Levitating Cells to Sort the Fit and the Fat

Area of Science:

• Biomedical Engineering
• Cell Biology
• Biophysics

Background:

• Cell density is a critical property influenced by lipid content, impacting biomedical applications like precision medicine.
• Current methods struggle to sort cells of the same type based on subtle density variations.
• Lipid accumulation in cardiomyocytes is linked to diseases like neutral lipid storage disease (NLSD).

Purpose of the Study:

• To develop a real-time method for sorting single cells based on density differences.
• To investigate lipid heterogeneity in human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from patients with NLSD.
• To demonstrate the capability of levitation-based sorting for isolating diseased and healthy cardiac cells.

Main Methods:

• A levitation-based strategy was employed to monitor and sort single cells in real time.
• Human-induced pluripotent stem cell-derived cardiomyocytes from NLSD patients were used as a model system.
• Pixel-tracking technology was utilized to analyze cell contraction differences.

Main Results:

• The levitation strategy successfully detected subpopulations of ATGL-deficient hiPSC-CMs with varying lipid content and density.
• Differential levitation heights allowed for real-time monitoring and sorting of these subpopulations.
• Sorted hiPSC-CMs retained viability and function, with distinct contraction patterns observed between healthy and NLSD cells.

Conclusions:

• This levitation-based approach enables the separation of diseased cell populations based on intracellular lipid content, overcoming limitations of traditional flow cytometry.
• The technique provides a unique tool for analyzing and isolating cells with heterogeneous lipid profiles.
• This method holds promise for advancing precision medicine and regenerative therapies by enabling precise cell sorting.