{"database":"Pride","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Txt":["ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/TMTlabelInfo.txt"],"Msf":["ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction1to20Combined.msf"],"Raw":["ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction1.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction16.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction11.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction5.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction14.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction7.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction12.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction9.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction4.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction2.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction19.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction20.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction10.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction17.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction13.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction6.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction15.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction18.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction3.raw","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/01/PXD067726/HFXP32400HpHFraction8.raw"]},"type":"primary"},"statusCodeValue":200,"statusCode":"OK"}],"scores":null,"additional":{"labhead_mail":["iain.searle@adelaide.edu.au"],"submitter":["Karthik Shantharam kamath"],"technology_type":["Data-dependent acquisition","Mass Spectrometry","Bottom-up proteomics"],"software":[""],"submitter_keywords":["Vicia sativa","Tmt-based proteomics","Neurotoxicity","Sh-sy5y cells"],"full_dataset_link":["https://www.ebi.ac.uk/pride/archive/projects/PXD067726"],"tissue":["Bone Marrow"],"sample_protocol":["Sample Preparation and Digestion: Toxin-treated and control SH-SY5Y cell pellets were lysed in 50 mM TEAB with 5% SDS, sonicated (30 s), boiled (95 °C, 5 min), and cooled. Equal protein amounts were normalized across samples. Disulfide bonds were reduced with 10 mM DTT (60 °C, 30 min), pH adjusted with phosphoric acid, and diluted in S-Trap binding buffer. Samples were loaded onto S-Trap columns, washed, and digested with trypsin (1:20 ratio, 47 °C, 1 h). Peptides were eluted with 50 mM TEAB.  TMT Labelling and Pooling: Equal peptide amounts from 10 samples (9 + 1 pooled reference) were labelled using a 10-plex TMT kit. Labels were reconstituted in anhydrous acetonitrile and incubated with peptides for 1 h at room temperature. Labelled peptides were pooled in a 1:1 ratio based on normalization factors and reconstituted in 2% acetonitrile, 0.1% formic acid for LC-MS/MS.  High-pH Reversed-Phase Fractionation: Pooled TMT-labelled peptides were desalted (C18 Sep-Pak), dried, and resuspended in 5 mM ammonia (pH 10.5). Using an Agilent 1260 HPLC system, peptides were separated over a 55 min gradient (3–30% acetonitrile) into 96 fractions, concatenated into 20, dried, and reconstituted in 0.1% formic acid for LC-MS/MS analysis. TMT-labelled, peptides were analysed using data-dependent acquisition (DDA) LC-MS/MS on a Q-Exactive HF-X mass spectrometer (ThermoFisher Scientific) coupled with an UltiMate 3000 nano-LC system. Peptides were loaded onto a C18 PepMap trap column, washed with 0.1% formic acid, and separated on an in-house packed Halo-C18 analytical column using a 110-minute gradient from 5% to 30% acetonitrile at 0.3 mL/min. MS1 scans were acquired at 60,000 resolution over a mass range of 350–1850 m/z, and the top 10 precursors (charge states +2 to +5) were selected for fragmentation via HCD (NCE 33, isolation width 0.8 m/z). MS2 scans were acquired at 45,000 resolution with a dynamic exclusion of 30 seconds, AGC target of 1×10⁵, and maximum injection time of 85 ms."],"repository":["Pride"],"quantification_method":[""],"modification":[""],"data_protocol":["Raw data were processed using Proteome Discoverer v2.1.0.81 (ThermoFisher Scientific) with SequestHT and Mascot search engines against the UniProt Homo sapiens database (reviewed and unreviewed). Search parameters included trypsin digestion with up to two missed cleavages, precursor mass tolerance of 20 ppm, and fragment mass tolerance of 0.02 Da. Dynamic modifications included oxidation (M), deamidation (N/Q), pyro-Glu (E/Q), acetylation (N-terminus), and TMT6plex (K/N-term), while carbamidomethylation (C) was set as a static modification. Protein, peptide, and PSM-level FDR thresholds were set to <1%, and only master proteins were retained for downstream analysis. Differential expression analysis was performed by comparing relative protein abundances across sample groups, identifying proteins with log₂ fold change ±0.5 and p-values <0.05 (two-tailed t-test) as significantly regulated. UniProt IDs were mapped to Ensembl annotations (EnsDb.Hsapiens.v86) using custom R scripts. Gene ontology (GO) enrichment was conducted using the enrichGO function in clusterProfiler v4.4.4 against the org.Hs.eg.db database from Bioconductor, with Benjamini-Hochberg adjusted p-values <0.05 considered significant. Protein interaction networks were visualised using cnetplotJam from multienrichJam, Cytoscape R (Rcy3 v2.16.0), and igraph v1.3.2."],"omics_type":["Proteomics"],"labhead":["Dr Iain Searle"],"instrument_platform":[""],"labhead_affiliation":["School of Biological Sciences, The University of Adelaide, Adelaide, South Australia, Australia"],"submission_type":["PARTIAL"],"species":["Homo Sapiens (human)"],"submitter_mail":["karthikskamath@gmail.com"],"publication":["41381656 Riley S, Nguyen V, Bhattacharjee R, Ng PQ, Ritchie T, Kamath KS, Fisk I, Gecz J, Kumar R, Searle IR. TMT-based quantitative proteomic assessment of Vicia sativa induced neurotoxicity by β-cyano-L-alanine and γ-glutamyl-β-cyano-L-alanine in SH-SY5Y cells. Sci Rep. 2025 16(1):510 10.1038/s41598-025-30121-2"],"submitter_affiliation":["Macquarie university"],"submitter_country":["Australia"],"pubmed_abstract":["β-cyano-L-alanine (BCA) and γ-glutamyl-β-cyano-L-alanine (GBCA) are the primary antinutritional compounds in Vicia sativa, a high-protein, drought-tolerant legume. While their neurotoxicity in monogastric animals has been reported, the molecular basis remains largely unknown. In this study, we optimised a rapid in vitro assay using retinoic acid-differentiated SH-SY5Y human neuroblastoma cells to assess BCA and GBCA toxicity, and then applied Tandem mass tags (TMT)-mass spectrometry (MS)-based quantitative proteomics to identify dysregulated proteins. BCA treatment dysregulated the proteins involved in DNA damage, translation, and oxidative stress, many of which are associated with neurodegenerative diseases such as amyotrophic lateral sclerosis and Alzheimer's disease, as well as various cancers. In contrast, GBCA impacted the proteins linked to mitosis, cell cycle regulation, and apoptosis pathways. Interestingly, the absence of overlapping dysregulated proteins between BCA- and GBCA-treated cells suggested that the two toxins likely induce neurotoxicity via distinct mechanisms. These findings offer new insights into the molecular and cellular alterations caused by V. sativa toxins and their implications for animal feed safety."],"pubmed_title":["TMT-based quantitative proteomic assessment of Vicia sativa induced neurotoxicity by β-cyano-L-alanine and γ-glutamyl-β-cyano-L-alanine in SH-SY5Y cells."],"pubmed_authors":["Riley Samuel S, Nguyen Vy V, Bhattacharjee Rudrarup R, Ng Pei Qin PQ, Ritchie Tarin T, Kamath Karthik S KS, Fisk Ian I, Gecz Jozef J, Kumar Raman R, Searle Iain R IR"],"additional_accession":[]},"is_claimable":false,"name":"TMT-based quantitative proteomic assessment of Vicia sativa induced neurotoxicity by β-cyano-L-alanine and γ-glutamyl-β-cyano-L-alanine in SH-SY5Y cells","description":"β-Cyano-L-alanine (BCA) and γ-glutamyl-β-cyano-L-alanine (GBCA) are the primary antinutritional compounds in Vicia sativa, a high-protein, drought-tolerant legume. While neurotoxicity in monogastric animals has been observed, its molecular basis remains largely unknown. In this study, we optimised an in vitro assay using retinoic acid-differentiated SH-SY5Y human neuroblastoma cells to assess BCA and GBCA toxicity and applied TMT-based quantitative proteomics to identify dysregulated proteins. BCA treatment affected proteins involved in DNA damage, translation, and oxidative stress, many of which are associated with neurodegenerative diseases such as amyotrophic lateral sclerosis and Alzheimer’s disease, as well as various cancers. In contrast, GBCA disrupted proteins linked to mitosis, cell cycle regulation, and apoptosis pathways. Interestingly, the absence of overlapping dysregulated proteins between BCA- and GBCA-treated cells suggests they induce neurotoxicity via distinct mechanisms. These findings offer new insights into the molecular toxicity of V. sativa toxins and their implications for animal feed 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