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Recombination drives genome evolution in outbreak-related Legionella pneumophila isolates

Abstract

Legionella pneumophila is a strictly environmental pathogen and the etiological agent of legionellosis. It is known that non-vertical processes have a major role in the short-term evolution of pathogens, but little is known about the relevance of these and other processes in environmental bacteria. We report the whole-genome sequencing of 69 L. pneumophila strains linked to recurrent outbreaks in a single location (Alcoy, Spain) over 11 years. We found some examples where the genome sequences of isolates of the same sequence type and outbreak did not cluster together and were more closely related to sequences from different outbreaks. Our analyses identify 16 recombination events responsible for almost 98% of the SNPs detected in the core genome and an apparent acceleration in the evolutionary rate. These results have profound implications for the understanding of microbial populations and for public health interventions in Legionella outbreak investigations.

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Figure 1: Distribution of the number of pairwise SNP distances in the core genome between the L. pneumophila strains from 13 different outbreaks that occurred in Alcoy (Spain) between 1999 and 2010.
Figure 2: Maximum-likelihood phylogenetic reconstruction of the core genome (2,448,996 bp) of 69 strains of L. pneumophila and 9 reference genomes.
Figure 3: Recent evolution of ST578 in Alcoy.
Figure 4: SNP density per core gene in the five highlighted branches of the tree.
Figure 5: Demographic dynamics of the ST578 strains.

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Acknowledgements

The authors acknowledge the Dirección General de Salud Pública (DGSP; Conselleria de Sanidad, Generalitat Valenciana) and the Centro de Salud Pública de Alcoy for sharing information and comments on the Legionella outbreaks in Alcoy and facilitating access to epidemiological data. We also thank the Microbiology Service at the Hospital Virgen de los Lírios (Alcoy) and the Laboratorio de Salud Pública for sharing the Legionella samples used in this study, as well as the Genomics section of the Serveis Centrals de Support a l'Investigació Experimental (SCSIE; University of Valencia) for their technical help in the deep sequencing of the strains. We would also like to thank J. Parkhill and S. Harris (Wellcome Trust Sanger Institute) for their comments as well as facilitating their computational resources during the revision of the manuscript. The work has been funded by project BFU2011-24112 from the Ministerio de Economía y Competitividad (MINECO) of the Spanish government. L.S.-B. is the recipient of a Formación de Profesorado Universitario (FPU) predoctoral fellowship from the Ministerio de Educación of the Spanish government. I.C. was supported by an Intra-European Fellowship (IEF; 272086) from Framework Programme 7 and Ramón y Cajal from the Spanish government (RYC-2012-10627).

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Authors

Contributions

L.S.-B. designed the study, performed the experiments, analyzed the data and drafted the manuscript. I.C. analyzed the data and wrote the manuscript. G.J. performed the experiments and analyzed the data. F.G.-C. designed the study, analyzed the data and wrote the manuscript.

Corresponding author

Correspondence to Fernando González-Candelas.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Distribution of the number of core genome pairwise SNP distances between and within the L. pneumophila strains included in the study.

(a) Intra– and inter–sequence type (ST) pairwise distances between L. pneumophila isolates are shown in gray and red, respectively. (b) Within-ST pairwise polymorphisms for the three most common profiles in the data set: ST578, ST637 and ST1.

Supplementary Figure 2 Sequence-based typing (SBT) and genome-wide SNP distances.

Correlation between the SNP distances found from SBT and core genome data for the 15 STs included in this study. Dots of different color show comparisons between each ST and the remainder.

Supplementary Figure 3 Inter-ST core genome variability.

Genetic variability measured by the nucleotide diversity (π, filled dots) and the population mutation rate (τ, unfilled dots) between the core genome of the three most abundant STs in our data set (ST1, ST578 and ST637; with 10, 45 and 6 isolates, respectively) measured using Variscan. Red represents the estimates from clinical samples (C), blue represent the estimates from environmental samples (E) and black represents the estimates from both groups together.

Supplementary Figure 4 Temporal variation in the genomic variability of L. pneumophila strains.

Nucleotide diversity (π filled dots) and population mutation rate (τ, unfilled dots) calculated for the core genome using Variscan (a) within and between the ST578 and ST637 strains grouped by outbreak or sporadic cases (sorted by the time at which each outbreak occurred) and (b) between the ST578 strains isolated in different years. Red represents the estimates in clinical samples (C), blue represents the estimates in environmental samples (E) and black shows the grouping of both together.

Supplementary Figure 5 Temporal signal in the data set used in the study.

The correlation between the root-to-tip distances for the strains included in the study and the isolation time estimated using Path-O-Gen in the initial core alignment (a) and in the non-recombining core alignment (b). The two outlier points in b correspond to strains ID_3355 and ID_7371, which have probably acquired mutations at a slightly higher rate than the other strains present in the data set. Removing these two outliers, the correlation and R2 parameters do not change significantly.

Supplementary Figure 6 Distribution of substitution rates.

The distribution of the substitution rates per branch (evaluated from the MCC reconstruction with BEAST using the BSP and uncorrelated lognormal clock) of the ST578 strains from Alcoy is represented as boxplots for the complete core genome and the non-recombining core genome, respectively. The B1–B5 labels for the outlier dots mark the five mainly recombinant branches found in the study. Summary statistics for the corresponding distributions are shown in the box below each plot.

Supplementary Figure 7 Expected and observed number of SNPs per gene.

Scatterplot showing the observed number of SNPs per gene against the expected number considering a random normal distribution. Red lines represent the 95% confidence interval for the regression analysis. The 3,120 genes of the initial core genome are represented as black dots, and the 2,688 genes of the non-recombining core genome are shown in orange.

Supplementary Figure 8 Examples of topological incongruence in recombinant genes.

Gene trees were compared topologically to the concatenate of the whole-core alignment. Sequences from other STs were included to account for recombination with external strains and are shown in different colors. (a) The topology of the concatenate. (b–f) The topologies of five different genes detected as recombinant. Note the external STs interspersed within the ST578 population.

Supplementary Figure 9 Non-recombining core per-gene SNP density.

The SNP density per non-recombinant gene is shown for branches B1, B2 and B5 taking into account the ancestral SNPs traced using Mesquite and the corresponding gene lengths. Branches B3 and B4 are not present in the topology of the 2,688-gene non-recombining MCC BEAST tree and thus are not represented in the plot. The 432 genes detected as recombinant are represented in the back as gray points for comparison purposes.

Supplementary Figure 10 Representation of the number of SNPs per gene per branch in the 3,120-gene ST578 core tree.

The tree on the left contains the node numbers that identify the different branches (the notation for the five branches, B1–B5, that accumulate more SNPs is shown in gray). The graph on the right shows the total number of SNPs per gene as the header. The following rows represent the number of SNPs per gene in each of the branches. Background colors represent the clades in the tree where the corresponding branches are present. The five branches on which this study focuses are marked in bold with black rectangles. Gray vertical lines represent the 247 genes detected with a non-vertical phylogenetic signal.

Supplementary Figure 11 Functional classification of the genes involved in recombination events.

The distribution of the function of the genes involved in the detected recombination events over Cluster of Orthologous Genes (COGs) classification. These genes include virulence factors involved in the type IV secretion system (sidA, sidF, lepA and lepB) and genes involved in invasion and motility (enhA, enhB, enhC and mviN), regulation (letA) and iron acquisition (feoA and feoB). Moreover, with recombination events B and C, ST578B could have incorporated SNPs in genes involved in DNA damage repair and mutagenesis, such as mutH, umuC and umuD. Letters on the x axis correspond to the functional categories described in ftp://ftp.ncbi.nlm.nih.gov/pub/COG/COG/fun.txt.

Supplementary Figure 12 Node height highest posterior density (HPD) intervals at 95%.

Comparison between the mean time to MRCA estimates (black dots) and the 95% HPD intervals (blue dots) before (A) and after (B) removing recombination events for the whole ST578 tree and the two sublineages ST578A and ST578B independently.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–12 and Supplementary Tables 1–6 and 8 (PDF 1769 kb)

Supplementary Table 7

Genes included in each recombination event (A–P). (XLSX 78 kb)

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Sánchez-Busó, L., Comas, I., Jorques, G. et al. Recombination drives genome evolution in outbreak-related Legionella pneumophila isolates. Nat Genet 46, 1205–1211 (2014). https://doi.org/10.1038/ng.3114

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