Cathepsin D Drives the Formation of Hybrid Insulin Peptides Relevant to the Pathogenesis of Type 1 Diabetes.

Hybrid insulin peptides (HIPs) form in pancreatic ß-cells through the formation of peptide bonds between proinsulin fragments and other peptides. HIPs have been identified in pancreatic islets by mass spectrometry and are targeted by CD4 T cells in patients with type 1 diabetes (T1D) as well as by pathogenic CD4 T-cell clones in nonobese diabetic (NOD) mice. The mechanism of HIP formation is currently poorly understood; however, it is well established that proteases can drive the formation of new peptide bonds in a side reaction during peptide bond hydrolysis. Here, we used a proteomic strategy on enriched insulin granules and identified cathepsin D (CatD) as the primary protease driving the specific formation of HIPs targeted by disease-relevant CD4 T cells in T1D. We also established that NOD islets deficient in cathepsin L (CatL), another protease implicated in the formation of disease-relevant HIPs, contain elevated levels of HIPs, indicating a role for CatL in the proteolytic degradation of HIPs. In summary, our data suggest that CatD may be a therapeutic target in efforts to prevent or slow the autoimmune destruction of ß-cells mediated by HIP-reactive CD4 T cells in T1D.

Building the bridge between animal movement and population dynamics.

While the mechanistic links between animal movement and population dynamics are ecologically obvious, it is much less clear when knowledge of animal movement is a prerequisite for understanding and predicting population dynamics. GPS and other technologies enable detailed tracking of animal location concurrently with acquisition of landscape data and information on individual physiology. These tools can be used to refine our understanding of the mechanistic links between behaviour and individual condition through 'spatially informed' movement models where time allocation to different behaviours affects individual survival and reproduction. For some species, socially informed models that address the movements and average fitness of differently sized groups and how they are affected by fission-fusion processes at relevant temporal scales are required. Furthermore, as most animals revisit some places and avoid others based on their previous experiences, we foresee the incorporation of long-term memory and intention in movement models. The way animals move has important consequences for the degree of mixing that we expect to find both within a population and between individuals of different species. The mixing rate dictates the level of detail required by models to capture the influence of heterogeneity and the dynamics of intra- and interspecific interaction.