Summary Correct localization of Rab GTPases in cells is critical for proper function in membrane trafficking, yet the mechanisms that target Rabs to specific subcellular compartments remain controversial. Guanine nucleotide exchange factors (GEFs) activate and consequently stabilize Rab substrates on membranes, thus implicating GEFs as the primary determinants of Rab localization. A competing hypothesis is that the Rab C-terminal hypervariable domain (HVD) serves as a subcellular targeting signal. In this study we present a unifying mechanism in which the HVD controls targeting of certain Rabs by mediating interaction with their GEFs. We demonstrate that the TRAPP complexes, two related GEFs that use the same catalytic site to activate distinct Rabs, distinguish between Ypt1 (Rab1) and Ypt31/32 (Rab11) via their divergent HVDs. Remarkably, we find that HVD length gates Rab access to the TRAPPII complex by constraining the distance between the nucleotide-binding domain and the membrane surface.

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Immune checkpoint inhibitors (ICIs), as a novel immunotherapy, are designed to modulate the immune system to attack malignancies. Despite their promising benefits, immune-related adverse events (IRAEs) may occur, and incidences are bound to increase with surging demand of this class of drugs in treating cancer. Myocarditis, although rare compared to other IRAEs, has a significantly higher fatal frequency. Due to the overwhelming complexity of the immune system, this condition is not well understood, despite the significant research efforts devoted to it. To better understand the development and progression of autoimmune myocarditis and the roles of ICIs therein, we suggest a new approach: mathematical modelling. Mathematical modelling of myocarditis has enormous potential to determine which parts of the immune system are critical to the development and progression of the disease, and therefore warrant further investigation. We provide the immunological background needed to develop a mathematical model of this disease and review relevant existing models of immunology that serve as the mathematical inspiration needed to develop this field.