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R2‐P2 rapid‐robotic phosphoproteomics enables multidimensional cell signaling studies

Recent developments in proteomics have enabled signaling studies where > 10,000 phosphosites can be routinely identified and quantified. Yet, current analyses are limited in throughput, reproducibility, and robustness, hampering experiments that involve multiple perturbations, such as those neede...

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Detalles Bibliográficos
Autores principales: Leutert, Mario, Rodríguez‐Mias, Ricard A, Fukuda, Noelle K, Villén, Judit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6920700/
https://www.ncbi.nlm.nih.gov/pubmed/31885202
http://dx.doi.org/10.15252/msb.20199021
Descripción
Sumario:Recent developments in proteomics have enabled signaling studies where > 10,000 phosphosites can be routinely identified and quantified. Yet, current analyses are limited in throughput, reproducibility, and robustness, hampering experiments that involve multiple perturbations, such as those needed to map kinase–substrate relationships, capture pathway crosstalks, and network inference analysis. To address these challenges, we introduce rapid‐robotic phosphoproteomics (R2‐P2), an end‐to‐end automated method that uses magnetic particles to process protein extracts to deliver mass spectrometry‐ready phosphopeptides. R2‐P2 is rapid, robust, versatile, and high‐throughput. To showcase the method, we applied it, in combination with data‐independent acquisition mass spectrometry, to study signaling dynamics in the mitogen‐activated protein kinase (MAPK) pathway in yeast. Our results reveal broad and specific signaling events along the mating, the high‐osmolarity glycerol, and the invasive growth branches of the MAPK pathway, with robust phosphorylation of downstream regulatory proteins and transcription factors. Our method facilitates large‐scale signaling studies involving hundreds of perturbations opening the door to systems‐level studies aiming to capture signaling complexity.