Correlating mechanical and gene expression data on the single cell level to investigate metastatic phenotypes.

Stiffness has been observed to decrease for many cancer cell types as their metastatic potential increases. Although cell mechanics and metastatic potential are related, the underlying molecular factors associated with these phenotypes remain unknown. Therefore, we have developed a workflow to measure the mechanical properties and gene expression of single cells that is used to generate large linked-datasets. The process combines atomic force microscopy to measure the mechanics of individual cells with multiplexed RT-qPCR gene expression analysis on the same single cells. Surprisingly, the genes that most strongly correlated with mechanical properties were not cytoskeletal, but rather were markers of extracellular matrix remodeling, epithelial-to-mesenchymal transition, cell adhesion, and cancer stemness. In addition, dimensionality reduction analysis showed that cell clustering was improved by combining mechanical and gene expression data types. The single cell genomechanics method demonstrates how single cell studies can identify molecular drivers that could affect the biophysical processes underpinning metastasis.

Scaling microfluidic throughput with flow-balanced manifolds to simply control devices with multiple inlets and outlets.

Microfluidics can bring unique functionalities to cell processing, but the small channel dimensions often limit the throughput for cell processing that prevents scaling necessary for key applications. While processing throughput can be improved by increasing cell concentration or flow rate, an excessive number or velocity of cells can result in device failure. Designing parallel channels can linearly increase the throughput by channel number, but for microfluidic devices with multiple inlets and outlets, the design of the channel architecture with parallel channels can result in intractable numbers of inlets and outlets. We demonstrate an approach to use multiple parallel channels for complex microfluidic designs that uses a second manifold layer to connect three inlets and five outlets per channel in a manner that balances flow properties through each channel. The flow balancing in the individual microfluidic channels was accomplished through a combination of analytical and finite element analysis modeling. Volumetric flow and cell flow velocity were measured in each multiplexed channel to validate these models. We demonstrate eight-channel operation of a label-free mechanical separation device that retains the accuracy of a single channel separation. Using the parallelized device and a model biomechanical cell system for sorting of cells based on their viability, we processed over 16 × 106 cells total over three replicates at a rate of 5.3 × 106 cells per hour. Thus, parallelization of complex microfluidics with a flow-balanced manifold system can enable higher throughput processing with the same number of inlet and outlet channels to control.