Background New approaches are urgently required to address increasing rates of gonorrhoea and the emergence and global spread of antibiotic-resistant Neisseria gonorrhoeae. Whole genome sequencing (WGS) can be applied to study transmission and track resistance. Methods We performed WGS on 1659 isolates from Brighton, UK, and 217 additional isolates from other UK locations. We included WGS data (n=196) from the USA. Estimated mutation rates, plus diversity observed within patients across anatomical sites and probable transmission pairs, were used to fit a coalescent model to determine the number of single nucleotide polymorphisms (SNPs) expected between sequences related by direct/indirect transmission, depending on the time between samples. Findings We detected extensive local transmission. 281/1061(26%) Brighton cases were indistinguishable (0 SNPs) to ≥1 previous case(s), and 786(74%) had evidence of a sampled direct or indirect Brighton source. There was evidence of sustained transmission of some lineages. We observed multiple related samples across geographic locations. Of 1273 infections in Brighton, 225(18%) were linked to another case from elsewhere in the UK, and 115(9%) to a case from the USA. Four lineages initially identified in Brighton could be linked to 70 USA sequences, including 61 from a lineage carrying the mosaic penA XXXIV associated with reduced cefixime susceptibility. Interpretation We present a WGS-based tool for genomic contact tracing of N. gonorrhoeae and demonstrate local, national and international transmission. WGS can be applied across geographical boundaries to investigate gonorrhoea transmission and to track antimicrobial resistance. Funding Oxford NIHR Health Protection Research Unit and Biomedical Research Centre.

BackgroundTracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes.ObjectivesWe investigate whether WGS and simultaneous analysis of multiple resistance determinants can be used to predict antimicrobial susceptibilities to the level of MICs in N. gonorrhoeae.MethodsWGS was used to identify previously reported potential resistance determinants in 681 N. gonorrhoeae isolates, from England, the USA and Canada, with phenotypes for cefixime, penicillin, azithromycin, ciprofloxacin and tetracycline determined as part of national surveillance programmes. Multivariate linear regression models were used to identify genetic predictors of MIC. Model performance was assessed using leave-one-out cross-validation.ResultsOverall 1785/3380 (53%) MIC values were predicted to the nearest doubling dilution and 3147 (93%) within ±1 doubling dilution and 3314 (98%) within ±2 doubling dilutions. MIC prediction performance was similar across the five antimicrobials tested. Prediction models included the majority of previously reported resistance determinants. Applying EUCAST breakpoints to MIC predictions, the overall very major error (VME; phenotypically resistant, WGS-prediction susceptible) rate was 21/1577 (1.3%, 95% CI 0.8%–2.0%) and the major error (ME; phenotypically susceptible, WGS-prediction resistant) rate was 20/1186 (1.7%, 1.0%–2.6%). VME rates met regulatory thresholds for all antimicrobials except cefixime and ME rates for all antimicrobials except tetracycline. Country of testing was a strongly significant predictor of MIC for all five antimicrobials.ConclusionsWe demonstrate a WGS-based MIC prediction approach that allows reliable MIC prediction for five gonorrhoea antimicrobials. Our approach should allow reasonably precise prediction of MICs for a range of bacterial species.

Increasing antibiotic resistance makes choosing antibiotics for suspected Gram-negative infection challenging. This study set out to identify key determinants of mortality among patients with Gram-negative bacteraemia, focusing particularly on the importance of appropriate empiric antibiotic treatment. We conducted a prospective observational study of 679 unselected adults with Gram-negative bacteraemia at ten acute english hospitals between October 2013 and March 2014. Appropriate empiric antibiotic treatment was defined as intravenous treatment on the day of blood culture collection with an antibiotic to which the cultured organism was sensitive in vitro. Mortality analyses were adjusted for patient demographics, co-morbidities and illness severity. The majority of bacteraemias were community-onset (70%); most were caused by Escherichia coli (65%), Klebsiella spp. (15%) or Pseudomonas spp. (7%). Main foci of infection were urinary tract (51%), abdomen/biliary tract (20%) and lower respiratory tract (14%). The main antibiotics used were co-amoxiclav (32%) and piperacillin-tazobactam (30%) with 34% receiving combination therapy (predominantly aminoglycosides). Empiric treatment was inappropriate in 34%. All-cause mortality was 8% at 7 days and 15% at 30 days. Independent predictors of mortality (p <0.05) included older age, greater burden of co-morbid disease, severity of illness at presentation and inflammatory response. Inappropriate empiric antibiotic therapy was not associated with mortality at either time-point (adjusted OR 0.82; 95% CI 0.35-1.94 and adjusted OR 0.92; 95% CI 0.50-1.66, respectively). Although our study does not exclude an impact of empiric antibiotic choice on survival in Gram-negative bacteraemia, outcome is determined primarily by patient and disease factors.