PXD072131

PXD072131 is an original dataset announced via ProteomeXchange.

Title	Benchmarking plasma from clinical and preclinical models
Description	The push for new clinical biomarkers has seen rapid innovation in biofluid analysis, particularly for plasma. For mass-spectrometry (MS)-based analysis, achieving depth and quantitative accuracy whilst ensuring throughput continues to shape plasma methods development. Numerous workflows have emerged that mitigate high-abundance suppression and expand dynamic range, especially when paired with next-generation MS instrumentation. Yet systematic evaluations that also consider biological variables (e.g., biofluid type, species) and technical parameters (e.g., MS methods) are limited. Here, we benchmarked eight sample-preparation workflows spanning neat approaches (SP3, STrap), depletion (perchloric acid, PerCA), and corona-enrichment strategies (MagNet HILIC/SAX, Enrich-iST, ProteoNano). We compared their performance across human plasma, human serum, and rat plasma, analysing all samples on an Orbitrap Astral (Thermo) using two plasma-optimised data-independent acquisition (DIA) methods: one discovery-maximised and one throughput-maximised. We identified 2,726 human and 3,767 rat proteins across workflows and methods, including ~1,000 from neat plasma. Increasing throughput incurred a ~20-30% reduction in depth, depending on workflow and species. EV-enrichment produced the deepest proteomes but with distinct compositions relative to neat, depleted, and secreted-protein-enriched samples, revealing a unique sub-proteome niche. Several workflows also performed markedly better in rat plasma, supporting improved sensitivity for preclinical analyses. Enrichment or depletion dramatically reshaped the balance of tissue- and cell-specific proteins detectable in plasma, suggesting that workflow choice should be guided by the organs, immune targets, or inflammatory signals most relevant to the study. In this vein, statistical analysis of differentially abundant proteins showed that >90% of detected proteins were significantly altered between workflows, with the largest numbers arising from the corona-enrichment strategies, underscoring how strongly workflow choice shapes the downstream proteome. Taken together, these findings emphasise a rapidly expanding plasma methodological landscape, where the most effective workflow is the one most precisely tailored to a cohort’s biology.
HostingRepository	PRIDE
AnnounceDate	2026-07-28
AnnouncementXML	Submission_2026-07-27_22:48:42.135.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Samantha Emery-Corbin
SpeciesList	scientific name: Homo sapiens (Human); NCBI TaxID: NEWT:9606; scientific name: Rattus norvegicus (Rat); NCBI TaxID: NEWT:10116;
ModificationList	acetylated residue; iodoacetamide derivatized residue
Instrument	Orbitrap Astral

Revision	Datetime	Status	ChangeLog Entry
0	2025-12-17 23:39:51	ID requested
⏵ 1	2026-07-27 22:48:42	announced

10.1016/J.MCPRO.2026.101626;

submitter keyword: Human, DIA, Serum, Plasma, Rat, Orbitrap Astral

Ralf Schittenhelm
contact affiliation	Monash Proteomics & Metabolomics Platform, Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, Victoria 3800, Australia
contact email	ralf.schittenhelm@monash.edu
lab head
Samantha Emery-Corbin
contact affiliation	Monash University
contact email	samantha.emery-corbin@monash.edu
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/07/PXD072131

PRIDE project URI

• PRIDE
  1. PXD072131
     1. Label: PRIDE project
     2. Name: Benchmarking plasma from clinical and preclinical models