It is currently believed that type I and III interferons (IFNs) have redundant functions. However, the preferential distribution of type III IFN receptor on epithelial cells suggests functional differences at epithelial surfaces. Here, using human intestinal epithelial cells we could show that although both type I and type III IFNs confer an antiviral state to the cells, they do so with distinct kinetics. Type I IFN signaling is characterized by an acute strong induction of interferon stimulated genes (ISGs) and confers fast antiviral protection. On the contrary, the slow acting type III IFN mediated antiviral protection is characterized by a weaker induction of ISGs in a delayed manner compared to type I IFN. Moreover, while transcript profiling revealed that both IFNs induced a similar set of ISGs, their temporal expression strictly depended on the IFNs, thereby leading to unique antiviral environments. Using a combination of data-driven mathematical modeling and experimental validation, we addressed the molecular reason for this differential kinetic of ISG expression. We could demonstrate that these kinetic differences are intrinsic to each signaling pathway and not due to different expression levels of the corresponding IFN receptors. We report that type III IFN is specifically tailored to act in specific cell types not only due to the restriction of its receptor but also by providing target cells with a distinct antiviral environment compared to type I IFN. We propose that this specific environment is key at surfaces that are often challenged with the extracellular environment.

SummaryEpigenetic changes represent an attractive mechanism for understanding the phenotypic changes associated with human aging. Age‐related changes in DNA methylation at the genome scale have been termed ‘epigenetic drift’, but the defining features of this phenomenon remain to be established. Human epidermis represents an excellent model for understanding age‐related epigenetic changes because of its substantial cell‐type homogeneity and its well‐known age‐related phenotype. We have now generated and analyzed the currently largest set of human epidermis methylomes (N = 108) using array‐based profiling of 450 000 methylation marks in various age groups. Data analysis confirmed that age‐related methylation differences are locally restricted and characterized by relatively small effect sizes. Nevertheless, methylation data could be used to predict the chronological age of sample donors with high accuracy. We also identified discontinuous methylation changes as a novel feature of the aging methylome. Finally, our analysis uncovered an age‐related erosion of DNA methylation patterns that is characterized by a reduced dynamic range and increased heterogeneity of global methylation patterns. These changes in methylation variability were accompanied by a reduced connectivity of transcriptional networks. Our findings thus define the loss of epigenetic regulatory fidelity as a key feature of the aging epigenome.