International genomic definition of pneumococcal lineages, to contextualise disease, antibiotic resistance and vaccine impact

Abstract

Background: Pneumococcal conjugate vaccines have reduced the incidence of invasive pneumococcal disease, caused by vaccine serotypes, but non-vaccine-serotypes remain a concern. We used whole genome sequencing to study pneumococcal serotype, antibiotic resistance and invasiveness, in the context of genetic background.

Methods: Our dataset of 13,454 genomes, combined with four published genomic datasets, represented Africa (40%), Asia (25%), Europe (19%), North America (12%), and South America (5%). These 20,027 pneumococcal genomes were clustered into lineages using PopPUNK, and named Global Pneumococcal Sequence Clusters (GPSCs). From our dataset, we additionally derived serotype and sequence type, and predicted antibiotic sensitivity. We then measured invasiveness using odds ratios that relating prevalence in invasive pneumococcal disease to carriage.

Findings: The combined collections (n = 20,027) were clustered into 621 GPSCs. Thirty-five GPSCs observed in our dataset were represented by >100 isolates, and subsequently classed as dominant-GPSCs. In 22/35 (63%) of dominant-GPSCs both non-vaccine serotypes and vaccine serotypes were observed in the years up until, and including, the first year of pneumococcal conjugate vaccine introduction. Penicillin and multidrug resistance were higher (p < .05) in a subset dominant-GPSCs (14/35, 9/35 respectively), and resistance to an increasing number of antibiotic classes was associated with increased recombination (R² = 0.27 p < .0001). In 28/35 dominant-GPSCs, the country of isolation was a significant predictor (p < .05) of its antibiogram (mean misclassification error 0.28, SD ± 0.13). We detected increased invasiveness of six genetic backgrounds, when compared to other genetic backgrounds expressing the same serotype. Up to 1.6-fold changes in invasiveness odds ratio were observed.

Interpretation: We define GPSCs that can be assigned to any pneumococcal genomic dataset, to aid international comparisons. Existing non-vaccine-serotypes in most GPSCs preclude the removal of these lineages by pneumococcal conjugate vaccines; leaving potential for serotype replacement. A subset of GPSCs have increased resistance, and/or serotype-independent invasiveness.

Fig. 1

Pairwise core SNP distances between and within GPSCs. Pairwise SNP distances, from a core alignment generated using Roary, between isolates in different GPSCs (left) are generally greater than pairwise SNP distances for isolates within the same GPSC (Right).

Fig. 2

Pairwise SNP distances within dominant-GPSCs. Violin plots of pairwise SNP distances within the 35 dominant-GPSCs after recombination removed from an alignment from mapping to an internal reference for each GPSC are largely comparable.

Fig. 3

Geographical and serotype diversity within Global Pneumococcal Sequence Clusters (GPSCs). Boxplots of minimum, first quartile, median, third quartile, and maximum values. (A) geographical diversity of dominant-GPSCs by country or continent, or (B) serotype diversity of dominant-GPSCs. Each point represents a dominant-GPSC. Only the unperturbed pre-PCV isolates was used to capture serotype diversity per GPSC. Diversity was measured using Simpsons 1-D that considers the number of locations/serotypes present, as well as the relative abundance of each location/serotype. Zero denotes no diversity and 1 denotes unlimited diversity.

Fig. 4

PCV composition of dominant Global Pneumococcal Sequence Clusters (GPSCs). (A) Venn diagram of the number of dominant-GPSCs (n = 35) in which combinations of PCV7 VTs, PCV10/13 unique VTs and NVTs were observed in the same GPSC pre-PCV. Over one-third (15/35) of the dominant-GPSCs expressed both PCV7 (blue), PCV13-unique (purple) and NVT (orange) pre-PCV, shown in the overlap. Whilst 24/35 dominant-GPSCs had at least one isolate expressing an NVT pre-PCV (orange area). (B) PCV13 VT contribution to GPSCs pre-PCV. Each point represents a dominant-GPSC (n = 35) and the percentage of its pre-PCV isolates expressing PCV13-VTs, with boxplot of minimum, first quartile, median, third quartile, and maximum values. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Fig. 5

Antibiotic resistance in the dominant Global Pneumococcal Sequence Clusters (GPSCs). Boxplots of minimum, first quartile, median, third quartile, and maximum percentage of pneumococcal isolates with antibiotic resistance to five common classes. Each dot represents a dominant-GPSC (n = 35). Only the unperturbed pre-PCV isolates was used to capture the distribution of resistance to each class across the dominant-GPSCs.