Cost-Effective Automated Preparation of Serum Samples for Reproducible Quantitative Clinical Proteomics.
Jihyeon LeeHyunsoo KimAreum SohnInjoon YeoYoungsoo KimPublished in: Journal of proteome research (2019)
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.
Keyphrases
- high throughput
- mass spectrometry
- single cell
- liquid chromatography
- multiple sclerosis
- ionic liquid
- deep learning
- machine learning
- clinical practice
- high performance liquid chromatography
- gas chromatography
- randomized controlled trial
- ms ms
- clinical trial
- risk assessment
- induced pluripotent stem cells
- human health
- anaerobic digestion
- living cells