Evaluation of an Optimal Epidemiological Typing Scheme for Legionella pneumophila with Whole-Genome Sequence Data Using Validation Guidelines

An outbreak of Legionnaires' disease linked to a municipal and industrial wastewater treatment plant, The Netherlands, September-October 2022

Wastewater treatment plants (WWTPs) are increasingly identified as Legionnaires' disease (LD) sources. An outbreak investigation was initiated following five LD cases reported in September 2022 in Houten, the Netherlands. Case identification was based on the European LD case definition, with symptom onset from 1 September 2022, residence in or within 5 km of Houten, or visit to Houten within the incubation period, without other likely sources. We sampled potential sources and genotyped environmental and clinical isolates. We identified 15 LD cases with onset between 13 September and 23 October 2022. A spatial source identification and wind direction model suggested an industrial (iWWTP) and a municipal WWTP (mWWTP) as potential sources, with the first discharging water into the latter. Both tested positive for Legionella pneumophila serogroups 1 and 6 with multiple sequence types (ST). We detected L. pneumophila sg1 ST42 in the mWWTP, matching with one of three available clinical isolates. Following control measures at the WWTPs, no further cases were observed. This outbreak underlines that municipal and industrial WWTPs can play an important role in community LD cases and outbreaks, especially those with favourable conditions for Legionella growth and dissemination, or even non-favourable conditions for growth but with the influx of contaminated water.

Evaluating Fourier-transform infrared spectroscopy with IR Biotyper as a faster and simpler method for investigating the sources of an outbreak of legionellosis

Fourier-transform infrared (FTIR) spectroscopy using the IR Biotyper and core genome single nucleotide polymorphism (cgSNP) analysis were performed on 12 Legionella isolates associated with an outbreak at a spa house in Kanagawa Prefecture, Japan, and 3 non-outbreak isolates. The discriminative power of FTIR spectroscopy for 48-h incubation conditions of L. pneumophila in this outbreak was lower than cgSNP-based typing but higher than serogroup typing. FTIR spectroscopy could screen outbreak isolates from a group of genetically related isolates and may be useful as an initial typing method in Legionella outbreak investigations.

From Investigating a Case of Cellulitis to Exploring Nosocomial Infection Control of ST1 Legionella pneumophila Using Genomic Approaches

Legionella pneumophila can cause a large panel of symptoms besides the classic pneumonia presentation. Here we present a case of fatal nosocomial cellulitis in an immunocompromised patient followed, a year later, by a second case of Legionnaires' disease in the same ward. While the first case was easily assumed as nosocomial based on the date of symptom onset, the second case required clear typing results to be assigned either as nosocomial and related to the same environmental source as the first case, or community acquired. To untangle this specific question, we applied core-genome multilocus typing (MLST), whole-genome single nucleotide polymorphism and whole-genome MLST methods to a collection of 36 Belgian and 41 international sequence-type 1 (ST1) isolates using both thresholds recommended in the literature and tailored threshold based on local epidemiological data. Based on the thresholds applied to cluster isolates together, the three methods gave different results and no firm conclusion about the nosocomial setting of the second case could been drawn. Our data highlight that despite promising results in the study of outbreaks and for large-scale epidemiological investigations, next-generation sequencing typing methods applied to ST1 outbreak investigation still need standardization regarding both wet-lab protocols and bioinformatics. A deeper evaluation of the L. pneumophila evolutionary clock is also required to increase our understanding of genomic differences between isolates sampled during a clinical infection and in the environment.

Matchtigs: minimum plain text representation of k-mer sets

We propose a polynomial algorithm computing a minimum plain-text representation of k-mer sets, as well as an efficient near-minimum greedy heuristic. When compressing read sets of large model organisms or bacterial pangenomes, with only a minor runtime increase, we shrink the representation by up to 59% over unitigs and 26% over previous work. Additionally, the number of strings is decreased by up to 97% over unitigs and 90% over previous work. Finally, a small representation has advantages in downstream applications, as it speeds up SSHash-Lite queries by up to 4.26× over unitigs and 2.10× over previous work.

Comparative Genomics of Legionella pneumophila Isolates from the West Bank and Germany Support Molecular Epidemiology of Legionnaires' Disease

Legionella pneumophila is an environmental bacterium and clinical pathogen that causes many life-threating outbreaks of an atypical pneumonia called Legionnaires' disease (LD). Studies of this pathogen have focused mainly on Europe and the United States. A shortage in L. pneumophila data is clearly observed for developing countries. To reduce this knowledge gap, L. pneumophila isolates were studied in two widely different geographical areas, i.e., the West Bank and Germany. For this study, we sequenced and compared the whole genome of 38 clinical and environmental isolates of L. pneumophila covering different MLVA-8(12) genotypes in the two areas. Sequencing was conducted using the Illumina HiSeq 2500 platform. In addition, two isolates (A194 and H3) were sequenced using a Pacific Biosciences (PacBio) RSII platform to generate complete reference genomes from each of the geographical areas. Genome sequences from 55 L. pneumophila strains, including 17 reference strains, were aligned with the genome sequence of the closest strain (L. pneumophila strain Alcoy). A whole genome phylogeny based on single nucleotide polymorphisms (SNPs) was created using the ParSNP software v 1.0. The reference genomes obtained for isolates A194 and H3 consisted of circular chromosomes of 3,467,904 bp and 3,691,263 bp, respectively. An average of 36,418 SNPs (min. 8569, max. 70,708 SNPs) against our reference strain L. pneumophila str. Alcoy, and 2367 core-genes were identified among the fifty-five strains. An analysis of the genomic population structure by SNP comparison divided the fifty-five L. pneumophila strains into six branches. Individual isolates in sub-lineages in these branches differed by less than 120 SNPs if they had the same MLVA genotype and were isolated from the same location. A bioinformatics analysis identified the genomic islands (GIs) for horizontal gene transfer and mobile genetic elements, demonstrating that L. pneumophila showed high genome plasticity. Four L. pneumophila isolates (H3, A29, A129 and L10-091) contained well-defined plasmids. On average, only about half of the plasmid genes could be matched to proteins in databases. In silico phage findings suggested that 43 strains contained at least one phage. However, none of them were found to be complete. BLASTp analysis of proteins from the type IV secretion Dot/Icm system showed those proteins highly conserved, with less than 25% structural differences in the new L. pneumophila isolates. Overall, we demonstrated that whole genome sequencing provides a molecular surveillance tool for L. pneumophila at the highest conceivable discriminatory level, i.e., two to eight SNPs were observed for isolates from the same location but several years apart.

Epidemiological analysis of Legionnaires' disease in Scotland: a genomic study

BACKGROUND

Legionella pneumophila is the main cause of a severe pneumonic illness known as Legionnaires' disease and is a global public health threat. Whole-genome sequencing (WGS) can be applied to trace environmental origins of L pneumophila infections, providing information to guide appropriate interventions. We aim to explore the evolutionary and epidemiological relationships in a 36-year Scottish L pneumophila reference isolate collection.

METHODS

We investigated the genomic epidemiology of Legionnaires' disease over 36 years in Scotland, comparing genome sequences for all clinical L pneumophila isolates (1984-2020) with a sequence dataset of 3211 local and globally representative isolates. We used a stratified clustering approach to capture epidemiological relationships by core genome Multi-locus Sequence Typing, followed by high-resolution phylogenetic analysis of clusters to measure diversity and evolutionary relatedness in context with epidemiological metadata.

FINDINGS

Clustering analysis showed that 111 (57·5 %) of 193 of L pneumophila infections in Scotland were caused by ten endemic lineages with a wide temporal and geographical distribution. Phylogenetic analysis of L pneumophila identified hospital-associated sublineages that had been detected in the hospital environment up to 19 years. Furthermore, 12 (30·0%) of 40 community-associated infections (excluding a single, large outbreak) that occurred over a 13 year period (from 2000 to 2013) were caused by a single widely distributed endemic clone (ST37), consistent with enhanced human pathogenicity. Finally, our analysis revealed clusters linked by national or international travel to distinct geographical regions, indicating several previously unrecognised travel links between closely related isolates (fewer than five single nucleotide polymorphisms) connected by geography.

INTERPRETATION

Our analysis reveals the existence of previously undetected endemic clones of L pneumophila that existed for many years in hospital, community, and travel-associated environments. In light of these findings, we propose that cluster and outbreak definitions should be reconsidered, and propose WGS-based surveillance as a critical public health tool for real-time identification and mitigation of clinically important endemic clones.

FUNDING

Chief Scientist Office, Biotechnology and Biological Sciences Research Council (UK), Medical Research Council Precision Medicine Doctoral Training Programme, Wellcome Trust, and Medical Research Council (UK).

Culture-Free Phylogenetic Analysis of Legionella pneumophila Using Targeted CRISPR/Cas9 Next-Generation Sequencing

Currently available methods for the laboratory investigation of Legionella pneumophila outbreaks require organism culture. The ability to sequence L. pneumophila directly from clinical samples would significantly reduce delays. Here, we develop a method for targeted next-generation sequencing (NGS) of selected L. pneumophila genes utilizing a CRISPR/Cas9-based target enrichment system. We determine the method's utility by typing cultured L. pneumophila isolates and subsequently apply the method directly to patient samples. We sequenced 10 L. pneumophila isolates by 2 methods, (i) whole-genome sequencing (WGS) and (ii) targeted (CRISPR/Cas9-based) finding low-abundance sequences by hybridization (FLASH)-NGS, sequencing 57 selected genes. The targeted NGS of 57 genes was more efficient than WGS, and phylogenetic analysis of the 57 genes yielded the same classification of the L. pneumophila isolates as that based on analysis of whole-genome data. Furthermore, targeted NGS of L. pneumophila performed directly on patient respiratory samples correctly classified the patients according to their corresponding cultured isolates. This provides proof of concept that targeted NGS can be used to sequence L. pneumophila directly from patient samples. Studies on a larger number of patient samples will further validate this method. Nonetheless, CRISPR/Cas9 targeted NGS methods have the potential to be widely applicable to microbial-outbreak investigations in the future, particularly in the context of difficult and slow-growing organisms. IMPORTANCE The bacterium Legionella pneumophila is responsible for outbreaks of serious and life-threatening pneumonia called Legionnaires' disease. There is a need for new molecular methods that allow investigation of Legionella outbreaks directly from patient samples, without the need for prior microbiological culture, which causes delays. Our study aims to address this problem. We have utilized a CRISPR/Cas9-based targeted next-generation sequencing (NGS) method that can be applied directly on human specimens. Furthermore, we show that analysis of the sequences of a small number of targeted genes offers the same classification of L. pneumophila as that based on data derived from the whole genome. Given the rising interest globally in sequencing pathogens directly from human samples, CRISPR/Cas9 targeted NGS methods have the potential to be widely applicable to microbial-outbreak investigations in the future, particularly in the context of difficult and slow-growing organisms.

Non-Legionella pneumophila serogroup 1 pneumonia: Diagnosis of a nosocomial legionellosis with the Biofire Pneumonia plus panel

We report a nosocomial case of Legionella pneumophila pneumonia caused by a serogroup 10 strain diagnosed with the Biofire® Pneumonia plus panel. Molecular investigations of the environment of the patient allowed us to identify the source of contamination.

Evaluation and identification of essential therapeutic proteins and vaccinomics approach towards multi-epitopes vaccine designing against Legionella pneumophila for immune response instigation

The Legionellaceae group comprises the Legionella, containing 58 species with 70 serotypes. For instance, Legionella pneumophila is the deadliest serotype to cause Legionnaires infectious and is responsible for 90% of the infections in humans. The bacterial pathogen is associated with a severe lung infection, known as legionaries' disease. It is resistant to multiple drugs, thus warranting novel vaccine candidates identification to immune the host against infections caused by the said pathogen. For this, we applied the subtractive proteomics and reverse vaccinology approaches to annotate the most essential genes suitable for vaccine designing. From the whole proteome, only five proteins (Q5ZVG4, Q5ZRZ1, Q5ZWE6, Q5ZT09, and Q5ZUZ8) as the best targets for further processing as they fulfill all the standard parameters set for in silico vaccine design. Immuno-informatics approaches were further applied to the selected protein sequences to prioritized antigenic epitopes for design a multi-epitope subunit vaccine. A multi-epitopes vaccine was designed by using suitable linkers to link the CTL (cytotoxic T lymphocytes), HTL (Helper T lymphocytes), B cell epitopes, and adjuvant to strengthen the vaccine's immunogenicity. The MEVC(multi-epitopes vaccine construct) was reported to interact with human immune receptor TLR-2 (toll-like receptor) robustly (docking score = -357.18 kcal/mol), and a higher expression was achieved in the Escherichia coli system (CAI = 0.88, and GC contents = 54.34%). Moreover, immune simulation revealed that on the 3rd day, the neutralization of the antigen started, while on the 5th day, the antigen was completely neutralized by the secreted immune factors. In conclusion, the designed vaccine candidate effectively triggered the immune response against eh pathogen; however, wet lab-based experimentations are highly recommended to prove the protective immunological proficiency of the vaccine against L. pneumophila.

Genome analysis of Legionella pneumophila ST23 from various countries reveals highly similar strains

ST23 isolated in Italy are analysed by cgMLST and SNP approaches and they are also compared with ST23 from other countries. They are found to be phylogenetically related independently on year, town, or country of isolation.

Legionella pneumophila serogroup 1 (Lp1) sequence type (ST) 23 is one of the most commonly detected STs in Italy where it currently causes all investigated outbreaks. ST23 has caused both epidemic and sporadic cases between 1995 and 2018 and was analysed at genomic level and compared with ST23 isolated in other countries to determine possible similarities and differences. A core genome multi-locus sequence typing (cgMLST), based on a previously described set of 1,521 core genes, and single-nucleotide polymorphisms (SNPs) approaches were applied to an ST23 collection including genomes from Italy, France, Denmark and Scotland. DNAs were automatically extracted, libraries prepared using NextEra library kit and MiSeq sequencing performed. Overall, 63 among clinical and environmental Italian Lp1 isolates and a further seven and 11 ST23 from Denmark and Scotland, respectively, were sequenced, and pangenome analysed. Both cgMLST and SNPs analyses showed very few loci and SNP variations in ST23 genomes. All the ST23 causing outbreaks and sporadic cases in Italy and elsewhere, were phylogenetically related independent of year, town or country of isolation. Distances among the ST23s were further shortened when SNPs due to horizontal gene transfers were removed. The Lp1 ST23 isolated in Italy have kept their monophyletic origin, but they are phylogenetically close also to ST23 from other countries. The ST23 are quite widespread in Italy, and a thorough epidemiological investigation is compelled to determine sources of infection when this ST is identified in both LD sporadic cases and outbreaks.

Legionella pneumophila in Municipal Shower Systems in Stavanger, Norway; A Longitudinal Surveillance Study Using Whole Genome Sequencing in Risk Management

Following an incidence of Legionnaires disease (LD) in 2007, where a municipal shower system was the likely source of infection, Stavanger municipality initiated a surveillance program for Legionella as part of establishing internal risk evaluation and prevention routines. More than 250 shower systems were examined for cultivatable Legionella pneumophila. The prevalence and diversity of serogroups (sg) and sequence types (STs) of L. pneumophila were mapped using available typing techniques over a period of more than 10 years (2010–2021). The surveillance showed an overall reduction in the L. pneumophila colonisation rate in municipal systems from 11 to 4.5% following prevention measures during the period, with the highest colonisation rate in complex systems (e.g., larger nursing homes and sports complexes). Further, an approximately even distribution between sg1 and 2–14 was seen. Whole genome sequencing (WGS) revealed that only a limited number of STs were detected, and they were consistent at specific locations over time. This study showed that environmental surveillance data in combination with available typing techniques and WGS can give the municipality a better tool for risk management and an overview of ST distributions that can be a valuable asset in future source investigations.

Genomic epidemiology links Burkholderia pseudomallei from individual human cases to B. pseudomallei from targeted environmental sampling in Northern Australia

Each case of melioidosis results from a single event when a human is infected by the environmental bacterium Burkholderia pseudomallei. Darwin in tropical northern Australia has the highest incidences of melioidosis globally and the Darwin Prospective Melioidosis Study (DPMS) commenced in 1989, documenting all culture confirmed melioidosis cases. From 2000-2019 we sampled DPMS patient's environments for B. pseudomallei when a specific location was considered to have been where infection occurred. With the aim to use genomic epidemiology to understand B. pseudomallei transmission and infecting scenarios. Environmental sampling was performed at 98 DPMS patient sites, where we collected 975 environmental samples (742 soil; 233 water). Genotyping matched the clinical and epidemiologically linked environmental B. pseudomallei for 19 patients (19%), with the environmental isolates cultured from soil (n=11) or water (n=8) sources. B. pseudomallei isolates from patients and their local environments that matched on genotyping were whole genome sequenced (WGS). Of the 19 patients with a clinical-environmental genotype match, 17 pairs clustered on a Darwin core genome single-nucleotide polymorphism (SNP) phylogeny, later confirmed by single ST phylogenies and pairwise comparative genomics. When related back to patient clinical scenarios, the matched clinical and environmental B. pseudomallei pairs informed likely modes of infection: percutaneous inoculation, inhalation, and ingestion. Targeted environmental sampling for B. pseudomallei can inform infecting scenarios for melioidosis and dangerous occupational and recreational activities and identify hot spots of B. pseudomallei presence. However, WGS and careful genomics are required to avoid overcalling the relatedness between clinical and environmental isolates of B. pseudomallei.

Acute Pneumonia Caused by Clinically Isolated Legionella pneumophila Sg 1, ST 62: Host Responses and Pathologies in Mice

Legionnaires’ disease is a severe form of lung infection caused by bacteria belonging to the genus Legionella. The disease severity depends on both host immunity and L. pneumophila virulence. The objective of this study was to describe the pathological spectrum of acute pneumonia caused by a virulent clinical isolate of L. pneumophila serogroup 1, sequence type 62. In A/JOlaHsd mice, we compared two infectious doses, namely, 10⁴ and 10⁶ CFU, and their impact on the mouse status, bacterial clearance, lung pathology, and blood count parameters was studied. Acute pneumonia resembling Legionnaires’ disease has been described in detail.

Occurrence of Legionella spp. in Man-Made Water Sources: Isolates Distribution and Phylogenetic Characterization in the Emilia-Romagna Region

Legionella species distribution in the Emilia-Romagna region, involving hospital (H) and community (C) environments, was conducted. Legionella culture, agglutination test, and mip-gene sequencing were applied on 240 isolates. The analysis showed a higher prevalence of non-Legionellapneumophila (n-Lp) species (84.1%) compared with L. pneumophila (Lp) (15.9%), with a higher frequency of n-Lp with respect to Lp species in both environments (77.6% and 96.4%, in H and C, respectively). The Shannon index showed a significant difference in Legionella distribution (p = 0.00017), with a significant abundance of Lp in the H compared with C environment (p = 0.00028). The continuous disinfection treatment in H could contribute to adaptive survival of the Lp species. Phylogenetic analysis revealed a conservative clade distribution between H and C: L. feeleii clade with three subclades in C and the Lp clade with five subclades in H and two in C, respectively. Our findings suggest the importance of Legionella surveillance both in H and C, with a focus on n-Lp species less connected to human disease. The Legionella prevalence and diversity found here indicate that geographical and temporal isolate evolution should be considered during surveillance, particularly in the light of global warming and changes in population risk factors.

minMLST: machine learning for optimization of bacterial strain typing

MOTIVATION

High-resolution microbial strain typing is essential for various clinical purposes, including disease outbreak investigation, tracking of microbial transmission events and epidemiological surveillance of bacterial infections. The widely used approach for multilocus sequence typing (MLST) that is based on the core genome, cgMLST, has the advantage of a high level of typeability and maximal discriminatory power. Yet, the transition from a seven loci-based scheme to cgMLST involves several challenges, that include the need by some users to maintain backward compatibility, growing difficulties in the day-to-day communication within the microbiology community with respect to nomenclature and ontology, issues with typeability, especially if a more stringent approach to loci presence is used, and computational requirements concerning laboratory data management and sharing with end-users. Hence, methods for optimizing cgMLST schemes through careful reduction of the number of loci are expected to be beneficial for practical needs in different settings.

RESULTS

We present a new machine learning-based methodology, minMLST, for minimizing the number of genes in cgMLST schemes by identifying subsets of informative genes and analyzing the trade-off between gene reduction and typing performance. The results achieved with minMLST over eight bacterial species show that despite the reduction in the number of genes up to a factor of 10, the typing performance remains very high and significant with an Adjusted Rand Index that ranges between 0.4 and 0.93 in different species and a P-value < 10-3. The identification of such optimized MLST schemes for bacterial strain typing is expected to improve the implementation of cgMLST by improving interlaboratory agreement and communication.

AVAILABILITY AND IMPLEMENTATION

The python package minMLST is available at https://PyPi.org/project/minmlst/PyPI and supported on Linux and Windows.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A Bioinformatic Pipeline for Improved Genome Analysis and Clustering of Isolates during Outbreaks of Legionnaires' Disease

Legionnaires' disease, a severe lung infection caused by the bacterium Legionella pneumophila, occurs as single cases or in outbreaks that are actively tracked by public health departments. To determine the point source of an outbreak, clinical isolates need to be compared to environmental samples to find matching isolates. One confounding factor is the genome plasticity of L. pneumophila, making an exact sequence comparison by whole-genome sequencing (WGS) challenging. Here, we present a WGS analysis pipeline, LegioCluster, that is designed to circumvent this problem by automatically selecting the best matching reference genome prior to mapping and variant calling. This approach reduces the number of false-positive variant calls, maximizes the fraction of all genomes that are being compared, and naturally clusters the isolates according to their reference strain. Isolates that are too distant from any genome in the database are added to the list of candidate references, thereby creating a new cluster. Short insertions or deletions are considered in addition to single-nucleotide polymorphisms for increased discriminatory power. This manuscript describes the use of this automated and "locked down" bioinformatic pipeline deployed at the New York State Department of Health's Wadsworth Center for investigating relatedness between clinical and environmental isolates. A similar pipeline has not been widely available for use to support these critically important public health investigations.

Characterization of Legionella pneumophila Populations by Multilocus Variable Number of Tandem Repeats (MLVA) Genotyping from Drinking Water and Biofilm in Hospitals from Different Regions of the West Bank

The West Bank can be considered a high-risk area for Legionnaires' disease (LD) due to its hot climate, intermittent water supply and roof storage of drinking water. Legionella, mostly L. pneumophila, are responsible for LD, a severe, community-acquired and nosocomial pneumonia. To date, no extensive assessment of Legionella spp and L. pneumophila using cultivation in combination with molecular approaches in the West Bank has been published. Two years of environmental surveillance of Legionella in water and biofilms in the drinking water distribution systems (DWDS) of eight hospitals was carried out; 180 L. pneumophila strains were isolated, mostly from biofilms in DWDS. Most of the isolates were identified as serogroup (Sg) 1 (60%) and 6 (30%), while a minor fraction comprised Sg 8 and 10. Multilocus Variable number of tandem repeats Analysis using 13 loci (MLVA-8(12)) was applied as a high-resolution genotyping method and compared to the standard Sequence Based Typing (SBT). The isolates were genotyped in 27 MLVA-8(12) genotypes (Gt), comprising four MLVA clonal complexes (VACC 1; 2; 5; 11). The major fraction of isolates constituted Sequence Type (ST)1 and ST461. Most of the MLVA-genotypes were highly diverse and often unique. The MLVA-genotype composition showed substantial regional variability. In general, the applied MLVA-method made it possible to reproducibly genotype the isolates, and was consistent with SBT but showed a higher resolution. The advantage of the higher resolution was most evident for the subdivision of the large strain sets of ST1 and ST461; these STs were shown to be highly pneumonia-relevant in a former study. This shows that the resolution by MLVA is advantageous for back-tracking risk sites and for the avoidance of outbreaks of L. pneumophila. Overall, our results provide important insights into the detailed population structure of L. pneumophila, allowing for better risk assessment for DWDS.

Detailed Evaluation of Data Analysis Tools for Subtyping of Bacterial Isolates Based on Whole Genome Sequencing: Neisseria meningitidis as a Proof of Concept

Whole genome sequencing is increasingly recognized as the most informative approach for characterization of bacterial isolates. Success of the routine use of this technology in public health laboratories depends on the availability of well-characterized and verified data analysis methods. However, multiple subtyping workflows are now often being used for a single organism, and differences between them are not always well described. Moreover, methodologies for comparison of subtyping workflows, and assessment of their performance are only beginning to emerge. Current work focuses on the detailed comparison of WGS-based subtyping workflows and evaluation of their suitability for the organism and the research context in question. We evaluated the performance of pipelines used for subtyping of Neisseria meningitidis, including the currently widely applied cgMLST approach and different SNP-based methods. In addition, the impact of the use of different tools for detection and filtering of recombinant regions and of different reference genomes were tested. Our benchmarking analysis included both assessment of technical performance of the pipelines and functional comparison of the generated genetic distance matrices and phylogenetic trees. It was carried out using replicate sequencing datasets of high- and low-coverage, consisting mainly of isolates belonging to the clonal complex 269. We demonstrated that cgMLST and some of the SNP-based subtyping workflows showed very good performance characteristics and highly similar genetic distance matrices and phylogenetic trees with isolates belonging to the same clonal complex. However, only two of the tested workflows demonstrated reproducible results for a group of more closely related isolates. Additionally, results of the SNP-based subtyping workflows were to some level dependent on the reference genome used. Interestingly, the use of recombination-filtering software generally reduced the similarity between the gene-by-gene and SNP-based methodologies for subtyping of N. meningitidis. Our study, where N. meningitidis was taken as an example, clearly highlights the need for more benchmarking comparative studies to eventually contribute to a justified use of a specific WGS data analysis workflow within an international public health laboratory context.

Genomic heterogeneity differentiates clinical and environmental subgroups of Legionella pneumophila sequence type 1

Legionella spp. are the cause of a severe bacterial pneumonia known as Legionnaires' disease (LD). In some cases, current genetic subtyping methods cannot resolve LD outbreaks caused by common, potentially endemic L. pneumophila (Lp) sequence types (ST), which complicates laboratory investigations and environmental source attribution. In the United States (US), ST1 is the most prevalent clinical and environmental Lp sequence type. In order to characterize the ST1 population, we sequenced 289 outbreak and non-outbreak associated clinical and environmental ST1 and ST1-variant Lp strains from the US and, together with international isolate sequences, explored their genetic and geographic diversity. The ST1 population was highly conserved at the nucleotide level; 98% of core nucleotide positions were invariant and environmental isolates unassociated with human disease (n = 99) contained ~65% more nucleotide diversity compared to clinical-sporadic (n = 139) or outbreak-associated (n = 28) ST1 subgroups. The accessory pangenome of environmental isolates was also ~30-60% larger than other subgroups and was enriched for transposition and conjugative transfer-associated elements. Up to ~10% of US ST1 genetic variation could be explained by geographic origin, but considerable genetic conservation existed among strains isolated from geographically distant states and from different decades. These findings provide new insight into the ST1 population structure and establish a foundation for interpreting genetic relationships among ST1 strains; these data may also inform future analyses for improved outbreak investigations.

Spatial structuring of a Legionella pneumophila population within the water system of a large occupational building

The diversity of Legionella pneumophila populations within single water systems is not well understood, particularly in those unassociated with cases of Legionnaires’ disease. Here, we performed genomic analysis of 235 L. pneumophila isolates obtained from 28 water samples in 13 locations within a large occupational building. Despite regular treatment, the water system of this building is thought to have been colonized by L. pneumophila for at least 30 years without evidence of association with Legionnaires’ disease cases. All isolates belonged to one of three sequence types (STs), ST27 (n=81), ST68 (n=122) and ST87 (n=32), all three of which have been recovered from Legionnaires’ disease patients previously. Pairwise single nucleotide polymorphism differences amongst isolates of the same ST were low, ranging from 0 to 19 in ST27, from 0 to 30 in ST68 and from 0 to 7 in ST87, and no homologous recombination was observed in any lineage. However, there was evidence of horizontal transfer of a plasmid, which was found in all ST87 isolates and only one ST68 isolate. A single ST was found in 10/13 sampled locations, and isolates of each ST were also more similar to those from the same location compared with those from different locations, demonstrating spatial structuring of the population within the water system. These findings provide the first insights into the diversity and genomic evolution of a L. pneumophila population within a complex water system not associated with disease.

Gene exchange drives the ecological success of a multi-host bacterial pathogen

The capacity for some pathogens to jump into different host-species populations is a major threat to public health and food security. Staphylococcus aureus is a multi-host bacterial pathogen responsible for important human and livestock diseases. Here, using a population-genomic approach, we identify humans as a major hub for ancient and recent S. aureus host-switching events linked to the emergence of endemic livestock strains, and cows as the main animal reservoir for the emergence of human epidemic clones. Such host-species transitions are associated with horizontal acquisition of genetic elements from host-specific gene pools conferring traits required for survival in the new host-niche. Importantly, genes associated with antimicrobial resistance are unevenly distributed among human and animal hosts, reflecting distinct antibiotic usage practices in medicine and agriculture. In addition to gene acquisition, genetic diversification has occurred in pathways associated with nutrient acquisition, implying metabolic remodelling after a host switch in response to distinct nutrient availability. For example, S. aureus from dairy cattle exhibit enhanced utilization of lactose-a major source of carbohydrate in bovine milk. Overall, our findings highlight the influence of human activities on the multi-host ecology of a major bacterial pathogen, underpinned by horizontal gene transfer and core genome diversification.

Population structure of Environmental and Clinical Legionella pneumophila isolates in Catalonia

Legionella is the causative agent of Legionnaires’ disease (LD). In Spain, Catalonia is the region with the highest incidence of LD cases. The characterisation of clinical and environmental isolates using molecular epidemiology techniques provides epidemiological data for a specific geographic region and makes it possible to carry out phylogenetic and population-based analyses. The aim of this study was to describe and compare environmental and clinical isolates of Legionella pneumophila in Catalonia using sequence-based typing and monoclonal antibody subgrouping. A total of 528 isolates were characterised. For data analysis, the isolates were filtered to reduce redundancies, and 266 isolates (109 clinical and 157 environmental) were finally included. Thirty-two per cent of the clinical isolates were ST23, ST37 and ST1 while 40% of the environmental isolates were ST284 and ST1. Although the index of diversity was higher in clinical than in environmental ST isolates, we observed that clinical STs were similar to those recorded in other regions but that environmental STs were more confined to particular study areas. This observation supports the idea that only certain STs trigger cases or outbreaks in humans. Therefore, comparison of the genomes of clinical and environmental isolates could provide important information about the traits that favour infection or environmental persistence.

Epidemiological information is key when interpreting whole genome sequence data - lessons learned from a large Legionella pneumophila outbreak in Warstein, Germany, 2013

Whole genome sequencing (WGS) is increasingly used in Legionnaires’ disease (LD) outbreak investigations, owing to its higher resolution than sequence-based typing, the gold standard typing method for Legionella pneumophila, in the analysis of endemic strains. Recently, a gene-by-gene typing approach based on 1,521 core genes called core genome multilocus sequence typing (cgMLST) was described that enables a robust and standardised typing of L. pneumophila. Methods: We applied this cgMLST scheme to isolates obtained during the largest outbreak of LD reported so far in Germany. In this outbreak, the epidemic clone ST345 had been isolated from patients and four different environmental sources. In total 42 clinical and environmental isolates were retrospectively typed. Results: Epidemiologically unrelated ST345 isolates were clearly distinguishable from the epidemic clone. Remarkably, epidemic isolates split up into two distinct clusters, ST345-A and ST345-B, each respectively containing a mix of clinical and epidemiologically-related environmental samples. Discussion/conclusion: The outbreak was therefore likely caused by both variants of the single sequence type, which pre-existed in the environmental reservoirs. The two clusters differed by 40 alleles located in two neighbouring genomic regions of ca 42 and 26 kb. Additional analysis supported horizontal gene transfer of the two regions as responsible for the difference between the variants. Both regions comprise virulence genes and have previously been reported to be involved in recombination events. This corroborates the notion that genomic outbreak investigations should always take epidemiological information into consideration when making inferences. Overall, cgMLST proved helpful in disentangling the complex genomic epidemiology of the outbreak.

Evaluation of phylogenetic reconstruction methods using bacterial whole genomes: a simulation based study

Background: Phylogenetic reconstruction is a necessary first step in many analyses which use whole genome sequence data from bacterial populations. There are many available methods to infer phylogenies, and these have various advantages and disadvantages, but few unbiased comparisons of the range of approaches have been made.

Methods: We simulated data from a defined 'true tree' using a realistic evolutionary model. We  built phylogenies from this data using a range of methods, and compared reconstructed trees to the true tree using two measures, noting the computational time needed for different phylogenetic reconstructions. We also used real data from Streptococcus pneumoniae alignments to compare individual core gene trees to a core genome tree.

Results: We found that, as expected, maximum likelihood trees from good quality alignments were the most accurate, but also the most computationally intensive. Using less accurate phylogenetic reconstruction methods, we were able to obtain results of comparable accuracy; we found that approximate results can rapidly be obtained using genetic distance based methods. In real data we found that highly conserved core genes, such as those involved in translation, gave an inaccurate tree topology, whereas genes involved in recombination events gave inaccurate branch lengths. We also show a tree-of-trees, relating the results of different phylogenetic reconstructions to each other.

Conclusions: We recommend three approaches, depending on requirements for accuracy and computational time. For the most accurate tree, use of either RAxML or IQ-TREE with an alignment of variable sites produced by mapping to a reference genome is best. Quicker approaches that do not perform full maximum likelihood optimisation may be useful for many analyses requiring a phylogeny, as generating a high quality input alignment is likely to be the major limiting factor of accurate tree topology.  We have publicly released our simulated data and code to enable further comparisons.

Low genomic diversity of Legionella pneumophila within clinical specimens

Objectives

Legionella pneumophila is the leading cause of Legionnaires' disease, a severe form of pneumonia acquired from environmental sources. Investigations of both sporadic cases and outbreaks rely mostly on analysis of a single to a few colony pick(s) isolated from each patient. However, because of the lack of data describing diversity within single patients, the optimal number of picks is unknown. Here, we investigated diversity within individual patients using sequence-based typing (SBT) and whole-genome sequencing (WGS).

Methods

Ten isolates of L. pneumophila were obtained from each of ten epidemiologically unrelated patients. SBT and WGS were undertaken, and single-nucleotide polymorphisms (SNPs) were identified between isolates from the same patient.

Results

The same sequence type (ST) was obtained for each set of ten isolates. Using genomic analysis, zero SNPs were identified between isolates from seven patients, a maximum of one SNP was found between isolates from two patients, and a maximum of two SNPs was found amongst isolates from one patient. Assuming that the full within-host diversity has been captured with ten isolates, statistical analyses showed that, on average, analysis of one isolate would yield a 70% chance of capturing all observed genotypes, and seven isolates would yield a 90% chance.

Conclusions

SBT and WGS analyses of multiple colony picks obtained from ten patients showed no, or very low, within-host genomic diversity in L. pneumophila, suggesting that analysis of one colony pick per patient will often be sufficient to obtain reliable typing data to aid investigation of cases of Legionnaires' disease.

Outbreak of Legionnaire's Disease Caused by Legionella pneumophila Serogroups 1 and 13

In Japan, hot springs and public baths are the major sources of legionellosis. In 2015, an outbreak of Legionnaires’ disease occurred among 7 patients who had visited a spa house. Laboratory investigation indicated that L. pneumophila serogroup 1 and 13 strains caused the outbreak and that these strains were genetically related.

Genome Sequencing Links Persistent Outbreak of Legionellosis in Sydney (New South Wales, Australia) to an Emerging Clone of Legionella pneumophila Sequence Type 211

The city of Sydney, Australia, experienced a persistent outbreak of Legionella pneumophila serogroup 1 (Lp1) pneumonia in 2016. To elucidate the source and guide public health actions, the genomes of clinical and environmental Lp1 isolates recovered over 7 weeks were examined. A total of 48 isolates from human cases and cooling towers were sequenced and compared using single-nucleotide polymorphism (SNP)-based core-genome multilocus sequencing typing (MLST) and pangenome approaches. All three methods confirmed phylogenetic relatedness between isolates associated with outbreaks in the Central Business District (CBD) in March and May and those in suburb 1. These isolates were designated the "main cluster" and consisted of isolates from two patients from the CBD March outbreak, one patient and one tower isolate from suburb 1, and isolates from two cooling towers and three patients from the CBD May outbreak. All main cluster isolates were sequence type 211 (ST211), which previously has only been reported in Canada. Significantly, pangenome analysis identified mobile genetic elements containing a unique type IV A F-type secretion system (T4ASS), which was specific to the main cluster, and cocirculating clinical strains, suggesting a potential mechanism for increased fitness and persistence of the outbreak clone. Genome sequencing enabled linking of the geographically dispersed environmental sources of infection among the spatially and temporally coinciding cases of legionellosis in a highly populated urban setting. The discovery of a unique T4ASS emphasizes the role of genome recombination in the emergence of successful Lp1 clones.IMPORTANCE A new emerging clone has been responsible for a prolonged legionellosis outbreak in Sydney, Australia. The use of whole-genome sequencing linked two outbreaks thought to be unrelated and confirmed the outliers. These findings led to the resampling and subsequent identification of the source, guiding public health actions and bringing the outbreak to a close. Significantly, the outbreak clone was identified as sequence type 211 (ST211). Our study reports this ST in the Southern Hemisphere and presents a description of ST211 genomes from both clinical and environmental isolates. A unique mobile genetic element containing a type IV secretion system was identified in Lp1 ST211 isolates linked to the main cluster and Lp1 ST42 isolates that were cocirculating at the time of the outbreak.

Comparison of SNP-based subtyping workflows for bacterial isolates using WGS data, applied to Salmonella enterica serotype Typhimurium and serotype 1,4,[5],12:i:

Whole genome sequencing represents a promising new technology for subtyping of bacterial pathogens. Besides the technological advances which have pushed the approach forward, the last years have been marked by considerable evolution of the whole genome sequencing data analysis methods. Prior to application of the technology as a routine epidemiological typing tool, however, reliable and efficient data analysis strategies need to be identified among the wide variety of the emerged methodologies. In this work, we have compared three existing SNP-based subtyping workflows using a benchmark dataset of 32 Salmonella enterica subsp. enterica serovar Typhimurium and serovar 1,4,[5],12:i:- isolates including five isolates from a confirmed outbreak and three isolates obtained from the same patient at different time points. The analysis was carried out using the original (high-coverage) and a down-sampled (low-coverage) datasets and two different reference genomes. All three tested workflows, namely CSI Phylogeny-based workflow, CFSAN-based workflow and PHEnix-based workflow, were able to correctly group the confirmed outbreak isolates and isolates from the same patient with all combinations of reference genomes and datasets. However, the workflows differed strongly with respect to the SNP distances between isolates and sensitivity towards sequencing coverage, which could be linked to the specific data analysis strategies used therein. To demonstrate the effect of particular data analysis steps, several modifications of the existing workflows were also tested. This allowed us to propose data analysis schemes most suitable for routine SNP-based subtyping applied to S. Typhimurium and S. 1,4,[5],12:i:-. Results presented in this study illustrate the importance of using correct data analysis strategies and to define benchmark and fine-tune parameters applied within routine data analysis pipelines to obtain optimal results.

Molecular typing of Legionella pneumophila isolates from environmental water samples and clinical samples using a five-gene sequence typing and standard Sequence-Based Typing

Inadequate discriminatory power to distinguish between L. pneumophila isolates, especially those belonging to disease-related prevalent sequence types (STs) such as ST1, ST36 and ST47, is an issue of SBT scheme. In this study, we developed a multilocus sequence typing (MLST) scheme based on two non-virulence loci (trpA, cca) and three virulence loci (icmK, lspE, lssD), to genotype 110 L. pneumophila isolates from various natural and artificial water sources in Guangdong province of China, and compared with the SBT. The isolates were assigned to 33 STs of the SBT and 91 new sequence types (nSTs) of the MLST. The indices of discrimination (IODs) of SBT and MLST were 0.920 and 0.985, respectively. Maximum likelihood trees of the concatenated SBT and MLST sequences both showed distinct phylogenetic relationships between the isolates from the two environments. More intragenic recombinations were detected in nSTs than in STs, and they were both more abundant in natural water isolates. We found out the MLST had a high discriminatory ability for the disease-associated ST1 isolates: 22 ST1 isolates were assigned to 19 nSTs. Furthermore, we assayed the discrimination of the MLST for 29 reference strains (19 clinical and 10 environmental). The clinical strains were assigned to eight STs and ten nSTs. The MLST could also subtype the prevalent clinical ST36 or ST47 strains: eight ST36 strains were subtyped into three nSTs and two ST47 strains were subtyped into two nSTs. We found different distribution patterns of nSTs between the environmental and clinical ST36 isolates, and between the outbreak clinical ST36 isolates and the sporadic clinical ST36 isolates. These results together revealed the MLST scheme could be used as part of a typing scheme that increased discrimination when necessary.

Seeding and Establishment of Legionella pneumophila in Hospitals: Implications for Genomic Investigations of Nosocomial Legionnaires' Disease

Background.

Legionnaires’ disease is an important cause of hospital-acquired pneumonia and is caused by infection with the bacterium Legionella. Because current typing methods often fail to resolve the infection source in possible nosocomial cases, we aimed to determine whether whole-genome sequencing (WGS) could be used to support or refute suspected links between cases and hospitals. We focused on cases involving a major nosocomial-associated strain, L. pneumophila sequence type (ST) 1.

Methods.

WGS data from 229 L. pneumophila ST1 isolates were analyzed, including 99 isolates from the water systems of 17 hospitals and 42 clinical isolates from patients with confirmed or suspected hospital-acquired infections, as well as isolates obtained from or associated with community-acquired sources of Legionnaires’ disease.

Results.

Phylogenetic analysis demonstrated that all hospitals from which multiple isolates were obtained have been colonized by 1 or more distinct ST1 populations. However, deep sampling of 1 hospital also revealed the existence of substantial diversity and ward-specific microevolution within the population. Across all hospitals, suspected links with cases were supported with WGS, although the degree of support was dependent on the depth of environmental sampling and available contextual information. Finally, phylogeographic analysis revealed that hospitals have been seeded with L. pneumophila via both local and international spread of ST1.

Conclusions.

WGS can be used to support or refute suspected links between hospitals and Legionnaires’ disease cases. However, deep hospital sampling is frequently required due to the potential coexistence of multiple populations, existence of substantial diversity, and similarity of hospital isolates to local populations.

Genomic investigation of a suspected outbreak of Legionella pneumophila ST82 reveals undetected heterogeneity by the present gold-standard methods, Denmark, July to November 2014

Between July and November 2014, 15 community-acquired cases of Legionnaires´ disease (LD), including four with Legionella pneumophila serogroup 1 sequence type (ST) 82, were diagnosed in Northern Zealand, Denmark. An outbreak was suspected. No ST82 isolates were found in environmental samples and no external source was established. Four putative-outbreak ST82 isolates were retrospectively subjected to whole genome sequencing (WGS) followed by phylogenetic analyses with epidemiologically unrelated ST82 sequences. The four putative-outbreak ST82 sequences fell into two clades, the two clades were separated by ca 1,700 single nt polymorphisms (SNP)s when recombination regions were included but only by 12 to 21 SNPs when these were removed. A single putative-outbreak ST82 isolate sequence segregated in the first clade. The other three clustered in the second clade, where all included sequences had < 5 SNP differences between them. Intriguingly, this clade also comprised epidemiologically unrelated isolate sequences from the UK and Denmark dating back as early as 2011. The study confirms that recombination plays a major role in L. pneumophila evolution. On the other hand, strains belonging to the same ST can have only few SNP differences despite being sampled over both large timespans and geographic distances. These are two important factors to consider in outbreak investigations.

A Supervised Statistical Learning Approach for Accurate Legionella pneumophila Source Attribution during Outbreaks

Public health agencies are increasingly relying on genomics during Legionnaires' disease investigations. However, the causative bacterium (Legionella pneumophila) has an unusual population structure, with extreme temporal and spatial genome sequence conservation. Furthermore, Legionnaires' disease outbreaks can be caused by multiple L. pneumophila genotypes in a single source. These factors can confound cluster identification using standard phylogenomic methods. Here, we show that a statistical learning approach based on L. pneumophila core genome single nucleotide polymorphism (SNP) comparisons eliminates ambiguity for defining outbreak clusters and accurately predicts exposure sources for clinical cases. We illustrate the performance of our method by genome comparisons of 234 L. pneumophila isolates obtained from patients and cooling towers in Melbourne, Australia, between 1994 and 2014. This collection included one of the largest reported Legionnaires' disease outbreaks, which involved 125 cases at an aquarium. Using only sequence data from L. pneumophila cooling tower isolates and including all core genome variation, we built a multivariate model using discriminant analysis of principal components (DAPC) to find cooling tower-specific genomic signatures and then used it to predict the origin of clinical isolates. Model assignments were 93% congruent with epidemiological data, including the aquarium Legionnaires' disease outbreak and three other unrelated outbreak investigations. We applied the same approach to a recently described investigation of Legionnaires' disease within a UK hospital and observed a model predictive ability of 86%. We have developed a promising means to breach L. pneumophila genetic diversity extremes and provide objective source attribution data for outbreak investigations.IMPORTANCE Microbial outbreak investigations are moving to a paradigm where whole-genome sequencing and phylogenetic trees are used to support epidemiological investigations. It is critical that outbreak source predictions are accurate, particularly for pathogens, like Legionella pneumophila, which can spread widely and rapidly via cooling system aerosols, causing Legionnaires' disease. Here, by studying hundreds of Legionella pneumophila genomes collected over 21 years around a major Australian city, we uncovered limitations with the phylogenetic approach that could lead to a misidentification of outbreak sources. We implement instead a statistical learning technique that eliminates the ambiguity of inferring disease transmission from phylogenies. Our approach takes geolocation information and core genome variation from environmental L. pneumophila isolates to build statistical models that predict with high confidence the environmental source of clinical L. pneumophila during disease outbreaks. We show the versatility of the technique by applying it to unrelated Legionnaires' disease outbreaks in Australia and the UK.

Characterization of Legionella Species from Watersheds in British Columbia, Canada

Many species of Legionella can cause Legionnaires’ disease, a significant cause of bacterial pneumonia. Legionella in human-made water systems such as cooling towers and building plumbing systems are the primary sources of Legionnaires’ disease outbreaks. In this temporal study of natural aquatic environments, Legionella relative abundance was shown to vary in watersheds associated with different land uses. Analysis of the Legionella sequences detected at these sites revealed highly diverse populations that included potentially novel Legionella species. These findings have important implications for understanding the ecology of Legionella and control measures for this pathogen that are aimed at reducing human disease.

Legionella spp. present in some human-made water systems can cause Legionnaires’ disease in susceptible individuals. Although legionellae have been isolated from the natural environment, variations in the organism’s abundance over time and its relationship to aquatic microbiota are poorly understood. Here, we investigated the presence and diversity of legionellae through 16S rRNA gene amplicon and metagenomic sequencing of DNA from isolates collected from seven sites in three watersheds with varied land uses over a period of 1 year. Legionella spp. were found in all watersheds and sampling sites, comprising up to 2.1% of the bacterial community composition. The relative abundance of Legionella tended to be higher in pristine sites than in sites affected by agricultural activity. The relative abundance levels of Amoebozoa, some of which are natural hosts of legionellae, were similarly higher in pristine sites. Compared to other bacterial genera detected, Legionella had both the highest richness and highest alpha diversity. Our findings indicate that a highly diverse population of legionellae may be found in a variety of natural aquatic sources. Further characterization of these diverse natural populations of Legionella will help inform prevention and control efforts aimed at reducing the risk of Legionella colonization of built environments, which could ultimately decrease the risk of human disease.

IMPORTANCE Many species of Legionella can cause Legionnaires’ disease, a significant cause of bacterial pneumonia. Legionella in human-made water systems such as cooling towers and building plumbing systems are the primary sources of Legionnaires’ disease outbreaks. In this temporal study of natural aquatic environments, Legionella relative abundance was shown to vary in watersheds associated with different land uses. Analysis of the Legionella sequences detected at these sites revealed highly diverse populations that included potentially novel Legionella species. These findings have important implications for understanding the ecology of Legionella and control measures for this pathogen that are aimed at reducing human disease.

Dynamics and impact of homologous recombination on the evolution of Legionella pneumophila

Legionella pneumophila is an environmental bacterium and the causative agent of Legionnaires' disease. Previous genomic studies have shown that recombination accounts for a high proportion (>96%) of diversity within several major disease-associated sequence types (STs) of L. pneumophila. This suggests that recombination represents a potentially important force shaping adaptation and virulence. Despite this, little is known about the biological effects of recombination in L. pneumophila, particularly with regards to homologous recombination (whereby genes are replaced with alternative allelic variants). Using newly available population genomic data, we have disentangled events arising from homologous and non-homologous recombination in six major disease-associated STs of L. pneumophila (subsp. pneumophila), and subsequently performed a detailed characterisation of the dynamics and impact of homologous recombination. We identified genomic "hotspots" of homologous recombination that include regions containing outer membrane proteins, the lipopolysaccharide (LPS) region and Dot/Icm effectors, which provide interesting clues to the selection pressures faced by L. pneumophila. Inference of the origin of the recombined regions showed that isolates have most frequently imported DNA from isolates belonging to their own clade, but also occasionally from other major clades of the same subspecies. This supports the hypothesis that the possibility for horizontal exchange of new adaptations between major clades of the subspecies may have been a critical factor in the recent emergence of several clinically important STs from diverse genomic backgrounds. However, acquisition of recombined regions from another subspecies, L. pneumophila subsp. fraseri, was rarely observed, suggesting the existence of a recombination barrier and/or the possibility of ongoing speciation between the two subspecies. Finally, we suggest that multi-fragment recombination may occur in L. pneumophila, whereby multiple non-contiguous segments that originate from the same molecule of donor DNA are imported into a recipient genome during a single episode of recombination.

Whole-genome sequencing for identification of the source in hospital-acquired Legionnaires' disease

Acquisition of Legionnaires' disease is a serious complication of hospitalization. Rapid determination of whether or not the infection is caused by strains of Legionella pneumophila in the hospital environment is crucial to avoid further cases. This study investigated the use of whole-genome sequencing to identify the source of infection in hospital-acquired Legionnaires' disease. Phylogenetic analyses showed close relatedness between one patient isolate and a strain found in hospital water, confirming suspicion of nosocomial infection. It was found that whole-genome sequencing can be a useful tool in the investigation of hospital-acquired Legionnaires' disease.

Legionellosis acquired through a dental unit: a case study

In 2012, an elderly immunocompromised man died from legionellosis at a hospital in Uppsala, Sweden. The patient had visited a dental ward at the hospital during the incubation period. Legionella spp. at a concentration of 2000 colony-forming units/L were isolated from the cupfiller outlet providing water for oral rinsing. Isolates from the patient and the dental unit were Legionella pneumophila serogroup 1, subgroup Knoxville and ST9. Pulsed-field gel electrophoresis and whole-genome sequencing strongly suggested that the isolates were of common origin. This report presents one of few documented cases of legionellosis acquired through a dental unit.

A bioinformatics tool for ensuring the backwards compatibility of Legionella pneumophila typing in the genomic era

OBJECTIVES

Whole genome sequencing (WGS) has revolutionized the subtyping of Legionella pneumophila but calling the traditional sequence-based type from genomic data is hampered by multiple copies of the mompS locus. We propose a novel bioinformatics solution for rectifying that limitation, ensuring the feasibility of WGS for cluster investigation.

METHODS

We designed a novel approach based on the alignment of raw reads with a reference sequence. With WGS, reads originating from either of the two mompS copies cannot be differentiated. Therefore, when non-identical copies were present, we applied a read-filtering strategy based on read alignment to a reference sequence via unique 'anchors'. If minimal read coverage was achieved after filtration (≥3X), a consensus sequence was built based on mapped reads followed by calling the sequence-based typing allele. The entire procedure was implemented using a Perl script.

RESULTS

The method was validated using a diverse sample of 265 L. pneumophila genomes, consisting of 59 different sequence types (STs) and 23 mompS variants; 57 of the 265 (22%) had non-identical mompS copies. In 237 of the 265 samples (89.4%), mompS calling was successful and no erroneous calling occurred. A 98.1% success was recorded among 109 samples meeting quality requirements. The method was superior to alternative approaches.

CONCLUSIONS

As WGS becomes more accessible, technical difficulties in routine clinical and surveillance work will arise. The case of mompS in L. pneumophila serves as an example for such limitations that necessitate the development of novel computational solutions that meet end-user demands.

SNP synteny analysis of Staphylococcus aureus and Pseudomonas aeruginosa population genomics

Genomic sequence diversity of a bacterial species mainly results from the frequency distribution of single nucleotide polymorphisms (SNPs). Here we report on an SNP matrix-based binary algorithm to determine the intraclonal or interclonal genomic diversity by the number of shared sequential SNPs, the so-called SNP synteny or haplotype. All SNP positions and the frequency and length distribution of haplotypes are determined from pairwise alignment of completely sequenced genomes. This metric is invariant regarding the reference genome chosen. Information is obtained about the size of haplotypes, genomic gradients of recombination frequency, relatedness of strains and population composition of a taxon or clonal populations. The approach is illustrated with whole genome data sets of Staphylococcus aureus and Pseudomonas aeruginosa strains.