protein assay was developed that consumes and detects down to 15 ng of protein. As a proof-of-principle, the modular automated workflow was applied to 0.5 and 1 mm2 mouse kidney cortex and medulla microdissections to show the method's potential for real-life small sample sources and to create kidney substructure-specific proteomes.
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Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica / Rim Idioma: En Ano de publicação: 2016 Tipo de documento: Article
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Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica / Rim Idioma: En Ano de publicação: 2016 Tipo de documento: Article