Massively Parallel Microfluidic Cell-pairing Platform for the Statistical Study of Immunological Cell-cell Interactions
- Category: MEMS & BioMEMS
- Tags: Joel Voldman, Melanie Hoehl
Many immune responses are mediated by cell-cell interactions. In particular, cytotoxic T cells form conjugates with pathogenic and cancer cells in order to fight disease. Moreover, T cell maturation and activation is governed by direct cell interactions with antigen-presenting cells (APCs). Errors in these processes can lead to the progression of severe diseases, such as multiple sclerosis (MS) and type 1 diabetes. The study of these intricate cell-cell interactions at the molecular scale is therefore crucial for understanding the dynamics and specificity of the immune response. One important feature of these interactions is the variability of response across populations. Cell-to-cell variability in presumably homogeneous populations exposed to the same environmental conditions is ubiquitous, yet has long been neglected in immunology due to the limitations of conventional assay methods [1] [2] . Traditional methods to study cell-cell interactions, such as bulk measurements [3] or immobilization of cell pairs on a dish [4] [5] , suffer from both the inability to control cell-pairing at the single cell level and the inability to study dynamic cell-cell interaction processes with high spatial and temporal resolution. We have overcome these limitations by developing a platform that can control cell pairing across thousands of individual immune cell pairs simultaneously while allowing visualization of the resulting responses. This approach enables us to quantify and understand variations in cell-cell interactions within large cell populations at the resolution of individual cell pairs. Previously, we developed a microfluidic device with the capability to create thousands of such single cell pairs for the study of stem cell reprogramming (Figure 1, [6] ). To adapt the approach to work with smaller primary immune cells, we performed hydrodynamic modeling to guide redesign of the trap geometry (Figure 2). The modeling was used to determine how to adjust the trap geometry to maximize flow through the center of the cups, which is crucial to the loading process. We determined that altering the cup-to-cup spacing transverse to the flow had the greatest impact on flow through the cups. We fabricated redesigned traps and are in the process of testing their pairing efficiency with primary immune cells.
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