Literature DB >> 30985128

Cost-Effective Automated Preparation of Serum Samples for Reproducible Quantitative Clinical Proteomics.

Jihyeon Lee, Hyunsoo Kim1, Areum Sohn, Injoon Yeo2, Youngsoo Kim1,2.   

Abstract

Reproducible sample preparation remains a significant challenge in large-scale clinical research using selected reaction monitoring-mass spectrometry (SRM-MS), which enables a highly sensitive multiplexed assay. Although automated liquid-handling platforms have tremendous potential for addressing this issue, the high cost of their consumables is a drawback that renders routine operation expensive. Here we evaluated the performance of a liquid-handling platform in preparing serum samples compared with a standard experiment while reducing the outlay for consumables, such as tips, wasted reagents, and reagent stock plates. A total of 26 multiplex assays were quantified by SRM-MS using four sets of 24 pooled human serum aliquots; the four sets used a fixed number (1, 4, 8, or 24) of tips to dispense digestion reagents. This study demonstrated that the use of 4 or 8 tips is comparable to 24 tips (standard experiment), as evidenced by their coefficients of variation: 13.5% (for 4 and 8 tips) versus 12.0% (24 tips). Thus we can save 37% of the total experimental cost compared with the standard experiment, maintaining nearly equivalent reproducibility. The routine operation of cost-effective liquid-handling platforms can enable researchers to process large-scale samples with high throughput, adding credibility to their findings by minimizing human error.

Entities:  

Keywords:  LC−MS/MS; automation; liquid-handling platform; selected reaction monitoring-mass spectrometry

Mesh:

Substances:

Year:  2019        PMID: 30985128     DOI: 10.1021/acs.jproteome.9b00023

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  3 in total

1.  A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19).

Authors:  Andrew T Rajczewski; Subina Mehta; Dinh Duy An Nguyen; Björn Grüning; James E Johnson; Thomas McGowan; Timothy J Griffin; Pratik D Jagtap
Journal:  Clin Proteomics       Date:  2021-05-10       Impact factor: 5.000

2.  A rigorous evaluation of optimal peptide targets for MS-based clinical diagnostics of Coronavirus Disease 2019 (COVID-19).

Authors:  Andrew T Rajczewski; Subina Mehta; Dinh Duy An Nguyen; Björn A Grüning; James E Johnson; Thomas McGowan; Timothy J Griffin; Pratik D Jagtap
Journal:  medRxiv       Date:  2021-03-01

3.  Modular automated bottom-up proteomic sample preparation for high-throughput applications.

Authors:  Yan Chen; Nurgul Kaplan Lease; Jennifer W Gin; Tadeusz L Ogorzalek; Paul D Adams; Nathan J Hillson; Christopher J Petzold
Journal:  PLoS One       Date:  2022-02-25       Impact factor: 3.240

  3 in total

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