{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Derks J"],"funding":["U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences","Cancer Research UK","European Research Council","Versus Arthritis","The Francis Crick Institute","NCI NIH HHS","Allen Foundation","Wellcome Trust","NIGMS NIH HHS"],"pagination":["50-59"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9839897"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["41(1)"],"pubmed_abstract":["Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completen"],"journal":["Nature biotechnology"],"pubmed_title":["Increasing the throughput of sensitive proteomics by plexDIA."],"pmcid":["PMC9839897"],"funding_grant_id":["1DP2GM123497","UG3 CA268117","DP2 GM123497","200829/Z/16/Z","FC001134","10134","Allen Distinguished Investigator award","951475"],"pubmed_authors":["Leduc A","Demichev V","Huffman RG","Willetts M","Specht H","Slavov N","Derks J","Wallmann G","Ralser M","Khan S"],"additional_accession":[]},"is_claimable":false,"name":"Increasing the throughput of sensitive proteomics by plexDIA.","description":"Current mass spectrometry methods enable high-throughput proteomics of large sample amounts, but proteomics of low sample amounts remains limited in depth and throughput. To increase the throughput of sensitive proteomics, we developed an experimental and computational framework, called plexDIA, for simultaneously multiplexing the analysis of peptides and samples. Multiplexed analysis with plexDIA increases throughput multiplicatively with the number of labels without reducing proteome coverage or quantitative accuracy. By using three-plex non-isobaric mass tags, plexDIA enables quantification of threefold more protein ratios among nanogram-level samples. Using 1-hour active gradients, plexDIA quantified ~8,000 proteins in each sample of labeled three-plex sets and increased data completen","dates":{"release":"2023-01-01T00:00:00Z","publication":"2023 Jan","modification":"2025-04-21T15:08:49.796Z","creation":"2025-04-21T15:08:49.796Z"},"accession":"S-EPMC9839897","cross_references":{"pubmed":["35835881"],"doi":["10.1038/s41587-022-01389-w"]}}