Luke Gamon (@lgamon.bsky.social)

Nice work but please if you’re going to try LCM with the PalmRobo just capture + process directly in a PCR cap either open in a humid chamber or with them placed on top of a 96-well PCR plate. Then acidify + spin into evotips or homemade stagetips. pubs.acs.org/doi/10.1021/...

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MR-SP2: A Microreactor-Based Workflow for Few-Cell Spatial Proteomics on the Legacy Zeiss PALM MicroBeam Laser capture microdissection (LCM) combined with liquid chromatography–tandem mass spectrometry (LC-MS/MS) enables spatial proteomics at the few-cell level but is constrained by cumulative losses during specimen capture, surface adsorption during processing, and sample transfer prior to LC-MS/MS analysis. The capture-associated losses are particularly relevant for pressure catapulting systems such as the legacy Zeiss PALM MicroBeam, which, despite discontinuation, remains in active use and therefore requires compatible low-loss workflows. We present MR-SP2 (microreactor-based sample preparation for spatial proteomics), a one-pot workflow integrating reproducible Zeiss LCM-cut specimen capture, processing with minimized adsorptive losses, and pipetting-free transfer with Evotip disposable precolumns. The workflow was evaluated using a formalin-fixed paraffin-embedded (FFPE) murine kidney tissue analyzed by timsTOF flex LC-MS/MS analysis. Across 50,000 μm3 regions (22 cells), MR-SP2 modestly improved proteome depth (3381 ± 80 versus 3174 ± 59 proteins). Decreasing sample input further accentuated the advantage of MR-SP2 in maintaining higher identification rates, highlighting the successful reduction of the adsorptive losses. At 12,500 μm3 (5–6 cells), identifications increased to 1145 ± 188 versus 302 ± 126. At 3125 μm3 (1–2 cells), identifications reached 695 ± 112 versus 206 ± 51. MR-SP2 improves identification depth for few-cell FFPE samples by nearly 3-fold compared to conventional tube-based workflows. https://pubs.acs.org/doi/10.1021/acs.jproteome.5c01231