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A Numerical Mechanical Model Integrating Actin Treadmilling and Receptor Recycling to Explain Selective Disengagement of Immune Cells.

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T-killer cells of the immune system eliminate virus-infected cells by releasing toxic granules through a direct cell to cell surface interface (synapse). The release of toxic granules only through the… Click to show full abstract

T-killer cells of the immune system eliminate virus-infected cells by releasing toxic granules through a direct cell to cell surface interface (synapse). The release of toxic granules only through the cell surface interface assures the specificity of the immune response. The toxic granule releasing apparatus, however, may not be aligned toward the synapse at the moment of the synapse formation. Therefore, mechanisms for reorienting the killing apparatus inside the T-killer cell to the interface with the target is required. Numerous research works were reported to suggest the mechanisms with direct and indirect evidence, but the most adversary situation, that is when the cell's initial orientation is the complete opposite of the desired direction, either remained answered or brought skepticism toward the suggested mechanisms. To address this issue, a computational mechanical model of T-killer cell synapse formation is constructed to test previously suggested models in a more realistic setting and at the same time to test previously neglected component in the model, namely the actin network formation on the synapse. In this model, by capturing the mechanical interaction between T-killer cell surface receptor dynamics and mechanical properties of synapse formation, it is shown that T-killer cells can selectively engage or disengage from the target cell depending on the killing apparatus alignment with the target. The mechanism works as a safeguard measure ensuring target-cell killing and specificity, so it will be effective when T-killer cells are stranded in situations where the alignment of the killing apparatus is challenging.

Keywords: synapse; killer; mechanical model; formation; cell

Journal Title: Mathematical biosciences
Year Published: 2019

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