METABOLOMIC PROFILING OF OSTEOBLAST EXTRACELLULAR VESICLES AND MATRIX BOUND VESICLES USING A PROTOTYPE BENCHTOP MULTI REFLECTING TIME-OF-FLIGHT (MRT) MASS SPECTROMETER

Importance of the Topic

Extracellular vesicles (EVs) and matrix-bound vesicles (MBVs) are fundamental mediators of intercellular communication and early bone mineralization. EVs circulate through extracellular fluids, while MBVs integrate with the collagenous matrix to drive hydroxyapatite deposition. Understanding their distinct metabolite cargo supports advances in bone biology, disease biomarker discovery, and therapeutic design.

Objective and Overview

This study aims to generate a comparative metabolomic profile for EVs and MBVs derived from MC3T3 pre-osteoblasts under osteogenic conditions using a prototype benchtop Multi Reflecting Time-of-Flight (MRT) mass spectrometer coupled to an ACQUITY Premier LC system. The goal is to identify differential small molecule signatures informing vesicle function in bone formation.

Methodology

• Sample Preparation: MC3T3 cells cultured with osteogenic supplements. EVs isolated by differential ultracentrifugation. MBVs released from the extracellular matrix via collagenase digestion followed by ultracentrifugation. Vesicles lysed by sonication without additional lysis buffer.
• Extraction: Water : MeOH : MTBE partitioning. Aqueous fraction analyzed by LC-MS.
• Chromatography: Dual mode separation using HILIC with BEH Amide column and reversed-phase with HSS T3 column. Injection volume 1 µL, column temperature 50 °C, flow rates 0.25 and 0.4 mL/min.
• Mass Spectrometry: Waters Xevo MRT MS operated in both positive and negative electrospray modes. Data independent acquisition over m/z 50–1200 Da at 10 Hz. Collision energy ramp 25–45 V. Mass resolution up to 100 000 FWHM and sub-ppm accuracy.
• Data Analysis: MARS platform for unsupervised PCA, volcano plots, and putative identification using human metabolome database searches.

Main Results and Discussion

• PCA analysis demonstrated clear separation between EV and MBV metabolite profiles in both HILIC and reversed-phase data sets.
• Volcano plot analysis revealed numerous statistically significant features, with approximately 80 percent of differentiating metabolites upregulated in EVs.
• Fatty acyls, glycerophospholipids, and glycerolipids dominated the differential profile. Notably 3-beta galactopyranosyl glucose exhibited a 50-fold higher abundance in EVs, implicating membrane stabilizing functions.
• Phospholipids such as palmitoylphosphatidylcholine showed fivefold enrichment in EVs, suggesting roles in mineralization processes.
• High resolution mass spectra (circa 70 000 FWHM) enabled confident isotope pattern matching and reduced false identifications.

Benefits and Practical Applications

This approach highlights the utility of benchtop MRT MS for routine metabolomic profiling of vesicles. Enhanced mass resolution and accuracy translate to increased compound coverage and reliable putative assignments. The method can be applied in bone research, biomarker discovery, and quality control of vesicle-based therapeutics.

Future Trends and Application Possibilities

• Expansion to targeted quantitative assays for key lipid mediators in osteogenesis.
• Integration with proteomic and lipidomic platforms for multi-omic vesicle characterization.
• In vivo tracking of vesicle metabolite changes in disease models.
• Development of standardized workflows for extracellular vesicle metabolomics in clinical laboratories.

Conclusion

Comparative metabolomic profiling of EVs and MBVs using a prototype benchtop MRT mass spectrometer revealed distinct lipid and small molecule signatures relevant to bone mineralization. The high resolving power and mass accuracy of the instrument facilitated confident identification of differential metabolites, supporting its potential for diverse OMIC applications.

Pouzitá instrumentace

• Waters ACQUITY Premier LC System
• Waters Xevo MRT Mass Spectrometer

References

1. Al Halawani A et al Int J Mol Sci 2022;23 3389
2. Boyan BD et al Cells 2022;11 1619
3. Davies OG Mol Ther 2023;31 1251
4. Mebarek S et al Biomolecules 2024;14 42