Multi-molecular hyperspectral PRM-SRS microscopy.

Area of Science:

• Biochemistry
• Cell Biology
• Medical Imaging

Background:

• Lipids are vital for biological processes, and understanding their spatial distribution and metabolic dynamics is key to aging and disease research.
• Existing imaging techniques have limitations in preserving native cellular environments, spatial resolution, or distinguishing lipid subtypes.

Purpose of the Study:

• To develop and present a novel hyperspectral imaging platform for high-resolution lipid analysis.
• To overcome the limitations of conventional imaging methods in lipid research.

Main Methods:

• Development of a hyperspectral imaging platform integrating Penalized Reference Matching (PRM) algorithm with Stimulated Raman Scattering (SRS) microscopy (PRM-SRS).
• Application of the PRM-SRS platform to visualize and identify specific lipid subtypes in various biological samples.

Main Results:

• Successful visualization and identification of high-density lipoprotein particles in human kidney.
• Detection of a high cholesterol to phosphatidylethanolamine ratio within mouse hippocampus granule cells.
• Mapping of subcellular distributions for sphingosine and cardiolipin in human brain tissue.

Conclusions:

• The PRM-SRS platform provides enhanced chemical specificity, subcellular resolution, and rapid data processing for lipid subtype analysis.
• This method is effective in distinguishing lipid subtypes across different organs and species, advancing lipid research in biology and medicine.