Vaccine value profile for Klebsiella pneumoniae.

Klebsiella pneumoniae causes community- and healthcare-associated infections in children and adults. Globally in 2019, an estimated 1.27 million (95% Uncertainty Interval [UI]: 0.91-1.71) and 4.95 million (95% UI: 3.62-6.57) deaths were attributed to and associated with bacterial antimicrobial resistance (AMR), respectively. K. pneumoniae was the second leading pathogen in deaths attributed to AMR resistant bacteria. Furthermore, the rise of antimicrobial resistance in both community- and hospital-acquired infections is a concern for neonates and infants who are at high risk for invasive bacterial disease. There is a limited antibiotic pipeline for new antibiotics to treat multidrug resistant infections, and vaccines targeted against K. pneumoniae are considered to be of priority by the World Health Organization. Vaccination of pregnant women against K. pneumoniae could reduce the risk of invasive K.pneumoniae disease in their young offspring. In addition, vulnerable children, adolescents and adult populations at risk of K. pneumoniae disease with underlying diseases such as immunosuppression from underlying hematologic malignancy, chemotherapy, patients undergoing abdominal and/or urinary surgical procedures, or prolonged intensive care management are also potential target groups for a K. pneumoniae vaccine. A 'Vaccine Value Profile' (VVP) for K.pneumoniae, which contemplates vaccination of pregnant women to protect their babies from birth through to at least three months of age and other high-risk populations, provides a high-level, holistic assessment of the available information to inform the potential public health, economic and societal value of a pipeline of K. pneumoniae vaccines and other preventatives and therapeutics. This VVP was developed by a working group of subject matter experts from academia, non-profit organizations, public-private partnerships, and multi-lateral organizations, and in collaboration with stakeholders from the WHO. All contributors have extensive expertise on various elements of the K.pneumoniae VVP and collectively aimed to identify current research and knowledge gaps. The VVP was developed using only existing and publicly available information.

Evaluating the relationship between ciprofloxacin prescription and non-susceptibility in Salmonella Typhi in Blantyre, Malawi: an observational study.

BACKGROUND: Ciprofloxacin is the first-line drug for treating typhoid fever in many countries in Africa with a high disease burden, but the emergence of non-susceptibility poses a challenge to public health programmes. Through enhanced surveillance as part of vaccine evaluation, we investigated the occurrence and potential determinants of ciprofloxacin non-susceptibility in Blantyre, Malawi. METHODS: We conducted systematic surveillance of typhoid fever cases and antibiotic prescription in two health centres in Blantyre, Malawi, between Oct 1, 2016, and Oct 31, 2019, as part of the STRATAA and TyVAC studies. In addition, blood cultures were taken from eligible patients presenting at Queen Elizabeth Central Hospital, Blantyre, as part of routine diagnosis. Inclusion criteria were measured or reported fever, or clinical suspicion of sepsis. Microbiologically, we identified Salmonella enterica serotype Typhi (S Typhi) isolates with a ciprofloxacin non-susceptible phenotype from blood cultures, and used whole-genome sequencing to identify drug-resistance mutations and phylogenetic relationships. We constructed generalised linear regression models to investigate associations between the number of ciprofloxacin prescriptions given per month to study participants and the proportion of S Typhi isolates with quinolone resistance-determining region (QRDR) mutations in the following month. FINDINGS: From 46 989 blood cultures from Queen Elizabeth Central Hospital, 502 S Typhi isolates were obtained, 30 (6%) of which had either decreased ciprofloxacin susceptibility, or ciprofloxacin resistance. From 11 295 blood cultures from STRATAA and TyVAC studies, 241 microbiologically confirmed cases of typhoid fever were identified, and 198 isolates from 195 participants sequenced (mean age 12·8 years [SD 10·2], 53% female, 47% male). Between Oct 1, 2016, and Aug 31, 2019, of 177 typhoid fever cases confirmed by whole-genome sequencing, four (2%) were caused by S Typhi with QRDR mutations, compared with six (33%) of 18 cases between Sept 1 and Oct 31, 2019. This increase was associated with a preceding spike in ciprofloxacin prescriptions. Every additional prescription of ciprofloxacin given to study participants in the preceding month was associated with a 4·2% increase (95% CI 1·8-7·0) in the relative risk of isolating S Typhi with a QRDR mutation (p=0·0008). Phylogenetic analysis showed that S Typhi isolates with QRDR mutations from September and October, 2019, belonged to two distinct subclades encoding two different QRDR mutations, and were closely related (4-10 single-nucleotide polymorphisms) to susceptible S Typhi endemic to Blantyre. INTERPRETATION: We postulate a causal relationship between increased ciprofloxacin prescriptions and an increase in fluoroquinolone non-susceptibility in S Typhi. Decreasing ciprofloxacin use by improving typhoid diagnostics, and reducing typhoid fever cases through the use of an efficacious vaccine, could help to limit the emergence of resistance. FUNDING: Wellcome Trust, Bill & Melinda Gates Foundation, and National Institute for Health and Care Research (UK).

A validated pangenome-scale metabolic model for the Klebsiella pneumoniae species complex.

The Klebsiella pneumoniae species complex (KpSC) is a major source of nosocomial infections globally with high rates of resistance to antimicrobials. Consequently, there is growing interest in understanding virulence factors and their association with cellular metabolic processes for developing novel anti-KpSC therapeutics. Phenotypic assays have revealed metabolic diversity within the KpSC, but metabolism research has been neglected due to experiments being difficult and cost-intensive. Genome-scale metabolic models (GSMMs) represent a rapid and scalable in silico approach for exploring metabolic diversity, which compile genomic and biochemical data to reconstruct the metabolic network of an organism. Here we use a diverse collection of 507 KpSC isolates, including representatives of globally distributed clinically relevant lineages, to construct the most comprehensive KpSC pan-metabolic model to date, KpSC pan v2. Candidate metabolic reactions were identified using gene orthology to known metabolic genes, prior to manual curation via extensive literature and database searches. The final model comprised a total of 3550 reactions, 2403 genes and can simulate growth on 360 unique substrates. We used KpSC pan v2 as a reference to derive strain-specific GSMMs for all 507 KpSC isolates, and compared these to GSMMs generated using a prior KpSC pan-reference (KpSC pan v1) and two single-strain references. We show that KpSC pan v2 includes a greater proportion of accessory reactions (8.8 %) than KpSC pan v1 (2.5 %). GSMMs derived from KpSC pan v2 also generate more accurate growth predictions, with high median accuracies of 95.4 % (aerobic, n=37 isolates) and 78.8 % (anaerobic, n=36 isolates) for 124 matched carbon substrates. KpSC pan v2 is freely available at https://github.com/kelwyres/KpSC-pan-metabolic-model, representing a valuable resource for the scientific community, both as a source of curated metabolic information and as a reference to derive accurate strain-specific GSMMs. The latter can be used to investigate the relationship between KpSC metabolism and traits of interest, such as reservoirs, epidemiology, drug resistance or virulence, and ultimately to inform novel KpSC control strategies.

Recent advances in modelling Shigella infection.

Shigella is an important human-adapted pathogen which contributes to a large global burden of diarrhoeal disease. Together with the increasing threat of antimicrobial resistance and lack of an effective vaccine, there is great urgency to identify novel therapeutics and preventatives to combat Shigella infection. In this review, we discuss the development of innovative technologies and animal models to study mechanisms underlying Shigella infection of humans. We examine recent literature introducing (i) the organ-on-chip model, and its substantial contribution towards understanding the biomechanics of Shigella infection, (ii) the zebrafish infection model, which has delivered transformative insights into the epidemiological success of clinical isolates and the innate immune response to Shigella, (iii) a pioneering oral mouse model of shigellosis, which has helped to discover new inflammasome biology and protective mechanisms against shigellosis, and (iv) the controlled human infection model, which has been effective in translating basic research into human health impact and assessing suitability of novel vaccine candidates. We consider the recent contributions of each model and discuss where the future of modelling Shigella infection lies.

High-level nitrofurantoin resistance in a clinical isolate of Klebsiella pneumoniae: a comparative genomics and metabolomics analysis.

Nitrofurantoin is a commonly used chemotherapeutic agent in the treatment of uncomplicated urinary tract infections caused by the problematic multidrug resistant Gram-negative pathogen Klebsiella pneumoniae. The present study aims to elucidate the mechanism of nitrofurantoin action and high-level resistance in K. pneumoniae using whole-genome sequencing (WGS), qPCR analysis, mutation structural modeling and untargeted metabolomic analysis. WGS profiling of evolved highly resistant mutants (nitrofurantoin minimum inhibitory concentrations > 256 mg/L) revealed modified expression of several genes related to membrane transport (porin ompK36 and efflux pump regulator oqxR) and nitroreductase activity (ribC and nfsB, involved in nitrofurantoin reduction). Untargeted metabolomics analysis of total metabolites extracted at 1 and 4 h post-nitrofurantoin treatment revealed that exposure to the drug caused a delayed effect on the metabolome which was most pronounced after 4 h. Pathway enrichment analysis illustrated that several complex interrelated metabolic pathways related to nitrofurantoin bacterial killing (aminoacyl-tRNA biosynthesis, purine metabolism, central carbohydrate metabolism, and pantothenate and CoA biosynthesis) and the development of nitrofurantoin resistance (riboflavin metabolism) were significantly perturbed. This study highlights for the first time the key role of efflux pump regulator oqxR in nitrofurantoin resistance and reveals global metabolome perturbations in response to nitrofurantoin, in K. pneumoniae.IMPORTANCEA quest for novel antibiotics and revitalizing older ones (such as nitrofurantoin) for treatment of difficult-to-treat Gram-negative bacterial infections has become increasingly popular. The precise antibacterial activity of nitrofurantoin is still not fully understood. Furthermore, although the prevalence of nitrofurantoin resistance remains low currently, the drug's fast-growing consumption worldwide highlights the need to comprehend the emerging resistance mechanisms. Here, we used multidisciplinary techniques to discern the exact mechanism of nitrofurantoin action and high-level resistance in Klebsiella pneumoniae, a common cause of urinary tract infections for which nitrofurantoin is the recommended treatment. We found that the expression of multiple genes related to membrane transport (including active efflux and passive diffusion of drug molecules) and nitroreductase activity was modified in nitrofurantoin-resistant strains, including oqxR, the transcriptional regulator of the oqxAB efflux pump. Furthermore, complex interconnected metabolic pathways that potentially govern the nitrofurantoin-killing mechanisms (e.g., aminoacyl-tRNA biosynthesis) and nitrofurantoin resistance (riboflavin metabolism) were significantly inhibited following nitrofurantoin treatment. Our study could help inform the improvement of nitrofuran derivatives, the development of new pharmacophores, or drug combinations to support the resurgence of nitrofurantoin in the management of multidrug resistant K. pneumouniae infection.

Typhoid fever.

Typhoid fever is an invasive bacterial disease associated with bloodstream infection that causes a high burden of disease in Africa and Asia. Typhoid primarily affects individuals ranging from infants through to young adults. The causative organism, Salmonella enterica subsp. enterica serovar Typhi is transmitted via the faecal-oral route, crossing the intestinal epithelium and disseminating to systemic and intracellular sites, causing an undifferentiated febrile illness. Blood culture remains the practical reference standard for diagnosis of typhoid fever, where culture testing is available, but novel diagnostic modalities are an important priority under investigation. Since 2017, remarkable progress has been made in defining the global burden of both typhoid fever and antimicrobial resistance; in understanding disease pathogenesis and immunological protection through the use of controlled human infection; and in advancing effective vaccination programmes through strategic multipartner collaboration and targeted clinical trials in multiple high-incidence priority settings. This Primer thus offers a timely update of progress and perspective on future priorities for the global scientific community.

Evolution and transmission of antibiotic resistance is driven by Beijing lineage Mycobacterium tuberculosis in Vietnam.

IMPORTANCE: Drug-resistant tuberculosis (TB) infection is a growing and potent concern, and combating it will be necessary to achieve the WHO's goal of a 95% reduction in TB deaths by 2035. While prior studies have explored the evolution and spread of drug resistance, we still lack a clear understanding of the fitness costs (if any) imposed by resistance-conferring mutations and the role that Mtb genetic lineage plays in determining the likelihood of resistance evolution. This study offers insight into these questions by assessing the dynamics of resistance evolution in a high-burden Southeast Asian setting with a diverse lineage composition. It demonstrates that there are clear lineage-specific differences in the dynamics of resistance acquisition and transmission and shows that different lineages evolve resistance via characteristic mutational pathways.

Genomics for antimicrobial resistance surveillance to support infection prevention and control in health-care facilities.

Integration of genomic technologies into routine antimicrobial resistance (AMR) surveillance in health-care facilities has the potential to generate rapid, actionable information for patient management and inform infection prevention and control measures in near real time. However, substantial challenges limit the implementation of genomics for AMR surveillance in clinical settings. Through a workshop series and online consultation, international experts from across the AMR and pathogen genomics fields convened to review the evidence base underpinning the use of genomics for AMR surveillance in a range of settings. Here, we summarise the identified challenges and potential benefits of genomic AMR surveillance in health-care settings, and outline the recommendations of the working group to realise this potential. These recommendations include the definition of viable and cost-effective use cases for genomic AMR surveillance, strengthening training competencies (particularly in bioinformatics), and building capacity at local, national, and regional levels using hub and spoke models.

Genomics for public health and international surveillance of antimicrobial resistance.

Historically, epidemiological investigation and surveillance for bacterial antimicrobial resistance (AMR) has relied on low-resolution isolate-based phenotypic analyses undertaken at local and national reference laboratories. Genomic sequencing has the potential to provide a far more high-resolution picture of AMR evolution and transmission, and is already beginning to revolutionise how public health surveillance networks monitor and tackle bacterial AMR. However, the routine integration of genomics in surveillance pipelines still has considerable barriers to overcome. In 2022, a workshop series and online consultation brought together international experts in AMR and pathogen genomics to assess the status of genomic applications for AMR surveillance in a range of settings. Here we focus on discussions around the use of genomics for public health and international AMR surveillance, noting the potential advantages of, and barriers to, implementation, and proposing recommendations from the working group to help to drive the adoption of genomics in public health AMR surveillance. These recommendations include the need to build capacity for genome sequencing and analysis, harmonising and standardising surveillance systems, developing equitable data sharing and governance frameworks, and strengthening interactions and relationships among stakeholders at multiple levels.

Evidence review and recommendations for the implementation of genomics for antimicrobial resistance surveillance: reports from an international expert group.

Nearly a century after the beginning of the antibiotic era, which has been associated with unparalleled improvements in human health and reductions in mortality associated with infection, the dwindling pipeline for new antibiotic classes coupled with the inevitable spread of antimicrobial resistance (AMR) poses a major global challenge. Historically, surveillance of bacteria with AMR typically relied on phenotypic analysis of isolates taken from infected individuals, which provides only a low-resolution view of the epidemiology behind an individual infection or wider outbreak. Recent years have seen increasing adoption of powerful new genomic technologies with the potential to revolutionise AMR surveillance by providing a high-resolution picture of the AMR profile of the bacteria causing infections and providing real-time actionable information for treating and preventing infection. However, many barriers remain to be overcome before genomic technologies can be adopted as a standard part of routine AMR surveillance around the world. Accordingly, the Surveillance and Epidemiology of Drug-resistant Infections Consortium convened an expert working group to assess the benefits and challenges of using genomics for AMR surveillance. In this Series, we detail these discussions and provide recommendations from the working group that can help to realise the massive potential benefits for genomics in surveillance of AMR.

Bactabolize is a tool for high-throughput generation of bacterial strain-specific metabolic models.

Metabolic capacity can vary substantially within a bacterial species, leading to ecological niche separation, as well as differences in virulence and antimicrobial susceptibility. Genome-scale metabolic models are useful tools for studying the metabolic potential of individuals, and with the rapid expansion of genomic sequencing there is a wealth of data that can be leveraged for comparative analysis. However, there exist few tools to construct strain-specific metabolic models at scale. Here, we describe Bactabolize, a reference-based tool which rapidly produces strain-specific metabolic models and growth phenotype predictions. We describe a pan reference model for the priority antimicrobial-resistant pathogen, Klebsiella pneumoniae, and a quality control framework for using draft genome assemblies as input for Bactabolize. The Bactabolize-derived model for K. pneumoniae reference strain KPPR1 performed comparatively or better than currently available automated approaches CarveMe and gapseq across 507 substrate and 2317 knockout mutant growth predictions. Novel draft genomes passing our systematically defined quality control criteria resulted in models with a high degree of completeness (≥99% genes and reactions captured compared to models derived from matched complete genomes) and high accuracy (mean 0.97, n=10). We anticipate the tools and framework described herein will facilitate large-scale metabolic modelling analyses that broaden our understanding of diversity within bacterial species and inform novel control strategies for priority pathogens.

Direct inference and control of genetic population structure from RNA sequencing data.

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

Shigella Serotypes Associated With Carriage in Humans Establish Persistent Infection in Zebrafish.

Shigella represents a paraphyletic group of enteroinvasive Escherichia coli. More than 40 Shigella serotypes have been reported. However, most cases within the men who have sex with men (MSM) community are attributed to 3 serotypes: Shigella sonnei unique serotype and Shigella flexneri 2a and 3a serotypes. Using the zebrafish model, we demonstrate that Shigella can establish persistent infection in vivo. Bacteria are not cleared by the immune system and become antibiotic tolerant. Establishment of persistent infection depends on the O-antigen, a key constituent of the bacterial surface and a serotype determinant. Representative isolates associated with MSM transmission persist in zebrafish, while representative isolates of a serotype not associated with MSM transmission do not. Isolates of a Shigella serotype establishing persistent infections elicited significantly less macrophage death in vivo than isolates of a serotype unable to persist. We conclude that zebrafish are a valuable platform to illuminate factors underlying establishment of Shigella persistent infection in humans.

Unlocking the Potential of Genomic Data to Inform Typhoid Fever Control Policy: Supportive Resources for Genomic Data Generation, Analysis, and Visualization.

The global response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic demonstrated the value of timely and open sharing of genomic data with standardized metadata to facilitate monitoring of the emergence and spread of new variants. Here, we make the case for the value of Salmonella Typhi (S. Typhi) genomic data and demonstrate the utility of freely available platforms and services that support the generation, analysis, and visualization of S. Typhi genomic data on the African continent and more broadly by introducing the Africa Centres for Disease Control and Prevention's Pathogen Genomics Initiative, SEQAFRICA, Typhi Pathogenwatch, TyphiNET, and the Global Typhoid Genomics Consortium.

Within-patient and global evolutionary dynamics of Klebsiella pneumoniae ST17.

Klebsiella pneumoniae sequence type (ST) 17 is a global problem clone that causes multidrug-resistant (MDR) hospital infections worldwide. In 2008-2009, an outbreak of MDR ST17 occurred at a neonatal intensive care unit (NICU) in Stavanger, Norway. Fifty-seven children were colonized. We observed intestinal persistence of ST17 in all of the children for up to two years after hospital discharge. Here, we investigated the within-host evolution of ST17 in 45 of those children during long-term colonization and compared the outbreak with 254 global strains. Ninety-two outbreak-related isolates were whole-genome sequenced. They had capsule locus KL25, O locus O5 and carried yersiniabactin. During within-host colonization ST17 remained stable with few single nucleotide polymorphisms, no acquisition of antimicrobial resistance (AMR) or virulence determinants, and persistent carriage of a bla CTX-M-15-encoding IncFII(K) IncFIB(K) plasmid (pKp2177_1). The global collection included ST17 from 1993 to 2020 from 34 countries, that were from human infection (41.3%), colonization (39.3%) and respiratory specimens (7.3%), from animals (9.3%), and from the environment (2.7%). We estimate that ST17 emerged mid-to-late 19th century (1859, 95 % HPD 1763-1939) and diversified through recombinations of the K and O loci to form several sublineages, with various AMR genes, virulence loci and plasmids. There was limited evidence of persistence of AMR genes in any of these lineages. A globally disseminated sublineage with KL25/O5 accounted for 52.7 % of the genomes. It included a monophyletic subclade that emerged in the mid-1980s, which comprised the Stavanger NICU outbreak and 10 genomes from three other countries, which all carried pKp2177_1. The plasmid was also observed in a KL155/OL101 subclade from the 2000s. Three clonal expansions of ST17 were identified; all were healthcare-associated and carried either yersiniabactin and/or pKp2177_1. To conclude, ST17 is globally disseminated and associated with opportunistic hospital-acquired infections. It contributes to the burden of global MDR infections, but many diverse lineages persist without acquired AMR. We hypothesize that non-human sources and human colonization may play a crucial role for severe infections in vulnerable patients, such as preterm neonates.

Acquisition of a large virulence plasmid (pINV) promoted temperature-dependent virulence and global dispersal of O96:H19 enteroinvasive Escherichia coli.

Enteroinvasive Escherichia coli (EIEC) and Shigella are closely related agents of bacillary dysentery. It is widely viewed that EIEC and Shigella species evolved from E. coli via independent acquisitions of a large virulence plasmid (pINV) encoding a type 3 secretion system (T3SS). Sequence Type (ST)99 O96:H19 E. coli is a novel clone of EIEC responsible for recent outbreaks in Europe and South America. Here, we use 92 whole genome sequences to reconstruct a dated phylogeny of ST99 E. coli, revealing distinct phylogenomic clusters of pINV-positive and -negative isolates. To study the impact of pINV acquisition on the virulence of this clone, we developed an EIEC-zebrafish infection model showing that virulence of ST99 EIEC is thermoregulated. Strikingly, zebrafish infection using a T3SS-deficient ST99 EIEC strain and the oldest available pINV-negative isolate reveals a separate, temperature-independent mechanism of virulence, indicating that ST99 non-EIEC strains were virulent before pINV acquisition. Taken together, these results suggest that an already pathogenic E. coli acquired pINV and that virulence of ST99 isolates became thermoregulated once pINV was acquired. IMPORTANCE Enteroinvasive Escherichia coli (EIEC) and Shigella are etiological agents of bacillary dysentery. Sequence Type (ST)99 is a clone of EIEC hypothesized to cause human disease by the recent acquisition of pINV, a large plasmid encoding a type 3 secretion system (T3SS) that confers the ability to invade human cells. Using Bayesian analysis and zebrafish larvae infection, we show that the virulence of ST99 EIEC isolates is highly dependent on temperature, while T3SS-deficient isolates encode a separate temperature-independent mechanism of virulence. These results indicate that ST99 non-EIEC isolates may have been virulent before pINV acquisition and highlight an important role of pINV acquisition in the dispersal of ST99 EIEC in humans, allowing wider dissemination across Europe and South America.

A point mutation in recC associated with subclonal replacement of carbapenem-resistant Klebsiella pneumoniae ST11 in China.

Adaptation to selective pressures is crucial for clinically important pathogens to establish epidemics, but the underlying evolutionary drivers remain poorly understood. The current epidemic of carbapenem-resistant Klebsiella pneumoniae (CRKP) poses a significant threat to public health. In this study we analyzed the genome sequences of 794 CRKP bloodstream isolates collected in 40 hospitals in China between 2014 and 2019. We uncovered a subclonal replacement in the predominant clone ST11, where the previously prevalent subclone OL101:KL47 was replaced by O2v1:KL64 over time in a stepwise manner. O2v1:KL64 carried a higher load of mobile genetic elements, and a point mutation exclusively detected in the recC of O2v1:KL64 significantly promotes recombination proficiency. The epidemic success of O2v1:KL64 was further associated with a hypervirulent sublineage with enhanced resistance to phagocytosis, sulfamethoxazole-trimethoprim, and tetracycline. The phenotypic alterations were linked to the overrepresentation of hypervirulence determinants and antibiotic genes conferred by the acquisition of an rmpA-positive pLVPK-like virulence plasmid and an IncFII-type multidrug-resistant plasmid, respectively. The dissemination of the sublineage was further promoted by more frequent inter-hospital transmission. The results collectively demonstrate that the expansion of O2v1:KL64 is correlated to a repertoire of genomic alterations convergent in a subpopulation with evolutionary advantages.

Assembling the perfect bacterial genome using Oxford Nanopore and Illumina sequencing.

A perfect bacterial genome assembly is one where the assembled sequence is an exact match for the organism's genome-each replicon sequence is complete and contains no errors. While this has been difficult to achieve in the past, improvements in long-read sequencing, assemblers, and polishers have brought perfect assemblies within reach. Here, we describe our recommended approach for assembling a bacterial genome to perfection using a combination of Oxford Nanopore Technologies long reads and Illumina short reads: Trycycler long-read assembly, Medaka long-read polishing, Polypolish short-read polishing, followed by other short-read polishing tools and manual curation. We also discuss potential pitfalls one might encounter when assembling challenging genomes, and we provide an online tutorial with sample data (github.com/rrwick/perfect-bacterial-genome-tutorial).

Nanopore-only assemblies for genomic surveillance of the global priority drug-resistant pathogen, Klebsiella pneumoniae.

Oxford Nanopore Technologies (ONT) sequencing has rich potential for genomic epidemiology and public health investigations of bacterial pathogens, particularly in low-resource settings and at the point of care, due to its portability and affordability. However, low base-call accuracy has limited the reliability of ONT data for critical tasks such as antimicrobial resistance (AMR) and virulence gene detection and typing, serotype prediction, and cluster identification. Thus, Illumina sequencing remains the standard for genomic surveillance despite higher capital and running costs. We tested the accuracy of ONT-only assemblies for common applied bacterial genomics tasks (genotyping and cluster detection, implemented via Kleborate, Kaptive and Pathogenwatch), using data from 54 unique Klebsiella pneumoniae isolates. ONT reads generated via MinION with R9.4.1 flowcells were basecalled using three alternative models [Fast, High-accuracy (HAC) and Super-accuracy (SUP), available within ONT's Guppy software], assembled with Flye and polished using Medaka. Accuracy of typing using ONT-only assemblies was compared with that of Illumina-only and hybrid ONT+Illumina assemblies, constructed from the same isolates as reference standards. The most resource-intensive ONT-assembly approach (SUP basecalling, with or without Medaka polishing) performed best, yielding reliable capsule (K) type calls for all strains (100 % exact or best matching locus), reliable multi-locus sequence type (MLST) assignment (98.3 % exact match or single-locus variants), and good detection of acquired AMR genes and mutations (88-100 % correct identification across the various drug classes). Distance-based trees generated from SUP+Medaka assemblies accurately reflected overall genetic relationships between isolates. The definition of outbreak clusters from ONT-only assemblies was problematic due to inflation of SNP counts by high base-call errors. However, ONT data could be reliably used to 'rule out' isolates of distinct lineages from suspected transmission clusters. HAC basecalling + Medaka polishing performed similarly to SUP basecalling without polishing. Therefore, we recommend investing compute resources into basecalling (SUP model), wherever compute resources and time allow, and note that polishing is also worthwhile for improved performance. Overall, our results show that MLST, K type and AMR determinants can be reliably identified with ONT-only R9.4.1 flowcell data. However, cluster detection remains challenging with this technology.