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However, these approaches often require expensive instrumentation upgrades and robotic automation that remain inaccessible to many research laboratories and core facilities. In this study, we address the feasibility of scaling up proteomic screening capabilities with minimal upgrade cost by focusing on (a) strategies for nonautomated high-throughput sample preparation from 96-well cell culture, (b) data acquisition on sub-50 Hz scan speed hybrid and tribrid Orbitrap instruments, and (c) data analysis strategies for label-free and labeled proteomic screening. We find that the 96-well format STrap, in combination with C18 plates, provides the most robust throughput for a nonautomated sample preparation workflow. Furthermore, we show that for static proteomes, an isobaric tandem mass tag (TMT)-based multiplexing approach provides deeper and more precise proteome coverage, whereas data-independent acquisition (DIA) is more accurate, albeit with a reduced dynamic range and more missing values. Finally, we extend the optimized workflow to proteome turnover studies using pulsed stable isotope labeling by amino acids in cell culture (pSILAC), highlighting the key advantages and trade-offs of DIA and TMT data-dependent acquisition strategies for capturing protein translation.<\/jats:p>","DOI":"10.1021\/acs.jproteome.6c00312","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T22:01:49Z","timestamp":1789509709000},"page":"5255-5266","source":"Crossref","is-referenced-by-count":0,"title":["Evaluation of\nDeep and Dynamic Proteomic Screening\nStrategies at Sub-50 Hz Scan Speed and without Robotic Sample Preparation"],"prefix":"10.1021","volume":"25","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2005-8077","authenticated-orcid":true,"given":"Bhavesh S.","family":"Parmar","sequence":"first","affiliation":[{"name":"Goethe University , , ,","place":["Frankfurt am Main, Germany, 60528"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanyuan","family":"Liu","sequence":"additional","affiliation":[{"name":"Goethe University , , ,","place":["Frankfurt am Main, Germany, 60528"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Parviz","family":"Ghezellou","sequence":"additional","affiliation":[{"name":"Goethe University , , ,","place":["Frankfurt am Main, Germany, 60528"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Mu\u0308nch","sequence":"additional","affiliation":[{"name":"Goethe University , , ,","place":["Frankfurt am Main, Germany, 60528"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,9,15]]},"reference":[{"key":"2026100208420150200_cit1","doi-asserted-by":"publisher","first-page":"100877","DOI":"10.1016\/j.mcpro.2024.100877","article-title":"Bridging the Gap From Proteomics Technology to Clinical Application:\nHighlights From the 68th Benzon Foundation Symposium","volume":"23","author":"Albrecht","year":"2024","journal-title":"Mol. 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Proteome\nRes."},{"key":"2026100208420150200_cit5","doi-asserted-by":"publisher","first-page":"MSB199111","DOI":"10.15252\/msb.20199111","article-title":"Automated sample preparation with SP3 for low-input\nclinical proteomics","volume":"16","author":"Mu\u0308ller","year":"2020","journal-title":"Mol. Syst. Biol."},{"key":"2026100208420150200_cit6","doi-asserted-by":"publisher","first-page":"2833","DOI":"10.1039\/D3SC05937E","article-title":"High-throughput drug target discovery using a fully automated proteomics\nsample preparation platform","volume":"15","author":"Wu","year":"2024","journal-title":"Chem. Sci."},{"key":"2026100208420150200_cit7","doi-asserted-by":"publisher","first-page":"100790","DOI":"10.1016\/j.mcpro.2024.100790","article-title":"Fully Automated\nWorkflow for Integrated Sample Digestion and Evotip Loading Enabling\nHigh-Throughput Clinical Proteomics","volume":"23","author":"Kverneland","year":"2024","journal-title":"Mol. 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