BACKGROUND: Accurate discovery assay workflows are critical for identifying authentic circulating protein biomarkers in diverse blood matrices. Maximizing the commonalities in the proteomic workflows between different biofluids simplifies the approach and increases the likelihood for reproducibility. We developed a workflow that can accommodate 3 blood-based proteomes: naive plasma, depleted plasma and dried blood. METHODS: Optimal conditions for sample preparation and data independent acquisition-mass spectrometry analysis were established in plasma then automated for depleted plasma and dried blood. The mass spectrometry workflow was modified to facilitate sensitive high-throughput analysis or deeper profiling with mid-throughput analysis. Analytical performance was evaluated by the linear response of peptides and proteins to a 6- or 7-point dilution curve and the reproducibility of the relative peptide and protein intensity for 5 digestion replicates per day on 3 different days for each biofluid. RESULTS: Using the high-throughput workflow, 74% (plasma), 93% (depleted), and 87% (dried blood) displayed an inter-day CV <30%. The mid-throughput workflow had 67% (plasma), 90% (depleted), and 78% (dried blood) of peptides display an inter-day CV <30%. Lower limits of detection and quantification were determined for peptides and proteins observed in each biofluid and workflow. Based on each protein and peptide's analytical performance, we could describe the observable, reliable, reproducible, and quantifiable proteomes for each biofluid and workflow. CONCLUSION: The standardized workflows established here allows for reproducible and quantifiable detection of proteins covering a broad dynamic range. We envisage that implementation of this standard workflow should simplify discovery approaches and facilitate the translation of candidate markers into clinical use.
Standardized Workflow for Precise Mid- and High-Throughput Proteomics of Blood Biofluids.
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作者:Mc Ardle Angela, Binek Aleksandra, Moradian Annie, Chazarin Orgel Blandine, Rivas Alejandro, Washington Kirstin E, Phebus Conor, Manalo Danica-Mae, Go James, Venkatraman Vidya, Coutelin Johnson Casey W, Fu Qin, Cheng Susan, Raedschelders Koen, Fert-Bober Justyna, Pennington Stephen R, Murray Christopher I, Van Eyk Jennifer E
| 期刊: | Clinical Chemistry | 影响因子: | 6.300 |
| 时间: | 2022 | 起止号: | 2022 Mar 4; 68(3):450-460 |
| doi: | 10.1093/clinchem/hvab202 | ||
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