Facilitating MALDI Imaging Sample Preparation: A High-Resolution, Reproducible, and User-Friendly Sublimation Device

Significance of the Topic

The spatially resolved molecular analysis enabled by MALDI Imaging depends critically on reproducible matrix deposition. Traditional solvent-based spraying methods often involve compromises between sensitivity and lateral resolution, while homemade sublimation setups lack standardization. By automating sublimation and introducing an optional recrystallization step, this work addresses a key bottleneck in high-resolution, quantitative imaging workflows.

Objectives and Study Overview

This study presents the design, implementation, and multi-site validation of an automated sublimation and recrystallization device for MALDI Imaging sample preparation. Key aims included:

• Ensuring uniform matrix coatings for DHAP, DHB, CHCA, and NEDC.
• Evaluating reproducibility across three identical devices, three laboratories, multiple tissue types, and different users.
• Comparing sensitivity and spatial fidelity of sublimation, sublimation with recrystallization, and spraying protocols.
• Demonstrating high lateral resolution imaging down to 1.5–5 µm pixel sizes.

Methodology and Instrumentation

Experimental Design:

• Matrices: 5 mg DHAP, DHB, CHCA; NEDC for metabolite imaging.
• Substrates: IntelliSlides with rat testis, brain, kidney tissues and Vero B4 cell cultures.
• Replicates: 3 runs × 3 slides × 3 matrices across 3 sites.
• Analysis: Gravimetric matrix transfer, pixel-intensity histograms, k-means clustering of imaging data.

Automated Sublimation Parameters:

• Heating zones: 90–160 °C; cooling at 10 °C; exposure times 60–300 s.
• Recrystallization: 50 °C for 10 s under controlled humidity.

Instrumentation

• Automated sublimation and recrystallization device (proprietary design).
• timsTOF fleX MALDI-2 platform; prototype transmission-mode MALDI for subcellular imaging.
• Optical scanning for homogeneity assessment; mass spectrometers from multiple vendors across labs.

Key Results and Discussion

Coating Reproducibility and Homogeneity:

• Consistent matrix transfer efficiency of 75±5 % for three matrices.
• Narrow pixel-intensity distributions indicating uniform deposition.
• DHAP produced the most homogeneous coating (width 8±2 intensity units).

Inter-Laboratory Consistency:

• Rat testis imaging at 10 µm pixel size yielded comparable data across three sites.
• Clustering analysis grouped spectra by tissue morphology, not by site or instrument.

Sensitivity and Spatial Fidelity:

• Sublimation alone improved resolution but had lower signal intensity.
• Adding recrystallization outperformed spraying in sensitivity while preserving sub-100 µm localization of lipids (e.g., PC(34:1), HexCer).
• Spraying often led to analyte delocalization, particularly for membrane lipids.

Lateral Resolution Enhancement:

• High-resolution imaging achieved at 5 µm for brain lipids and single cells; 1.5 µm for kidney metabolites.
• Single-cell and subcellular features, including nuclei, visualized without artifacts.

Practical Benefits and Applications

• Standardized sample preparation across laboratories reduces variability in QA/QC and research settings.
• Artifact-free coatings allow reliable detection of low-abundance analytes.
• High lateral resolution extends MALDI Imaging to single-cell and subcellular studies.
• Adaptable to multiple matrix chemistries and tissue types for diverse workflows.

Future Trends and Opportunities

• Integration with automated high-throughput workflows and laboratory information management systems.
• Development of novel matrices and coating chemistries for targeted small molecules and peptides.
• Miniaturized sublimation modules for benchtop or clinical use.
• Multimodal imaging combining MALDI with optical or ion microscopy and AI-driven data analysis for spatial multiomics.

Conclusion

The automated sublimation and recrystallization device delivers reproducible, homogeneous matrix coatings for multiple MALDI matrices, enabling high-quality imaging down to single-cell resolution. Cross-lab validation confirms its robustness, offering a reliable tool for advanced spatial analysis in both research and applied settings.