Mechanophenotyping Cytometer Measures Cell Elasticity Rapidly

A new microfluidic device called a mechanophenotyping cytometer enables high-throughput measurement of cell size and stiffness, known as mechanical phenotype. Developed by Brown University researchers and collaborators, this tool addresses limitations of slower methods like atomic force microscopy. Accurate assessment of cell elasticity changes can reveal disease signatures, such as softening cancer cells prone to metastasis or stiffened red blood cells in malaria and sickle cell disease. Mechanical alterations also appear in neurodegenerative, cardiovascular, and chronic inflammatory conditions. 

The device uses time-of-flight measurements, tracking how long cells take to travel through narrow liquid channels. Softer cells migrate to the channel center where fluid flows fastest, while stiffer cells remain near the edges with slower flow. Fluorescence signals determine cell size, and time-of-flight reveals stiffness. Lead author Graylen Chickering noted this approach processes 60 to 100 cells per second—far surpassing atomic force microscopy's one cell every 30 seconds.

“This method essentially works by poking a cell,” Chickering said of AFM. “Imagine looking at a water balloon, and if you poke right on the edge of the balloon versus the center, it might feel different. Poking cells is also fairly slow, making it difficult to study large numbers of cells in a reasonable amount of time.”

With the new methodology, “The cell is essentially traveling from one checkpoint to another, and we take timestamps from each checkpoint to determine the time-of-flight,” Chickering added.

The study, published in Lab on a Chip, validated the cytometer using synthetic cell-like particles from Brown’s Institute for Biology, Engineering and Medicine. These polymer mimics provided known sizes and stiffnesses for calibration. Collaborators at the National Institute of Standards and Technology created the design for the device with multiple measurement regions for precise error quantification, demonstrating low biological and technical variability.

“The proof of concept was when Graylen produced data showing that cell particles of different stiffnesses and different sizes had different correlational time of flights, which aligned with, theoretically, what we were expecting,” said senior author Eric Darling. “The method was so clean and reproducible compared to previous methods, which can result in different measurements depending on how they’re used.”