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Bottom-Up Proteomics: Advancements in Sample Preparation

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. L...

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Detalles Bibliográficos
Autores principales: Duong, Van-An, Lee, Hookeun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10049050/
https://www.ncbi.nlm.nih.gov/pubmed/36982423
http://dx.doi.org/10.3390/ijms24065350
Descripción
Sumario:Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.