{"database":"Pride","file_versions":[{"headers":{"Content-Type":["application/json"]},"body":{"files":{"Tabular":["ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/20250624_082329_ZIH342_BSG_PGSpec_PeptideReport.tsv","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/20250624_082329_ZIH342_BSG_PGSpec_ProteinReport.tsv"],"Other":["ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X014_Fe_high_3_44_1_61.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X002_Control_1_32_1_49.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X003_Control_2_33_1_50.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X025_Fe_Cu_high_4_55_1_72.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X022_Fe_Cu_high_1_52_1_69.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X008_Fe_low_2_38_1_55.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X020_Fe_Cu_low_4_50_1_67.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X009_Fe_low_3_39_1_56.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X019_Fe_Cu_low_3_49_1_66.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X023_Fe_Cu_high_2_53_1_70.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X015_Fe_high_4_45_1_62.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X013_Fe_high_2_43_1_60.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X017_Fe_Cu_low_1_47_1_64.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X024_Fe_Cu_high_3_54_1_71.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X018_Fe_Cu_low_2_48_1_65.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X007_Fe_low_1_37_1_54.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X004_Control_3_34_1_51.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X012_Fe_high_1_42_1_59.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X010_Fe_low_4_40_1_57.d.zip","ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2026/09/PXD070837/ZIH342X005_Control_4_35_1_52.d.zip"]},"type":"primary"},"statusCode":"OK","statusCodeValue":200}],"scores":null,"additional":{"labhead_mail":["hans.zischka@helmholtz-munich.de"],"submitter":["Christine von Toerne"],"technology_type":["Mass Spectrometry","Data-independent acquisition"],"software":[""],"submitter_keywords":["Iron overload","Methanobactin","Iron-sulfur cluster enzymes","Mitochondria","Hemochromatosis","Liver","Trace metals"],"full_dataset_link":["https://www.ebi.ac.uk/pride/archive/projects/PXD070837"],"tissue":["Liver"],"sample_protocol":["Proteome Analysis 1.5x106 cells  were incubated for 24 h with 1 or 10 mM FAC (with and without copper) in DMEM (10% FCS). Afterwards, cells were trypsinized and counted. Cell viability was determined by Erythrosin B staining. 1-2x106 cells were pelleted and once PBS washed. The protein concentration was determined by the Bradford assay and a total of 50 µg protein per replicate was stored at -80 °C. These samples were then further prepared under the supervision of  CvT using the iST kit (PreOmics, Munich, Germany) for MS measurement. MS measurement: MS data were acquired in DIA-PASEF mode on a timsTOF HT mass spectrometer (Bruker, Bremen, Germany). Equal amounts of peptides were loaded to the online coupled VanquishNeo (Thermo Fisher Scientific, Dreieich, Germany) HPLC system. A Nano-Trap column was used (300 µm inner diameter (ID) × 5 mm), packed with Acclaim PepMap100 C18, 5 µm, 100 Å from LC Packings, Sunnyvale, CA, USA, before separation by reversed-phase chromatography (Aurora 75 µm ID × 250 mm, 1.8 µm from Ionoptics, Fitzroy, Australia) at 40 °C. Peptides were eluted from the column at 250 nL/min using increasing ACN concentration in 0.1% formic acid from 3 to 40% over a 45-min gradient. The DIA-PASEF method covered a mass range from 300 to 1,250 m/z and a mobility range from 0.65 to 1.35 1/ko. Precursor peptides were isolated with 34 equal windows. Collision energy for 0.6 1/ko was set to 20 and for 1.6 1/ko to 59. Estimated cycle time was 1.91 s."],"repository":["Pride"],"quantification_method":[""],"modification":[""],"data_protocol":["Data Processing: DIA files were processed with Spectronaut (Version 19, Biognosys) as direct DIA analysis against a SwissProt human database (Release 2020_02, 20432 sequences) using BSG factory settings for Pulsar search. For DIA analysis, default settings were applied. For quantification, precursor filtering was set on Qvalue, with cross run normalization. Imputation was set to run-wise. Quantity MS level was set to MS2; Quantity type was area, and protein quantification is based on the summed-up peptide intensities. Protein-group specific peptides were allowed for quantification. Protein mapping and pathway analysis: The quantified data were further preprocessed in Python using specified dependencies including pandas (≥2.3.0), scikit-learn (1.6), matplotlib (3.9), and the Reactome API. Firstly, protein identifiers were extracted and data cleaned for API compatibility. Annotation was achieved by submitting protein identifiers to retrieve relevant biological pathways, with gene-to-pathway mapping accomplished via Reactome's GMT file, supplemented by API queries for missing data. The analysis focused on iron-related biological processes using semantic keyword search patterns (\"iron|ferr|heme\") in the descriptive columns of the proteome data ('GO Cellular Component', 'GO Molecular Function', 'GO Biological Process'). Results were visualized through volcano plots for all underlying pathways and per individual pathway."],"omics_type":["Proteomics"],"labhead":["Hans Zischka"],"instrument_platform":[""],"submission_type":["PARTIAL"],"labhead_affiliation":["Institute of Toxicology and Environmental Hygiene, TUM School of Medicine and Health, Technical University of Munich; Munich, Germany"],"species":["Homo Sapiens (human)"],"submitter_mail":["vontoerne@helmholtz-muenchen.de"],"publication":["42763343 Sailer J, Gottal J, Kaub L, Jauch AT, Engler J, Eberhagen C, von Toerne C, Hansen-Palmus L, Wachinger V, Akdogan B, Engelhardt S, Knolle P, DiSpirito AA, Protzer U, Vujić Spasić M, Zischka H. Cuproptosis in iron overload hepatocytes. Cell Death Dis. 2026 17(1):816 10.1038/s41419-026-09275-y"],"submitter_affiliation":["Helmholtz Zentrum München"],"submitter_country":["Germany"],"pubmed_abstract":["A long-standing clinical conundrum is the pronounced phenotypic heterogeneity of hereditary hemochromatosis. Patients with identical HFE genotypes and similar degrees of iron overload can have vastly different clinical outcomes, ranging from being completely asymptomatic to developing severe cirrhosis, diabetes, or cardiomyopathy. This variability strongly implies the existence of genetic or environmental modifiers that dictate disease penetrance. Here, copper may be a compelling disease-modifying candidate, due to its intimately intertwined metabolism with iron. Indeed, profound iron loading in hemochromatosis mice (Hfe knockout) and hemochromatosis Huh7 hepatocytes does not cause overt toxicity. However, the addition of copper, even in trace amounts and harmless on its own, dramatically amplifies adverse effects to induce profound cell toxicity. We find that copper-provoked iron vulnerability is not driven by Fenton chemistry-driven ROS damage, but instead induces a cuproptotic-like mechanism, characterized by proteotoxic stress, loss of iron-sulfur cluster enzyme activity, and severe mitochondrial dysfunction. Remarkably, high-affinity copper chelation rescued Huh7 cells, whereas inhibition of other canonical cell death pathways did not. These findings spotlight copper as a critical modifier in iron overload toxicity, capable of converting largely compensated iron overload into severe cellular injury and death, thereby providing a mechanistic explanation for the phenotypic heterogeneity in hemochromatosis."],"pubmed_title":["Cuproptosis in iron overload hepatocytes."],"pubmed_authors":["Sailer Judith J, Gottal Jonas J, Kaub Leon L, Jauch Adrian T AT, Engler Jonas J, Eberhagen Carola C, von Toerne Christine C, Hansen-Palmus Lea L, Wachinger Valerie V, Akdogan Banu B, Engelhardt Stefan S, Knolle Percy P, DiSpirito Alan A AA, Protzer Ulrike U, Vujić Spasić Maja M, Zischka Hans H"],"additional_accession":[]},"is_claimable":false,"name":"Iron Toxicity targeting mitochondrial Iron-Sulfur cluster enzymes","description":"Unregulated nutritional iron absorption in hereditary hemochromatosis causes its overload, especially in liver. While this may lead to severe pathology, intriguingly, it may also frequently go unrecognized. Indeed, profound iron loading in hemochromatosis Hfe knockout mice and hemochromatosis Huh7 hepatocytes trigger cellular responses—especially affecting iron storage and release—that plausibly prevent overt iron toxicity. Nevertheless, excess iron caused mild bioenergetic alterations concerning mitochondrial function. Importantly, the addition of copper, even in trace amounts and harmless on their own, dramatically increases this adverse effect to induce profound cell toxicity. We find that this copper-provoked iron vulnerability is independent of Fenton-chemistry ROS-mediated damage but rather driven by proteotoxic stress with a profound loss of iron-sulfur cluster enzyme activity and severe mitochondrial dysfunction. Remarkably, high affinity copper chelation rescued cells, while inhibition of canonical cell death pathways did not. These findings spotlight copper as a critical factor capable of converting compensated iron overload into severe cellular injury. Monitoring and managing copper status could be essential in patients suffering from hepatic iron 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