Tu34 - Microgels of tunable stiffness levels as co-flowing standards for cell classification by microfluidic deformability cytometry

In fifteen words or less, explain the significance of this contribution (Novel Aspect).: Standardized microgels enable impedance-based, label-free classification of cell deformability for real-time cytometry

Abstract Text:

Cellular subpopulations are a common feature of cell types with multiple functions, such as cancer, immune and stem cells. Their quantification and association with functional attributes are essential to assess disease progression and immune response. Cellular biophysical properties, such as cell size, shape, deformability, membrane capacitance and nuclear to cell size are associated with mechano-transduction cues, such as cell migration, immune cell activation and cell differentiation.  Single-cell microfluidic deformability cytometry can classify cell subpopulations on mechanical metrics but is limited by its inability to rapidly quantify the metrics of each assessed cell within a heterogeneous sample for activating cell sorting. To address this challenge, we present the utilization of microgels, composed of polyethylene glycol diacrylate (PEGDA) hydrogel microparticles as tunable mechanical standards. Using droplet microfluidics, PEGDA droplets with their photo-initiator are cured under an ultraviolet light source to fabricate microgels of 10-30 µm size range, with the PEGDA composition used to modulate stiffness of the microgels in the 1-10 kPa range, as validated by a dynamic mechanical analyzer (DMA). The deformation metrics of stiffness controlled microgels with sizes that mimic cell size distributions in a heterogeneous sample under microfluidic extensional flows are determined by image cytometry to serve as calibration plots of deformability versus size distributions for each microgel type of specific stiffness levels. Since 1D impedance cytometry signal trains can be processed more rapidly in comparison to 2D image cytometry signals, the specific impedance signal metrics that correlate with shape anisotropy are determined by impedance and flow simulations on microgels of controlled size and stiffness, while the impedance measurements are validated by image cytometry for corresponding events. In this manner, our future work will utilize these calibration plots together with near-sensor impedance signal processing for real-time recognition of cell deformability threshold levels in heterogeneous samples to activate cell sorting for single-cell immunofluorescence imaging, so that cellular biomechanical properties can be coupled with molecular markers to select cells of specific phenotypes for drug screening.