BACKGROUND: Microbial genome-wide association studies (GWAS) are crucial for linking genetic variation to phenotypic traits in bacteria. However, current tools often involve complex manual processing, limited scalability, and fragmented workflows, which constrain large-scale or routine bacterial GWAS. RESULTS: We developed BaGPipe, an automated and flexible bacterial GWAS pipeline built using Nextflow and incorporating Pyseer for association analysis. BaGPipe integrates pre-processing, statistical analysis, and downstream visualisation into a unified workflow that is reproducible and easy to deploy across diverse computational environments. BaGPipe was validated on a publicly available dataset of Streptococcus pneumoniae whole-genome sequences, and reproduced published findings with improved computational efficiency. BaGPipe was then applied to a dataset of Staphylococcus aureus whole-genome sequences, successfully identifying known and novel antibiotic resistance associations. CONCLUSIONS: By offering an accessible, efficient, and reproducible platform, BaGPipe accelerates bacterial GWAS and facilitates deeper exploration into the genetic underpinnings of phenotypic traits. BaGPipe is freely available at https://github.com/sanger-pathogens/BaGPipe .

The increasing threat from infection with drug-resistant pathogens is among the most serious public health challenges of our time. Formed by Wellcome in 2018, the Surveillance and Epidemiology of Drug-Resistant Infections Consortium (SEDRIC) is an international think tank whose aim is to inform policy and change the way countries track, share, and analyse data relating to drug-resistant infections, by defining knowledge gaps and identifying barriers to the delivery of global surveillance. SEDRIC delivers its aims through discussions and analyses by world-leading scientists that result in recommendations and advocacy to Wellcome and others. As a result, SEDRIC has made key contributions in furthering global and national actions. Here, we look back at the work of the consortium between 2018-2024, highlighting notable successes. We provide specific examples where technical analyses and recommendations have helped to inform policy and funding priorities that will have real-world impact on the surveillance and epidemiology of infections with drug-resistant pathogens.

Combining antibiotics remains a promising approach to treat patients and to prevent the emergence of antimicrobial resistance

OBJECTIVE:This study evaluated drug resistance profiles of Mycobacterium tuberculosis (Mtb) isolates in West Java, Indonesia through phenotypic and genomic approaches. METHODS:We performed phenotypic drug-susceptibility testing (DST), coupled with whole-genome sequencing (WGS) of 142 Mtb isolates identified as RIF-R (Rifampicin resistant) using the Xpert MTB/RIF platform. RESULTS:We found 107/142 (75%) isolates had high-level isoniazid resistance (INH-R) and rifampicin resistance (RIF-R). Of 107 isolates, we found two had novel katG mutations and three had large genome deletions encompassing the katG gene conferring INH-R. We also did not detect pre-existing mutations resistant to new and repurposed oral drugs bedaquiline (BDQ), pretomanid (Pa) and linezolid (LZD). CONCLUSIONS:Known drug-resistance conferring mutations reported in this study can be detected by the newly launched Xpert MTB/XDR together with Xpert MTB/RIF, providing clinicians with an expanded drug-susceptibility report without the need for culturing and WGS. On the other hand,the novel mutations and deletions found in this study are escaping routine diagnostics and could drive outbreaks of MDR-TB in Indonesia. The mass rollout of new and repurposed drugs for the treatment of drug-resistant TB in Indonesia is reassured by the absence of pre-existing mutations in this study. However, tools for rapid detection of resistance to these new drugs are urgently required to circumvent treatment-emergent resistance.

Antimicrobial resistance continues to be a growing threat globally, specifically in health-care settings in which antimicrobial-resistant pathogens cause a substantial proportion of health-care-associated infections (HAIs). Next-generation sequencing (NGS) and the analysis of the data produced therein (ie, bioinformatics) represent an opportunity to enhance our capacity to address these threats. The 3rd Geneva Infection Prevention and Control Think Tank brought together experts to identify gaps, propose solutions, and set priorities for the use of NGS for HAIs and antimicrobial-resistant pathogens. The major deliverable recommendation from this meeting was a proposed framework for implementing the sequencing of HAI pathogens, specifically those harbouring antimicrobial-resistance mechanisms. The key components of the proposed framework relate to wet laboratory quality, sequence data quality, database and tool selection, bioinformatic analyses, data sharing, and NGS data integration, to support public health and actions for infection prevention and control. In this Personal View we detail and discuss the framework in the context of global implementation, specifically in low-income and middle-income countries.

The increasing threat from infection with drug-resistant pathogens is among the most serious public health challenges of our time. Formed by Wellcome in 2018, the Surveillance and Epidemiology of Drug-Resistant Infections Consortium (SEDRIC) is an international think tank whose aim is to inform policy and change the way countries track, share, and analyse data relating to drug-resistant infections, by defining knowledge gaps and identifying barriers to the delivery of global surveillance. SEDRIC delivers its aims through discussions and analyses by world-leading scientists that result in recommendations and advocacy to Wellcome and others. As a result, SEDRIC has made key contributions in furthering global and national actions. Here, we look back at the work of the consortium between 2018-2024, highlighting notable successes. We provide specific examples where technical analyses and recommendations have helped to inform policy and funding priorities that will have real-world impact on the surveillance and epidemiology of infections with drug-resistant pathogens.

Staphylococcus aureus is an important human pathogen and a commensal of the human nose and skin. Survival and persistence during colonisation are likely major drivers of S. aureus evolution. Here we applied a genome-wide mutation enrichment approach to a genomic dataset of 3060 S. aureus colonization isolates from 791 individuals. Despite limited within-host genetic diversity, we observed an excess of protein-altering mutations in metabolic genes, in regulators of quorum-sensing (agrA and agrC) and in known antibiotic targets (fusA, pbp2, dfrA and ileS). We demonstrated the phenotypic effect of multiple adaptive mutations in vitro, including changes in haemolytic activity, antibiotic susceptibility, and metabolite utilisation. Nitrogen metabolism showed the strongest evidence of adaptation, with the assimilatory nitrite reductase (nasD) and urease (ureG) showing the highest mutational enrichment. We identified a nasD natural mutant with enhanced growth under urea as the sole nitrogen source. Inclusion of 4090 additional isolate genomes from 731 individuals revealed eight more genes including sasA/sraP, darA/pstA, and rsbU with signals of adaptive variation that warrant further characterisation. Our study provides a comprehensive picture of the heterogeneity of S. aureus adaptive changes during colonisation, and a robust methodological approach applicable to study in host adaptive evolution in other bacterial pathogens.

BACKGROUND:DNA sequencing could become an alternative to in vitro antibiotic susceptibility testing (AST) methods for determining antibiotic resistance by detecting genetic determinants associated with decreased antibiotic susceptibility. Here, we aimed to assess and improve the accuracy of antibiotic resistance determination from Enterococcus faecium genomes for diagnosis and surveillance purposes. METHODS:In this retrospective diagnostic accuracy study, we first conducted a literature search in PubMed on Jan 14, 2021, to compile a catalogue of genes and mutations predictive of antibiotic resistance in E faecium. We then evaluated the diagnostic accuracy of this database to determine susceptibility to 12 different, clinically relevant antibiotics using a diverse population of 4382 E faecium isolates with available whole-genome sequences and in vitro culture-based AST phenotypes. Isolates were obtained from various sources in 11 countries worldwide between 2000 and 2018. We included isolates tested with broth microdilution, Vitek 2, and disc diffusion, and antibiotics with at least 50 susceptible and 50 resistant isolates. Phenotypic resistance was derived from raw minimum inhibitory concentrations and measured inhibition diameters, and harmonised primarily using the breakpoints set by the European Committee on Antimicrobial Susceptibility Testing. A bioinformatics pipeline was developed to process raw sequencing reads, identify antibiotic resistance genetic determinants, and report genotypic resistance. We used our curated database, as well as ResFinder, AMRFinderPlus, and LRE-Finder, to assess the accuracy of genotypic predictions against phenotypic resistance. FINDINGS:We curated a catalogue of 228 genetic markers involved in resistance to 12 antibiotics in E faecium. Very accurate genotypic predictions were obtained for ampicillin (sensitivity 99·7% [95% CI 99·5-99·9] and specificity 97·9% [95·8-99·0]), ciprofloxacin (98·0% [96·4-98·9] and 98·8% [95·9-99·7]), vancomycin (98·8% [98·3-99·2] and 98·8% [98·0-99·3]), and linezolid resistance (after re-testing false negatives: 100·0% [90·8-100·0] and 98·3% [97·8-98·7]). High sensitivity was obtained for tetracycline (99·5% [99·1-99·7]), teicoplanin (98·9% [98·4-99·3]), and high-level resistance to aminoglycosides (97·7% [96·6-98·4] for streptomycin and 96·8% [95·8-97·5] for gentamicin), although at lower specificity (60-90%). Sensitivity was expectedly low for daptomycin (73·6% [65·1-80·6]) and tigecycline (38·3% [27·1-51·0]), for which the genetic basis of resistance is not fully characterised. Compared with other antibiotic resistance databases and bioinformatic tools, our curated database was similarly accurate at detecting resistance to ciprofloxacin and linezolid and high-level resistance to streptomycin and gentamicin, but had better sensitivity for detecting resistance to ampicillin, tigecycline, daptomycin, and quinupristin-dalfopristin, and better specificity for ampicillin, vancomycin, teicoplanin, and tetracycline resistance. In a validation dataset of 382 isolates, similar or improved diagnostic accuracies were also achieved. INTERPRETATION:To our knowledge, this work represents the largest published evaluation to date of the accuracy of antibiotic susceptibility predictions from E faecium genomes. The results and resources will facilitate the adoption of whole-genome sequencing as a tool for the diagnosis and surveillance of antimicrobial resistance in E faecium. A complete characterisation of the genetic basis of resistance to last-line antibiotics, and the mechanisms mediating antibiotic resistance silencing, are needed to close the remaining sensitivity and specificity gaps in genotypic predictions. FUNDING:Wellcome Trust, UK Department of Health, British Society for Antimicrobial Chemotherapy, Academy of Medical Sciences and the Health Foundation, Medical Research Council Newton Fund, Vietnamese Ministry of Science and Technology, and European Society of Clinical Microbiology and Infectious Disease.

Summary Background Environmental acquisition of Burkholderia pseudomallei can cause melioidosis, a life-threatening yet underreported disease. Understanding environmental exposure is essential for effective public health interventions, yet existing tools are limited in their ability to quantify exposure risks. Methods We conducted two complementary studies across a 15,118 km2 area of northeast Thailand to improve detection methods and investigate risk factors for melioidosis. In the first study, we compared a newly developed, equipment-light CRISPR-based assay (CRISPR-BP34) with conventional culture methods using both spiked samples and real water samples from household and community sources (November 2020 - November 2021). The second study involved a case-control analysis of 1,135 participants (October 2019 - January 2023) to evaluate the association between environmental exposure to B. pseudomallei (detected in Study 1) and melioidosis risk. Findings The CRISPR-BP34 assay demonstrated improved sensitivity (93.52% vs 19.44% for conventional methods) and specificity (100% vs 97.98%), allowing for more accurate detection of B. pseudomallei and exposure risk quantification. Environmental exposure to B. pseudomallei in water sources within a 10 km radius of participant households was significantly associated with increased melioidosis risk (OR: 2.74 [95% CI 1.38-5.48]). This risk was also heightened by known factors: occupational exposure among agricultural workers (4.46 [2.91-6.91]), and health factors like elevated hemoglobin A1c, indicating diabetes (1.35 [1.19-1.31]). Interpretation Our findings underscore the impact of environmental contamination on melioidosis risk. The robust association between contaminated water sources, including piped water systems, and clinical cases highlights the urgent need for improved water sanitation to mitigate melioidosis risk. Funding Wellcome Trust ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement CChe was funded by the Wellcome International Intermediate Fellowship (216457/Z/19/Z), the Sanger International Fellowship, and the University of Oxford Nuffield Department of Medicine Career Development Scheme. This research was funded in part by the Wellcome Trust [220211 and 206194]. For the purpose of Open Access, the author has applied a CC BY public copyright license to any Author Accepted Manuscript version arising from this submission. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: This study received ethical approval from the Sunpasitthiprasong Hospital Ethical Review Board (015/62C) and the Oxford Tropical Research Ethics Committee (OxTREC 25-19). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors

Genomic epidemiology enhances the ability to detect and refute methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in healthcare settings, but its routine introduction requires further evidence of benefits for patients and resource utilization. We performed a 12 month prospective study at Cambridge University Hospitals NHS Foundation Trust in the UK to capture its impact on hospital infection prevention and control (IPC) decisions. MRSA-positive samples were identified via the hospital microbiology laboratory between November 2018 and November 2019. We included samples from in-patients, clinic out-patients, people reviewed in the Emergency Department and healthcare workers screened by Occupational Health. We sequenced the first MRSA isolate from 823 consecutive individuals, defined their pairwise genetic relatedness, and sought epidemiological links in the hospital and community. Genomic analysis of 823 MRSA isolates identified 72 genetic clusters of two or more isolates containing 339/823 (41 %) of the cases. Epidemiological links were identified between two or more cases for 190 (23 %) individuals in 34/72 clusters. Weekly genomic epidemiology updates were shared with the IPC team, culminating in 49 face-to-face meetings and 21 written communications. Seventeen clusters were identified that were consistent with hospital MRSA transmission, discussion of which led to additional IPC actions in 14 of these. Two outbreaks were also identified where transmission had occurred in the community prior to hospital presentation; these were escalated to relevant IPC teams. We identified 38 instances where two or more in-patients shared a ward location on overlapping dates but carried unrelated MRSA isolates (pseudo-outbreaks); research data led to de-escalation of investigations in six of these. Our findings provide further support for the routine use of genomic epidemiology to enhance and target IPC resources.

The major human bacterial pathogen Pseudomonas aeruginosa causes multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution of P. aeruginosa and highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

Antibiograms have been used during outbreak investigations for decades as a surrogate for genetic relatedness of Methicillin-resistant Staphylococcus aureus (MRSA). In this study, we evaluate the accuracy of antibiograms in detecting transmission, using genomic epidemiology as the reference standard. We analysed epidemiological and genomic data from 1,465 patients and 1,465 MRSA isolates collected at a single clinical microbiology laboratory in the United Kingdom over a one-year period. A total of 132 unique antibiograms (AB) were identified based on VITEK 2 susceptibility testing, with two profiles (AB1 and AB2) accounting for 698 isolates (48%). We identified MRSA-positive patients with a known hospital or community contact and evaluated the prediction of MRSA transmission based on identical antibiograms. The sensitivity and specificity of identical antibiograms to infer genetically related MRSA isolates (≤25 SNPs) within hospital contacts (presumed transmission events) was 66.4% and 85.5% respectively and 73.8% and 85.7% within community contacts. Reanalysis, where any single drug mismatch in susceptibility results was allowed, increased sensitivity but reduced specificity: 95.2% and 58.8%, respectively, for hospital contacts; and 91.7% and 62.6% for community contacts. Overall, the sensitivity and specificity of identical antibiograms for inferring genetically related MRSA isolates (≤25 SNPs), regardless of epidemiological links, were 49.1% and 87.5%, respectively. We conclude that using an antibiogram with one mismatch can detect most transmission events; however, its poor specificity may lead to an increased workload through the evaluation of numerous pseudo-outbreaks. This study further supports the integration of genomic epidemiology into routine practice for the detection and control of MRSA transmission.

Summary Background Melioidosis is a grossly neglected but often-fatal tropical disease. The disease is named “a great mimicker” after its broad clinical manifestations, which makes disease diagnosis challenging and time-consuming. To improve diagnosis, we developed and evaluated the performance of the CRISPR-Cas12a system called “CRISPR-BP34” to detect Burkholderia pseudomallei DNA across clinical specimens from patients suspected to have melioidosis. Methods We documented time taken for diagnosis, antibiotics prescribed during the waiting period, and infection outcomes in 875 melioidosis patients treated in a hospital in northeast Thailand between October 2019 and December 2022. In the last six months, we performed CRISPR-BP34 detection on clinical specimens (blood, urine, respiratory secretion, pus and other body fluids) collected from 330 patients with suspected melioidosis and compared its performance to the current gold-standard culture-based method. Discordant results were validated by three independent qPCR tests. Findings A window of 3-4 days was required for gold-standard culture diagnosis, which resulted in delayed treatment. 199 [22·7%] of 875 patients died prior to diagnosis results while 114 [26·3%] of 433 follow-up cases had been diagnosed, treated, but died within 28 days of admission. A shorter sample-to-diagnosis time of less than 4 hours offered by CRISPR-BP34 technology could lead to faster administration of correct treatment. We demonstrated an improved sensitivity of CRISPR-BP34 (106 [93·0%] of 114 positive cases, 95% CI 86·6 - 96·9) compared to the culture approach (76 [66·7%] of 114 positive cases, 95% CI 57·2 - 75·2); while maintaining similar specificity (209 [96·8%] of 216 negative cases, 95% CI 93·4-98·7) to the culture (216 [100 %] of 216 negative cases, 95% CI 98·3-100·0). Interpretation The sensitivity, specificity, speed, window of clinical intervention, and ease of operation offered by the CRISPR-BP34 support its use as a point-of-care diagnostic for melioidosis. Funding Chiang Mai University Thailand and Wellcome Trust UK Research in context Evidence before this study Melioidosis is an often-severe infectious disease caused by the bacterium Burkholderia pseudomallei . It is estimated to affect 165,000 individuals annually worldwide, of which 89,000 cases are fatal. The disease diagnosis is challenging due to diverse clinical presentations, low awareness, limited diagnostic options, or even a lack of diagnostic tests. A PubMed search conducted from the database inception to 6 May 2023, using the terms “melioidosis” AND “diagnosis test,” yielded 207 results, 40 of which presented clinical evaluations of rapid melioidosis diagnostic tests. Antigen-based diagnostic tests, which detect the presence of B. pseudomallei , reported high specificity (median = 98·6%, IQR 94·0 - 100·0), but low sensitivity (median = 57·1%, IQR = 44·3 - 82·5). The test sensitivity suffers from the often-low concentration of the bacterial antigens in patients’ samples, which can vary by specimen type and stage of infection. Antibody-based diagnostic tests that detect host antibodies against B. pseudomallei typically exhibit satisfactory specificity (median = 94·5%, IQR = 88·6 - 96·2) but poor sensitivity (median = 80·2%, IQR = 71·0 - 88·1). These tests are often impacted by variations in antibody responses to B. pseudomallei and the duration required for antibody production. Furthermore, standardisation remains challenging due to the influence of different serum titres on sensitivity and background of the tests. Likewise, quantitative PCR exhibits a high degree of specificity (median = 99·8%, IQR = 91·6-100·0), but an observed low sensitivity for melioidosis (median = 77·1%, IQR = 20·8-97·8), which is likely attributed to the genetic heterogeneity of B. pseudomallei genomes. Additionally, these studies consistently reported a demand for improved speed and ease of implementation in resource-limited settings where melioidosis is endemic. With the limitations of current diagnostic methods, a culture-confirmed approach with 60% sensitivity, 100% specificity, and a diagnosis time of 2-7 days still stands as the gold standard for melioidosis diagnosis. Added value of this study To date, no study has measured the impact of delayed diagnosis on melioidosis. We assessed the number of deaths occurring prior to culture-confirmed diagnosis (22·7%) and those after diagnosis but within 28 days post-admission (26·3%), highlighting the urgent need for prompt action. To address this, we developed the CRISPR-BP34 test, which utilises isothermal amplification of a nucleic acid target followed by site-specific detection using a CRISPR-Cas12a enzyme. We successfully implemented this assay in a resource-limited setting in northeast Thailand, where the disease prevalence is among the highest in the world. The assay achieved a diagnostic sensitivity and specificity of 93·0% and 96·8%, respectively, with a limit of detection ranging from 50-250 cfu/mL. Early diagnosis can be achieved within four hours of patient admission, which is significantly faster than the gold-standard test that typically takes several days. Moreover, the ultrasensitivity of the CRISPR-BP34 assay enabled the detection of low levels of B. pseudomallei in hemoculture bottles, which could be missed due to mixed infections, poor aseptic technique, or other causes, leading to undiagnosed melioidosis. Implications of all available evidence The CRISPR-BP34 assay holds great promise for the management and control of melioidosis. Its minimal setup and shallow learning curve make it well-suited for resource-limited settings. Additionally, its speed and high sensitivity enable early diagnosis and treatment, which are crucial for saving patients’ lives.

Antimicrobial resistance (AMR) is a serious threat to global public health, with approximately 5 million deaths associated with bacterial AMR in 2019. Tackling AMR requires a multifaceted and cohesive approach that ranges from increased understanding of mechanisms and drivers at the individual and population levels, AMR surveillance, antimicrobial stewardship, improved infection prevention and control measures, and strengthened global policies and funding to development of novel antimicrobial therapeutic strategies. In this rapidly advancing field, this Review provides a concise update on AMR, encompassing epidemiology, evolution, underlying mechanisms (primarily those related to last-line or newer generation of antibiotics), infection prevention and control measures, access to antibiotics, antimicrobial stewardship, AMR surveillance, and emerging non-antibiotic therapeutic approaches. The Review also discusses the potential roles of artificial intelligence in addressing AMR, including antimicrobial susceptibility testing, AMR surveillance, antimicrobial stewardship, diagnosis, and antimicrobial drug discovery and development. This Review highlights the urgent need for addressing the global effects of AMR and for rapid advancement of relevant technology in this dynamic field.

OBJECTIVES:The objective of this study is to assess the frequency of the novel sodium bicarbonate (NaHCO3)-responsive phenotype, wherein clinical methicillin-resistant Staphylococcus aureus (MRSA) isolates are rendered susceptible to standard-of-care β-lactams in the presence of NaHCO3, in a collection of 103 clinical U.S. MRSA skin and soft-tissue infection (SSTI) isolates and 22 clinical European SSTI isolates. This study determined the correlation between specific phenotypic and genotypic metrics and the NaHCO3-responsive phenotype among U.S. SSTI isolates. METHODS:Antimicrobial susceptibility testing was performed to determine susceptibility phenotypes. Targeted and whole-genome sequencing with a genome-wide sequence analysis were conducted to identify specific and novel genotypes of interest that may be associated with the NaHCO3-responsive phenotype. Gene expression analysis and targeted gene deletion were performed to assess the role of a specific novel genetic locus in the NaHCO3-responsive phenotype. RESULTS:The NaHCO3-responsive phenotype was identified in 78/103 U.S. isolates and 4/22 UK isolates to cefazolin (CFZ), and in 17/103 U.S. isolates and 1/22 UK isolates to oxacillin. In U.S. isolates, a significant association was identified between NaHCO3-responsiveness to CFZ and: (a) susceptibility to amoxicillin-clavulanate; (b) a specific mecA genotype; (c) clonal complex type 8; and (d) spa type t008. Genome-wide sequence analysis identified single nucleotide polymorphisms (SNPs) in an AraC family regulator (SAUSA300_RS00540) to be exclusively found in NaHCO3-non-responsive SSTI strains. In vitro HCO3 exposures of NaHCO3-responsive strains, but not -non-responsive strains, caused >2-fold upregulated expression of this gene. Deletion of this gene rendered NaHCO3-responsive strain MRSA 11/11 no longer NaHCO3-responsive to CFZ; we have termed this gene the staphylococcal AraC bicarbonate-response regulator. DISCUSSION:NaHCO3-responsiveness is highly associated with clonal complex type 8/spa type t008, a commonly circulating genetic background in North America. The AraC bicarbonate-response regulator, staphylococcal AraC bicarbonate-response regulator, appears to be associated with the mechanism of NaHCO3-responsiveness, but more work is needed to verify.

Streptococcus agalactiae (Group B Streptococcus ; GBS) is a common cause of sepsis in neonates. Previous work detected GBS DNA in the placenta in ~5% of women before the onset of labour, but the clinical significance of this finding is unknown. Here we re-analysed this dataset as a case control study of neonatal unit (NNU) admission. Of 436 infants born at term (≥37 weeks of gestation), 7/30 with placental GBS and 34/406 without placental GBS were admitted to the NNU (odds ratio (OR) 3.3, 95% confidence interval (CI) 1.3–7.8). We then performed a validation study using non-overlapping subjects from the same cohort. This included a further 239 cases of term NNU admission and 686 term controls: 16/36 with placental GBS and 223/889 without GBS were admitted to the NNU (OR 2.4, 95% CI 1.2–4.6). Of the 36 infants with placental GBS, 10 were admitted to the NNU with evidence of probable but culture-negative sepsis (OR 4.8, 95% CI 2.2–10.3), 2 were admitted with proven GBS sepsis (OR 66.6, 95% CI 7.3–963.7), 6 were admitted and had chorioamnionitis (inflammation of the foetal membranes) (OR 5.3, 95% CI 2.0–13.4), and 5 were admitted and had funisitis (inflammation of the umbilical cord) (OR 6.7, 95% CI 12.5–17.7). Foetal cytokine storm (two or more pro-inflammatory cytokines >10 times median control levels in umbilical cord blood) was present in 36% of infants with placental GBS DNA and 4% of cases where the placenta was negative (OR 14.2, 95% CI 3.6–60.8). Overall, ~1 in 200 term births had GBS detected in the placenta, which was associated with infant NNU admission and morbidity.

ObjectivesTo compare success of applicants to specialty training posts in the UK by gender, ethnicity and disability status.DesignCross-sectional observational study.SettingNational Health Service, UK.ParticipantsAll specialty training post applications to Health Education England, UK, during the 2021–2022 recruitment cycle.InterventionNil.Primary and secondary outcome measuresComparison of success at application to specialty training posts by gender, ethnicity, country of qualification (UK vs non-UK) and disability. The influence of ethnicity on success was investigated using a logistic regression model, where country of qualification was included as a covariate.Results12 419/37 971 (32.7%) of applicants to specialty training posts were successful, representing 58 specialties. The difference in percentage of successful females (6480/17 523, 37.0%) and males (5625/19 340, 29.1%) was 7.9% (95% CI 6.93% to 8.86%), in favour of females. Segregation of applications to specialties by gender was observed; surgical specialties had the highest proportion of male applicants, while obstetrics and gynaecology had the highest proportion of female applicants. The proportion of successful recruits to specialties largely reflected the number of applications. 11/15 minority ethnic groups (excluding ‘not stated’) had significantly lower adjusted ORs for success compared with white-British applicants. ‘Mixed white and black African’ (OR 0.52, 95% CI 0.44 to 0.61, p≤0.001) were the least successful minority group in our study, while non-UK graduates had an adjusted ORs for success of 0.43 (95% CI 0.41 to 0.46, p≤0.001) compared with UK graduates. The difference in percentage of success by disabled applicants (179/464, 38.6%) and non-disabled applicants (11 940/36 418, 32.8%) was 5.79% (95% CI 1.23% to 10.4%), in favour of disabled applicants. No disabled applicants were accepted to 21/58 (36.2%) of specialties.ConclusionsDespite greater success by female applicants overall, there is an attraction issue to specialties by gender. Further, most ethnic minority groups are less successful at application when compared with white-British applicants. This requires continuous monitoring and evaluation of the reasons behind observed differences.Trial RegistrationNot applicable.

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.

16S rRNA gene sequencing is widely used to characterize human and environmental microbiomes. Sequencing at scale facilitates better powered studies but is limited by cost and time. We identified two areas in our 16S rRNA gene library preparation protocol where modifications could provide efficiency gains, including (1) pooling of multiple PCR amplifications per sample to reduce PCR drift and (2) manual preparation of mastermix to reduce liquid handling. Using nasal samples from healthy human participants and a serially diluted mock microbial community, we compared alpha and beta diversity, and compositional abundance where the PCR amplification was conducted in triplicate, duplicate or as a single reaction, and where manually prepared or premixed mastermix was used. One hundred and fifty-eight 16S rRNA gene sequencing libraries were prepared, including a replicate experiment. Comparing PCR pooling strategies, we found no significant difference in high-quality read counts and alpha diversity, and beta diversity by Bray–Curtis index clustered by replicate on principal coordinate analysis (PCoA) and non-metric dimensional scaling (NMDS) analysis. Choice of mastermix had no significant impact on high-quality read and alpha diversity, and beta diversity by Bray–Curtis index clustered by replicate in PCoA and NMDS analysis. Importantly, we observed contamination and variability of rare species (<0.01 %) across replicate experiments; the majority of contaminants were accounted for by removal of species present at <0.1 %, or were linked to reagents (including a primer stock). We demonstrate no requirement for pooling of PCR amplifications or manual preparation of PCR mastermix, resulting in a more efficient 16S rRNA gene PCR protocol.

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.