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Asset Tag: Legionella pneumophila

July 7, 2019  |  

Whole-genome mapping as a novel high-resolution typing tool for Legionella pneumophila.

Legionella is the causative agent for Legionnaires’ disease (LD) and is responsible for several large outbreaks in the world. More than 90% of LD cases are caused by Legionella pneumophila, and studies on the origin and transmission routes of this pathogen rely on adequate molecular characterization of isolates. Current typing of L. pneumophila mainly depends on sequence-based typing (SBT). However, studies have shown that in some outbreak situations, SBT does not have sufficient discriminatory power to distinguish between related and nonrelated L. pneumophila isolates. In this study, we used a novel high-resolution typing technique, called whole-genome mapping (WGM), to differentiate between epidemiologically related and nonrelated L. pneumophila isolates. Assessment of the method by various validation experiments showed highly reproducible results, and WGM was able to confirm two well-documented Dutch L. pneumophila outbreaks. Comparison of whole-genome maps of the two outbreaks together with WGMs of epidemiologically nonrelated L. pneumophila isolates showed major differences between the maps, and WGM yielded a higher discriminatory power than SBT. In conclusion, WGM can be a valuable alternative to perform outbreak investigations of L. pneumophila in real time since the turnaround time from culture to comparison of the L. pneumophila maps is less than 24 h. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

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July 7, 2019  |  

Hybrid de novo tandem repeat detection using short and long reads.

As one of the most studied genome rearrangements, tandem repeats have a considerable impact on genetic backgrounds of inherited diseases. Many methods designed for tandem repeat detection on reference sequences obtain high quality results. However, in the case of a de novo context, where no reference sequence is available, tandem repeat detection remains a difficult problem. The short reads obtained with the second-generation sequencing methods are not long enough to span regions that contain long repeats. This length limitation was tackled by the long reads obtained with the third-generation sequencing platforms such as Pacific Biosciences technologies. Nevertheless, the gain on the read length came with a significant increase of the error rate. The main objective of nowadays studies on long reads is to handle the high error rate up to 16%.In this paper we present MixTaR, the first de novo method for tandem repeat detection that combines the high-quality of short reads and the large length of long reads. Our hybrid algorithm uses the set of short reads for tandem repeat pattern detection based on a de Bruijn graph. These patterns are then validated using the long reads, and the tandem repeat sequences are constructed using local greedy assemblies.MixTaR is tested with both simulated and real reads from complex organisms. For a complete analysis of its robustness to errors, we use short and long reads with different error rates. The results are then analysed in terms of number of tandem repeats detected and the length of their patterns.Our method shows high precision and sensitivity. With low false positive rates even for highly erroneous reads, MixTaR is able to detect accurate tandem repeats with pattern lengths varying within a significant interval.

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July 7, 2019  |  

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. Copyright © 2017 American Society for Microbiology.

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July 7, 2019  |  

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.

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July 7, 2019  |  

Legionnaires’ disease outbreakcaused by endemic strain of Legionella pneumophila, New York, New York, USA, 2015.

During the summer of 2015, New York, New York, USA, had one of the largest and deadliest outbreaks of Legionnaires’ disease in the history of the United States. A total of 138 cases and 16 deaths were linked to a single cooling tower in the South Bronx. Analysis of environmental samples and clinical isolates showed that sporadic cases of legionellosis before, during, and after the outbreak could be traced to a slowly evolving, single-ancestor strain. Detection of an ostensibly virulent Legionella strain endemic to the Bronx community suggests potential risk for future cases of legionellosis in the area. The genetic homogeneity of the Legionella population in this area might complicate investigations and interpretations of future outbreaks of Legionnaires’ disease.

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July 7, 2019  |  

Evaluation of an optimal epidemiologic typing scheme for Legionella pneumophila with whole genome sequence data using validation guidelines.

Sequence-based typing (SBT), analogous to multi-locus sequence typing (MLST), is the current gold-standard typing method for investigation of legionellosis outbreaks caused by Legionella pneumophila However, as common sequence types (STs) cause many infections, some investigations remain unresolved. Here, various whole genome sequencing (WGS)-based methods were evaluated according to published guidelines, including: i) single nucleotide polymorphism (SNP)-based; ii) extended multi-locus sequence typing (MLST) using different numbers of genes; iii) gene presence/absence, and iv) kmer-based. L. pneumophila serogroup 1 isolates (n=106) from the standard “typing panel”, previously used by the European Society for Clinical Microbiology Study Group on Legionella Infections (ESGLI) were tested together with another 229 isolates.Over 98% isolates were considered typable using the mapping- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50-gene) to 86.8% (1455-gene) whilst only 41.5% produced a full profile with the gene presence/absence scheme. Replicates demonstrated that all methods offer 100% reproducibility. Indices of discrimination range from 0.972 (ribosomal MLST) to 0.999 (SNP-based), and all values are higher than that achieved with SBT (0.940). Epidemiological concordance is generally inversely related to discriminatory power. We propose that an extended MLST scheme with ~50 genes provides optimal epidemiological concordance whilst substantially improving the discrimination offered by SBT, and can be used as part of a hierarchical typing scheme that should maintain backwards compatibility and increase discrimination where necessary. This analysis will be useful for the ESGLI to design a scheme that has the potential to become the new gold standard typing method for L. pneumophila. Copyright © 2016 David et al.

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July 7, 2019  |  

Complete genome sequences of three outbreak-associated Legionella pneumophila isolates.

We report here the complete genome sequences of three Legionella pneumophila isolates that are associated with a Legionnaires’ disease outbreak in New York in 2012. Two clinical isolates (D7630 and D7632) and one environmental isolate (D7631) were recovered from this outbreak. A single isolate-specific virulence gene was found in D7632. These isolates were included in a large study evaluating the genomic resolution of various bioinformatics approaches for L. pneumophila serogroup 1 isolates. Copyright © 2016 Morrison et al.

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July 7, 2019  |  

Genomic analysis reveals novel diversity among the 1976 Philadelphia Legionnaires’ disease outbreak isolates and additional ST36 strains.

Legionella pneumophila was first recognized as a cause of severe and potentially fatal pneumonia during a large-scale outbreak of Legionnaires’ disease (LD) at a Pennsylvania veterans’ convention in Philadelphia, 1976. The ensuing investigation and recovery of four clinical isolates launched the fields of Legionella epidemiology and scientific research. Only one of the original isolates, “Philadelphia-1”, has been widely distributed or extensively studied. Here we describe the whole-genome sequencing (WGS), complete assembly, and comparative analysis of all Philadelphia LD strains recovered from that investigation, along with L. pneumophila isolates sharing the Philadelphia sequence type (ST36). Analyses revealed that the 1976 outbreak was due to multiple serogroup 1 strains within the same genetic lineage, differentiated by an actively mobilized, self-replicating episome that is shared with L. pneumophila str. Paris, and two large, horizontally-transferred genomic loci, among other polymorphisms. We also found a completely unassociated ST36 strain that displayed remarkable genetic similarity to the historical Philadelphia isolates. This similar strain implies the presence of a potential clonal population, and suggests important implications may exist for considering epidemiological context when interpreting phylogenetic relationships among outbreak-associated isolates. Additional extensive archival research identified the Philadelphia isolate associated with a non-Legionnaire case of “Broad Street pneumonia”, and provided new historical and genetic insights into the 1976 epidemic. This retrospective analysis has underscored the utility of fully-assembled WGS data for Legionella outbreak investigations, highlighting the increased resolution that comes from long-read sequencing and a sequence type-matched genomic data set.

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July 7, 2019  |  

Active and adaptive Legionella CRISPR-Cas reveals a recurrent challenge to the pathogen.

Clustered regularly interspaced short palindromic repeats with CRISPR-associated gene (CRISPR-Cas) systems are widely recognized as critical genome defense systems that protect microbes from external threats such as bacteriophage infection. Several isolates of the intracellular pathogen Legionella pneumophila possess multiple CRISPR-Cas systems (type I-C, type I-F and type II-B), yet the targets of these systems remain unknown. With the recent observation that at least one of these systems (II-B) plays a non-canonical role in supporting intracellular replication, the possibility remained that these systems are vestigial genome defense systems co-opted for other purposes. Our data indicate that this is not the case. Using an established plasmid transformation assay, we demonstrate that type I-C, I-F and II-B CRISPR-Cas provide protection against spacer targets. We observe efficient laboratory acquisition of new spacers under ‘priming’ conditions, in which initially incomplete target elimination leads to the generation of new spacers and ultimate loss of the invasive DNA. Critically, we identify the first known target of L. pneumophila CRISPR-Cas: a 30?kb episome of unknown function whose interbacterial transfer is guarded against by CRISPR-Cas. We provide evidence that the element can subvert CRISPR-Cas by mutating its targeted sequences – but that primed spacer acquisition may limit this mechanism of escape. Rather than generally impinging on bacterial fitness, this element drives a host specialization event – with improved fitness in Acanthamoeba but a reduced ability to replicate in other hosts and conditions. These observations add to a growing body of evidence that host range restriction can serve as an existential threat to L. pneumophila in the wild.© 2016 The Authors Cellular Microbiology Published by John Wiley & Sons Ltd.

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July 7, 2019  |  

Complete genome sequences of six Legionella pneumophila isolates from two collocated outbreaks of Legionnaires’ disease in 2005 and 2008 in Sarpsborg/Fredrikstad, Norway.

Here, we report the complete genome sequences of Legionella pneumophila isolates from two collocated outbreaks of Legionnaires’ disease in 2005 and 2008 in Sarpsborg/Fredrikstad, Norway. One clinical and two environmental isolates were sequenced from each outbreak. The genome of all six isolates consisted of a 3.36 Mb-chromosome, while the 2005 genomes featured an additional 68 kb-episome sharing high sequence similarity with the L. pneumophila Lens plasmid. All six genomes contained multiple mobile genetic elements including novel combinations of type-IVA secretion systems. A comparative genomics study will be launched to resolve the genetic relationship between the L. pneumophila isolates. Copyright © 2016 Dybwad et al.

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