Genomic Resolution of Outbreak-Associated Legionella pneumophila Serogroup 1 Isolates from New York State

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.

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.

Legionnaires' Disease Outbreak Associated With a Hot Tub Display at the North Carolina Mountain State Fair, September 2019

OBJECTIVES

On September 23, 2019, the North Carolina Division of Public Health identified a legionellosis increase in western North Carolina; most patients had recently attended the North Carolina Mountain State Fair. We conducted a source investigation.

METHODS

Cases were fair attendees with laboratory-confirmed legionellosis and symptom onset within 2 to 14 days (Legionnaires' disease) or ≤3 days (Pontiac fever). We conducted a case-control study matching cases to non-ill fair attendees as control participants and an environmental investigation, and we performed laboratory testing (Legionella bacteria culture and polymerase chain reaction) of 27 environmental samples from fairgrounds and hot tubs and 14 specimens from case patients. We used multivariable unconditional logistic regression models to calculate adjusted odds ratios for potential Legionella exposure sources and risk factors.

RESULTS

Of 136 people identified with fair-associated legionellosis, 98 (72%) were hospitalized and 4 (3%) died. Case patients were more likely than control participants to report walking by hot tub displays (adjusted odds ratio = 10.0; 95% CI, 4.2-24.1). Complete hot tub water treatment records were not kept, precluding evaluation of water maintenance conducted on display hot tubs. Legionella pneumophila sequence types (STs) were consistent among 10 typed clinical specimens (ST224) but distinct from the only positive environmental sample from the fair (ST7 and ST8).

CONCLUSIONS

Hot tub displays were identified as the most likely outbreak source, making this the largest hot tub-associated Legionnaires' disease outbreak worldwide. Following the investigation, the North Carolina Division of Public Health and the Centers for Disease Control and Prevention released guidance on mitigating risk of Legionella exposure from hot tub displays. Results highlight the importance of properly maintaining equipment that aerosolizes water, including hot tubs intended for display purposes only.

Long-read sequencing for reliably calling the mompS allele in Legionella pneumophila sequence-based typing

Sequence-based typing (SBT) of Legionella pneumophila is a valuable tool in epidemiological studies and outbreak investigations of Legionnaires' disease. In the L. pneumophila SBT scheme, mompS2 is one of seven genes that determine the sequence type (ST). The Legionella genome typically contains two copies of mompS (mompS1 and mompS2). When they are non-identical it can be challenging to determine the mompS2 allele, and subsequently the ST, from Illumina short-reads. In our collection of 233 L. pneumophila genomes, there were 62 STs, 18 of which carried non-identical mompS copies. Using short-reads, the mompS2 allele was misassembled or untypeable in several STs. Genomes belonging to ST154 and ST574, which carried mompS1 allele 7 and mompS2 allele 15, were assigned an incorrect mompS2 allele and/or mompS gene copy number when short-read assembled. For other isolates, mainly those carrying non-identical mompS copies, short-read assemblers occasionally failed to resolve the structure of the mompS-region, also resulting in untypeability from the short-read data. In this study, we wanted to understand the challenges we observed with calling the mompS2 allele from short-reads, assess if other short-read methods were able to resolve the mompS-region, and investigate the possibility of using long-reads to obtain the mompS alleles, and thereby perform L. pneumophila SBT from long-reads only. We found that the choice of short-read assembler had a major impact on resolving the mompS-region and thus SBT from short-reads, but no method consistently solved the mompS2 allele. By using Oxford Nanopore Technology (ONT) sequencing together with Trycycler and Medaka for long-read assembly and polishing we were able to resolve the mompS copies and correctly identify the mompS2 allele, in accordance with Sanger sequencing/EQA results for all tested isolates (n=35). The remaining six genes of the SBT profile could also be determined from the ONT-only reads. The STs called from ONT-only assemblies were also consistent with hybrid-assemblies of Illumina and ONT reads. We therefore propose ONT sequencing as an alternative method to perform L. pneumophila SBT to overcome the mompS challenge observed with short-reads. To facilitate this, we have developed ONTmompS (https://github.com/marithetland/ONTmompS), an in silico approach to determine L. pneumophila ST from long-read or hybrid assemblies.

Investigation of a legionellosis outbreak in Sydney CBD - a brief report

OBJECTIVE

To identify and control a source of Legionella in Sydney CBD.

METHODS

Clinical, epidemiological, environmental and genomic techniques were employed to identify cases and the source of Legionella.

RESULTS

Eleven legionellosis cases were linked to Sydney CBD with a median age of 69 years. All were hospitalised and had risk factors for Legionella infection. Eight of 11 cases identified as male. Genomic analysis linked three cases to a contaminated cooling water source in Sydney CBD, with a further case infected with a similar strain to that found in Sydney CBD. Another case, although epidemiologically linked to Sydney CBD, was infected with a genomically different strain to that found in Sydney CBD. Six other cases had no viable sample for genomic analysis.

CONCLUSION/IMPLICATIONS FOR PUBLIC HEALTH

An outbreak of legionellosis is a serious public health threat that requires rapid investigation and environmental control. We were able to identify a source in Sydney CBD through the application of clinical, epidemiological, environmental and genomic techniques. Genomic analysis is a powerful tool that can be used to confirm the source location but requires close collaboration between clinicians, public health units and microbiologists to recover viable sputum cultures from cases diagnosed with legionellosis.

Rapid adaptations of Legionella pneumophila to the human host

Legionella pneumophila are host-adapted bacteria that infect and reproduce primarily in amoeboid protists. Using similar infection mechanisms, they infect human macrophages, and cause Legionnaires' disease, an atypical pneumonia, and the milder Pontiac fever. We hypothesized that, despite the similarities in infection mechanisms, the hosts are different enough that there exist high-selective value mutations that would dramatically increase the fitness of Legionella inside the human host. By comparing a large number of isolates from independent infections, we identified two genes, mutated in three unrelated patients, despite the short duration of the incubation period (2-14 days). One is a gene coding for an outer membrane protein (OMP) belonging to the OmpP1/FadL family. The other is a gene coding for an EAL-domain-containing protein involved in cyclic-di-GMP regulation, which in turn modulates flagellar activity. The clinical strain, carrying the mutated EAL-domain-containing homologue, grows faster in macrophages than the wild-type strain, and thus appears to be better adapted to the human host. As human-to-human transmission is very rare, fixation of these mutations into the population and spread into the environment is unlikely. Therefore, parallel evolution - here mutations in the same genes observed in independent human infections - could point to adaptations to the accidental human host. These results suggest that despite the ability of L. pneumophila to infect, replicate in and exit from macrophages, its human-specific adaptations are unlikely to be fixed in the population.

Investigation of a Legionella pneumophila Outbreak at a Bath Facility in Japan Using Whole-Genome Sequencing of Isolates from Clinical and Environmental Samples

Exposure to aerosols containing Legionella from artificially made water systems has been established as a primary cause of Legionnaires' disease. In this study, we investigated an outbreak of L. pneumophila serogroup 1 sequence type 138 which occurred at a bath facility in 2022. The whole-genome sequencing of isolates revealed that the colonization of L. pneumophila at the bath facility had occurred before 2013, and the patients had been exposed to multiple genetic lineages of the strain. Our study demonstrates the importance of performing a careful comparative genetic analysis of clinical and environmental isolates from LD outbreaks in order to effectively investigate and prevent future LD outbreaks.

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).

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.

Hospital-acquired Legionella pneumonia outbreak at an academic medical center: Lessons learned

BACKGROUND

An outbreak of Legionella pneumonia occurred at a university hospital using copper-silver ionization for potable water disinfection. We present the epidemiological and laboratory investigation of the outbreak, and associated case-control study.

METHODS

Cases were defined by syndrome compatible with Legionella pneumonia with laboratory-confirmed Legionella infection. The water circuit and disinfection system were assessed, and water samples collected for Legionella culture. Whole genome multi-locus sequence typing (wgMLST) was used to compare the genetic similarity of patient and environmental isolates. A case-control study was conducted to identify risk factors for Legionella pneumonia.

RESULTS

We identified 13 cases of hospital-acquired Legionella. wgMLST revealed >99.9% shared allele content among strains isolated from clinical and water samples. Smoking (P= .008), steroid use (P= .007), and documented shower during hospitalization (P= .03) were risk factors for Legionella pneumonia on multivariable analysis. Environmental assessment identified modifications to the hospital water system had occurred in the month preceding the outbreak. Multiple mitigation efforts and application of point of use water filters stopped the outbreak.

CONCLUSIONS

Potable water system Legionella colonization occurs despite existing copper-silver ionization systems, particularly after structural disruptions. Multidisciplinary collaboration and direct monitoring for Legionella are important for outbreak prevention. Showering is a modifiable risk factor for nosocomial Legionella pneumonia. Shower restriction and point-of-use filters merit consideration during an outbreak.

Improvements to the Success of Outbreak Investigations of Legionnaires' Disease: 40 Years of Testing and Investigation in New York State

Since 1978, the New York State Department of Health's public health laboratory, Wadsworth Center (WC), in collaboration with epidemiology and environmental partners, has been committed to providing comprehensive public health testing for Legionella in New York. Statewide, clinical case counts have been increasing over time, with the highest numbers identified in 2017 and 2018 (1,022 and 1,426, respectively). Over the course of more than 40 years, the WC Legionella testing program has continuously implemented improved testing methods. The methods utilized have transitioned from solely culture-based methods for organism recovery to development of a suite of reference testing services, including identification and characterization by PCR and pulsed-field gel electrophoresis (PFGE). In the last decade, whole-genome sequencing (WGS) has further refined the ability to link outbreak strains between clinical specimens and environmental samples. Here, we review Legionnaires' disease outbreak investigations during this time period, including comprehensive testing of both clinical and environmental samples. Between 1978 and 2017, 60 outbreaks involving clinical and environmental isolates with matching PFGE patterns were detected in 49 facilities from the 157 investigations at 146 facilities. However, 97 investigations were not solved due to the lack of clinical or environmental isolates or PFGE matches. We found 69% of patient specimens from New York State (NYS) were outbreak associated, a much higher rate than observed in other published reports. The consistent application of new cutting-edge technologies and environmental regulations has resulted in successful investigations resulting in remediation efforts. IMPORTANCE Legionella, the causative agent of Legionnaires' disease (LD), can cause severe respiratory illness. In 2018, there were nearly 10,000 cases of LD reported in the United States (https://www.cdc.gov/legionella/fastfacts.html; https://wonder.cdc.gov/nndss/static/2018/annual/2018-table2h.html), with actual incidence believed to be much higher. About 10% of patients with LD will die, and as high as 90% of patients diagnosed will be hospitalized. As Legionella is spread predominantly through engineered building water systems, identifying sources of outbreaks by assessing environmental sources is key to preventing further cases LD.

Using Neisseria meningitidis genomic diversity to inform outbreak strain identification

Meningococcal disease is a life-threatening illness caused by the human-restricted bacterium Neisseria meningitidis. Outbreaks in the USA involve at least two cases in an organization or community caused by the same serogroup within three months. Genome comparisons, including phylogenetic analysis and quantification of genome distances can provide confirmatory evidence of pathogen transmission during an outbreak. Interpreting genome distances depends on understanding their distribution both among isolates from outbreaks and among those not from outbreaks. Here, we identify outbreak strains based on phylogenetic relationships among 141 N. meningitidis isolates collected from 28 outbreaks in the USA during 2010-2017 and 1516 non-outbreak isolates collected through contemporaneous meningococcal surveillance. We show that genome distance thresholds based on the maximum SNPs and allele distances among isolates in the phylogenetically defined outbreak strains are sufficient to separate most pairs of non-outbreak isolates into separate strains. Non-outbreak isolate pairs that could not be distinguished from each other based on genetic distances were concentrated in the clonal complexes CC11, CC103, and CC32. Within each of these clonal complexes, phylodynamic analysis identified a group of isolates with extremely low diversity, collected over several years and multiple states. Clusters of isolates with low genetic diversity could indicate increased pathogen transmission, potentially resulting in local outbreaks or nationwide clonal expansions.

Next generation sequencing approaches to evaluate water and wastewater quality

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

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.

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.

Status and potential of bacterial genomics for public health practice: a scoping review

Background

Next-generation sequencing (NGS) is increasingly being translated into routine public health practice, affecting the surveillance and control of many pathogens. The purpose of this scoping review is to identify and characterize the recent literature concerning the application of bacterial pathogen genomics for public health practice and to assess the added value, challenges, and needs related to its implementation from an epidemiologist’s perspective.

Methods

In this scoping review, a systematic PubMed search with forward and backward snowballing was performed to identify manuscripts in English published between January 2015 and September 2018. Included studies had to describe the application of NGS on bacterial isolates within a public health setting. The studied pathogen, year of publication, country, number of isolates, sampling fraction, setting, public health application, study aim, level of implementation, time orientation of the NGS analyses, and key findings were extracted from each study. Due to a large heterogeneity of settings, applications, pathogens, and study measurements, a descriptive narrative synthesis of the eligible studies was performed.

Results

Out of the 275 included articles, 164 were outbreak investigations, 70 focused on strategy-oriented surveillance, and 41 on control-oriented surveillance. Main applications included the use of whole-genome sequencing (WGS) data for (1) source tracing, (2) early outbreak detection, (3) unraveling transmission dynamics, (4) monitoring drug resistance, (5) detecting cross-border transmission events, (6) identifying the emergence of strains with enhanced virulence or zoonotic potential, and (7) assessing the impact of prevention and control programs. The superior resolution over conventional typing methods to infer transmission routes was reported as an added value, as well as the ability to simultaneously characterize the resistome and virulome of the studied pathogen. However, the full potential of pathogen genomics can only be reached through its integration with high-quality contextual data.

Conclusions

For several pathogens, it is time for a shift from proof-of-concept studies to routine use of WGS during outbreak investigations and surveillance activities. However, some implementation challenges from the epidemiologist’s perspective remain, such as data integration, quality of contextual data, sampling strategies, and meaningful interpretations. Interdisciplinary, inter-sectoral, and international collaborations are key for an appropriate genomics-informed surveillance.

Electronic supplementary material

The online version of this article (10.1186/s13012-019-0930-2) contains supplementary material, which is available to authorized users.

Legionella: a reemerging pathogen

PURPOSE OF REVIEW

The present review summarizes new knowledge about Legionella epidemiology, clinical characteristics, community-associated and hospital-based outbreaks, molecular typing and molecular epidemiology, prevention, and detection in environmental and clinical specimens.

RECENT FINDINGS

The incidence of Legionnaire's disease is rising and the mortality rate remains high, particularly for immunocompromised patients. Extracorporeal membrane oxygenation may help support patients with severe respiratory failure. Fluoroquinolones and macrolides appear to be equally efficacious for treating Legionnaires' disease. Whole genome sequencing is an important tool for determining the source for Legionella infections and for understanding routes of transmission and mechanisms by which new pathogenic clones emerge. Real-time quantitative polymerase chain reaction testing of respiratory specimens may improve our ability to diagnose Legionnaire's disease. The frequency of viable but nonculturable organisms is quite high in some water systems but their role in causing clinical disease has not been defined.

SUMMARY

Legionellosis remains an important public health threat. To prevent these infections, staff of municipalities and large buildings must implement effective water system management programs that reduce Legionella growth and transmission and all Medicare-certified healthcare facilities must have water management policies. In addition, we need better methods for detecting Legionella in water systems and in clinical specimens to improve prevention strategies and clinical diagnosis.

Analysis of Genetic Characterization and Clonality of Legionella pneumophila Isolated from Cooling Towers in Japan

We investigated the genetic characteristics of 161 Legionella pneumophila strains isolated over a period of 10 years from cooling towers in Japan. Minimum spanning tree analysis based on the sequence-based typing (SBT) of them identified three clonal complexes (CCs); CC1 (105/161, 65.2%), CC2 (22 /161, 13.7%), and CC3 (20/161, 12.4%). CC1 was formed by serogroup (SG) 1 and SG7, whereas CC2 was mainly formed by SG1. All of the CC3 isolates except two strains were SG13. The major sequence types (STs) in CC1 and CC2 were ST1 (88/105, 83.8%) and ST154 (15/22, 68.2%), respectively. These STs are known as typical types of L. pneumophila SG1 in Japanese cooling tower. Additionally, we identified 15 strains of ST2603 as the major type in CC3. This ST has not been reported in Japanese cooling tower. Whole genome sequencing (WGS) analysis of the representative strains in the three CCs, which were isolated from various cooling towers over the 10 years, elucidated high clonal population of L. pneumophila in Japanese cooling tower. Moreover, it revealed that the strains of CC2 are phylogenetically distant compared to those of CC1 and CC3, and belonged to L. pneumophila subsp. fraseri.

Legionella, water and biotechnology

Legionella spp. are microorganisms that are generally found in the aquatic environment (rivers, streams, lakes, among others). The importance in public health is in the fact that this bacterium is capable of multiplying and propagating in artificial aquatic systems (piping systems, storage tanks, fountains, and cooling towers), giving rise to diseases in humans called legionellosis, transmitted by inhalation of contaminated water droplets or aerosols and whose complications can lead to the death of the patient. Legionellosis is of worldwide distribution, Legionella pneumophila being the most commonly involved species in outbreaks and reported cases. The people most at risk are the elderly, people with weakened immune systems, and people with a history of smoking. Around the world, regulatory agencies and health organizations have issued and established recommendations with the purpose of controlling and preventing the risk of contracting this disease, which include the sanitation of water supplies, maintenance through regular cleaning and disinfection of facilities and devices for reducing the presence of this pathogen. The main objective of this review is to present in a general manner, aspects related to the disease known as legionellosis, its casual agents, habitat, transmission form, and phenotypic and metabolic characteristics. Likewise, the methods of control and prevention of these pathogens are presented, including a potential biotechnological alternative that can contribute to actions in favour of the protection of public health through the use of compounds with surface activity called biosurfactants.

The sporadic nature of Legionella pneumophila, Legionella pneumophila Sg1 and Mycobacterium avium occurrence within residences and office buildings across 36 states in the United States

Aim

Premise plumbing may disseminate the bacteria Legionella pneumophila and Mycobacterium avium, the causative agents for legionellosis and pulmonary nontuberculous mycobacterium disease respectively.

Methods and Results

Using quantitative PCR, the occurrence and persistence of L. pneumophila, L. pneumophila serogroup (Sg)1 and M. avium were evaluated in drinking water samples from 108 cold water taps (residences: n = 43) and (office buildings: n = 65). Mycobacterium avium, L. pneumophila and L. pneumophila Sg1 were detected 45, 41 and 25% of all structures respectively. Two occurrence patterns were evaluated: sporadic (a single detection from the three samplings) and persistent (detections in two or more of the three samples).

Conclusions

The micro‐organism's occurrence was largely sporadic. Office buildings were prone to microbial persistence independent of building age and square footage. Microbial persistence at residences was observed in those older than 40 years for L. pneumophila and was rarely observed for M. avium. The microbial occurrence was evenly distributed between structure types but there were differences in density and persistence.

Significance of and Impact of the Study

The study is important because residences are often suspected to be the source when a case of disease is reported. These data demonstrate that this may not be the case for a sporadic incidence.

Culture of Clinical Specimens Reveals Extensive Diversity of Legionella pneumophila Strains in Arizona

Between 2000 and 2017, a total of 236 Legionella species isolates from Arizona were submitted to the CDC for reference testing. Most of these isolates were recovered from bronchoalveolar lavage specimens. Although the incidence of legionellosis in Arizona is less than the overall U.S. incidence, Arizona submits the largest number of isolates to the CDC for testing compared to those from other states. In addition to a higher proportion of culture confirmation of legionellosis cases in Arizona than in other states, all Legionellapneumophila isolates are forwarded to the CDC for confirmatory testing. Compared to that from other states, a higher proportion of isolates from Arizona were identified as belonging to L. pneumophila serogroups 6 (28.2%) and 8 (8.9%). Genome sequencing was conducted on 113 L. pneumophila clinical isolates not known to be associated with outbreaks in order to understand the genomic diversity of strains causing legionellosis in Arizona. Whole-genome multilocus sequence typing (wgMLST) revealed 17 clusters of isolates sharing at least 99% identical allele content. Only two of these clusters contained isolates from more than one individual with exposure at the same facility. Additionally, wgMLST analysis revealed a group of 31 isolates predominantly belonging to serogroup 6 and containing isolates from three separate clusters. Single nucleotide polymorphism (SNP) and pangenome analysis were used to further resolve genome sequences belonging to a subset of isolates. This study demonstrates that culture of clinical specimens for Legionella spp. reveals a highly diverse population of strains causing legionellosis in Arizona which could be underappreciated using other diagnostic approaches.IMPORTANCE Culture of clinical specimens from patients with Legionnaires' disease is rarely performed, restricting our understanding of the diversity and ecology of Legionella Culture of Legionella from patient specimens in Arizona revealed a greater proportion of non-serogroup 1 Legionellapneumophila isolates than in other U.S. isolates examined. Disease caused by such isolates may go undetected using other diagnostic methods. Moreover, genome sequence analysis revealed that these isolates were genetically diverse, and understanding these populations may help in future environmental source attribution studies.

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.

Insights into the long-term persistence of Legionella in facilities from whole-genome sequencing

We investigated the value of whole-genome sequencing (WGS) and single nucleotide polymorphism (SNP) analyses in determining the relationships among and evolutionary rates of Legionella species with long-term persistence in three healthcare facilities. We examined retrospective clinical and environmental isolates of Legionella micdadei and Legionella pneumophila serogroup 1 isolates with identical PFGE DNA fingerprints sampled over the course of up to 18 years. WGS analyses demonstrated that heterogeneous populations of Legionella were present within each facility despite displaying the same PFGE profiles. Additionally, clustering of some clinical isolates with those from a separate but related institution exposed a source of infection not previously detected, underscoring the importance of considering phylogenetic relationships when assessing epidemiological links. The data supported an average substitution rate of 0.80 SNPs per genome per year for L. micdadei but a reliable estimate for L. pneumophila serogroup 1 could not be obtained due to complicating factors such as non-chronological links among isolates and inadequate sampling depths. While the substitution rate for L. micdadei is consistent with previous estimates for L. pneumophila, the lack of a temporal signal in our sequence data for L. pneuomphila serogroup 1 isolates suggests either insufficient change to provide an estimate or variable evolutionary rates, which could reflect the presence of both actively dividing and viable but non-culturable Legionella spp. in the built environment. This study highlights the increased discriminatory power of WGS SNP analysis as compared to PFGE, emphasizes the need for extended sampling, and provides insight into the evolution of Legionella from longitudinal investigations.

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.

Legionnaires' Disease Outbreak Caused 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.

Salmonella in Foods: A Reemerging Problem

The number of human salmonellosis within the European Union tended to increase since 2013. One of the reasons might be Salmonella Enteritidis rising in laying hens flocks by around 17% in 2015 vs 2014 and by 57% in 2016 vs 2015. The most important sources of food-borne Salmonella outbreaks are still eggs and egg products as well as ready-to-eat foods having a long shelf life. Specific actions are suggested to restart decreasing the number of human salmonellosis: (1) revision of sampling schemes to solve pathogen under detection in both animals and foods; (2) integration of microbiological criteria with fit for purpose performance objectives and food safety objectives; and (3) improvement of epidemiological investigations of human, food, and animal isolates by using whole-genome sequencing in order to effectively track salmonellosis and verify which prevention measures are most effective.

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.

Comparative genome analysis reveals a complex population structure of Legionella pneumophila subspecies

The majority of Legionnaires' disease (LD) cases are caused by Legionella pneumophila, a genetically heterogeneous species composed of at least 17 serogroups. Previously, it was demonstrated that L. pneumophila consists of three subspecies: pneumophila, fraseri and pascullei. During an LD outbreak investigation in 2012, we detected that representatives of both subspecies fraseri and pascullei colonized the same water system and that the outbreak-causing strain was a new member of the least represented subspecies pascullei. We used partial sequence based typing consensus patterns to mine an international database for additional representatives of fraseri and pascullei subspecies. As a result, we identified 46 sequence types (STs) belonging to subspecies fraseri and two STs belonging to subspecies pascullei. Moreover, a recent retrospective whole genome sequencing analysis of isolates from New York State LD clusters revealed the presence of a fourth L. pneumophila subspecies that we have termed raphaeli. This subspecies consists of 15 STs. Comparative analysis was conducted using the genomes of multiple members of all four L. pneumophila subspecies. Whereas each subspecies forms a distinct phylogenetic clade within the L. pneumophila species, they share more average nucleotide identity with each other than with other Legionella species. Unique genes for each subspecies were identified and could be used for rapid subspecies detection. Improved taxonomic classification of L. pneumophila strains may help identify environmental niches and virulence attributes associated with these genetically distinct subspecies.

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.

Methodological approaches for monitoring opportunistic pathogens in premise plumbing: A review

Opportunistic premise (i.e., building) plumbing pathogens (OPPPs, e.g., Legionella pneumophila, Mycobacterium avium complex, Pseudomonas aeruginosa, Acanthamoeba, and Naegleria fowleri) are a significant and growing source of disease. Because OPPPs establish and grow as part of the native drinking water microbiota, they do not correspond to fecal indicators, presenting a major challenge to standard drinking water monitoring practices. Further, different OPPPs present distinct requirements for sampling, preservation, and analysis, creating an impediment to their parallel detection. The aim of this critical review is to evaluate the state of the science of monitoring OPPPs and identify a path forward for their parallel detection and quantification in a manner commensurate with the need for reliable data that is informative to risk assessment and mitigation. Water and biofilm sampling procedures, as well as factors influencing sample representativeness and detection sensitivity, are critically evaluated with respect to the five representative bacterial and amoebal OPPPs noted above. Available culturing and molecular approaches are discussed in terms of their advantages, limitations, and applicability. Knowledge gaps and research needs towards standardized approaches are identified.

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.

Construction of a Pan-Genome Allele Database of Salmonella enterica Serovar Enteritidis for Molecular Subtyping and Disease Cluster Identification

We built a pan-genome allele database with 395 genomes of Salmonella enterica serovar Enteritidis and developed computer tools for analysis of whole genome sequencing (WGS) data of bacterial isolates for disease cluster identification. A web server (http://wgmlst.imst.nsysu.edu.tw) was set up with the database and the tools, allowing users to upload WGS data to generate whole genome multilocus sequence typing (wgMLST) profiles and to perform cluster analysis of wgMLST profiles. The usefulness of the database in disease cluster identification was demonstrated by analyzing a panel of genomes from 55 epidemiologically well-defined S. Enteritidis isolates provided by the Minnesota Department of Health. The wgMLST-based cluster analysis revealed distinct clades that were concordant with the epidemiologically defined outbreaks. Thus, using a common pan-genome allele database, wgMLST can be a promising WGS-based subtyping approach for disease surveillance and outbreak investigation across laboratories.

Next-Generation Epidemiology: Using Real-Time Core Genome Multilocus Sequence Typing To Support Infection Control Policy

Multidrug-resistant bacteria are responsible for substantial morbidity and mortality worldwide. Tracking the nosocomial spread of resistant bacteria is critical to infection control. Mellmann et al. (J. Clin. Microbiol. 54:2874-2881, 2016, http://dx.doi.org/10.1128/JCM.00790-16) have described prospective whole-genome sequencing with core genome multilocus sequencing typing (cgMLST) analysis for real-time surveillance and have addressed the practical aspects of implementing this type of operation in the hospital setting.

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.