Optical stretching in continuous flows

Critical review of single-cell mechanotyping approaches for biomedical applications

Accurate mechanical measurements of cells has the potential to improve diagnostics, therapeutics and advance understanding of disease mechanisms, where high-resolution mechanical information can be measured by deforming individual cells. Here we evaluate recently developed techniques for measuring cell-scale stiffness properties; while many such techniques have been developed, much of the work examining single-cell stiffness is impacted by difficulties in standardization and comparability, giving rise to large variations in reported mechanical moduli. We highlight the role of underlying mechanical theories driving this variability, and note opportunities to develop novel mechanotyping devices and theoretical models that facilitate convenient and accurate mechanical characterisation. Moreover, many high-throughput approaches are confounded by factors including cell size, surface friction, natural population heterogeneity and convolution of elastic and viscous contributions to cell deformability. We nevertheless identify key approaches based on deformability cytometry as a promising direction for further development, where both high-throughput and accurate single-cell resolutions can be realized.

Microfluidic device featuring micro-constrained channels for multi-parametric assessment of cellular biomechanics and high-precision mechanical phenotyping of gastric cells

BACKGROUND

Cellular biomechanics plays a significant role in the regulation of cellular physiological and pathological processes. In recent years, multiple methods have been developed to evaluate cellular biomechanics, such as atomic force microscopy (AFM), micropipette aspiration, and magnetic tweezers. However, most of these methods only focus on a single parameter and cannot automate the process at a high-efficiency level. A novel microfluidic method is necessary to achieve the simultaneous multi-parametric measurement of cellular biomechanics and high-precision cellular mechanical phenotyping at high throughput.

RESULTS

To tackle the issue concerning the low-throughput and cellular single-parameter evaluation, we designed and fabricated a microfluidic chip featuring multiple micro-constrained channels structure, providing a simultaneous multi-parametric assessment of cellular biomechanics, including elastic modulus, recovery capability, and deformability. We compared the biomechanical properties of normal human gastric mucosal epithelial cells (GES-1) and human gastric cancer cells (AGS and MKN-45) by the chip. Results demonstrated that the elastic modulus of GES-1, AGS, and MKN-45 cells decreased sequentially, which was the opposite of their invasiveness and metastasis potential, suggesting the inverse correlation between cellular elastic modulus and malignancy. Meanwhile, the recovery capability and deformability of GES-1, AGS, and MKN-45 cells increased sequentially, demonstrating the positive correlation between cellular deformability and malignancy. Furthermore, multiple parameters were used to distinguish gastric cancer cells from normal gastric cells via machine learning. An accuracy of over 94.8% for identifying gastric cancer cells was achieved.

SIGNIFICANCE

This study provides a deep insight into the biophysical mechanism of gastric cancer metastasis at the single-cell level and possesses great potential to function as a valuable tool for single-cell analysis, thereby facilitating high-precision and high-throughput discrimination of cellular phenotypes that are not easily discernible through single-marker analysis.

Mechanical Heterogeneity in Tissues Promotes Rigidity and Controls Cellular Invasion

We study the influence of cell-level mechanical heterogeneity in epithelial tissues using a vertex-based model. Heterogeneity is introduced into the cell shape index (p_{0}) that tunes the stiffness at a single-cell level. The addition of heterogeneity can always enhance the mechanical rigidity of the epithelial layer by increasing its shear modulus, hence making it more rigid. There is an excellent scaling collapse of our data as a function of a single scaling variable f_{r}, which accounts for the overall fraction of rigid cells. We identify a universal threshold f_{r}^{*} that demarcates fluid versus solid tissues. Furthermore, this rigidity onset is far below the contact percolation threshold of rigid cells. These results give rise to a separation of rigidity and contact percolation processes that leads to distinct types of solid states. We also investigate the influence of heterogeneity on tumor invasion dynamics. There is an overall impedance of invasion as the tissue becomes more rigid. Invasion can also occur in an intermediate heterogeneous solid state that is characterized by significant spatial-temporal intermittency.