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Updated: Feb 4, 2026

Laser Microdissection-Based Protocol for the LC-MS/MS Analysis of the Proteomic Profile of Neuromelanin Granules
Published on: December 16, 2021
Low-Input Proteomics Protocols for Laser-Captured FFPE Samples with Orbitrap Astral DIA-MS.
Daniele Musiani1, Alessandro Cuomo2
1European Institute of Oncology (IEO), Mass Spectrometry Unit (MSU), Milan, Italy.
Two new protocols for laser microdissection (LMD) and mass spectrometry (MS) enable sensitive proteomic analysis of tiny tissue samples. These methods minimize sample loss for detailed investigation of tissue heterogeneity in clinical samples.
Area of Science:
- Proteomics
- Molecular Biology
- Biochemistry
Background:
- Laser microdissection (LMD) coupled with mass spectrometry (MS) is vital for analyzing tissue heterogeneity.
- Analyzing low-input tissue samples presents significant challenges in proteomic studies.
- Existing protocols may not be optimized for minimal sample loss or manual processing.
Purpose of the Study:
- To present two optimized protocols for low-input sample preparation for LMD-MS analysis.
- To enable sensitive, high-resolution proteomic analysis of microdissected tissue regions.
- To provide guidance for reproducible proteomic profiling of clinical samples.
Main Methods:
- Development and optimization of two low-input sample preparation workflows: Solid-Phase Enhanced Preparation (SP3) and Detergent/Organic Solvent (DDM/ACN).
- Application of protocols to small tissue areas (down to 1500 μm² of 10 μm thick FFPE tissue).
- Integration with high-resolution mass spectrometry (Orbitrap Astral) using Data-Independent Acquisition (DIA).
Main Results:
- Protocols minimize sample loss, enabling analysis of very small tissue regions.
- Achieved reproducible proteomic profiling with substantial proteome depth from low-input samples.
- Demonstrated sensitive and high-resolution proteomic analysis of microdissected FFPE tissue.
Conclusions:
- The developed SP3 and DDM/ACN protocols offer robust solutions for low-input LMD-MS.
- These methods facilitate the investigation of spatial heterogeneity in clinical samples with high precision.
- The protocols are suitable for manual processing, increasing accessibility for researchers without automation platforms.
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