3D printed hardware for automation of proteomics sample preparation at the Meso-Scale
Mass spectrometry-based proteomics is the dominant method for measuring peptides and proteins from complex mixtures. In bottom-up approaches, proteins are digested or proteolyzed prior to LC-MS/MS analysis. Peptides are fragmented, and proteins are inferred via peptide spectral matching (PSM). The t...
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Elsevier
2025-12-01
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| Series: | Talanta Open |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666831925001079 |
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| author | Sadie R. Schultz Matthew M. Champion |
| author_facet | Sadie R. Schultz Matthew M. Champion |
| author_sort | Sadie R. Schultz |
| collection | DOAJ |
| description | Mass spectrometry-based proteomics is the dominant method for measuring peptides and proteins from complex mixtures. In bottom-up approaches, proteins are digested or proteolyzed prior to LC-MS/MS analysis. Peptides are fragmented, and proteins are inferred via peptide spectral matching (PSM). The throughput of this process is surprisingly low; a proteomics core facility might analyse <20 samples/day per instrument using UHPLC-MS/MS. Because of this, automation in proteomics is rare, and virtually all preparation is performed by hand. We developed 3D printed hardware and automated sample preparation modules for a lower-cost Andrew Alliance pipetting robot. The robot operates on simple principles, using traditional pipettes and follows protocols closely resembling manual preparation. Here, we present modular protocols for the major techniques in proteomics preparation: in-solution and S-Trap digestion; Tip and solid-phase extraction (SPE) based desalting. Both approaches yield dense protein identifications from complex proteomes. Automated samples had high reproducibility: ∼60 % of proteins identified from in-solution and S-Trap digested samples had a measured CV of ≤20 %. In contrast, 52 % of in-solution digested and 63 % of S-Trap digested of proteins identified from manually prepared samples had CVs ≤20 %. Automated sample digestion and tip-based desalting had reduced ≅ 70 % and 40 % quantitative yield respectively compared to manual preparation according to the protein label-free quantification (LFQ). Increasing injection amount to normalize the yield restored protein and peptide identifications which demonstrates the differences between manual and automated methods were predominantly due to reduced recovery. Overall, automation of bottom-up proteomics sample preparation at the meso‑scale offers increased reproducibility in non sample-limited applications. |
| format | Article |
| id | doaj-art-0fccb3e03e2d4f4eb8aa851323d9ae60 |
| institution | OA Journals |
| issn | 2666-8319 |
| language | English |
| publishDate | 2025-12-01 |
| publisher | Elsevier |
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| series | Talanta Open |
| spelling | doaj-art-0fccb3e03e2d4f4eb8aa851323d9ae602025-08-20T02:35:19ZengElsevierTalanta Open2666-83192025-12-011210050510.1016/j.talo.2025.1005053D printed hardware for automation of proteomics sample preparation at the Meso-ScaleSadie R. Schultz0Matthew M. Champion1Department of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556 USA; University of Notre Dame, Notre Dame, IN 46556 USADepartment of Chemistry and Biochemistry, University of Notre Dame, Notre Dame, IN 46556 USA; Berthiaume Institute for Precision Health, University of Notre Dame, Notre Dame, IN 46556 USA; University of Notre Dame, Notre Dame, IN 46556 USA; Corresponding author.Mass spectrometry-based proteomics is the dominant method for measuring peptides and proteins from complex mixtures. In bottom-up approaches, proteins are digested or proteolyzed prior to LC-MS/MS analysis. Peptides are fragmented, and proteins are inferred via peptide spectral matching (PSM). The throughput of this process is surprisingly low; a proteomics core facility might analyse <20 samples/day per instrument using UHPLC-MS/MS. Because of this, automation in proteomics is rare, and virtually all preparation is performed by hand. We developed 3D printed hardware and automated sample preparation modules for a lower-cost Andrew Alliance pipetting robot. The robot operates on simple principles, using traditional pipettes and follows protocols closely resembling manual preparation. Here, we present modular protocols for the major techniques in proteomics preparation: in-solution and S-Trap digestion; Tip and solid-phase extraction (SPE) based desalting. Both approaches yield dense protein identifications from complex proteomes. Automated samples had high reproducibility: ∼60 % of proteins identified from in-solution and S-Trap digested samples had a measured CV of ≤20 %. In contrast, 52 % of in-solution digested and 63 % of S-Trap digested of proteins identified from manually prepared samples had CVs ≤20 %. Automated sample digestion and tip-based desalting had reduced ≅ 70 % and 40 % quantitative yield respectively compared to manual preparation according to the protein label-free quantification (LFQ). Increasing injection amount to normalize the yield restored protein and peptide identifications which demonstrates the differences between manual and automated methods were predominantly due to reduced recovery. Overall, automation of bottom-up proteomics sample preparation at the meso‑scale offers increased reproducibility in non sample-limited applications.http://www.sciencedirect.com/science/article/pii/S2666831925001079AutomationProteomicsMass spectrometryMeso-scaleLiquid-handlingBottom-up |
| spellingShingle | Sadie R. Schultz Matthew M. Champion 3D printed hardware for automation of proteomics sample preparation at the Meso-Scale Talanta Open Automation Proteomics Mass spectrometry Meso-scale Liquid-handling Bottom-up |
| title | 3D printed hardware for automation of proteomics sample preparation at the Meso-Scale |
| title_full | 3D printed hardware for automation of proteomics sample preparation at the Meso-Scale |
| title_fullStr | 3D printed hardware for automation of proteomics sample preparation at the Meso-Scale |
| title_full_unstemmed | 3D printed hardware for automation of proteomics sample preparation at the Meso-Scale |
| title_short | 3D printed hardware for automation of proteomics sample preparation at the Meso-Scale |
| title_sort | 3d printed hardware for automation of proteomics sample preparation at the meso scale |
| topic | Automation Proteomics Mass spectrometry Meso-scale Liquid-handling Bottom-up |
| url | http://www.sciencedirect.com/science/article/pii/S2666831925001079 |
| work_keys_str_mv | AT sadierschultz 3dprintedhardwareforautomationofproteomicssamplepreparationatthemesoscale AT matthewmchampion 3dprintedhardwareforautomationofproteomicssamplepreparationatthemesoscale |