Characterizing mouse platelet heterogeneity across diverse disease models using spectral flow cytometry and...

Area of Science:

• Hematology
• Immunology
• Preclinical Research

Background:

• Standard platelet assessments overlook critical heterogeneity in platelet subpopulations.
• Platelet subtypes are linked to various diseases, necessitating detailed characterization.
• Mouse models are crucial for preclinical research, but analyzing platelet heterogeneity is challenging.

Purpose of the Study:

• Develop and validate a mouse-specific spectral flow cytometry panel.
• Integrate this panel with a high-dimensional analysis pipeline.
• Characterize platelet subpopulations and activation states in physiological and pathological conditions.

Main Methods:

• Optimized a 12-marker spectral flow cytometry panel.
• Integrated the panel with the PlateletProfiler pipeline for multidimensional analysis.
• Applied the workflow to agonist-induced activation and mouse models of inflammation, myeloproliferative neoplasms, and breast cancer.

Main Results:

• Identified four major platelet subpopulations: resting, primed, aggregatory, and procoagulant.
• Observed distinct changes in platelet subsets across different disease models.
• Noted upregulation of activation and procoagulant markers, and increased reticulated platelets in disease models.

Conclusions:

• The developed workflow provides a robust platform for studying platelet heterogeneity in disease.
• The PlateletProfiler pipeline is adaptable for both mouse and human datasets.
• This research supports broad experimental and translational applications in hematology and immunology.