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

Abstract

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.

Figure 1. Transmission calibration sampling frames.

Panel A shows the genetic variation within six randomly chosen clinical samples, 12-14 colonies were sequenced independently. Within each clinical sample sequences from the first colony chosen were compared to all other colonies sequenced. On the right-hand side, each colour represents a different clinical sample. The area of the circles is proportional to the number of colonies with identical genome sequences. Lines between circles represent the numbers of SNPs between colonies. In 5 samples all sequences were identical, shown as a single circle. Panel B shows the diversity present across different anatomical sites in the same patient. Panel C shows the diversity present between highly probable transmission pairs. Panel D shows the variation in the same patient over time. Panel E shows the diversity between different patients in Brighton. All first samples from each infection in each patient were compared pairwise.

Figure 2. Transmission Nomogram.

SNPs expected between direct or indirect transmission pairs for varying time between samples are shaded (99% prediction interval). The dotted line shows the mean number of SNPs. The upper panel shows expected numbers of SNPs over the longest interval possible between samples in the study. Of 1061 distinct infections, only 2 (0.2%) had a potential source with lower than the expected number of SNPs, 0 SNPs after 466 days, and 1 SNP after 686 days. The lower panel shows the expected number of SNPs over a time between samples of up to 1 year.

Figure 3. Percentage of Brighton infections genetically linked to a previous sampled case by maximum time between cases.

Brighton vs. Brighton compares cases in Brighton (2011-2015) to all previous Brighton cases (2004 onwards). To avoid double counting of cases, cases were only compared to previous cases, accepting sampling dates may not indicate the direction of transmission. In the Brighton vs. UK and Brighton vs. USA plots all cases from Brighton (2004-2015) were compared to all cases from the rest of the UK or USA respectively, independent of the order of sampling.

Figure 4. Brighton clusters of genetically linked cases.

Cases within Brighton were clustered based on those related by SNP distances and time compatible with transmission. Panel A shows clusters for 1061 cases between January 2011 and March 2015. Panel B restricts clustering to where sampling of consecutive cases within a cluster occurred within 30 days.

Figure 5. Genetic clusters within Brighton, UK and USA.

Each genetic cluster contains all cases related by a number of SNPs and time compatible with transmission. Each genetic cluster is plotted on its own horizontal line, with individual cases indicated as dots. For ease of visualisation, clusters arising from January 2011 are shown separately on the right-hand side. Samples obtained in Brighton in 2004 and 2005 were collected within a 2-month interval, but the exact collection dates were not available. These samples have been randomly distributed throughout the 2 months of sampling. Similarly, only the month and year of collection was known for the USA samples, and a random day has been assigned.