Comprehensive identification of single nucleotide polymorphisms associated with beta-lactam resistance within pneumococcal mosaic genes

Abstract

Traditional genetic association studies are very difficult in bacteria, as the generally limited recombination leads to large linked haplotype blocks, confounding the identification of causative variants. Beta-lactam antibiotic resistance in Streptococcus pneumoniae arises readily as the bacteria can quickly incorporate DNA fragments encompassing variants that make the transformed strains resistant. However, the causative mutations themselves are embedded within larger recombined blocks, and previous studies have only analysed a limited number of isolates, leading to the description of "mosaic genes" as being responsible for resistance. By comparing a large number of genomes of beta-lactam susceptible and non-susceptible strains, the high frequency of recombination should break up these haplotype blocks and allow the use of genetic association approaches to identify individual causative variants. Here, we performed a genome-wide association study to identify single nucleotide polymorphisms (SNPs) and indels that could confer beta-lactam non-susceptibility using 3,085 Thai and 616 USA pneumococcal isolates as independent datasets for the variant discovery. The large sample sizes allowed us to narrow the source of beta-lactam non-susceptibility from long recombinant fragments down to much smaller loci comprised of discrete or linked SNPs. While some loci appear to be universal resistance determinants, contributing equally to non-susceptibility for at least two classes of beta-lactam antibiotics, some play a larger role in resistance to particular antibiotics. All of the identified loci have a highly non-uniform distribution in the populations. They are enriched not only in vaccine-targeted, but also non-vaccine-targeted lineages, which may raise clinical concerns. Identification of single nucleotide polymorphisms underlying resistance will be essential for future use of genome sequencing to predict antibiotic sensitivity in clinical microbiology.

Figure 1. Summary of the genome-wide-association study conducted in two separate datasets.

Manhattan plots summarize the association of whole-genome SNP variants with beta-lactam susceptibility in the Maela and Massachusetts data as well as particular gene regions which show strong associations. Top panel represents the statistical significance of association (y-axis) for each variant arranged in order on the genome (x-axis) in the Maela (red) and Massachusetts (blue) data. Horizontal dotted lines in both top and bottom panels indicate a significance cut-off after Bonferroni correction of p = 0.01. Genes with significant associations are annotated on top. Genes coding for penicillin binding proteins: pbp2x, pbp1a, and pbp2b, whose roles in beta-lactam resistance are well characterized, are highlighted in grey. Bottom panel expands the view of penicillin binding protein genes where most of the significant associations are detected: from left to right: pbp2x, pbp1a, and pbp2b. Protein domains identified within these genes are shaded in pale grey and labelled. The vertical dotted lines represent the active sites of the transpeptidase domain. Plus signs denote synonymous SNPs and dots denote non-synonymous SNPs.

Figure 2. Summary of single nucleotide polymorphisms (SNPs) associated with beta-lactam non-susceptibility.

A Venn diagram summarises the number of SNPs reaching significance in each of the Maela and Massachusetts datasets, and those that are co-detected in both.

Figure 3. Specificity of association signals for co-detected candidate loci with different classes of beta-lactam antibiotics.

Bonferroni-adjusted p-values from associations with continuous phenotypes with each co-detected SNP were grouped into their linkage loci. Positive values on the y-axis show stronger association with penicillin resistance while negative values show stronger association with cephalosporin resistance. Horizontal dotted lines represent the 99^th percentile.

Figure 4. Frequency of putative resistance alleles from candidate loci in the Maela and Massachusetts populations.

The resistant allele frequency at each locus (rows) in each population cluster (columns) is represented by different shades on a blue-grey scale. Vaccine and non-vaccine serotype status of each cluster are shown at the top of each column. Asterisks highlight two drug resistant global clones: * represents the PMEN1 lineage; ** represents the PMEN14 lineage. Note that mixed population clusters have been removed from the diagram.