Whole genome sequencing of Neisseria gonorrhoeae reveals transmission clusters involving patients of mixed HIV serostatus.

OBJECTIVES: Prevention and control of gonorrhoea depends on understanding the nature of sexual networks and risk factors for infection. We aimed to use high-resolution typing (whole genome sequencing (WGS)) of Neisseria gonorrhoeae isolates plus patient questionnaire data to gain insights into transmission patterns in a high prevalence setting. METHODS: During a 9-month period (July 2014-March 2015), patients diagnosed with gonorrhoea attending sexual health service in Brighton, UK, were invited to provide anonymised detailed information by questionnaire about risk factors for infection. Questionnaire data plus WGS data from cultured isolates were analysed to yield information about sexual networks and risk factors for infection. RESULTS: 104/149 individuals who consented to participate in the study were culture positive. 97/104 (93%) were male. 80 self-reported to be men who have sex with men (MSM). 35/104 (34%) of patients were HIV positive. 51/104 (49%) individuals reported using geosocial networking applications to facilitate contact. Sex under the influence of drugs was reported by 16/34 (46%) of HIV-positive MSM, 17/41 (41%) of HIV-negative MSM and 5/15 (31%) of heterosexuals. WGS data were available for 100 isolates from 83 patients. 55 isolates (66%) belonged to genetically related subtypes involving one or more patients, who could be plausibly linked through recent direct or indirect transmission. Four transmission clusters containing 3-12 individuals were composed of MSM of mixed HIV serostatus. CONCLUSIONS: We show that data obtained from WGS of N. gonorrhoeae and enhanced epidemiological data obtained from patient questionnaires are mutually supportive and reveal insights into sexual networks. Our findings suggest that serosorting may have declined as a practice and indicate the importance of designing public health interventions that target infection risks associated with recreational drug use and contact made using geosocial networking applications.

WGS to predict antibiotic MICs for Neisseria gonorrhoeae.

Background: Tracking the spread of antimicrobial-resistant Neisseria gonorrhoeae is a major priority for national surveillance programmes. Objectives: We 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. Methods: WGS 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. Results: Overall 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. Conclusions: We 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.

The copy number and mutational landscape of recurrent ovarian high-grade serous carcinoma.

The drivers of recurrence and resistance in ovarian high grade serous carcinoma remain unclear. We investigate the acquisition of resistance by collecting tumour biopsies from a cohort of 276 women with relapsed ovarian high grade serous carcinoma in the BriTROC-1 study. Panel sequencing shows close concordance between diagnosis and relapse, with only four discordant cases. There is also very strong concordance in copy number between diagnosis and relapse, with no significant difference in purity, ploidy or focal somatic copy number alterations, even when stratified by platinum sensitivity or prior chemotherapy lines. Copy number signatures are strongly correlated with immune cell infiltration, whilst diagnosis samples from patients with primary platinum resistance have increased rates of CCNE1 and KRAS amplification and copy number signature 1 exposure. Our data show that the ovarian high grade serous carcinoma genome is remarkably stable between diagnosis and relapse and acquired chemotherapy resistance does not select for common copy number drivers.

Copy number signatures and mutational processes in ovarian carcinoma.

The genomic complexity of profound copy number aberrations has prevented effective molecular stratification of ovarian cancers. Here, to decode this complexity, we derived copy number signatures from shallow whole-genome sequencing of 117 high-grade serous ovarian cancer (HGSOC) cases, which were validated on 527 independent cases. We show that HGSOC comprises a continuum of genomes shaped by multiple mutational processes that result in known patterns of genomic aberration. Copy number signature exposures at diagnosis predict both overall survival and the probability of platinum-resistant relapse. Measurement of signature exposures provides a rational framework to choose combination treatments that target multiple mutational processes.

Whole-genome sequencing to determine transmission of Neisseria gonorrhoeae: an observational study.

BACKGROUND: New approaches are urgently required to address increasing rates of gonorrhoea and the emergence and global spread of antibiotic-resistant Neisseria gonorrhoeae. We used whole-genome sequencing to study transmission and track resistance in N gonorrhoeae isolates. METHODS: We did whole-genome sequencing of isolates obtained from samples collected from patients attending sexual health services in Brighton, UK, between Jan 1, 2011, and March 9, 2015. We also included isolates from other UK locations, historical isolates from Brighton, and previous data from a US study. Samples from symptomatic patients and asymptomatic sexual health screening underwent nucleic acid amplification testing; positive samples and all samples from symptomatic patients were cultured for N gonorrhoeae, and resulting isolates were whole-genome sequenced. Cefixime susceptibility testing was done in selected isolates by agar incorporation, and we used sequence data to determine multi-antigen sequence types and penA genotypes. We derived a transmission nomogram to determine the plausibility of direct or indirect transmission between any two cases depending on the time between samples: estimated mutation rates, plus diversity noted within patients across anatomical sites and probable transmission pairs, were used to fit a coalescent model to determine the number of single nucleotide polymorphisms expected. FINDINGS: 1407 (98%) of 1437 Brighton isolates between Jan 1, 2011, and March 9, 2015 were successfully sequenced. We identified 1061 infections from 907 patients. 281 (26%) of these infections were indistinguishable (ie, differed by zero single nucleotide polymorphisms) from one or more previous cases, and 786 (74%) had evidence of a sampled direct or indirect Brighton source. We observed multiple related samples across geographical locations. Of 1273 infections in Brighton (including historical data), 225 (18%) were linked to another case elsewhere in the UK, and 115 (9%) to a case in 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 allele, which is associated with reduced cefixime susceptibility. INTERPRETATION: We present a whole-genome-sequencing-based tool for genomic contact tracing of N gonorrhoeae and demonstrate local, national, and international transmission. Whole-genome sequencing can be applied across geographical boundaries to investigate gonorrhoea transmission and to track antimicrobial resistance. FUNDING: Oxford National Institute for Health Research Health Protection Research Unit and Biomedical Research Centre.

Purifying selection in deeply conserved human enhancers is more consistent than in coding sequences.

Comparison of polymorphism at synonymous and non-synonymous sites in protein-coding DNA can provide evidence for selective constraint. Non-coding DNA that forms part of the regulatory landscape presents more of a challenge since there is not such a clear-cut distinction between sites under stronger and weaker selective constraint. Here, we consider putative regulatory elements termed Conserved Non-coding Elements (CNEs) defined by their high level of sequence identity across all vertebrates. Some mutations in these regions have been implicated in developmental disorders; we analyse CNE polymorphism data to investigate whether such deleterious effects are widespread in humans. Single nucleotide variants from the HapMap and 1000 Genomes Projects were mapped across nearly 2000 CNEs. In the 1000 Genomes data we find a significant excess of rare derived alleles in CNEs relative to coding sequences; this pattern is absent in HapMap data, apparently obscured by ascertainment bias. The distribution of polymorphism within CNEs is not uniform; we could identify two categories of sites by exploiting deep vertebrate alignments: stretches that are non-variant, and those that have at least one substitution. The conserved category has fewer polymorphic sites and a greater excess of rare derived alleles, which can be explained by a large proportion of sites under strong purifying selection within humans--higher than that for non-synonymous sites in most protein coding regions, and comparable to that at the strongly conserved trans-dev genes. Conversely, the more evolutionarily labile CNE sites have an allele frequency distribution not significantly different from non-synonymous sites. Future studies should exploit genome-wide re-sequencing to obtain better coverage in selected non-coding regions, given the likelihood that mutations in evolutionarily conserved enhancer sequences are deleterious. Discovery pipelines should validate non-coding variants to aid in identifying causal and risk-enhancing variants in complex disorders, in contrast to the current focus on exome sequencing.