Population structure and minimum core genome typing of Legionella pneumophila

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.

High performance Legionella pneumophila source attribution using genomics-based machine learning classification

Fundamental to effective Legionnaires' disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionized pathogen surveillance, but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here, we present a powerful machine learning approach that assigns the geographical source of Legionnaires' disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires' disease outbreaks through detailed case investigations. Our classification models were developed in a cross-validation framework using only environmental L. pneumophila genomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534-genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance-agreement with epidemiological information. Our multivariate statistical learning approach maximizes the use of genomic variation data and is thus well-suited for supporting Legionnaires' disease outbreak investigations.IMPORTANCEIdentifying the sources of Legionnaires' disease outbreaks is crucial for effective control. Current genomic methods, while useful, often fall short due to the complex ecology and population structure of Legionella pneumophila, the causative agent. Our study introduces a high-performing machine learning approach for more accurate geographical source attribution of Legionnaires' disease outbreaks. Developed using cross-validation on environmental L. pneumophila genomes, our models demonstrate excellent predictive sensitivity and specificity. Importantly, this new approach outperforms traditional methods like phylogenomic trees and core genome multi-locus sequence typing, proving more efficient at leveraging genomic variation data to infer outbreak sources. Our machine learning algorithms, harnessing both core and accessory genomic variation, offer significant promise in public health settings. By enabling rapid and precise source identification in Legionnaires' disease outbreaks, such approaches have the potential to expedite intervention efforts and curtail disease transmission.

Development of heat-shock resistance in Legionella pneumophila modeled by experimental evolution

Because it can grow in buildings with complex hot water distribution systems (HWDS), healthcare facilities recognize the waterborne bacterium Legionella pneumophila as a major nosocomial infection threat and often try to clear the systems with a pasteurization process known as superheat-and-flush. After this treatment, many facilities find that the contaminating populations slowly recover, suggesting the possibility of in situ evolution favoring increased survival in high-temperature conditions. To mimic this process in a controlled environment, an adaptive laboratory evolution model was used to select a wild-type strain of L. pneumophila for survival to transient exposures to temperatures characteristic of routine hot water use or failed pasteurization processes in HWDS. Over their evolution, these populations became insensitive to exposure to 55°C and developed the ability to survive short exposures to 59°C heat shock. Heat-adapted lineages maintained a higher expression of heat-shock genes during low-temperature incubation in freshwater, suggesting a pre-adaptation to heat stress. Although there were distinct mutation profiles in each of the heat-adapted lineages, each acquired multiple mutations in the DnaJ/DnaK/ClpB disaggregase complex, as well as mutations in chaperone htpG and protease clpX. These mutations were specific to heat-shock survival and were not seen in control lineages included in the experimental model without exposure to heat shock. This study supports in situ observations of adaptation to heat stress and demonstrates the potential of L. pneumophila to develop resistance to control measures. IMPORTANCE As a bacterium that thrives in warm water ecosystems, Legionella pneumophila is a key factor motivating regulations on hot water systems. Two major measures to control Legionella are high circulating temperatures intended to curtail growth and the use of superheat-and-flush pasteurization processes to eliminate established populations. Facilities often suffer recolonization of their hot water systems; hospitals are particularly at risk due to the severe nosocomial pneumoniae caused by Legionella. To understand these long-term survivors, we have used an adaptive laboratory evolution model to replicate this process. We find major differences between the mutational profiles of heat-adapted and heat-naïve L. pneumophila populations including mutations in major heat-shock genes like chaperones and proteases. This model demonstrates that well-validated treatment protocols are needed to clear contaminated systems and-in an analog to antibiotic resistance-the importance of complete eradication of the resident population to prevent selection for more persistent bacteria.

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.

Legionnaires' Disease in China Caused by Legionella pneumophila Corby

Legionella pneumophila is an intracellular pathogen causing pneumonia in humans. In February 2022, Legionnaires' disease caused by L. pneumophila strain Corby in a patient with lung adenocarcinoma was identified for the first time in China. This paper includes the case report and phenotypic and genomic analysis of the Corby (ICDC) strain. Its biological characteristics were evaluated by antibiotic sensitivity testing and cytology experiments, and genomic analysis was performed to understand its genetic evolution. The patient's clinical manifestations included cough, fever, pulmonary infiltration, and significantly decreased activity endurance. After empirical antimicrobial therapy, infection indicators decreased. The Corby (ICDC) strain was susceptible to nine antibiotics and exhibited strong intracellular proliferation ability. A phylogenetic tree showed that the Corby (ICDC) strain was closely related to the Corby strain, but under the pressure of a complex environment, its genome had undergone more rearrangement and inversion. The type IF CRISPR-Cas system was identified in its genome, and spacer analysis indicated that it had been invaded by several foreign plasmids, bacteria, and viruses during evolution. Legionnaires' disease caused by L. pneumophila strain Corby may be ignored in China, and it is urgent to improve long-term monitoring and investigation of aquatic environments and patients with respiratory infections to prevent a large-scale outbreak of Legionnaires' disease.

Genomic characterization and assessment of pathogenic potential of Legionella spp. isolates from environmental monitoring

Several species in the genus Legionella are known to cause an acute pneumonia when the aerosols containing the bacteria from man-made water systems are inhaled. The disease is usually caused by Legionella pneumophila, but other species have been implicated in the infection. The disease is frequently manifested as an outbreak, which means several people are affected when exposed to the common source of Legionella contamination. Therefor environmental surveillance which includes isolation and identification of Legionella is performed routinely. However, usually no molecular or genome-based methods are employed in further characterization of the isolates during routine environmental monitoring. During several years of such monitoring, isolates from different geographical locations were collected and 39 of them were sequenced by hybrid de novo approach utilizing short and long sequencing reads. In addition, the isolates were typed by standard culture and MALDI-TOF method. The sequencing reads were assembled and annotated to produce high-quality genomes. By employing discriminatory genome typing, four potential new species in the Legionella genus were identified, which are yet to be biochemically and morphologically characterized. Moreover, functional annotations concerning virulence and antimicrobial resistance were performed on the sequenced genomes. The study contributes to the knowledge on little-known non-pneumophila species present in man-made water systems and establishes support for future genetic relatedness studies as well as understanding of their pathogenic potential.

Population analysis of Legionella pneumophila reveals a basis for resistance to complement-mediated killing

Legionella pneumophila is the most common cause of the severe respiratory infection known as Legionnaires' disease. However, the microorganism is typically a symbiont of free-living amoeba, and our understanding of the bacterial factors that determine human pathogenicity is limited. Here we carried out a population genomic study of 902 L. pneumophila isolates from human clinical and environmental samples to examine their genetic diversity, global distribution and the basis for human pathogenicity. We find that the capacity for human disease is representative of the breadth of species diversity although some clones are more commonly associated with clinical infections. We identified a single gene (lag-1) to be most strongly associated with clinical isolates. lag-1, which encodes an O-acetyltransferase for lipopolysaccharide modification, has been distributed horizontally across all major phylogenetic clades of L. pneumophila by frequent recent recombination events. The gene confers resistance to complement-mediated killing in human serum by inhibiting deposition of classical pathway molecules on the bacterial surface. Furthermore, acquisition of lag-1 inhibits complement-dependent phagocytosis by human neutrophils, and promoted survival in a mouse model of pulmonary legionellosis. Thus, our results reveal L. pneumophila genetic traits linked to disease and provide a molecular basis for resistance to complement-mediated killing.

Legionella pneumophila Risk from Cooling Tower Systems in China

Legionella pneumophila (LP) widely exists in natural and artificial water environments, which facilitates LP to infect people. LP infection causes Legionnaires' disease (LD), which is an important but relatively uncommon respiratory infection. Approximately 90% of LD is caused by L. pneumophila serogroup 1 (Lp1). Meteorological conditions may affect the infectivity and virulence of Lp1, but the exact relationship between them is still unclear. In this study, we evaluated the virulence of Lp1 by screening of total 156 Lp1 strains isolated from cooling tower water in different region of China by detecting their abilities to activate NF-κB signaling pathway in vitro. In addition, we screened the distribution of some selected virulence genes in these strains. The virulence, virulence gene distribution and the meteorological factors were analyzed. We found that both the virulence and the distribution of virulence genes had a certain regional and meteorological correlation. Although loss of several virulence genes showed significant effects on the virulence of Lp1 strains, the distribution of virulence genes had very limited effects on the virulence of Lp1. IMPORTANCE LD is likely to be under-recognized in many countries. Due to the widespread existence of LP in natural and artificial water environments, and to the lack of cross-protection against different strains, LP is a potentially serious threat to human health. Therefore, effective monitoring of the virulence of LP in the water environment is very important to prevent and control the prevalence of LD. Understanding the virulence of LP can not only help us to predict the risk of possible outbreaks in advance, but can also enable more targeted clinical treatment. This study highlights the importance of understanding the epidemiology and ecology of LP isolated from public facilities in terms of public health and biology. Due to the potential for water sources to harbor and disseminate LP, and to the fact that geographical conditions influence the virulence of LP, timely and accurate LP virulence surveillance is urgently needed.

Development of a multiplex-PCR serotyping assay for characterizing Legionella pneumophila serogroups based on the diversity of LPS biosynthetic loci

Legionella pneumophila, which is the main cause of Legionnaires' disease, comprises at least 15 serogroups (SGs). We show here the diversity of LPS biosynthetic loci among serogroups and describe the development of a PCR serotyping assay for 15 SGs based on the sequences of LPS biosynthetic loci. Using this multiplex-PCR (M-PCR) system, serogroup(s) were detected using primers that specifically amplify the sequences of SG1, SG2, SG5, SG7, SG8, SG9, SG11, SG13, SG3/15, and SG6/12. When PCR products of the expected sizes were not detected, we used primers that identified SG4/10/14. The PCR serotyping system specifically amplified the sequences corresponding SGs of 238 L. pneumophila strains. This method will be very useful for conducting epidemiological studies and investigating outbreak of Legionnaires' disease.

A Vibrio cholerae Core Genome Multilocus Sequence Typing Scheme To Facilitate the Epidemiological Study of Cholera

Core genome multilocus sequence typing (cgMLST) has gained popularity in recent years in epidemiological research and subspecies-level classification. cgMLST retains the intuitive nature of traditional MLST but offers much greater resolution by utilizing significantly larger portions of the genome. Here, we introduce a cgMLST scheme for Vibrio cholerae, a bacterium abundant in marine and freshwater environments and the etiologic agent of cholera. A set of 2,443 core genes ubiquitous in V. cholerae were used to analyze a comprehensive data set of 1,262 clinical and environmental strains collected from 52 countries, including 65 newly sequenced genomes in this study. We established a sublineage threshold based on 133 allelic differences that creates clusters nearly identical to traditional MLST types, providing backwards compatibility to new cgMLST classifications. We also defined an outbreak threshold based on seven allelic differences that is capable of identifying strains from the same outbreak and closely related isolates that could give clues on outbreak origin. Using cgMLST, we confirmed the South Asian origin of modern epidemics and identified clustering affinity among sublineages of environmental isolates from the same geographic origin. Advantages of this method are highlighted by direct comparison with existing classification methods, such as MLST and single-nucleotide polymorphism-based methods. cgMLST outperforms all existing methods in terms of resolution, standardization, and ease of use. We anticipate this scheme will serve as a basis for a universally applicable and standardized classification system for V. cholerae research and epidemiological surveillance in the future. This cgMLST scheme is publicly available on PubMLST (https://pubmlst.org/vcholerae/).IMPORTANCE Toxigenic Vibrio cholerae isolates of the O1 and O139 serogroups are the causative agents of cholera, an acute diarrheal disease that plagued the world for centuries, if not millennia. Here, we introduce a core genome multilocus sequence typing scheme for V. cholerae Using this scheme, we have standardized the definition for subspecies-level classification, facilitating global collaboration in the surveillance of V. cholerae In addition, this typing scheme allows for quick identification of outbreak-related isolates that can guide subsequent analyses, serving as an important first step in epidemiological research. This scheme is also easily scalable to analyze thousands of isolates at various levels of resolution, making it an invaluable tool for large-scale ecological and evolutionary analyses.

Genomic Epidemiology of an Outbreak of Klebsiella pneumoniae ST471 Producing Extended-Spectrum β-Lactamases in a Neonatal Intensive Care Unit

Purpose

Klebsiella pneumoniae producing extended-spectrum β-lactamases (ESBLs) causes nosocomial infections worldwide. The present study aimed to determine the molecular subtyping characteristics and antibiotic resistance mechanisms of ESBL-producing K. pneumoniae strains collected during an outbreak. Moreover, we attempted to reveal the fine transmission route of the strains within this outbreak using whole-genome sequencing (WGS).

Methods

Collecting cases and strain information were carried out. Outbreak-related strains were identified using pulsed-field gel electrophoresis (PFGE). The antibiotic susceptibility, drug-resistant genes, and molecular subtype characteristics of ESBL-producing K. pneumoniae were analyzed. The fine transmission route of the strains within this outbreak was revealed using WGS and minimum core genome (MCG) sequence typing.

Results

In mid-January, 2015, five cases of neonatal pneumonia caused by ESBL-producing K. pneumoniae were observed in the neonatal intensive care unit (NICU) of the Affiliated Hospital of Chifeng University, China. Eight ESBL-producing K. pneumoniae were isolated from these five cases, and two additional strains from another two cases were identified using PFGE. All ten isolates harbored bla _CTX-M-15, bla _TEM-1, bla _SHV-108, and bla _OXA-1 genes, and belonged to the sequence type 471 (ST471) clone. A putative transmission map was constructed via comprehensive consideration of genomic and epidemiological information. WGS identified the initial case and the "superspreader". The genomic epidemiological investigation revealed that the outbreak was caused by the introduction of the bacteria one month before the first case appeared.

Conclusion

As far as we know, this is the first report to describe the characteristics of an ST471 ESBL-producing K. pneumoniae outbreak. The data showed that epidemiological inferences could be greatly improved by interpretation in the context of WGS and that K. pneumoniae strains isolated from the same outbreak contain sufficient genomic differences to refine epidemiological linkages on the basis of genetic lineage. These findings suggested that integration of genomic and epidemiological data can help us to have a clearer understanding of when and how outbreaks occur, so as to better control nosocomial transmission.

A novel taxon selection method, aimed at minimizing recombination, clarifies the discovery of a new sub-population of Helicobacter pylori from Australia

We present a novel method for taxon selection, the aim being to minimize problems arising from highly recombinant species such as Helicobacter pylori. Helicobacter pylori has accompanied modern-human migration out of Africa and is marked by a phylogeographic strain distribution, which has been exploited to add an extra layer of information about human migrations to that obtained from human sources. However, H. pylori's genome has high sequence heterogeneity combined with a very high rate of recombination, causing major allelic diversification across strains. On the other hand, recombination events that have become preserved in sub-populations are a useful source of phylogenetic information. This creates a potential problem in selecting representative strains for particular genetic or phylogeographic clusters and generally ameliorating the impact on analyses of extensive low-level recombination. To address this issue, we perform multiple population structure-based analyses on core genomes to select exemplar strains, called 'quintessents', which exhibit limited recombination. In essence, quintessent strains are representative of their specific phylogenetic clades and can be used to refine the current MLST concatenation-based population structure classification system. The use of quintessents reduces the noise due to local recombination events, while preserving recombination events that have become fixed in sub-populations. We illustrate the method with an analysis of core genome concatenations from 185 H. pylori strains, which reveals a recent speciation event resulting from the recombination of strains from phylogeographic clade hpSahul, carried by Aboriginal Australians, and hpEurope, carried by some of the people who arrived in Australia over the past 200 years. The signal is much clearer when based on quintessent strains, but absent from the analysis based on MLST concatenations.

Comparison of Whole-Genome Sequences of Legionella pneumophila in Tap Water and in Clinical Strains, Flint, Michigan, USA, 2016

During the water crisis in Flint, Michigan, USA (2014-2015), 2 outbreaks of Legionnaires' disease occurred in Genesee County, Michigan. We compared whole-genome sequences of 10 clinical Legionella pneumophila isolates submitted to a laboratory in Genesee County during the second outbreak with 103 water isolates collected the following year. We documented a genetically diverse range of L. pneumophila strains across clinical and water isolates. Isolates belonging to 1 clade (3 clinical isolates, 3 water isolates from a Flint hospital, 1 water isolate from a Flint residence, and the reference Paris strain) had a high degree of similarity (2-1,062 single-nucleotide polymorphisms), all L. pneumophila sequence type 1, serogroup 1. Serogroup 6 isolates belonging to sequence type 2518 were widespread in Flint hospital water samples but bore no resemblance to available clinical isolates. L. pneumophila strains in Flint tap water after the outbreaks were diverse and similar to some disease-causing strains.

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.

The virulence of Legionella pneumophila is positively correlated with its ability to stimulate NF-κB activation

AIM

Our work is to study the correlation between the virulence of different Legionella pneumophila in mouse model and its ability to activate NF-κB signaling pathway in vitro.

MATERIALS & METHODS

We measured the abilities of different strains of L. pneumophila to induce the activation of NF-κB signaling pathway in vitro. By using A/J mice, we also detected the virulence of different strains in vivo.

RESULTS & CONCLUSION

We demonstrated that different strains of L. pneumophila induce different levels of activation to NF-κB signaling pathway in vitro. We also found that L. pneumophila strain induced higher NF-κB activation in vitro showed more severe weight losses, higher mortality, more severe lung inflammation and higher levels of serum cytokines production in mice.

Multiplex polymerase chain reaction of genetic markers for detection of potentially pathogenic environmental Legionella pneumophila isolates

Background & objectives:

Genomic constitution of the bacterium Legionella pneumophila plays an important role in providing them a pathogenic potential. Here, we report the standardization and application of multiplex polymerase chain reaction (PCR) for the detection of molecular markers of pathogenic potential in L. pneumophila in hospital environment.

Methods:

Culture of the standard strains of L. pneumophila was performed in buffered charcoal-yeast extract agar with L-cysteine at pH 6.9. Primers were designed for multiplex PCR, and standardization for the detection of five markers annotated to L. pneumophila plasmid pLPP (11A2), lipopolysaccharide synthesis (19H4), CMP-N-acetylneuraminic acid synthetase (10B12), conjugative coupling factor (24B1) and hypothetical protein (8D6) was done. A total of 195 water samples and 200 swabs were collected from the hospital environment. The bacterium was isolated from the hospital environment by culture and confirmed by 16S rRNA gene PCR and restriction enzyme analysis. A total of 45 L. pneumophila isolates were studied using the standardized multiplex PCR.

Results:

The PCR was sensitive to detect 0.1 ng/μl DNA and specific for the two standard strains used in the study. Of the 45 hospital isolates tested, 11 isolates had four markers, 12 isolates had three markers, 10 isolates had two markers, nine isolates had one marker and three isolates had none of the markers. None of the isolates had all the five markers.

Interpretation & conclusions:

The findings of this study showed the presence of gene markers of pathogenic potential of the bacterium L. pneumophila. However, the genomic constitution of the environmental isolates should be correlated with clinical isolates to prove their pathogenic potential. Rapid diagnostic methods such as multiplex PCR reported here, for elucidating gene markers, could help in future epidemiological studies of bacterium L. pneumophila.

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.

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.

Transforming bacterial disease surveillance and investigation using whole-genome sequence to probe the trace

Two decades have passed since the first bacterial whole-genome sequencing, which provides new opportunity for microbial genome. Consequently, considerable genetic diversity encoded by bacterial genomes and among the strains in the same species has been revealed. In recent years, genome sequencing techniques and bioinformatics have developed rapidly, which has resulted in transformation and expedited the application of strategy and methodology for bacterial genome comparison used in dissection of infectious disease epidemics. Bacterial whole-genome sequencing and bioinformatic computing allow genotyping to satisfy the requirements of epidemiological study in disease control. In this review, we outline the significance and summarize the roles of bacterial genome sequencing in the context of bacterial disease control and prevention.We discuss the applications of bacterial genome sequencing in outbreak detection, source tracing, transmission mode discovery, and new epidemic clone identification. Wide applications of genome sequencing and data sharing in infectious disease surveillance networks will considerably promote outbreak detection and early warning to prevent the dissemination of bacterial diseases.

Molecular evolution of virulence genes and non-virulence genes in clinical, natural and artificial environmental Legionella pneumophila isolates

Background

L. pneumophila is the main causative agent of Legionnaires’ disease. Free-living amoeba in natural aquatic environments is the reservoir and shelter for L. pneumophila. From natural water sources, L. pneumophila can colonize artificial environments such as cooling towers and hot-water systems, and then spread in aerosols, infecting the susceptible person. Therefore, molecular phylogeny and genetic variability of L. pneumophila from different sources (natural water, artificial water, and human lung tissue) might be distinct because of the selection pressure in different environments. Several studies researched genetic differences between L. pneumophila clinical isolates and environmental isolates at the nucleotide sequence level. These reports mainly focused on the analysis of virulence genes, and rarely distinguished artificial and natural isolates.

Methods

We have used 139 L. pneumophila isolates to study their genetic variability and molecular phylogeny. These isolates include 51 artificial isolates, 59 natural isolates, and 29 clinical isolates. The nucleotide sequences of two representative non-virulence (NV) genes (trpA, cca) and three representative virulence genes (icmK, lspE, lssD) were obtained using PCR and DNA sequencing and were analyzed.

Results

Levels of genetic variability including haplotypes, haplotype diversity, nucleotide diversity, nucleotide difference and the total number of mutations in the virulence loci were higher in the natural isolates. In contrast, levels of genetic variability including polymorphic sites, theta from polymorphic sites and the total number of mutations in the NV loci were higher in clinical isolates. A phylogenetic analysis of each individual gene tree showed three to six main groups, but not comprising the same L. pneumophila isolates. We detected recombination events in every virulence loci of natural isolates, but only detected them in the cca locus of clinical isolates. Neutrality tests showed that variations in the virulence genes of clinical and environmental isolates were under neutral evolution. TrpA and cca loci of clinical isolates showed significantly negative values of Tajima’s D, Fu and Li’s D* and F*, suggesting the presence of negative selection in NV genes of clinical isolates.

Discussion

Our findingsreinforced the point that the natural environments were the primary training place for L. pneumophila virulence, and intragenic recombination was an important strategy in the adaptive evolution of virulence gene. Our study also suggested the selection pressure had unevenly affected these genes and contributed to the different evolutionary patterns existed between NV genes and virulence genes. This work provides clues for future work on population-level and genetics-level questions about ecology and molecular evolution of L. pneumophila, as well as genetic differences of NV genes and virulence genes between this host-range pathogen with different lifestyles.

Distribution of Secretion Systems in the Genus Legionella and Its Correlation with Pathogenicity

The genus Legionella comprises over 60 species, which are important human pathogens. Secretion systems in Legionella pneumophila have been studied extensively because of the essential role of protein secretion in bacterial infection. However, there are few reports describing the secretion systems in non-L. pneumophila species. In this study, we analyzed the distribution of secretion systems in L. pneumophila and 18 species of non-L. pneumophila based on whole genome sequences. A total of 74 whole genome sequences from 19 species of Legionella were analyzed. Type II and IVB secretion systems were detected in all Legionella strains, but the type I secretion systems was restricted to L. pneumophila. The type IVA secretion system was randomly distributed among different species. Furthermore, we found the type VI secretion system in three non-L. pneumophila strains (Legionella cherrii DSM 19213, Legionella dumoffii Tex-KL, and Legionella gormanii ATCC 33297). In population structure analysis, L. pneumophila formed a conservative cluster and was located at the terminal of the evolutionary tree. At the same time, L. pneumophila, especially eight clone groups (named MCGG1–MCGG8), showed higher intracellular growth ability than non-L. pneumophila species. These results suggest that L. pneumophila has acquired additional secretion systems during evolution, resulting in increased pathogenicity.

Molecular Typing of Legionella pneumophila Isolates in the Province of Quebec from 2005 to 2015

Legionella is found in natural and man-made aquatic environments, such as cooling towers and hot water plumbing infrastructures. Legionella pneumophila serogroup 1 (Lp1) is the most common etiological agent causing waterborne disease in the United States and Canada. This study reports the molecular characterization of Lp strains during a 10 year period. We conducted sequence-based typing (SBT) analysis on a large set of Lp isolates (n = 284) to investigate the province of Quebec sequence types (STs) distribution in order to identify dominant clusters. From 2005 to 2015, 181 clinical Lp isolates were typed by SBT (141 sporadic cases and 40 outbreak related cases). From the same period of time, 103 environmental isolates were also typed. Amongst the 108 sporadic cases of Lp1 typed, ST-62 was the most frequent (16.6%), followed by ST-213 (10.2%), ST-1 (8.3%) and ST-37 (8.3%). Amongst other serogroups (SG), ST-1327 (SG5) (27.3%) and ST-378 (SG10) (12.2%) were the most frequent. From the environmental isolates, ST-1 represent the more frequent SBT type (26.5%). Unweighted pair group method with arithmetic mean (UPGMA) dendrogram from the 108 sporadic cases of SG1 contains 4 major clusters (A to D) of related STs. Cluster B contains the majority of the strains (n = 61) and the three most frequent STs in our database (ST-62, ST-213 and ST-1). During the study period, we observed an important increase in the incidence rate in Quebec. All the community associated outbreaks, potentially or confirmed to be associated with a cooling tower were caused by Lp1 strains, by opposition to hospital associated outbreaks that were caused by serogroups of Lp other than SG1. The recent major Quebec City outbreak caused by ST-62, and the fact that this genotype is the most common in the province supports whole genome sequencing characterization of this particular sequence type in order to understand its evolution and associated virulence factors.

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

Sequence-based typing (SBT), analogous to multilocus 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. In this study, various whole-genome sequencing (WGS)-based methods were evaluated according to published guidelines, including (i) a single nucleotide polymorphism (SNP)-based method, (ii) extended MLST using different numbers of genes, (iii) determination of gene presence or absence, and (iv) a kmer-based method. 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% of isolates were considered typeable using the SNP- and kmer-based methods. Percentages of isolates with complete extended MLST profiles ranged from 99.1% (50 genes) to 86.8% (1,455 genes), while 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 were 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 while 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.