INNOTARGETS has recruited and trained 12 doctoral students.
Genes essential for growth of Streptococcus suis in in vitro models of virulence (blood, mucus, cerebrospinal fluid) and pig models (nasal organoids, saliva). have been identified using a transposon library. An Oxford Nanopore Technology (ONT) for sequencing and a custom bioinformatic pipeline to analyze the output and generate a list of potential conditionally essential genes, have been developed, and screening compound libraries have identified compounds capable of inhibiting the virulent S. suis strains. To investigate Staphylococcus aureus metabolisms during infection, in vitro and in vivo models (3D skin and mouse model) followed by proteomics, was utilized. Several proteins were identified as potential targets for future therapy of skin infections. Compound screening identified several antimicrobial compounds potentially affecting S. aureus, one of which had not previously been described.
Furthermore, INNOTARGETS has identified targets, where blocking, re-sensitize MRSA Staphylococcus aureus to oxacilling and tetracyline and Escherichia coli to macrolides, aminoglycosides and fosfomycin. In these bacteria, the approach was through construction of transposon libraries to identify genes, where knock-out caused loss of the ability to grow in the presence of antimicrobials. Through high-throughput screening, several potential lead molecules re-sensitizing the resistant S. aures and E. coli were identified. These findings form the basis for future validation of the potential of these compounds as antimicrobials or helper drugs. In addition, genes involved in the spread of conjugative plasmids have been identified, and a new high-throughput screening method for identifying compounds preventing conjugation has been developed.
There is a high level of redundancy in the metabolism, i.e. more than one enzyme can lead to production of the same metabolite. Such pairs of enzymes may be putative targets for both antimicrobial and helper drugs, if they are blocked simultaneously. To identify such pairs, INNOTARGETS has constructed mathematical models of the metabolism in Escherichia coli and Staphylococcus aureus. As part of this effort, results from transposon and proteomic studies are built into the modelling to generate much more precise modelling. The models were validated, confirming their potential in predicting metabolic changes. The models were used to investigate the effect of gene knockouts to identify redundant gene pairs. To be able to identify lead molecules which can block pairs of enzymes, one doctoral student has set up a novel system for screening libraries of bioactive molecules. Currently, novel metabolites from Microbispora are purified, for further analysis of their activity.
In one of the doctoral projects, a laboratory method to predict toxicity of drug candidates, and their downstream metabolic by-products was set up. For validation of the system, 28 commercial drugs with known toxicity profile, belonging to several medical classes, were validated in seven cell lines representative of major mammalian body systems and derived from two different animal species and humans.
INNOTARGETS has established a joint training syllabus designed to widen the career prospects of the doctoral students, and to optimize their professional competences. During the training period, technical courses (transposon techniques and proteomes) as well as complementary skills course (data management, scientific writing, IPR rights, entrepreneurship and personal impact) have been offered to the network’s early-stage researchers. INNOTARGETS has communicated preliminary results to the scientific community through participation in international and national meetings and have contributed to public science events centered on the topic of the global antimicrobial crises. Furthermore, main findings and methods developed have been published in peer reviewed publications.
