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Updated: Aug 6, 2026
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A Plasma Sample Preparation for Mass Spectrometry using an Automated Workstation
Published on: April 24, 2020
"If the Shoe Fits?"-Benchmarking Plasma Proteomic Sample-Preparation Workflows Across Human and Rat Biofluids
Samantha J Emery-Corbin1, Joel R Steele1, Dylan H Multari1
1Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia.
Molecular & Cellular Proteomics : MCP
|July 18, 2026
Summary
Choosing the right plasma sample preparation workflow is crucial for biomarker discovery. Different methods significantly alter detected proteins, highlighting the need for tailored approaches based on study biology and goals.
Area of Science:
- Proteomics
- Biomarker Discovery
- Mass Spectrometry
Background:
- Advancements in biofluid analysis, especially plasma, are driven by the need for clinical biomarkers.
- Mass spectrometry (MS)-based plasma analysis faces challenges in depth, quantitative accuracy, and throughput.
- Limited systematic evaluations exist for plasma-specific workflows across biological and technical variables.
Purpose of the Study:
- To benchmark eight distinct plasma sample-preparation workflows.
- To compare workflow performance across human plasma, human serum, and rat plasma.
- To evaluate the impact of data-independent acquisition (DIA) methods on proteome depth and throughput.
Main Methods:
- Eight sample-preparation workflows were benchmarked: neat (SP3, STrap), depletion (PerCA), and corona-enrichment (MagNet HILIC/SAX, Enrich-iST, ProteoNano).
- Analyses were performed on an Orbitrap Astral MS using discovery- and throughput-maximised DIA methods.
- Performance was assessed across human plasma, human serum, and rat plasma.
Main Results:
- 2,726 human and 3,767 rat proteins were identified across workflows and methods.
- Increasing throughput reduced proteome depth by ~20-30%.
- EV-enrichment yielded the deepest proteomes but with distinct compositions; several workflows performed better in rat plasma.
Conclusions:
- Workflow choice dramatically reshapes the detectable plasma proteome, impacting tissue- and cell-specific protein detection.
- Over 90% of detected proteins were significantly altered between workflows, with corona-enrichment strategies showing the largest impact.
- The optimal plasma analysis workflow depends on precise tailoring to the study's biological context and objectives.
