Levitating Cells to Sort the Fit and the Fat.

Density is a core material property and varies between different cell types, mainly based on differences in their lipid content. Sorting based on density enables various biomedical applications such as multi-omics in precision medicine and regenerative repair in medicine. However, a significant challenge is sorting cells of the same type based on density differences. Here, a new method for real-time monitoring and sorting of single cells based on their inherent levitation profiles driven by their lipid content is reported. As a model system, human-induced pluripotent stem cell (hiPSC)-derived cardiomyocytes (CMs) from a patient with neutral lipid storage disease (NLSD) due to loss of function of adipose triglyceride lipase (ATGL) resulting in abnormal lipid storage in cardiac muscle are used. This levitation-based strategy detects subpopulations within ATGL-deficient hiPSC-CMs with heterogenous lipid content, equilibrating at different levitation heights due to small density differences. In addition, sorting of these differentially levitating subpopulations are monitored in real time. Using this approach, sorted healthy and diseased hiPSC-CMs maintain viability and function. Pixel-tracking technologies show differences in contraction between NLSD and healthy hiPSC-CMs. Overall, this is a unique approach to separate diseased cell populations based on their intracellular lipid content that cannot be achieved using traditional flow cytometry techniques.