Current molecular diagnostics of human pathogens provide limited information that is often not sufficient for outbreak and transmission investigation. Next generation sequencing (NGS) determines the DNA sequence of a complete bacterial genome in a single sequence run, and from these data, information on resistance and virulence, as well as information for typing is obtained, useful for outbreak investigation. The obtained genome data can be further used for the development of an outbreak-specific screening test. In this review, a general introduction to NGS is presented, including the library preparation and the major characteristics of the most common NGS platforms, such as the MiSeq (Illumina) and the Ion PGM™ (ThermoFisher). An overview of the software used for NGS data analyses used at the medical microbiology diagnostic laboratory in the University Medical Center Groningen in The Netherlands is given. Furthermore, applications of NGS in the clinical setting are described, such as outbreak management, molecular case finding, characterization and surveillance of pathogens, rapid identification of bacteria using the 16S-23S rRNA region, taxonomy, metagenomics approaches on clinical samples, and the determination of the transmission of zoonotic micro-organisms from animals to humans. Finally, we share our vision on the use of NGS in personalised microbiology in the near future, pointing out specific requirements.

The implementation of routine whole-genome sequencing (WGS) promises to transform our ability to monitor the emergence and spread of bacterial pathogens. Here we combined WGS data from 308 invasive Staphylococcus aureus isolates corresponding to a pan-European population snapshot, with epidemiological and resistance data. Geospatial visualization of the data is made possible by a generic software tool designed for public health purposes that is available at the project URL (http://www.microreact.org/project/EkUvg9uY?tt=rc). Our analysis demonstrates that high-risk clones can be identified on the basis of population level properties such as clonal relatedness, abundance, and spatial structuring and by inferring virulence and resistance properties on the basis of gene content. We also show that in silico predictions of antibiotic resistance profiles are at least as reliable as phenotypic testing. We argue that this work provides a comprehensive road map illustrating the three vital components for future molecular epidemiological surveillance: (i) large-scale structured surveys, (ii) WGS, and (iii) community-oriented database infrastructure and analysis tools.

Sequencing of at least 13 Staphylococcus aureus isolates has shown that genomic plasticity impacts significantly on the repertoire of virulence factors. However, genome sequencing does not reveal which genes are expressed by individual isolates. Here, we have therefore performed a comprehensive survey of the composition and variability of the S. aureus exoproteome. This involved multilocus sequence typing, virulence gene, and prophage profiling by multiplex PCR, and proteomic analyses of secreted proteins using 2-DE. Dissection of the exoproteomes of 25 clinical isolates revealed that only seven out of 63 identified secreted proteins were produced by all isolates, indicating a remarkably high exoproteome heterogeneity within one bacterial species. Most interesting, the observed variations were caused not only by genome plasticity, but also by an unprecedented variation in secretory protein production due to differences in transcriptional and post-transcriptional regulation. Our data imply that genomic studies on virulence gene conservation patterns need to be complemented by analyses of the extracellular protein pattern to assess the full virulence potential of bacterial pathogens like S. aureus. Importantly, the extensive variability of secreted virulence factors in S. aureus also suggests that development of protective vaccines against this pathogen requires a carefully selected combination of invariably produced antigens.