Development of Microfluidic System Enabling High-Throughput Characterization of Multiple Biophysical Parameters of Single Cells

This article developed a microfluidic platform enabling high-throughput characterization of inherent single-cell biomechanical and bioelectrical parameters simultaneously leveraging constriction microchannels. Individual cells entered into and squeezed through the constriction microchannel with deformation images and impedance variations captured and processed into cytoplasmic viscosity ${mu} _{c}$ , cortical tension $T_{c}$ , specific membrane capacitance $C_{sm}$ , and cytoplasmic conductivity ${sigma}_{cy}$ based on a home-developed biophysical model. Using this microfluidic platform, four inherent biophysical parameters of hundreds of individual cells of A549, CAL 27, HepG2, A431, SACC-83, SACC-LM, K562, CD-treated K562, and ConA-treated K562 cells were quantified for the first time. Leveraging ${mu}_{c}$ , $T_{c}$ , $C_{sm}$ , and $sigma_{cy}$ : 1) success rates of classifying A549, CAL 27, HepG2, and A431 were improved from 67.6 +/- 4.7% of ${mu}_{c}$ , 60.0% +/- 3.5% of $T_{c}$ , 74.1% +/- 8.8% of $C_{sm}$ and 66.0% +/- 11.3% of ${sigma}_{cy}$ to 83.1% +/- 6.3% based on ${mu}_{c}$ , $T_{c}$ , $C_{sm}$ , and ${sigma}_{cy}$ and 2) success rates of classifying paired oral tumor cell types of SACC-83 versus SACC-LM were improved from 67.6% of ${mu}_{{c}}$ , 60.0% of $T_{c}$ , 80.4% of $C_{sm}$ , and 64.4% of ${sigma}_{cy}$ to 88.9% based on ${mu}_{c}$ , $T_{c}$ , $C_{sm}$ , and ${sigma}_{cy}$ ; success rates of classifying native versus treated K562 cells were improved from 62.1% +/- 6.5% of $mu_{c}$ , 61.5 +/- 4.4% of $T_{c}$ , 64.4% +/- 3.4% of $C_{sm}$ , and 61.3% +/- 3.2% of ${sigma}_{cy}$ to 73.9% +/- 2.7% based on ${mu}_{c}$ , $T_{c}$ , $C_{sm}$ , and ${sigma}_{cy}$ . In conclusion, this developed microfluidic platform can characterize single-cell ${mu}_{c}$ , $T_{c}$ , $C_{sm}$ , and ${sigma}_{cy}$ concurrently and provide a comprehensive evaluation of single cells from the perspective of biophysical properties.

Automated summary

This article develops a microfluidic platform to characterize the biomechanical and bioelectrical parameters of individual cells simultaneously. It quantifies the inherent biophysical parameters of various cell types and improves the classification success rates using these parameters.