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Small"],"technology_type":["Mass Spectrometry","Bottom-up proteomics","Data-independent acquisition"],"software":[""],"submitter_keywords":[""],"full_dataset_link":["https://www.ebi.ac.uk/pride/archive/projects/PXD073093"],"tissue":["Seminal Vesicle Fluid"],"sample_protocol":["Proteomics 1ml of 4% sodium deoxycholate (SDC), 100mM Tris-HCL buffer (pH = 8) and a stainless-steel bead were added to frozen whole SVF samples. Tissues were boiled for 10 min at 95 °C at 1000 rpm in a ThermoMixer (Eppendorf) and homogenised by steel bead disruption for 2 minutes in a bead mill (Retsch). Samples were then boiled for another 10 minutes at 95 °C and 1000 rpm in a ThermoMixer and then centrifuged (Eppendorf) for 10 min at 20,000 g to clarify. The supernatant was then transferred to a new 1.5 ml Eppendorf and stored at -80 °C until used for protein quantification.  Samples were defrosted at room temperature, and we performed a bicinchoninic protein assay (BCA) (Sigma-Adrich) to quantify total protein per sample. Based on the BCA, a total of 30 µg of protein in 40 µL of 4% SDC buffer was added to each well of a 1000 µL 96 deep-well plate.  Proteins were reduced and alkylated by adding TCEP (Thermo Fisher) and 2-chloroacetamide (Sigma-Adrich) with a final concentration of 10 mM and 40 mM respectively. Plates were vortexed for 10 minutes at 95 °C at 1000 rpm. The SDC buffer was diluted to 1% by adding 140 µL of MS-grade water. Samples were cooled to 37 °C and Trypsin (Sigma-Adrich) and LysC (Novachem) were added in a 1:50 protease: protein concentration. Samples were then left to digest at 37 °C at 1000 rpm for 16 hours in a ThermoMixer.   Digested peptides were diluted 1:1 with 99% ethyl-acetate and 1% trifluoracetic acid (TFA) and centrifuged for 1 minute at 2000 g. 100 µl of the bottom phase was then added to 200 µl equilibrated StageTips with punched SDB-RPS discs and mounted into a 3D-printed holder with a polypropylene waste plate. StageTips were washed twice with 100 µL of 99% ethyl-acetate and 1% TFA, then once with 100 µL of 0.2% TFA. StageTips in the 3D-printed holder were then mounted onto a clean 96-well non-skirted PCR plate (Thermo Fisher Scientific) and 100 µL of 1.25% ammonium hydroxide and 80% acetonitrile was added. Peptides were then dried in a vacuum concentrator (Genevac) set at a maximum temperature of 45 °C and NH3-H2O mode for 2 hours. Peptides were resuspended in 80 µL of 5% formic acid and stored at 5 °C overnight. Peptides were then transferred to 96-well V-bottom plate (Greiner) and covered with a clear silicone micromat (Thermo Fisher scientific) and stored at 4 °C until used for mass spectrometry.   Mass spectrometry: For each sample, ~500 1 µng of peptide in 1 µL was injected from the 96 well plate on a Neo Vanquish 4 UHPLC system (Thermo Fisher Scientific) interfaced with an Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific). Peptides were subjected to liquid chromatography-tandem mass spectrometry using an in-house fabricated 25 cm column (150 μM ID), packed with 1.9 μM C18 ReproSil Pur AQ particles (Dr. Maisch HPLC GmbH, Ammerbuch, DEU), Column temperature was maintained at 60 ◦C with a Sonation column oven. Peptides were separated over a 52.5 min method using a binary buffer system comprising 0.1% formic acid (buffer A) and 80% ACN plus 0.1% formic (buffer B), at a flow rate of 1.2 µl/min, with a gradient of 5-35% buffer B over 48 min, followed by 35–60% buffer B over 1 min, 60–98% buffer B over 0.5 min and a column wash of 98% buffer B held over 3 min. Peptides were analysed with one full scan (350–1650 m/z, R = 30,000, followed by 20 data-independent acquisition (DIA) MS/MS scans spanning 350–1650 m/z at a resolution of 30,000 fragments in the Orbitrap and a collision energy of 25%."],"repository":["Pride"],"quantification_method":[""],"modification":[""],"data_protocol":["Raw data were processed using DIA-NN (version 1.9.2) (PMID: 31768060) with an in silico generated spectral library, standard settings with ‘‘QuantUMS high accuracy’’ and ‘‘MBR’’ activated. Peptides were searched against a reference mouse proteome (UP000000589) downloaded from www.uniprot.org on 08/07/2024. The resulting unique_genes_matrix file was read into R. All further analyses were conducted in the R environment (version 4.3.3) using RStudio (version 2023.12.1 + 402)."],"omics_type":["Proteomics"],"labhead":["Lewin Small"],"instrument_platform":[""],"labhead_affiliation":["Charles Perkins Centre, School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW, 2006, Australia."],"submission_type":["PARTIAL"],"species":["Mus Musculus (mouse)"],"publication":["42336377 Macartney EL, Senior AM, Small L, Crean AJ, Pini T, Pulpitel TJ, Nobrega MA, Barrès R, Simpson SJ. Paternal dietary macronutrients affect the seminal vesicle fluid proteome and fetal development: a geometric framework for nutrition study in mice. Proc Biol Sci. 2026 293(2073):20260535 10.1098/rspb.2026.0535"],"submitter_mail":["lewin.small@sydney.edu.au"],"submitter_affiliation":["University of Sydney"],"submitter_country":["Australia"],"pubmed_abstract":["Seminal plasma can have wide-ranging effects on reproductive fitness-from affecting sperm fertilization capacity and female reproductive physiology to influencing offspring viability and health. Seminal plasma can also change in response to environmental conditions including diet, which of itself is known to affect reproductive traits and fitness outcomes. However, an understanding of how paternal diet alters seminal plasma composition and how these effects relate to fetal development remains elusive. Here, we applied the geometric framework for nutrition to systematically manipulate dietary macronutrient balance in male mice and determine dietary effects on the seminal vesicle fluid (SVF; comprising much of the seminal plasma) proteome, as well as relate differences in the proteome to aspects of fetal development. We (i) identified the largest number of proteins in the mouse SVF proteome to date, (ii) determined a set of proteins that were significantly affected by dietary macronutrients, (iii) showed that differences in a protein related to lipid mobilization and metabolism (APOA4) were correlated with fetal development, and (iv) detected dietary effects on aspects of fetal development that were unrelated to SVF protein abundance. This study provides a comprehensive characterization of the male SVF proteome across nutritional space and highlights potential functional ways in which male diet and the seminal plasma may mediate fitness."],"pubmed_title":["Paternal dietary macronutrients affect the seminal vesicle fluid proteome and fetal development: a geometric framework for nutrition study in mice."],"pubmed_authors":["Macartney Erin L EL, Senior Alistair M AM, Small Lewin L, Crean Angela J AJ, Pini Taylor T, Pulpitel Tamara J TJ, Nobrega Marcelo A MA, Barrès Romain R, Simpson Stephen J SJ"],"additional_accession":[]},"is_claimable":false,"name":"Paternal dietary macronutrients affect the seminal vesicle fluid proteome and foetal development","description":"Seminal fluid can have wide-ranging effects on reproductive fitness – from affecting sperm fertilisation capacity and female reproductive physiology, to influencing offspring viability and health. Seminal fluid can also change in response to environmental conditions including diet, which of itself is known to affect reproductive traits and fitness outcomes. However, an understanding of how paternal diet alters seminal fluid composition and how these effects relate to foetal development remains elusive. Here, we applied the Geometric Framework for Nutrition to systematically manipulate dietary macronutrient balance in male mice and determine dietary effects on the seminal vesicle fluid (SVF) proteome and related differences to aspects of foetal development in offspring sired by these males. We 1) identify and determine the largest number of proteins in the mouse SVF proteome to date, 2) identify a set of proteins that are significantly affected by dietary macronutrient balance, 3) show that differences in a protein related to lipid mobilisation and metabolism (APOA4) are correlated with foetal development, and 4) detect dietary effects on aspects of foetal development that were unrelated to SVF protein abundance. This study provides a comprehensive characterisation of the male SVF proteome across nutritional space and highlights potential functional ways in which male diet and the seminal fluid may mediate fitness.","dates":{"publication":"2026-07-23","submission":"2026-01-15"},"accession":"PXD073093","cross_references":{"TAXONOMY":["NEWT:1773","NEWT:6945","NEWT:3555","NEWT:38783","NEWT:8727","NEWT:1182590","NEWT:8726","NEWT:2","NEWT:157546","NEWT:10090","NEWT:935293","NEWT:749200","NEWT:35554","NEWT:4120","NEWT:5693","NEWT:9417","NEWT:347515","NEWT:8724","NEWT:1216979","NEWT:307972","NEWT:92867","NEWT:8723","NEWT:990346","NEWT:544496","NEWT:5334","NEWT:145953","NEWT:257309","NEWT:5180","NEWT:284812","NEWT:115104","NCBITaxon:1313","NEWT:1081927","NEWT:43330","NEWT:67825","NEWT:44544","NEWT:13076","NEWT:1249668","NEWT:373995","NEWT:544404","NEWT:3702","NEWT:8839","NEWT:376741","NEWT:317","NEWT:4232","NEWT:990119","NEWT:1736309","NEWT:4113","NEWT:7227","NEWT:11298","NEWT:7469","NEWT:885318","NEWT:171101","NEWT:876138","NEWT:4081","NEWT:554","NEWT:5691","NEWT:98334","NEWT:408170","NEWT:260710","NEWT:3708","NEWT:106592","NEWT:237561","NEWT:9913","NEWT:10036","NEWT:4100","NEWT:7574","NEWT:1351","NEWT:1076","NEWT:6763","NEWT:7215","NEWT:803","NEWT:8030","NEWT:380394","NEWT:272563","NEWT:507601","NEWT:1639","NEWT:188229","NEWT:4909","NCBITaxon:79857","NEWT:95648","NEWT:746360","NEWT:6239","NEWT:1589","NEWT:135588","NEWT:135622","NEWT:216257","NEWT:6915","NEWT:9986","NEWT:101510","NEWT:95486","NEWT:3880","NEWT:58002","NEWT:9103","NEWT:4577","NEWT:5664","NEWT:2157","NEWT:146479","NEWT:1911079","NEWT:1000589","NEWT:145943","NEWT:1902","NEWT:85962","NEWT:160488","NEWT:317447","NEWT:3635","NEWT:7955","NCBITaxon:2","NEWT:235443","NEWT:1480154","NEWT:985076","NEWT:7959","NEWT:2261","NEWT:3197","NEWT:9615","NEWT:884019","NEWT:4565","NEWT:1264690","NEWT:169963","NCBITaxon:38727","NEWT:36329","NEWT:34305","NEWT:59729","NCBITaxon:183674","NEWT:224308","NEWT:626528","NEWT:139927","NEWT:4558","NEWT:9606","NEWT:367830","NEWT:157295","NEWT:243230","NEWT:931281","NEWT:373153","NEWT:7029","NEWT:1283300","NEWT:334747","NEWT:470","NCBITaxon:79824","NCBITaxon:4563","NEWT:3218","NEWT:5759","NEWT:9838","NCBITaxon:9615","NEWT:1736231","NEWT:1193501","NEWT:3055","NEWT:6287","NEWT:2242","NEWT:6326","NEWT:9796","NEWT:2762","NEWT:5476","NEWT:1174673","NEWT:562","NEWT:260707","NEWT:287","NEWT:10117","NEWT:10239","NEWT:10116","NEWT:1280","NEWT:1836","NEWT:1735272","NEWT:29760","NEWT:260705","NEWT:80863","NEWT:1148","NEWT:4932","NEWT:70448","NEWT:9825","NEWT:3603","NEWT:698936","NEWT:2759","NEWT:39946","NEWT:11676","NEWT:9823","NEWT:100226","NCBITaxon:6073","NEWT:4530","NEWT:4896","NEWT:6279","NEWT:7370","NEWT:573","NEWT:6282","NEWT:7091","NEWT:1134506"],"pubmed":["42336377"],"ORCID":["0000-0002-9767-9464"]}}