The mechanical phenotype of a cell is an inherent biophysical marker of its state and function, with potential value in clinical diagnostics. Several microfluidic-based methods developed in recent years have enabled single-cell mechanophenotyping at throughputs comparable to flow cytometery. Here we present a highly standardized cross-laboratory study comparing three leading microfluidic-based approaches to measure cell mechanical phenotype: constriction-based deformability cytometry (cDC), shear flow deformability cytometry (sDC), and extensional flow deformability cytometry (xDC). We show that all three methods detect cell deformability changes induced by exposure to altered osmolarity. However, a dose-dependent deformability increase upon latrunculin B-induced actin disassembly was detected only with cDC and sDC, which suggests that when exposing cells to the higher strain rate imposed by xDC, other cell components dominate the response. The direct comparison presented here serves to unify deformability cytometry methods and provides context for the interpretation of deformability measurements performed using different platforms.

The identification and separation of specific cells from heterogeneous populations is an essential prerequisite for further analysis or use. Conventional passive and active separation approaches rely on fluorescent or magnetic tags introduced to the cells of interest through molecular markers. Such labeling is time-and cost-intensive, can alter cellular properties, and might be incompatible with subsequent use, for example, in transplantation. Alternative label-free approaches utilizing morphological or mechanical features are attractive, but lack molecular specificity. Here we combine image-based real-time fluorescence and deformability cytometry (RT-FDC) with downstream cell sorting using standing surface acoustic waves (SSAW). We demonstrate basic sorting capabilities of the device by separating cell mimics and blood cell types based on fluorescence as well as deformability and other image parameters. The identification of blood sub-populations is enhanced by flow alignment and deformation of cells in the microfluidic channel constriction. In addition, the classification of blood cells using established fluorescence-based markers provides hundreds of thousands of labeled cell images used to train a deep neural network. The trained algorithm, with latency optimized to below 1 ms, is then used to identify and sort unlabeled blood cells at rates of 100 cells/sec. This approach transfers molecular specificity into labelfree sorting and opens up new possibilities for basic biological research and clinical therapeutic applications.

During osmotic changes of their environment, cells actively regulate their volume and plasma membrane tension that can passively change through osmosis. How tension and volume are coupled during osmotic adaptation remains unknown, as their quantitative characterization is lacking. Here, we performed dynamic membrane tension and cell volume measurements during osmotic shocks. During the first few seconds following the shock, cell volume varied to equilibrate osmotic pressures inside and outside the cell, and membrane tension dynamically followed these changes. A theoretical model based on the passive, reversible unfolding of the membrane as it detaches from the actin cortex during volume increase quantitatively describes our data. After the initial response, tension and volume recovered from hypoosmotic shocks but not from hyperosmotic shocks. Using a fluorescent membrane tension probe (fluorescent lipid tension reporter [Flipper-TR]), we investigated the coupling between tension and volume during these asymmetric recoveries. Caveolae depletion and pharmacological inhibition of ion transporters and channels, mTORCs, and the cytoskeleton all affected tension and volume responses. Treatments targeting mTORC2 and specific downstream effectors caused identical changes to both tension and volume responses, their coupling remaining the same. This supports that the coupling of tension and volume responses to osmotic shocks is primarily regulated by mTORC2.