Automated Cell Mechanical Characterization by On-Chip Sequential Squeezing: From Static to Dynamic

Photocell-Based Optofluidic Device for Clogging-Free Cell Transit Time Measurements

Measuring the transit time of a cell forced through a bottleneck is one of the most widely used techniques for the study of cell deformability in flow. It in turn provides an accessible and rapid way of obtaining crucial information regarding cell physiology. Many techniques are currently being investigated to reliably retrieve this time, but their translation to diagnostic-oriented devices is often hampered by their complexity, lack of robustness, and the bulky external equipment required. Herein, we demonstrate the benefits of coupling microfluidics with an optical method, like photocells, to measure the transit time. We exploit the femtosecond laser irradiation followed by chemical etching (FLICE) fabrication technique to build a monolithic 3D device capable of detecting cells flowing through a 3D non-deformable constriction which is fully buried in a fused silica substrate. We validated our chip by measuring the transit times of pristine breast cancer cells (MCF-7) and MCF-7 cells treated with Latrunculin A, a drug typically used to increase their deformability. A difference in transit times can be assessed without the need for complex external instrumentation and/or demanding computational efforts. The high throughput (4000-10,000 cells/min), ease of use, and clogging-free operation of our device bring this approach much closer to real scenarios.

Tunable microfluidic chip for single-cell deformation study

Microfluidic phenotyping methods have been of vital importance for cellular characterization, especially for evaluating single cells. In order to study the deformability of a single cell, we devised and tested a tunable microfluidic chip-based method. A pneumatic polymer polydimethylsiloxane (PDMS) membrane was designed and fabricated abutting a single-cell trapping structure, so the cell could be squeezed controllably in a lateral direction. Cell contour changes under increasing pressure were recorded, enabling the deformation degree of different types of single cell to be analyzed and compared using computer vision. This provides a new perspective for studying mechanical properties of cells at the single cell level.

Altered physical phenotypes of leukemia cells that survive chemotherapy treatment

The recurrence of cancer following chemotherapy treatment is a major cause of death across solid and hematologic cancers. In B-cell acute lymphoblastic leukemia (B-ALL), relapse after initial chemotherapy treatment leads to poor patient outcomes. Here we test the hypothesis that chemotherapy-treated versus control B-ALL cells can be characterized based on cellular physical phenotypes. To quantify physical phenotypes of chemotherapy-treated leukemia cells, we use cells derived from B-ALL patients that are treated for 7 days with a standard multidrug chemotherapy regimen of vincristine, dexamethasone, and L-asparaginase (VDL). We conduct physical phenotyping of VDL-treated versus control cells by tracking the sequential deformations of single cells as they flow through a series of micron-scale constrictions in a microfluidic device; we call this method Quantitative Cyclical Deformability Cytometry. Using automated image analysis, we extract time-dependent features of deforming cells including cell size and transit time (TT) with single-cell resolution. Our findings show that VDL-treated B-ALL cells have faster TTs and transit velocity than control cells, indicating that VDL-treated cells are more deformable. We then test how effectively physical phenotypes can predict the presence of VDL-treated cells in mixed populations of VDL-treated and control cells using machine learning approaches. We find that TT measurements across a series of sequential constrictions can enhance the classification accuracy of VDL-treated cells in mixed populations using a variety of classifiers. Our findings suggest the predictive power of cell physical phenotyping as a complementary prognostic tool to detect the presence of cells that survive chemotherapy treatment. Ultimately such complementary physical phenotyping approaches could guide treatment strategies and therapeutic interventions. Insight box Cancer cells that survive chemotherapy treatment are major contributors to patient relapse, but the ability to predict recurrence remains a challenge. Here we investigate the physical properties of leukemia cells that survive treatment with chemotherapy drugs by deforming individual cells through a series of micron-scale constrictions in a microfluidic channel. Our findings reveal that leukemia cells that survive chemotherapy treatment are more deformable than control cells. We further show that machine learning algorithms applied to physical phenotyping data can predict the presence of cells that survive chemotherapy treatment in a mixed population. Such an integrated approach using physical phenotyping and machine learning could be valuable to guide patient treatments.

Cell pairing for biological analysis in microfluidic devices

Cell pairing at the single-cell level usually allows a few cells to contact or seal in a single chamber and provides high-resolution imaging. It is pivotal for biological research, including understanding basic cell functions, creating cancer treatment technologies, developing drugs, and more. Laboratory chips based on microfluidics have been widely used to trap, immobilize, and analyze cells due to their high efficiency, high throughput, and good biocompatibility properties. Cell pairing technology in microfluidic devices provides spatiotemporal research on cellular interactions and a highly controlled approach for cell heterogeneity studies. In the last few decades, many researchers have emphasized cell pairing research based on microfluidics. They designed various microfluidic device structures for different biological applications. Herein, we describe the current physical methods of microfluidic devices to trap cell pairs. We emphatically summarize the practical applications of cell pairing in microfluidic devices, including cell fusion, cell immunity, gap junction intercellular communication, cell co-culture, and other applications. Finally, we review the advances and existing challenges of the presented devices and then discuss the possible development directions to promote medical and biological research.