The current overuse of antibiotics is leading to the emergence of multidrug resistant (MDR) bacteria. These MDR pathogens continue to evolve at a terrifying rate and confer resistance to most or all presently available antibacterial treatments. Antimicrobial resistance is an eminent global problem that calls for an integrated approach that surpasses national borders, sectors, and disciplines. The COFUND ALERT programme addresses this call by establishing a dedicated doctoral training programme with an international, interdisciplinary and inter-sectoral focus. Nineteen excellent Early Stage Researchers (ESRs) will be employed at the University of Groningen (RUG). ALERT is based at RUG but is tightly connected with multiple international academic and private partner organisations, each providing complementary research or training. ALERT aims to develop the best practices in high quality training and research. ALERT achieves this through advanced multidisciplinary research training extended with development of dedicated transferable and entrepreneurial skills. ESRs will develop novel antimicrobial drug candidates through chemical, biotechnological and nanotechnological synthesis and subsequent in vivo testing. All ALERT Principal Investigators have ample experience with supervising PhD students, which ensures an attractive and vibrant research environment for the ESRs. In addition, access to excellent modern research facilities is guaranteed. Thus, the ALERT programme creates an optimal research and training environment that is far greater than the sum of its individual parts. ALERT’s long-term ambitions are to establish a strong and coherent international network that links together highly skilled young researchers as well as established scientists, who far beyond the funding period will continue to inspire each other to excel in antimicrobial resistance research in order to tackle the antimicrobial challenge.

Fast advances in genome sequencing and sequence processing technology leave ~30% of predicted proteins as orphans, meaning without known function or closely related enzymes. Being able to assign a function to such orphans opens avenues to select for and design powerful biocatalysts – individual enzymes, biosynthetic pathways or entire organisms. The herein proposed research aims at developing a de-orphanizing pipeline “fORPHAN” based on computational and experimental characterization of enzymes from the fungal kingdom. Fungi are known to be prolific producers of secondary metabolites, however, the study of the underlying biosynthetic gene clusters is still a fairly young field. The use of automated search and annotation pipelines is currently limited by the small number of experimentally characterized genes and gene clusters that can be used to train the algorithms. Therefore, I propose to use deep targeted database searches to identify key biosynthetic enzymes in the publicly available genomes of fungi. First targets will be the thus-far uncharacterized family of putative chalcone isomerases and the recently discovered family of type III polyketide synthases, which both have great potential for in vivo and in vitro applications. Several gene candidates will be expressed in vitro and in recombinant microbial hosts, and tested for activity on a range of substrates. Interesting candidates will also be characterized by X-ray crystallography. This research will not only yield biotechnologically-relevant catalysts but also provide the bioinformatic foundation for more challenging genome mining projects.

Enzymes perform essential reactions that sustain life with un-matched specificity and selectivity. Foldamers provide an opportunity to mimic Nature’s best catalysts as they are conformationally ordered structures that resemble proteins or enzymes. However, costly and time-consuming synthetic efforts have yielded only a small set of foldamers that exhibit poor catalytic activity in water. Here, we propose to combine for the first time Dynamic Combinatorial Chemistry (expertise of the host) and high-throughput screening methods (expertise of the ER) to identify a catalytically active foldamer that operates fully in aqueous solutions. The catalytic foldamer will emerge, with little synthetic effort, from a Dynamic Combinatorial Library (DCL) which contains building blocks that display key catalytic centers. The emerging foldamers will be tested for catalytic activity (e.g. hydrazone formation, ester hydrolysis) using newly-developed UPLC/UV-vis/fluorescence high-throughput protocols. This will allow rapid screening across a large substrate scope and range of experimental conditions, leading to the identification of foldamers that exhibit weak catalytic function. The activity of these hit foldamers will be optimized by combining different building blocks with optimized structures. Screening will be done in an iterative fashion to quickly survey the possible foldamer structural landscape generated from a mixture of two (or more) building blocks. The resulting data will allow essential design rules to be formulated regarding the relationship between building block structure/library components and catalytic activity. The three-dimensional structure of the discovered catalytic foldamers will be confirmed by X-ray crystallography (expertise of the secondment host).