Recent advances in mass spectrometry have boosted both analytical speed and sensitivity, allowing for deeper proteome coverage and larger experimental cohorts. However, traditional nano-flow direct injection UHPLC workflows are still hindered by long sample loading times, which limit throughput and instrument use. Adding trap columns to UHPLC workflows is an effective way to solve these challenges, enabling fast, high-pressure loading at higher flow rates without sacrificing analytical quality.
We developed a range of UHPLC workflows that integrate a novel trap-column design to minimise sample-loading overhead while maximising the time dedicated to chromatographic separation. In addition to improved throughput, these trap-based methods extend the longevity of analytical columns, reduce maintenance frequency, and deliver scalable solutions suitable for next-generation, high-throughput proteomic studies.
Trap performance was systematically evaluated in a trap-and-elute setup with IonOpticks Aurora analytical columns, supporting up to 200 samples per day. Trap performance was compared to direct injection workflows to evaluate chromatographic and quantitative characteristics under high-throughput conditions. HeLa digests were used as the sample matrix and loaded under controlled flow and solvent conditions. Data acquisition was performed using nano-flow UHPLC systems coupled to high-resolution mass spectrometers from Bruker and Thermo Fisher Scientific.
Trap column workflows delivered excellent chromatographic performance, with less than 5% variation in peptide identifications relative to direct injection. Consistent retention-time stability and peptide identifications across replicates demonstrated the robustness and reproducibility of the high-throughput workflows.
By greatly reducing sample loading times while maintaining depth of coverage, these advances enhance high-throughput proteomics, enabling faster large-scale analyses and supporting more comprehensive, time-efficient biological discovery.