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102-Plex Approach for Accurate and Multiplexed Proteome Quantification.
Wu, Zhen; Huang, Xirui; Huang, Lin; Zhang, Xumin.
Afiliação
  • Wu Z; State Key Laboratory of Genetic Engineering, Department of Biochemistry and Biophysics, School of Life Sciences, Fudan University, Shanghai 200438, China.
  • Huang X; State Key Laboratory of Genetic Engineering, Department of Biochemistry and Biophysics, School of Life Sciences, Fudan University, Shanghai 200438, China.
  • Huang L; State Key Laboratory of Genetic Engineering, Department of Biochemistry and Biophysics, School of Life Sciences, Fudan University, Shanghai 200438, China.
  • Zhang X; State Key Laboratory of Genetic Engineering, Department of Biochemistry and Biophysics, School of Life Sciences, Fudan University, Shanghai 200438, China.
Anal Chem ; 96(4): 1402-1409, 2024 01 30.
Article em En | MEDLINE | ID: mdl-38215345
ABSTRACT
Hyperplexing approaches have been aimed to meet the demand for large-scale proteomic analyses. Currently, the analysis capacity has expanded to up to 54 samples within a single experiment by utilizing different isotopic and isobaric reagent combinations. In this report, we propose a super multiplexed approach to enable the analysis of up to 102 samples in a single experiment, by the combination of our recently developed TAG-TMTpro and TAG-IBT16 labeling. We systematically investigated the identification and quantification performance of the 102-plex approach using the mixtures of E. coli and HeLa peptides. Our results revealed that all labeling series demonstrated accurate and reliable quantification performance. The combination of TAG-IBT16 and TAG-TMTpro approaches expands the multiplexing capacity to 102 plexes, providing a more multiplexed quantification method for even larger-scale proteomic analysis. Data are available via ProteomeXchange with the identifier PXD042398.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteoma / Proteômica Idioma: En Ano de publicação: 2024 Tipo de documento: Article