Implementing WGS-Based Strain Characterization into Pathogen Surveillance: Introducing the Strategy of the Robert Koch Institute

The Robert Koch Institute is the Central Public Health Institute in Germany. The German Infection Protection Act (“Infektionssschutzgesetz”) and the German Antimicrobial Resistance Strategy DART define, amongst other documents, the institute’s legal framework and guide activities in the field of pathogen surveillance of community-associated, health-care associated and food- and water-borne infections, antimicrobial resistance and consumption. The institute hosts a network of reference and conciliar laboratories for more the 80 pathogens (mainly notifiable diseases), some of them directly located at the institute. NGS technology has been introduced about 10 years ago at the institute. WGS-based analyses have been used in recent years in various pilot projects funded by the institute and research activities financed by external funds (viruses, bacteria, metagenomics).

As part of all these diverse, recent activities, various expertise and experiences were gained at different groups, units and departments at the institute. Fast evolving requests for high throughput NGS techniques by an increasing number of groups at the institute embedded in a framework of limited additional resources, led to a common and agreed strategy of consolidation of machines, experiences and resources. Currently, we have (i) consolidated our machine park into a single core sequencing facility; (ii) streamlined our bioinformatics needs in a core bioinformatic service flanked by external expertise in research groups (not primarily dedicated to service activities) and individual expertise in several divisions and departments and (iii) prioritized our WGS-based requirements in an institute’s wide strategy for an “intensified and integrated molecular pathogen surveillance”. The talk will provide some detailed information about these aspects and thoughts. Suitability of existing infrastructure, sequencing techniques and bioinformatics pipelines will be demonstrated using a few recent examples.