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We have previously shown that the maize pathogen Colletotrichum graminicola is able to synthesise cytokinins (CKs). However, it remained unsettled whether fungal CK production is essential for virulence in this hemibiotrophic fungus. Here, we identified a candidate gene, CgIPT1, that is homologous to MOD5 of Saccharomyces cerevisiae and genes from other fungi and plants, which encode tRNA-isopentenyltransferases (IPTs). We show that the wild type strain mainly synthesises cis-zeatin-type (cisZ) CKs whereas ΔCgipt1 mutants are severely impeded to do so. The spectrum of CKs produced confirms bioinformatical analyses predicting that CgIpt1 is a tRNA-IPT. The virulence of the ΔCgipt1 mutants is moderately reduced. Furthermore, the mutants exhibit increased sensitivities to osmotic stress imposed by sugar alcohols and salts, as well as cell wall stress imposed by Congo red. Amendment of media with CKs did not reverse this phenotype suggesting that fungal-derived CKs do not explain the role of CgIpt1 in mediating abiotic stress tolerance. Moreover, the mutants still cause green islands on senescing maize leaves indicating that the cisZ-type CKs produced by the fungus do not cause this phenotype.

Mainly because of the large number of people affected and associated significant health policy implications, the Robert Koch Institute (RKI) is developing a public health surveillance system using diabetes as an example. In a first step to ensure long-term and comparable data collection and establish efficient surveillance structures, the RKI has defined a set of relevant indicators for diabetes surveillance. An extensive review of the available literature followed by a structured process of consensus provided the basis for a harmonised set of 30 core and 10 supplementary indicators. They correspond to the following four fields of activity: (1) reducing diabetes risk, (2) improving diabetes early detection and treatment, (3) reducing diabetes complications, (4) reducing the disease burden and overall costs of the disease. In future, in addition to the primary data provided by RKI health monitoring diabetes surveillance needs to also consider the results from secondary data sources. Currently, barriers to accessing this data remain, which will have to be overcome, and gaps in the data closed. The RKI intentends to continuously update this set of indicators and at some point apply it also to further chronic diseases with high public health relevance.