Researchers at the University of California, Los Angeles have developed a method to rapidly quantify the mechanical properties of single cells at high resolution using hydrodynamic and inertial fluid focusing.
Cells undergo structural changes during disease states, particularly in certain cancer cell lines. For example, tumor cells with increased invasive potential exhibit increased deformability, which aids them during their migration into surrounding tissues1. Measuring the mechanical properties of single cells as a biomarker of cell health using conventional Atomic Force Microscopy (AFM) or micropipette aspiration is time-consuming and requires extensive sample prep, limiting the analysis to a few cells. Dino Di Carlo’s group and collaborators developed a way to apply fluids to stretch single cells along two axes using hydrodynamic flow and perpendicular cross-flows without waiting for cells to stop within the channel. This method, termed ‘hydropipetting’, is compatible with inline microfluidic rinsing, capable of processing 65000 cells/sec, and utilizes automatic image processing to rapidly derive the mechanical phenotype of cell populations.
Hydropipetting starts with inertial fluid focusing of cells to position them precisely in a flow channel by balancing lift forces and secondary flows by fine control over the Reynolds number of the fluid. Cell-free liquid is then excluded and cells are deformed both parallel and perpendicular to the main channel flow. Automated image data analysis then extracts metrics of cell strain, viscosity, diameter and deformability from high speed observation during cell deformation.
Di Carlo and his group demonstrated the hydropipetting technique on two cancer cell lines (HeLa and Jurkat cells) and observed increases in cell deformability upon drug treatment to increase invasiveness, metastatic potential, and when disrupting structural cellular filaments.
 S. E. Cross, Y. Jin, J. Rao and J. K. Gimzewski, Nature Nanotechnology, 2007, 2, 780-783.
Pinched-flow hydrodynamic stretching of single-cells
Jaideep S. Dudani, Daniel R. Gossett, Henry T. K. Tse and Dino Di Carlo. Lab Chip, 2013, 13, 3728-3734.