Genomic Analysis Reveals Novel Diversity among the 1976 Philadelphia Legionnaires' Disease Outbreak Isolates and Additional ST36 Strains

Can genomics and meteorology predict outbreaks of legionellosis in urban settings?

Legionella pneumophila is ubiquitous and sporadically infects humans causing Legionnaire's disease (LD). Globally, reported cases of LD have risen fourfold from 2000 to 2014. In 2016, Sydney, Australia was the epicenter of an outbreak caused by L. pneumophila serogroup 1 (Lpsg1). Whole-genome sequencing was instrumental in identifying the causal clone which was found in multiple locations across the city. This study examined the epidemiology of Lpsg1 in an urban environment, assessed typing schemes to classify resident clones, and investigated the association between local climate variables and LD outbreaks. Of 223 local Lpsg1 isolates, we identified dominant clones with one clone isolated from patients in high frequency during outbreak investigations. The core genome multi-locus sequence typing scheme was the most reliable in identifying this Lpsg1 clone. While an increase in humidity and rainfall was found to coincide with a rise in LD cases, the incidence of the major L. pneumophila outbreak clone did not link to weather phenomena. These findings demonstrated the role of high-resolution typing and weather context assessment in determining source attribution for LD outbreaks in urban settings, particularly when clinical isolates remain scarce.IMPORTANCEWe investigated the genomic and meteorological influences of infections caused by Legionella pneumophila in Sydney, Australia. Our study contributes to a knowledge gap of factors that drive outbreaks of legionellosis compared to sporadic infections in urban settings. In such cases, clinical isolates can be rare, and thus, other data are needed to inform decision-making around control measures. The study revealed that core genome multi-locus sequence typing is a reliable and adaptable technique when investigating Lpsg1 outbreaks. In Sydney, the genomic profile of Lpsg1 was dominated by a single clone, which was linked to numerous community cases over a period of 40 years. Interestingly, the peak in legionellosis cases during Autumn was not associated with this prevalent outbreak clone. Incorporating meteorological data with Lpsg1 genomics can support risk assessment strategies for legionellosis in urban environments, and this approach may be relevant for other densely populated regions globally.

High-glucose conditions attenuate the response of macrophages to Legionella pneumophila infection by inhibiting NOD1 and MAPK signaling

BACKGROUND

Patients with diabetes are particularly susceptible to Legionella pneumophila (LP) infection, but the exact pathogenesis of LP infection in diabetic patients is still not fully understood. Herein, we investigated the effect of diabetes on immune function during LP infection in vitro and in vivo.

METHODS

The time course of LP infection in macrophages under normal and high-glucose (HG) conditions was examined in vitro. Western blot was used to determine nucleotide-binding oligomerization domain 1 (NOD1), kinase 1/2 (ERK1/2), mitogen-activated protein kinase p38 (MAPK p38), and c-Jun N-terminal kinases (JNK). Enzyme-linked immunosorbent assay (ELISA) was used to assess the secretion of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6). Cell Counting Kit-8 (CCK8) assay assessed U937 cell viability after treating cells with different concentrations of high sugar medium and ML130 (NOD1 inhibitor). For the in vivo study, normal and streptozocin-induced diabetic guinea pigs were infected with LP for 6, 24, and 72 h, after which NOD1, MAPK-related signals, TNF-α, and IL-6 expression in lung tissues were assessed using immunohistochemistry, western blot, and RT-PCR.

RESULTS

HG attenuated the upregulation of NOD1 expression and reduced TNF-α and IL-6 secretion caused by LP compared with LP-infected cells exposed to normal glucose levels (all p < 0.05). In diabetic guinea pigs, HG inhibited the upregulation of NOD1 expression in lung tissues and the activation of p38, ERK1/2, and cJNK caused by LP infection compared to control pigs (all p < 0.05).

CONCLUSION

HG attenuates the response of macrophages to LP infection by inhibiting NOD1 upregulation and the activation of MAPK signaling.

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.

Whole-genome sequencing of the clinical isolate of Legionella pneumophila ALAW1 from the West Bank allows high-resolution typing and determination of pathogenicity mechanisms

Background

Legionella pneumophila is water-based bacterium causing Legionnaires' disease (LD). We describe the first documented case of nosocomial LD caused by L. pneumophila sequence type (ST) 461 and serogroup 6. The etiology of LD was confirmed by culturing the bronchoalveolar lavage sample retrieving L. pneumophila strain ALAW1. A 7-days treatment of the LD patient with Azithromycin and Levofloxacin allowed complete recovery.

Methods

In details, we sequenced the whole genome of the L. pneumophila ALAW1 using Illumina HiSeq platform. The sequence of ALAW1 was aligned with the genome sequence from the closely related reference strain Alcoy 2300/99 and a whole-genome phylogeny based on single nucleotide polymorphisms (SNPs) was created using Parsnp software. Also, the TYGS web-server was used in order to compare the genome with type strain.

Results

An analysis of the population structure by SNP and TYGS comparison clustered ALAW1 with the reference genome Alcoy 2300/99. Blastp analysis of the type IV secretion Dot/Icm system genes showed that these genes were highly conserved with (≤25%) structural differences at the protein level.

Conclusions

Overall, this study provides insights into detailed genome structure and demonstrated the value of whole-genome sequencing as the ultimate typing tool for Legionella.

Typing methods based on whole genome sequencing data

Whole genome sequencing (WGS) of foodborne pathogens has become an effective method for investigating the information contained in the genome sequence of bacterial pathogens. In addition, its highly discriminative power enables the comparison of genetic relatedness between bacteria even on a sub-species level. For this reason, WGS is being implemented worldwide and across sectors (human, veterinary, food, and environment) for the investigation of disease outbreaks, source attribution, and improved risk characterization models. In order to extract relevant information from the large quantity and complex data produced by WGS, a host of bioinformatics tools has been developed, allowing users to analyze and interpret sequencing data, starting from simple gene-searches to complex phylogenetic studies. Depending on the research question, the complexity of the dataset and their bioinformatics skill set, users can choose between a great variety of tools for the analysis of WGS data. In this review, we describe the relevant approaches for phylogenomic studies for outbreak studies and give an overview of selected tools for the characterization of foodborne pathogens based on WGS data. Despite the efforts of the last years, harmonization and standardization of typing tools are still urgently needed to allow for an easy comparison of data between laboratories, moving towards a one health worldwide surveillance system for foodborne pathogens.

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.

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.

The major outer membrane protein of Legionella pneumophila Lpg1974 shows pore-forming characteristics similar to the human mitochondrial outer membrane pore, hVDAC1

Legionella pneumophila is an aerobic and nonspore-forming pathogenic Gram-negative bacterium of the genus Legionella. It is the causative agent of Legionnaires' disease, also known as Legionellosis. The hosts of this organism are diverse, ranging from simple water borne protozoans such as amoebae to more complex hosts such as macrophages in humans. Genome analyses have shown the presence of genes coding for eukaryotic like proteins in several Legionella species. The presence of these proteins may assist L. pneumophila in its adaptation to the eukaryotic host. We studied the characteristics of a protein (Lpg1974) of L. pneumophila that shows remarkable homologies in length of the primary sequence and for the identity/homology of many amino acids to the voltage dependent anion channel (human VDAC1, Porin 31HL) of human mitochondria. Two different forms of Lpg1974 were overexpressed in Escherichia coli and purified to homogeneity: the one containing a putative N-terminal signal sequence and one without it. Reconstituted protein containing the signal sequence formed ion-permeable pores in lipid bilayer membranes with a conductance of approximately 5.4 nS in 1 M KCl. When the predicted N-terminal signal peptide of Lpg1974 comprising an α-helical structure similar to that at the N-terminus of hVDAC1 was removed, the channels formed in reconstitution experiments had a conductance of 7.6 nS in 1 M KCl. Both Lpg1974 proteins formed pores that were voltage-dependent and anion-selective similar to the pores formed by hVDAC1. These results suggest that Lpg1974 of L. pneumophila is indeed a structural and functional homologue to hVDAC1.

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.

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.

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.

Dating the Cryptococcus gattii Dispersal to the North American Pacific Northwest

The recent emergence of the pathogenic fungus Cryptococcus gattii in the Pacific Northwest (PNW) resulted in numerous investigations into the epidemiological and enzootic impacts, as well as multiple genomic explorations of the three primary molecular subtypes of the fungus that were discovered. These studies lead to the general conclusion that the subtypes identified likely emerged out of Brazil. Here, we conducted genomic dating analyses to determine the ages of the various lineages seen in the PNW and propose hypothetical causes for the dispersal events. Bayesian evolutionary analysis strongly suggests that these independent fungal populations in the PNW are all 60 to 100 years old, providing a timing that is subsequent to the opening of the Panama Canal, which allowed for more direct shipping between Brazil and the western North American coastline, a possible driving event for these fungal translocation events.

The emergence of Cryptococcus gattii, previously regarded as a predominantly tropical pathogen, in the temperate climate of the North American Pacific Northwest (PNW) in 1999 prompted several questions. The most prevalent among these was the timing of the introduction of this pathogen to this novel environment. Here, we infer tip-dated timing estimates for the three clonal C. gattii populations observed in the PNW, VGIIa, VGIIb, and VGIIc, based on whole-genome sequencing of 134 C. gattii isolates and using Bayesian evolutionary analysis by sampling trees (BEAST). We estimated the nucleotide substitution rate for each lineage (1.59 × 10⁻⁸, 1.59 × 10⁻⁸, and 2.70 × 10⁻⁸, respectively) to be an order of magnitude higher than common neutral fungal mutation rates (2.0 × 10⁻⁹), indicating a microevolutionary rate (e.g., successive clonal generations in a laboratory) in comparison to a species’ slower, macroevolutionary rate (e.g., when using fossil records). The clonal nature of the PNW C. gattii emergence over a narrow number of years would therefore possibly explain our higher mutation rates. Our results suggest that the mean time to most recent common ancestor for all three sublineages occurred within the last 60 to 100 years. While the cause of C. gattii dispersal to the PNW is still unclear, our research estimates that the arrival is neither ancient nor very recent (i.e., <25 years ago), making a strong case for an anthropogenic introduction.

IMPORTANCE The recent emergence of the pathogenic fungus Cryptococcus gattii in the Pacific Northwest (PNW) resulted in numerous investigations into the epidemiological and enzootic impacts, as well as multiple genomic explorations of the three primary molecular subtypes of the fungus that were discovered. These studies lead to the general conclusion that the subtypes identified likely emerged out of Brazil. Here, we conducted genomic dating analyses to determine the ages of the various lineages seen in the PNW and propose hypothetical causes for the dispersal events. Bayesian evolutionary analysis strongly suggests that these independent fungal populations in the PNW are all 60 to 100 years old, providing a timing that is subsequent to the opening of the Panama Canal, which allowed for more direct shipping between Brazil and the western North American coastline, a possible driving event for these fungal translocation events.

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.

Whole-Genome Sequencing of Bacterial Pathogens: the Future of Nosocomial Outbreak Analysis

Outbreaks of multidrug-resistant bacteria present a frequent threat to vulnerable patient populations in hospitals around the world. Intensive care unit (ICU) patients are particularly susceptible to nosocomial infections due to indwelling devices such as intravascular catheters, drains, and intratracheal tubes for mechanical ventilation. The increased vulnerability of infected ICU patients demonstrates the importance of effective outbreak management protocols to be in place. Understanding the transmission of pathogens via genotyping methods is an important tool for outbreak management. Recently, whole-genome sequencing (WGS) of pathogens has become more accessible and affordable as a tool for genotyping. Analysis of the entire pathogen genome via WGS could provide unprecedented resolution in discriminating even highly related lineages of bacteria and revolutionize outbreak analysis in hospitals. Nevertheless, clinicians have long been hesitant to implement WGS in outbreak analyses due to the expensive and cumbersome nature of early sequencing platforms. Recent improvements in sequencing technologies and analysis tools have rapidly increased the output and analysis speed as well as reduced the overall costs of WGS. In this review, we assess the feasibility of WGS technologies and bioinformatics analysis tools for nosocomial outbreak analyses and provide a comparison to conventional outbreak analysis workflows. Moreover, we review advantages and limitations of sequencing technologies and analysis tools and present a real-world example of the implementation of WGS for antimicrobial resistance analysis. We aimed to provide health care professionals with a guide to WGS outbreak analysis that highlights its benefits for hospitals and assists in the transition from conventional to WGS-based outbreak analysis.

Type II Secretion Substrates of Legionella pneumophila Translocate Out of the Pathogen-Occupied Vacuole via a Semipermeable Membrane

Legionella pneumophila replicates in macrophages in a host-derived phagosome, termed the Legionella-containing vacuole (LCV). While the translocation of type IV secretion (T4S) effectors into the macrophage cytosol is well established, the location of type II secretion (T2S) substrates in the infected host cell is unknown. Here, we show that the T2S substrate ProA, a metalloprotease, translocates into the cytosol of human macrophages, where it associates with the LCV membrane (LCVM). Translocation is detected as early as 10 h postinoculation (p.i.), which is approximately the midpoint of the intracellular life cycle. However, it is detected as early as 6 h p.i. if ProA is hyperexpressed, indicating that translocation depends on the timing of ProA expression and that any other factors necessary for translocation are in place by that time point. Translocation occurs with all L. pneumophila strains tested and in amoebae, natural hosts for L. pneumophila. It was absent in murine bone marrow-derived macrophages and murine macrophage cell lines. The ChiA chitinase also associated with the cytoplasmic face of the LCVM at 6 h p.i. and in a T2S-dependent manner. Galectin-3 and galectin-8, eukaryotic proteins whose localization is influenced by damage to host membranes, appeared within the LCV of infected human but not murine macrophages beginning at 6 h p.i. Thus, we hypothesize that ProA and ChiA are first secreted into the vacuolar lumen by the activity of the T2S and subsequently traffic into the macrophage cytosol via a novel mechanism that involves a semipermeable LCVM.

Infection of macrophages and amoebae plays a central role in the pathogenesis of L. pneumophila, the agent of Legionnaires’ disease. We have previously demonstrated that the T2S system of L. pneumophila greatly contributes to intracellular infection. However, the location of T2S substrates within the infected host cell is unknown. This report presents the first evidence of a L. pneumophila T2S substrate in the host cell cytosol and, therefore, the first evidence of a non-T4S effector trafficking out of the LCV. We also provide the first indication that the LCV is not completely intact but is instead semipermeable and that this occurs in human but not murine macrophages. Given this permeability, we hypothesize that other T2S substrates and LCV lumenal contents can escape into the host cell cytosol. Thus, these substrates may represent a battery of previously unidentified effectors that can interact with host factors and contribute to intracellular infection by L. pneumophila.

A Comparative Analysis of the Lyve-SET Phylogenomics Pipeline for Genomic Epidemiology of Foodborne Pathogens

Modern epidemiology of foodborne bacterial pathogens in industrialized countries relies increasingly on whole genome sequencing (WGS) techniques. As opposed to profiling techniques such as pulsed-field gel electrophoresis, WGS requires a variety of computational methods. Since 2013, United States agencies responsible for food safety including the CDC, FDA, and USDA, have been performing whole-genome sequencing (WGS) on all Listeria monocytogenes found in clinical, food, and environmental samples. Each year, more genomes of other foodborne pathogens such as Escherichia coli, Campylobacter jejuni, and Salmonella enterica are being sequenced. Comparing thousands of genomes across an entire species requires a fast method with coarse resolution; however, capturing the fine details of highly related isolates requires a computationally heavy and sophisticated algorithm. Most L. monocytogenes investigations employing WGS depend on being able to identify an outbreak clade whose inter-genomic distances are less than an empirically determined threshold. When the difference between a few single nucleotide polymorphisms (SNPs) can help distinguish between genomes that are likely outbreak-associated and those that are less likely to be associated, we require a fine-resolution method. To achieve this level of resolution, we have developed Lyve-SET, a high-quality SNP pipeline. We evaluated Lyve-SET by retrospectively investigating 12 outbreak data sets along with four other SNP pipelines that have been used in outbreak investigation or similar scenarios. To compare these pipelines, several distance and phylogeny-based comparison methods were applied, which collectively showed that multiple pipelines were able to identify most outbreak clusters and strains. Currently in the US PulseNet system, whole genome multi-locus sequence typing (wgMLST) is the preferred primary method for foodborne WGS cluster detection and outbreak investigation due to its ability to name standardized genomic profiles, its central database, and its ability to be run in a graphical user interface. However, creating a functional wgMLST scheme requires extended up-front development and subject-matter expertise. When a scheme does not exist or when the highest resolution is needed, SNP analysis is used. Using three Listeria outbreak data sets, we demonstrated the concordance between Lyve-SET SNP typing and wgMLST.

Availability: Lyve-SET can be found at https://github.com/lskatz/Lyve-SET.