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 Klebsiella group, found in humans, livestock, plants, soil, water and wild animals, is genetically and ecologically diverse. Many species are opportunistic pathogens and can harbour diverse classes of antimicrobial resistance genes. Healthcare-associated Klebsiella pneumoniae clones that are non-susceptible to carbapenems can spread rapidly, representing a high public health burden. Here we report an analysis of 3,482 genome sequences representing 15 Klebsiella species sampled over a 17-month period from a wide range of clinical, community, animal and environmental settings in and around the Italian city of Pavia. Northern Italy is a hotspot for hospital-acquired carbapenem non-susceptible Klebsiella and thus a pertinent setting to examine the overlap between isolates in clinical and non-clinical settings. We found no genotypic or phenotypic evidence for non-susceptibility to carbapenems outside the clinical environment. Although we noted occasional transmission between clinical and non-clinical settings, our data point to a limited role of animal and environmental reservoirs in the human acquisition of Klebsiella spp. We also provide a detailed genus-wide view of genomic diversity and population structure, including the identification of new groups.

Antibacterial resistance (ABR) is a major global health security threat, with a disproportionate burden on lower-and middle-income countries (LMICs). It is not understood how ‘One Health’, where human health is co-dependent on animal health and the environment, might impact the burden of ABR in LMICs. Thailand's 2017 “National Strategic Plan on Antimicrobial Resistance” (NSP-AMR) aims to reduce AMR morbidity by 50% through 20% reductions in human and 30% in animal antibacterial use (ABU). There is a need to understand the implications of such a plan within a One Health perspective. A model of ABU, gut colonisation with extended-spectrum beta-lactamase (ESBL)-producing bacteria and transmission was calibrated using estimates of the prevalence of ESBL-producing bacteria in Thailand. This model was used to project the reduction in human ABR over 20 years (2020–2040) for each One Health driver, including individual transmission rates between humans, animals and the environment, and to estimate the long-term impact of the NSP-AMR intervention. The model predicts that human ABU was the most important factor in reducing the colonisation of humans with resistant bacteria (maximum 65.7–99.7% reduction). The NSP-AMR is projected to reduce human colonisation by 6.0–18.8%, with more ambitious targets (30% reductions in human ABU) increasing this to 8.5–24.9%. Our model provides a simple framework to explain the mechanisms underpinning ABR, suggesting that future interventions targeting the simultaneous reduction of transmission and ABU would help to control ABR more effectively in Thailand.

Metagenomic high-throughput sequencing (mHTS) is a hypothesis-free, universal pathogen detection technique for determination of the DNA/RNA sequences in a variety of sample types and infectious syndromes. mHTS is still in its early stages of translating into clinical application. To support the development, implementation and standardization of mHTS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mHTS for viral diagnostics to share methodologies and experiences, and to develop application recommendations. This manuscript aims to provide practical recommendations for the wet lab procedures necessary for implementation of mHTS for virus diagnostics and to give recommendations for development and validation of laboratory methods, including mHTS quality assurance, control and quality assessment protocols.

Metagenomic next-generation sequencing (mNGS) is an untargeted technique for determination of microbial DNA/RNA sequences in a variety of sample types from patients with infectious syndromes. mNGS is still in its early stages of broader translation into clinical applications. To further support the development, implementation, optimization and standardization of mNGS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mNGS for viral diagnostics to share methodologies and experiences, and to develop application guidelines. Following the ENNGS publication Recommendations for the introduction of mNGS in clinical virology, part I: wet lab procedure in this journal, the current manuscript aims to provide practical recommendations for the bioinformatic analysis of mNGS data and reporting of results to clinicians.