Pathogen diversity and antimicrobial resistance transmission of Salmonella enterica serovars Typhi and Paratyphi A in Bangladesh, Nepal, and Malawi: a genomic epidemiological study.

BACKGROUND: Enteric fever is a serious public health concern. The causative agents, Salmonella enterica serovars Typhi and Paratyphi A, frequently have antimicrobial resistance (AMR), leading to limited treatment options and poorer clinical outcomes. We investigated the genomic epidemiology, resistance mechanisms, and transmission dynamics of these pathogens at three urban sites in Africa and Asia. METHODS: S Typhi and S Paratyphi A bacteria isolated from blood cultures of febrile children and adults at study sites in Dhaka (Bangladesh), Kathmandu (Nepal), and Blantyre (Malawi) during STRATAA surveillance were sequenced. Isolates were charactered in terms of their serotypes, genotypes (according to GenoTyphi and Paratype), molecular determinants of AMR, and population structure. We used phylogenomic analyses incorporating globally representative genomic data from previously published surveillance studies and ancestral state reconstruction to differentiate locally circulating from imported pathogen AMR variants. Clusters of sequences without any single-nucleotide variants in their core genome were identified and used to explore spatiotemporal patterns and transmission dynamics. FINDINGS: We sequenced 731 genomes from isolates obtained during surveillance across the three sites between Oct 1, 2016, and Aug 31, 2019 (24 months in Dhaka and Kathmandu and 34 months in Blantyre). S Paratyphi A was present in Dhaka and Kathmandu but not Blantyre. S Typhi genotype 4.3.1 (H58) was common in all sites, but with different dominant variants (4.3.1.1.EA1 in Blantyre, 4.3.1.1 in Dhaka, and 4.3.1.2 in Kathmandu). Multidrug resistance (ie, resistance to chloramphenicol, co-trimoxazole, and ampicillin) was common in Blantyre (138 [98%] of 141 cases) and Dhaka (143 [32%] of 452), but absent from Kathmandu. Quinolone-resistance mutations were common in Dhaka (451 [>99%] of 452) and Kathmandu (123 [89%] of 138), but not in Blantyre (three [2%] of 141). Azithromycin-resistance mutations in acrB were rare, appearing only in Dhaka (five [1%] of 452). Phylogenetic analyses showed that most cases derived from pre-existing, locally established pathogen variants; 702 (98%) of 713 drug-resistant infections resulted from local circulation of AMR variants, not imported variants or recent de novo emergence; and pathogen variants circulated across age groups. 479 (66%) of 731 cases clustered with others that were indistinguishable by point mutations; individual clusters included multiple age groups and persisted for up to 2·3 years, and AMR determinants were invariant within clusters. INTERPRETATION: Enteric fever was associated with locally established pathogen variants that circulate across age groups. AMR infections resulted from local transmission of resistant strains. These results form a baseline against which to monitor the impacts of control measures. FUNDING: Wellcome Trust, Bill & Melinda Gates Foundation, EU Horizon 2020, and UK National Institute for Health and Care Research.

In vivo selection of carbapenem resistance during persistent Klebsiella pneumoniae sequence type 395 bloodstream infection due to OmpK36 deletion.

Non-carbapenemase-producing carbapenem-resistant Enterobacterales (non-CP CRE) may be associated with a grave outcome. The common underlying mechanism is beta-lactamases and mutations in outer membrane porins. We report a case of a deep-seated infection caused by Klebsiella pneumoniae ST395 not amenable to source control, involving recurrent bloodstream infection, resulting in in vivo selection of carbapenem resistance under therapy. Three consecutive K. pneumoniae blood isolates were studied using short- and long-read sequencing. The genomes were subject to resistome and virulome, phylogenetic, and plasmid analyses. ompK36 porins were analyzed at the nucleotide and amino acid levels. Genomes were compared to 297 public ST395 K. pneumoniae genomes using cgMLST, resistome, and porin analyses and the EuSCAPE project. Relevant ompK36 and micF sequences were extracted and analyzed as above. The three sequential K. pneumoniae blood isolates belonged to the same clone. Subsequent CR isolates revealed a new large deletion of the ompK36 gene also involving the upstream region (deletion of micF). Comparison with public ST395 genomes revealed the study isolates belonged to clade B, representing a separate clone. N-terminal large ompK36 truncations were uncommon in both public data sets. In vivo selection of non-CP CRE K. pneumoniae could have substantial clinical implications. Such selection should be scrutinized through repeated cultures and frequent susceptibility testing during antimicrobial treatment, especially in the context of persistent or recurrent bloodstream infections and when adequate source control cannot be achieved. The occurrence of an unusually large deletion involving the ompK36 locus and upstream micF should be further studied.

Precision public health in the era of genomics and big data.

Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level-thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for 'precision' to enhance traditional public health approaches.

PHA4GE quality control contextual data tags: standardized annotations for sharing public health sequence datasets with known quality issues to facilitate testing and training.

As public health laboratories expand their genomic sequencing and bioinformatics capacity for the surveillance of different pathogens, labs must carry out robust validation, training, and optimization of wet- and dry-lab procedures. Achieving these goals for algorithms, pipelines and instruments often requires that lower quality datasets be made available for analysis and comparison alongside those of higher quality. This range of data quality in reference sets can complicate the sharing of sub-optimal datasets that are vital for the community and for the reproducibility of assays. Sharing of useful, but sub-optimal datasets requires careful annotation and documentation of known issues to enable appropriate interpretation, avoid being mistaken for better quality information, and for these data (and their derivatives) to be easily identifiable in repositories. Unfortunately, there are currently no standardized attributes or mechanisms for tagging poor-quality datasets, or datasets generated for a specific purpose, to maximize their utility, searchability, accessibility and reuse. The Public Health Alliance for Genomic Epidemiology (PHA4GE) is an international community of scientists from public health, industry and academia focused on improving the reproducibility, interoperability, portability, and openness of public health bioinformatic software, skills, tools and data. To address the challenges of sharing lower quality datasets, PHA4GE has developed a set of standardized contextual data tags, namely fields and terms, that can be included in public repository submissions as a means of flagging pathogen sequence data with known quality issues, increasing their discoverability. The contextual data tags were developed through consultations with the community including input from the International Nucleotide Sequence Data Collaboration (INSDC), and have been standardized using ontologies - community-based resources for defining the tag properties and the relationships between them. The standardized tags are agnostic to the organism and the sequencing technique used and thus can be applied to data generated from any pathogen using an array of sequencing techniques. The tags can also be applied to synthetic (lab created) data. The list of standardized tags is maintained by PHA4GE and can be found at https://github.com/pha4ge/contextual_data_QC_tags. Definitions, ontology IDs, examples of use, as well as a JSON representation, are provided. The PHA4GE QC tags were tested, and are now implemented, by the FDA's GenomeTrakr laboratory network as part of its routine submission process for SARS-CoV-2 wastewater surveillance. We hope that these simple, standardized tags will help improve communication regarding quality control in public repositories, in addition to making datasets of variable quality more easily identifiable. Suggestions for additional tags can be submitted to PHA4GE via the New Term Request Form in the GitHub repository. By providing a mechanism for feedback and suggestions, we also expect that the tags will evolve with the needs of the community.

Genomic diversity and antimicrobial resistance in clinical Klebsiella pneumoniae isolates from tertiary hospitals in Southern Ghana.

OBJECTIVES: Comprehensive data on the genomic epidemiology of hospital-associated Klebsiella pneumoniae in Ghana are scarce. This study investigated the genomic diversity, antimicrobial resistance patterns, and clonal relationships of 103 clinical K. pneumoniae isolates from five tertiary hospitals in Southern Ghana-predominantly from paediatric patients aged under 5 years (67/103; 65%), with the majority collected from urine (32/103; 31%) and blood (25/103; 24%) cultures. METHODS: We generated hybrid Nanopore-Illumina assemblies and employed Pathogenwatch for genotyping via Kaptive [capsular (K) locus and lipopolysaccharide (O) antigens] and Kleborate (antimicrobial resistance and hypervirulence) and determined clonal relationships using core-genome MLST (cgMLST). RESULTS: Of 44 distinct STs detected, ST133 was the most common, comprising 23% of isolates (n = 23/103). KL116 (28/103; 27%) and O1 (66/103; 64%) were the most prevalent K-locus and O-antigen types. Single-linkage clustering highlighted the global spread of MDR clones such as ST15, ST307, ST17, ST11, ST101 and ST48, with minimal allele differences (1-5) from publicly available genomes worldwide. Conversely, 17 isolates constituted novel clonal groups and lacked close relatives among publicly available genomes, displaying unique genetic diversity within our study population. A significant proportion of isolates (88/103; 85%) carried resistance genes for ≥3 antibiotic classes, with the blaCTX-M-15 gene present in 78% (n = 80/103). Carbapenem resistance, predominantly due to blaOXA-181 and blaNDM-1 genes, was found in 10% (n = 10/103) of the isolates. CONCLUSIONS: Our findings reveal a complex genomic landscape of K. pneumoniae in Southern Ghana, underscoring the critical need for ongoing genomic surveillance to manage the substantial burden of antimicrobial resistance.

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.

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.

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).

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.

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.

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.

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.