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PXD063239-1

PXD063239 is an original dataset announced via ProteomeXchange.

Dataset Summary
TitleEvaluating Protein Enrichment Methods to Improve Biomarker Discovery in Equine Neurological Disorders
DescriptionThis study evaluated and compared three sample preparation strategies for proteomic analysis of equine cerebrospinal fluid (CSF): native in-solution digestion, the ProteoMiner™ Small-Capacity Enrichment Kit (Bio-Rad®), and the PreOmics Enrich-iST™ Kit (PreOmics®). CSF is in direct contact with the central nervous system (CNS), and its protein content reflects both physiological and pathological states, making it an ideal fluid for biomarker discovery in neurological diseases. However, its analysis is hindered by the wide dynamic range of protein concentrations and the predominance of highly abundant proteins (HAPs), such as albumin, which can obscure the detection of diagnostically relevant low-abundance proteins (LAPs). To address these limitations, enrichment kits such as ProteoMiner and PreOmics have been employed to reduce HAPs and enhance LAP detection prior to mass spectrometry. While ProteoMiner uses a combinatorial hexapeptide ligand library to compress the dynamic range by saturating binding sites of abundant proteins, PreOmics relies on paramagnetic beads with hydrophobic and charge-based retention to selectively bind peptides and improve sample purity. This is the first study to apply the PreOmics Enrich-iST kit to equine CSF. Label-free LC-MS/MS was used to analyse the samples. A total of 849 unique proteins were identified across all methods, with the PreOmics kit identifying the highest number of proteins and achieving the most consistent depletion of HAPs. emPAI scores were used to quantify protein abundance, revealing that albumin levels decreased by over 60% with PreOmics but slightly increased with ProteoMiner. Pathway enrichment analysis using PANTHER showed that the PreOmics kit enabled detection of a broader and more statistically significant array of biological pathways, while ProteoMiner selectively enriched for HAPs with known roles in neurodegenerative disorders, such as Dickkopf WNT signalling pathway inhibitor 3 (DKK3) and clusterin (CLU). These findings highlight that although both kits are capable of enriching LAPs, they differ in their enrichment patterns and efficiency. PreOmics provides better overall proteome coverage and greater statistical power in pathway analysis, whereas ProteoMiner may be more effective for targeted studies of specific neuropathology-related proteins. This study provides valuable insights into the applicability and complementarity of these enrichment methods for biomarker discovery in equine neurological disease.
HostingRepositoryPRIDE
AnnounceDate2026-04-13
AnnouncementXMLSubmission_2026-04-12_16:16:47.359.xml
DigitalObjectIdentifierhttps://doi.org/10.6019/PXD063239
ReviewLevelPeer-reviewed dataset
DatasetOriginOriginal dataset
RepositorySupportSupported dataset by repository
PrimarySubmitterFederico Foti
SpeciesList scientific name: Equus caballus (Horse); NCBI TaxID: NEWT:9796;
ModificationListiodoacetamide derivatized residue
InstrumentQ Exactive HF
Dataset History
RevisionDatetimeStatusChangeLog Entry
02025-04-23 05:01:25ID requested
12026-04-12 16:16:48announced
Publication List
10.1002/vms3.70933;
Federico F, Amie W, Alzbeta C, Anders J, David LP, Mandy PJ, Evaluating Protein Enrichment Methods to Improve Biomarker Discovery in Equine Cerebrospinal Fluid. Vet Med Sci, 12(3):e70933(2026) [pubmed]
10.6019/PXD063239;
Keyword List
submitter keyword: Cerebrospinal fluid (CSF)
Proteomics
Native digestion
ProteoMiner™ Small-Capacity Enrichment Kit
PreOmics Enrich-iST™
Liquid chromatography with tandem mass spectrometry (LC-MS/MS)
Contact List
Mandy Peffers
contact affiliationHead of Department Musculoskeletal Ageing Science |Institute of Life Course and Medical Sciences | Faculty of Health & Life Sciences |University of Liverpool | United Kingdom
contact emailpeffs@liverpool.ac.uk
lab head
Federico Foti
contact affiliationUniversity of Liverpool
contact emailfederico.foti@liverpool.ac.uk
dataset submitter
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Dataset FTP location
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