Massively Parallel Microfluidic Cell-pairing Platform for the Statistical Study of Immunological Cell-cell Interactions

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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