Characterisation of the circulating acellular proteome of healthy sheep using LC-MS/MS-based proteomics analysis of serum.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28615994", "kind": "science-record", "revision": 6, "content_hash": "sha256:43ccf533b0334c206a0c21b71a015c648548e0e0189e1d2a79970905571e3629", "created_at": "2026-11-01T15:40:26Z", "updated_at": "2026-11-01T21:20:57Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Characterisation of the circulating acellular proteome of healthy sheep using LC-MS/MS-based proteomics analysis of serum.", "doi": "10.1186/s12953-017-0119-z", "pmid": "28615994", "authors": ["Saul Chemonges", "Rajesh Gupta", "Paul C Mills", "Steven R Kopp", "Pawel Sadowski"], "journal": "Proteome science", "year": 2016, "abstract": "BACKGROUND: Unlike humans, there is currently no publicly available reference mass spectrometry-based circulating acellular proteome data for sheep, limiting the analysis and interpretation of a range of physiological changes and disease states. The objective of this study was to develop a robust and comprehensive method to characterise the circulating acellular proteome in ovine serum.\nMETHODS: Serum samples from healthy sheep were subjected to shotgun proteomic analysis using nano liquid chromatography nano electrospray ionisation tandem mass spectrometry (nanoLC-nanoESI-MS/MS) on a quadrupole time-of-flight instrument (TripleTOF® 5600+, SCIEX). Proteins were identified using ProteinPilot™ (SCIEX) and Mascot (Matrix Science) software based on a minimum of two unmodified highly scoring unique peptides per protein at a false discovery rate (FDR) of 1% software by searching a subset of the Universal Protein Resource Knowledgebase (UniProtKB) database (http://www.uniprot.org). PeptideShaker (CompOmics, VIB-UGent) searches were used to validate protein identifications from ProteinPilot™ and Mascot.\nRESULTS: ProteinPilot™ and Mascot identified 245 and 379 protein groups (IDs), respectively, and PeptideShaker validated 133 protein IDs from the entire dataset. Since Mascot software is considered the industry standard and identified the most proteins, these were analysed using the Protein ANalysis THrough Evolutionary Relationships (PANTHER) classification tool revealing the association of 349 genes with 127 protein pathway hits. These data are available via ProteomeXchange with identifier PXD004989.\nCONCLUSIONS: These results demonstrated for the first time the feasibility of characterising the ovine circulating acellular proteome using nanoLC-nanoESI-MS/MS. This peptide spectral data contributes to a protein library that can be used to identify a wide range of proteins in ovine serum.", "claims": [{"id": "claim-method", "statement": "Peptides and proteins were inferred from the spectrum identification results using PeptideShaker version 1.13.0 [32]. Peptide Spectrum Matches (PSMs), peptides and proteins were validated at a 1.0% False Discovery Rate (FDR) estimated using the decoy hit distribution. The mass spectrometry data that support the findings of this study along with the identification results were deposited to ProteomeXchange Consortium [52] via the proteomics identifications (PRIDE) partner repository [53] with the dataset identifiers PXD004989 and 10.6019/PXD004989 with the following data access details: Reviewer account details: Username: reviewer99399@ebi.ac.uk; Password: QBFFTGzl.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28615994", "locator": "sections[15] \"Secondary protein sequence database search for protein identification and validation\" paragraph 3", "quote": "Peptides and proteins were inferred from the spectrum identification results using PeptideShaker version 1.13.0 [32]."}, {"asset": "source:pmid:28615994", "locator": "sections[15] \"Secondary protein sequence database search for protein identification and validation\" paragraph 3", "quote": "Peptide Spectrum Matches (PSMs), peptides and proteins were validated at a 1.0% False Discovery Rate (FDR) estimated using the decoy hit distribution."}, {"asset": "source:pmid:28615994", "locator": "sections[29] \"Availability of data and materials\" paragraph 2", "quote": "The mass spectrometry data that support the findings of this study along with the identification results were deposited to ProteomeXchange Consortium [52] via the proteomics identifications (PRIDE) partner repository [53] with the dataset identifiers PXD004989 and 10.6019/PXD004989 with the following data access details: Reviewer account details: Username: reviewer99399@ebi.ac.uk; Password: QBFFTGzl."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The mass spectrometry data that support the findings of this study along with the identification results were deposited to ProteomeXchange Consortium [52] via the proteomics identifications (PRIDE) partner repository [53] with the dataset identifiers PXD004989 and 10.6019/PXD004989 with the following data access details: Reviewer account details: Username: reviewer99399@ebi.ac.uk; Password: QBFFTGzl.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28615994", "locator": "sections[29] \"Availability of data and materials\" paragraph 2", "quote": "The mass spectrometry data that support the findings of this study along with the identification results were deposited to ProteomeXchange Consortium [52] via the proteomics identifications (PRIDE) partner repository [53] with the dataset identifiers PXD004989 and 10.6019/PXD004989 with the following data access details: Reviewer account details: Username: reviewer99399@ebi.ac.uk; Password: QBFFTGzl."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using a sheep-only UniProtKB search with a 1% FDR and at least two peptides per protein, the study identified 379 serum proteins with Mascot and validated 133 with PeptideShaker; the source mass-spectrometry data were deposited in ProteomeXchange under PXD004989.", "kind": "quantitative", "target": {"value": 1.0, "unit": "per cent", "tolerance": null, "source": "A secondary analysis using PeptideShaker of this same entire dataset yielded 133 IDs (1% FDR and ≥ 2 unique validated peptides)."}, "evidence": [{"asset": "source:pmid:28615994", "locator": "sections[21] \"Combined protein identifications from 1D SDS-PAGE and in-solution digestion of serum using ProteinPilot™ and Mascot database search engines and PeptideShaker search\" paragraph 2", "quote": "Protein yields of a composite search of all the sample data from the three workflows (first, second and third in-gel and in-solution digestion) using a sheep-only UniProtKB database optimised for PeptideShaker Software were as follows: ProteinPilot™: 245 IDs and Mascot: 379 IDs."}, {"asset": "source:pmid:28615994", "locator": "sections[21] \"Combined protein identifications from 1D SDS-PAGE and in-solution digestion of serum using ProteinPilot™ and Mascot database search engines and PeptideShaker search\" paragraph 2", "quote": "A secondary analysis using PeptideShaker of this same entire dataset yielded 133 IDs (1% FDR and ≥ 2 unique validated peptides)."}, {"asset": "source:pmid:28615994", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "These data are available via ProteomeXchange with identifier PXD004989."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using a sheep-only UniProtKB search with a 1% FDR and at least two peptides per protein, the study identified 379 serum proteins with Mascot and validated 133 with PeptideShaker; 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