Laser microdissection (LMD) combined with high-resolution mass spectrometry (MS) has become a powerful approach for analyzing targeted regions of fixed tissues, enabling detailed investigation of their heterogeneity. Here, we present two protocols optimized for low-input samples: a solid-phase enhanced preparation method (SP3) and a detergent/organic solvent-based approach (DDM/ACN). Both workflows are designed to minimize sample loss and are suitable for manual processing when automation platforms are not available. We provide practical guidance to reduce input requirements down to 1500 μm2 of 10 μm thick FFPE tissue while maintaining reproducibility and proteome depth. These protocols, when coupled with fast instruments such as the Orbitrap Astral mass spectrometer working in DIA acquisition mode, enable sensitive, high-resolution proteomic analysis of microdissected tissue regions. Together, they establish a robust approach for investigating spatial heterogeneity in clinical samples with high coverage and precision.

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Low-Input Proteomics Protocols for Laser-Captured FFPE Samples with Orbitrap Astral DIA-MS

  • Daniele Musiani,
  • Alessandro Cuomo

摘要

Laser microdissection (LMD) combined with high-resolution mass spectrometry (MS) has become a powerful approach for analyzing targeted regions of fixed tissues, enabling detailed investigation of their heterogeneity. Here, we present two protocols optimized for low-input samples: a solid-phase enhanced preparation method (SP3) and a detergent/organic solvent-based approach (DDM/ACN). Both workflows are designed to minimize sample loss and are suitable for manual processing when automation platforms are not available. We provide practical guidance to reduce input requirements down to 1500 μm2 of 10 μm thick FFPE tissue while maintaining reproducibility and proteome depth. These protocols, when coupled with fast instruments such as the Orbitrap Astral mass spectrometer working in DIA acquisition mode, enable sensitive, high-resolution proteomic analysis of microdissected tissue regions. Together, they establish a robust approach for investigating spatial heterogeneity in clinical samples with high coverage and precision.