SummaryBackgroundTraditional methods for molecular epidemiology of Neisseria gonorrhoeae are suboptimal. Whole-genome sequencing (WGS) offers ideal resolution to describe population dynamics and to predict and infer transmission of antimicrobial resistance, and can enhance infection control through linkage with epidemiological data. We used WGS, in conjunction with linked epidemiological and phenotypic data, to describe the gonococcal population in 20 European countries. We aimed to detail changes in phenotypic antimicrobial resistance levels (and the reasons for these changes) and strain distribution (with a focus on antimicrobial resistance strains in risk groups), and to predict antimicrobial resistance from WGS data.MethodsWe carried out an observational study, in which we sequenced isolates taken from patients with gonorrhoea from the European Gonococcal Antimicrobial Surveillance Programme in 20 countries from September to November, 2013. We also developed a web platform that we used for automated antimicrobial resistance prediction, molecular typing (N gonorrhoeae multi-antigen sequence typing [NG-MAST] and multilocus sequence typing), and phylogenetic clustering in conjunction with epidemiological and phenotypic data.FindingsThe multidrug-resistant NG-MAST genogroup G1407 was predominant and accounted for the most cephalosporin resistance, but the prevalence of this genogroup decreased from 248 (23%) of 1066 isolates in a previous study from 2009–10 to 174 (17%) of 1054 isolates in this survey in 2013. This genogroup previously showed an association with men who have sex with men, but changed to an association with heterosexual people (odds ratio=4·29). WGS provided substantially improved resolution and accuracy over NG-MAST and multilocus sequence typing, predicted antimicrobial resistance relatively well, and identified discrepant isolates, mixed infections or contaminants, and multidrug-resistant clades linked to risk groups.InterpretationTo our knowledge, we provide the first use of joint analysis of WGS and epidemiological data in an international programme for regional surveillance of sexually transmitted infections. WGS provided enhanced understanding of the distribution of antimicrobial resistance clones, including replacement with clones that were more susceptible to antimicrobials, in several risk groups nationally and regionally. We provide a framework for genomic surveillance of gonococci through standardised sampling, use of WGS, and a shared information architecture for interpretation and dissemination by use of open access software.FundingThe European Centre for Disease Prevention and Control, The Centre for Genomic Pathogen Surveillance, Örebro University Hospital, and Wellcome.

Phage display technology involves the display of proteins or peptides, as coat protein fusions, on the surface of a phage or phagemid particles. Using standard technology, helper phage are essential for the replication and assembly of phagemid particles, during library production and biopanning. We have eliminated the need to add helper phage by using 'bacterial packaging cell lines' that provide the same functions. These cell lines contain M13-based helper plasmids that express phage packaging proteins which assemble phagemid particles as efficiently as helper phage, but without helper phage contamination. This results in genetically pure phagemid particle preparations. Furthermore, by using constructs differing in the form of gene 3 that they contain, we have shown that the display, from a single library, can be modulated between monovalent (phagemid-like) and multivalent display (phage-like) without any further engineering. These packaging cells eliminate the use of helper phage from phagemid-based selection protocols; reducing the amount of technical preparation, facilitating automation, optimizing selections by matching display levels to diversity, and effectively using the packaged phagemid particles as means to transfer genetic information at an efficiency approaching 100%.

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The GUT1 gene of Saccharomyces cerevisiae, encoding glycerol kinase, was cloned and sequenced. The cloned genomic DNA fragment contains an open reading frame potentially coding for a protein of 709 amino acids with homology to bacterial glycerol kinases (40.8% identity over 502 amino acids, and 42.1% identity over 496 amino acids, in comparison to the smaller E. coli and B. subtilis enzymes). Disruption of GUT1 showed that the gene is required for growth on glycerol, but not on glucose or ethanol media. No glycerol kinase activity was detected in the disruption mutant. According to enzyme activity and transcript analysis, synthesis of glycerol kinase is repressed by glucose, and derepression is ADR1-dependent.