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Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis.
Fu, Qin; Murray, Christopher I; Karpov, Oleg A; Van Eyk, Jennifer E.
Afiliação
  • Fu Q; Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Murray CI; Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Karpov OA; Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • Van Eyk JE; Smidt Heart Institute, Advanced Clinical Biosystems Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.
Mass Spectrom Rev ; 42(2): 873-886, 2023 03.
Article em En | MEDLINE | ID: mdl-34786750
ABSTRACT
Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Proteômica Tipo de estudo: Guideline Limite: Humans Idioma: En Revista: Mass Spectrom Rev Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Proteínas / Proteômica Tipo de estudo: Guideline Limite: Humans Idioma: En Revista: Mass Spectrom Rev Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos