KmerAperture: Retaining k-mer synteny for alignment-free extraction of core and accessory differences between bacterial genomes.

By decomposing genome sequences into k-mers, it is possible to estimate genome differences without alignment. Techniques such as k-mer minimisers, for example MinHash, have been developed and are often accurate approximations of distances based on full k-mer sets. These and other alignment-free methods avoid the large temporal and computational expense of alignment. However, these k-mer set comparisons are not entirely accurate within-species and can be completely inaccurate within-lineage. This is due, in part, to their inability to distinguish core polymorphism from accessory differences. Here we present a new approach, KmerAperture, which uses information on the k-mer relative genomic positions to determine the type of polymorphism causing differences in k-mer presence and absence between pairs of genomes. Single SNPs are expected to result in k unique contiguous k-mers per genome. On the other hand, contiguous series > k may be caused by accessory differences of length S-k+1; when the start and end of the sequence are contiguous with homologous sequence. Alternatively, they may be caused by multiple SNPs within k bp from each other and KmerAperture can determine whether that is the case. To demonstrate use cases KmerAperture was benchmarked using datasets including a very low diversity simulated population with accessory content independent from the number of SNPs, a simulated population where SNPs are spatially dense, a moderately diverse real cluster of genomes (Escherichia coli ST1193) with a large accessory genome and a low diversity real genome cluster (Salmonella Typhimurium ST34). We show that KmerAperture can accurately distinguish both core and accessory sequence diversity without alignment, outperforming other k-mer based tools.

Transmission, adaptation and geographical spread of the Pseudomonas aeruginosa Liverpool epidemic strain.

The Liverpool epidemic strain (LES) is an important transmissible clonal lineage of Pseudomonas aeruginosa that chronically infects the lungs of people with cystic fibrosis (CF). Previous studies have focused on the genomics of the LES in a limited number of isolates, mostly from one CF centre in the UK, and from studies highlighting identification of the LES in Canada. Here we significantly extend the current LES genome database by genome sequencing 91 isolates from multiple CF centres across the UK, and we describe the comparative genomics of this large collection of LES isolates from the UK and Canada. Phylogenetic analysis revealed that the 145 LES genomes analysed formed a distinct clonal lineage when compared with the wider P. aeruginosa population. Notably, the isolates formed two clades: one associated with isolates from Canada, and the other associated with UK isolates. Further analysis of the UK LES isolates revealed clustering by clinic geography. Where isolates clustered closely together, the association was often supported by clinical data linking isolates or patients. When compared with the earliest known isolate, LESB58 (from 1988), many UK LES isolates shared common loss-of-function mutations, such as in genes gltR and fleR. Other loss-of-function mutations identified in previous studies as common adaptations during CF chronic lung infections were also identified in multiple LES isolates. Analysis of the LES accessory genome (including genomic islands and prophages) revealed variations in the carriage of large genomic regions, with some evidence for shared genomic island/prophage complement according to clinic location. Our study reveals divergence and adaptation during the spread of the LES, within the UK and between continents.

A megaplasmid family driving dissemination of multidrug resistance in Pseudomonas.

Multidrug resistance (MDR) represents a global threat to health. Here, we used whole genome sequencing to characterise Pseudomonas aeruginosa MDR clinical isolates from a hospital in Thailand. Using long-read sequence data we obtained complete sequences of two closely related megaplasmids (>420 kb) carrying large arrays of antibiotic resistance genes located in discrete, complex and dynamic resistance regions, and revealing evidence of extensive duplication and recombination events. A comprehensive pangenomic and phylogenomic analysis indicates that: 1) these large plasmids comprise an emerging family present in different members of the Pseudomonas genus, and associated with multiple sources (geographical, clinical or environmental); 2) the megaplasmids encode diverse niche-adaptive accessory traits, including multidrug resistance; 3) the accessory genome of the megaplasmid family is highly flexible and diverse. The history of the megaplasmid family, inferred from our analysis of the available database, suggests that members carrying multiple resistance genes date back to at least the 1970s.

Genomic characterisation of an international Pseudomonas aeruginosa reference panel indicates that the two major groups draw upon distinct mobile gene pools.

Pseudomonas aeruginosa is an important opportunistic pathogen, especially in the context of infections of cystic fibrosis (CF). In order to facilitate coordinated study of this pathogen, an international reference panel of P. aeruginosa isolates was assembled. Here we report the genome sequencing and analysis of 33 of these isolates and 7 reference genomes to further characterise this panel. Core genome single nucleotide variant phylogeny demonstrated that the panel strains are widely distributed amongst the P. aeruginosa population. Common loss-of-function mutations reported as adaptive during CF (such as in mucA and mexA) were identified amongst isolates from chronic respiratory infections. From the 40 strains analysed, 37 unique resistomes were predicted, based on the Resistance Gene Identifier method using the Comprehensive Antibiotic Resistance Database. Notably, hierarchical clustering and phylogenetic reconstructions based on the presence/absence of genomic islands (GIs), prophages and other regions of genome plasticity (RGPs) supported the subdivision of P. aeruginosa into two main groups. This is the largest, most diverse analysis of GIs and associated RGPs to date, and the results suggest that, at least at the largest clade grouping level (group 1 vs group 2), each group may be drawing upon distinct mobile gene pools.

Pseudomonas aeruginosa adaptation and diversification in the non-cystic fibrosis bronchiectasis lung.

To characterise Pseudomonas aeruginosa populations during chronic lung infections of non-cystic fibrosis bronchiectasis patients, we used whole-genome sequencing to 1) assess the diversity of P. aeruginosa and the prevalence of multilineage infections; 2) seek evidence for cross-infection or common source acquisition; and 3) characterise P. aeruginosa adaptations.189 isolates, obtained from the sputa of 91 patients attending 16 adult bronchiectasis centres in the UK, were whole-genome sequenced.Bronchiectasis isolates were representative of the wider P. aeruginosa population. Of 24 patients from whom multiple isolates were examined, there were seven examples of multilineage infections, probably arising from multiple infection events. The number of nucleotide variants between genomes of isolates from different patients was in some cases similar to the variations observed between isolates from individual patients, implying the possible occurrence of cross-infection or common source acquisition.Our data indicate that during infections of bronchiectasis patients, P. aeruginosa populations adapt by accumulating loss-of-function mutations, leading to changes in phenotypes including different modes of iron acquisition and variations in biofilm-associated polysaccharides. The within-population diversification suggests that larger scale longitudinal surveillance studies will be required to capture cross-infection or common source acquisition events at an early stage.