Identification of a hypervariable region containing new Legionella pneumophila Icm/Dot translocated substrates by using the conserved icmQ regulatory signature

The Legionella genus core effectors display functional conservation among orthologs by themselves or combined with an accessory protein

•

The Legionella genus contains nine core effectors.

•

Three Legionella pneumophila core effectors are required for intracellular growth.

•

The Legionella genus core effectors display functional conservation among orthologs.

•

One Legionella core effector requires an accessory protein to perform its function.

The intracellular pathogen Legionella pneumophila, as well as other Legionella species, utilize the Icm/Dot type-IV secretion system to translocate an exceptionally large and diverse repertoire of effectors into their host cells. However, only nine core effectors were found to be present in all analyzed Legionella species. In this study, we investigated the core effectors, and used intracellular growth complementation to determine whether orthologs of core effectors perform the same function in different Legionella species. We found that three out of the nine L. pneumophila core effectors are required for maximal intracellular growth. Examination of orthologous core effectors from four Legionella species spread over the Legionella phylogenetic tree revealed that most of them perform the same function. Nevertheless, some of the orthologs of the core effector LegA3 did not complement the L. pneumophila legA3 deletion mutant for intracellular growth. LegA3 is encoded as part of an operon together with another gene, which we named legA3C, encoding a non-translocated protein. We found that LegA3 and LegA3C physically interact with each other, are both required for maximal intracellular growth, and the LegA3-LegA3C orthologous pairs from all the Legionella species examined fully complement the L. pneumophila legA3 deletion mutant for intracellular growth. Our results indicate that the Legionella core effectors orthologs generally perform the same function and establish that LegA3 requires LegA3C to fulfill its conserved function.

Autorepressor PsrA is required for optimal Legionella pneumophila growth in Acanthamoeba castellanii protozoa

Legionella pneumophila possesses a unique intracellular lifecycle featuring distinct morphological stages that include replicative forms and transmissive cyst forms. Expression of genes associated with virulence traits and cyst morphogenesis is concomitant, and governed by a complex stringent response based-regulatory network and the stationary phase sigma factor RpoS. In Pseudomonas spp., rpoS expression is controlled by the autorepressor PsrA, and orthologs of PsrA and RpoS are required for cyst formation in Azotobacter. Here we report that the L. pneumophila psrA ortholog, expressed as a leaderless monocistronic transcript, is also an autorepressor, but is not a regulator of rpoS expression. Further, the binding site sequence recognized by L. pneumophila PsrA is different from that of Pseudomonas PsrA, suggesting a repertoire of target genes unique to L. pneumophila. While PsrA was dispensable for growth in human U937-derived macrophages, lack of PsrA affected bacterial intracellular growth in Acanthamoeba castellanii protozoa, but also increased the quantity of poly-3-hydroxybutyrate (PHB) inclusions in matured transmissive cysts. Interestingly, overexpression of PsrA increased the size and bacterial load of the replicative vacuole in both host cell types. Taken together, we report that PsrA is a host-specific requirement for optimal temporal progression of L. pneumophila intracellular lifecycle in A. castellanii.

Mitigation of Expression of Virulence Genes in Legionella pneumophila Internalized in the Free-Living Amoeba Willaertia magna C2c Maky

Legionella pneumophila is a human pathogen responsible for a severe form of pneumonia named Legionnaire disease. Its natural habitat is aquatic environments, being in a free state or intracellular parasites of free-living amoebae, such as Acanthamoeba castellanii. This pathogen is able to replicate within some amoebae. Willaertia magna C2c Maky, a non-pathogenic amoeba, was previously demonstrated to resist to L. pneumophila and even to be able to eliminate the L. pneumophila strains Philadelphia, Lens, and Paris. Here, we studied the induction of seven virulence genes of three L. pneumophila strains (Paris, Philadelphia, and Lens) within W. magna C2c Maky in comparison within A. castellanii and with the gene expression level of L. pneumophila strains alone used as controls. We defined a gene expression-based virulence index to compare easily and without bias the transcript levels in different conditions and demonstrated that W. magna C2c Maky did not increase the virulence of L. pneumophila strains in contrast to A. castellanii. These results confirmed the non-permissiveness of W. magna C2c Maky toward L. pneumophila strains.

Assessing the impact, genomics and evolution of type II secretion across a large, medically important genus: the Legionella type II secretion paradigm

The type II secretion system (T2SS) plays a major role in promoting bacterial survival in the environment and in human hosts. One of the best characterized T2SS is that of Legionella pneumophila, the agent of Legionnaires’ disease. Secreting at least 25 proteins, including degradative enzymes, eukaryotic-like proteins and novel effectors, this T2SS contributes to the ability of L. pneumophila to grow at low temperatures, infect amoebal and macrophage hosts, damage lung tissue, evade the immune system, and undergo sliding motility. The genes encoding the T2SS are conserved across the genus Legionella, which includes 62 species and >30 pathogens in addition to L. pneumophila. The vast majority of effectors associated with L. pneumophila are shared by a large number of Legionella species, hinting at a critical role for them in the ecology of Legionella as a whole. However, no other species has the same repertoire as L. pneumophila, with, as a general rule, phylogenetically more closely related species sharing similar sets of effectors. T2SS effectors that are involved in infection of a eukaryotic host(s) are more prevalent throughout Legionella, indicating that they are under stronger selective pressure. The Legionella T2SS apparatus is closest to that of Aquicella (another parasite of amoebae), and a significant number of L. pneumophila effectors have their closest homologues in Aquicella. Thus, the T2SS of L. pneumophila probably originated within the order Legionellales, with some of its effectors having arisen within that Aquicella-like progenitor, while other effectors derived from the amoebal host, mimiviruses, fungi and less closely related bacteria.

Systematic analysis and prediction of type IV secreted effector proteins by machine learning approaches

In the course of infecting their hosts, pathogenic bacteria secrete numerous effectors, namely, bacterial proteins that pervert host cell biology. Many Gram-negative bacteria, including context-dependent human pathogens, use a type IV secretion system (T4SS) to translocate effectors directly into the cytosol of host cells. Various type IV secreted effectors (T4SEs) have been experimentally validated to play crucial roles in virulence by manipulating host cell gene expression and other processes. Consequently, the identification of novel effector proteins is an important step in increasing our understanding of host-pathogen interactions and bacterial pathogenesis. Here, we train and compare six machine learning models, namely, Naïve Bayes (NB), K-nearest neighbor (KNN), logistic regression (LR), random forest (RF), support vector machines (SVMs) and multilayer perceptron (MLP), for the identification of T4SEs using 10 types of selected features and 5-fold cross-validation. Our study shows that: (1) including different but complementary features generally enhance the predictive performance of T4SEs; (2) ensemble models, obtained by integrating individual single-feature models, exhibit a significantly improved predictive performance and (3) the 'majority voting strategy' led to a more stable and accurate classification performance when applied to predicting an ensemble learning model with distinct single features. We further developed a new method to effectively predict T4SEs, Bastion4 (Bacterial secretion effector predictor for T4SS), and we show our ensemble classifier clearly outperforms two recent prediction tools. In summary, we developed a state-of-the-art T4SE predictor by conducting a comprehensive performance evaluation of different machine learning algorithms along with a detailed analysis of single- and multi-feature selections.

Using an optimal set of features with a machine learning-based approach to predict effector proteins for Legionella pneumophila

Type IV secretion systems exist in a number of bacterial pathogens and are used to secrete effector proteins directly into host cells in order to change their environment making the environment hospitable for the bacteria. In recent years, several machine learning algorithms have been developed to predict effector proteins, potentially facilitating experimental verification. However, inconsistencies exist between their results. Previously we analysed the disparate sets of predictive features used in these algorithms to determine an optimal set of 370 features for effector prediction. This study focuses on the best way to use these optimal features by designing three machine learning classifiers, comparing our results with those of others, and obtaining de novo results. We chose the pathogen Legionella pneumophila strain Philadelphia-1, a cause of Legionnaires’ disease, because it has many validated effector proteins and others have developed machine learning prediction tools for it. While all of our models give good results indicating that our optimal features are quite robust, Model 1, which uses all 370 features with a support vector machine, has slightly better accuracy. Moreover, Model 1 predicted 472 effector proteins that are deemed highly probable to be effectors and include 94% of known effectors. Although the results of our three models agree well with those of other researchers, their models only predicted 126 and 311 candidate effectors.

An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach

Type IV secretion systems (T4SS) are multi-protein complexes in a number of bacterial pathogens that can translocate proteins and DNA to the host. Most T4SSs function in conjugation and translocate DNA; however, approximately 13% function to secrete proteins, delivering effector proteins into the cytosol of eukaryotic host cells. Upon entry, these effectors manipulate the host cell’s machinery for their own benefit, which can result in serious illness or death of the host. For this reason recognition of T4SS effectors has become an important subject. Much previous work has focused on verifying effectors experimentally, a costly endeavor in terms of money, time, and effort. Having good predictions for effectors will help to focus experimental validations and decrease testing costs. In recent years, several scoring and machine learning-based methods have been suggested for the purpose of predicting T4SS effector proteins. These methods have used different sets of features for prediction, and their predictions have been inconsistent. In this paper, an optimal set of features is presented for predicting T4SS effector proteins using a statistical approach. A thorough literature search was performed to find features that have been proposed. Feature values were calculated for datasets of known effectors and non-effectors for T4SS-containing pathogens for four genera with a sufficient number of known effectors, Legionella pneumophila, Coxiella burnetii, Brucella spp, and Bartonella spp. The features were ranked, and less important features were filtered out. Correlations between remaining features were removed, and dimensional reduction was accomplished using principal component analysis and factor analysis. Finally, the optimal features for each pathogen were chosen by building logistic regression models and evaluating each model. The results based on evaluation of our logistic regression models confirm the effectiveness of our four optimal sets of features, and based on these an optimal set of features is proposed for all T4SS effector proteins.

RavN is a member of a previously unrecognized group of Legionella pneumophila E3 ubiquitin ligases

The eukaryotic ubiquitylation machinery catalyzes the covalent attachment of the small protein modifier ubiquitin to cellular target proteins in order to alter their fate. Microbial pathogens exploit this post-translational modification process by encoding molecular mimics of E3 ubiquitin ligases, eukaryotic enzymes that catalyze the final step in the ubiquitylation cascade. Here, we show that the Legionella pneumophila effector protein RavN belongs to a growing class of bacterial proteins that mimic host cell E3 ligases to exploit the ubiquitylation pathway. The E3 ligase activity of RavN was located within its N-terminal region and was dependent upon interaction with a defined subset of E2 ubiquitin-conjugating enzymes. The crystal structure of the N-terminal region of RavN revealed a U-box-like motif that was only remotely similar to other U-box domains, indicating that RavN is an E3 ligase relic that has undergone significant evolutionary alteration. Substitution of residues within the predicted E2 binding interface rendered RavN inactive, indicating that, despite significant structural changes, the mode of E2 recognition has remained conserved. Using hidden Markov model-based secondary structure analyses, we identified and experimentally validated four additional L. pneumophila effectors that were not previously recognized to possess E3 ligase activity, including Lpg2452/SdcB, a new paralog of SidC. Our study provides strong evidence that L. pneumophila is dedicating a considerable fraction of its effector arsenal to the manipulation of the host ubiquitylation pathway.

Bacterial pathogens often hijack conserved host pathways by encoding proteins that are molecular mimics of eukaryotic enzymes, thus tricking the host cell into surrendering its resources to the bacteria. Here, we show that the intracellular pathogen Legionella pneumophila uses such a strategy to exploit ubiquitylation, a conserved post-translational modification that is mediated by E3 ubiquitin ligases. L. pneumophila encodes molecular mimics of host E3 ligases, including the effector protein RavN, thereby subverting the ubiquitylation pathway for its own benefit during infection. Using protein crystallography, we show that the fold of RavN has only residual resemblance to conventional eukaryotic E3s, yet its mode of interaction with E2 enzymes, host proteins that are important for the ubiquitin transfer reaction, has been preserved throughout evolution. Inspired by the discovery of RavN, we performed an in silico fold homology search and discovered several additional E3 ligase candidates within the effector repertoire of L. pneumophila that, until now, had remained hidden due to lack of primary sequence similarity. Our study supports the hypothesis that E3 ligases are a vital part of the virulence program of L. pneumophila, and that these effectors, despite having undergone extensive evolutionary changes, have retained features that are critical for their biological function, including the ability to hijack host factors that are part of the ubiquitylation machinery.

Expression of flagellin and key regulatory flagellar genes in the non-motile bacterium Piscirickettsia salmonis

The Piscirickettsia salmonis genome was screened to evaluate potential flagella-related open reading frames, as well as their genomic organization and eventual expression. A complete and organized set of flagellar genes was found for P. salmonis, although no structural flagellum has ever been reported for this bacterium. To gain further understanding, the hierarchical flagellar cascade described for Legionella pneumophila was used as a reference model for putative analysis in P. salmonis. Specifically, 5 of the most relevant genes from this cascade were chosen, including 3 regulatory genes (fleQ, triggers the cascade; fliA, regulates the σ28-coding gene; and rpoN, an RNA polymerase-dependent gene) and 2 terminal structural genes (flaA and flaB, flagellin and a flagellin-like protein, respectively). Kinetic experiments evaluated gene expressions over time, with P. salmonis assessed in 2 liquid, cell-free media and during infection of the SHK-1 fish cell line. Under all conditions, the 5 target genes were primarily expressed during early growth/infection and were differentially expressed when bacteria encountered environmental stress (i.e. a high-salt concentration). Intriguingly, the flagellin monomer was fully expressed under all growth conditions and was located near the bacterial membrane. While no structural flagellum was detected under any condition, the recombinant flagellin monomer induced a proinflammatory response in SHK-1 cells, suggesting a possible immunomodulatory function. The potential implications of these observations are discussed in the context of P. salmonis biology and pathogenic potential.

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

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

Exposure to synthetic gray water inhibits amoeba encystation and alters expression of Legionella pneumophila virulence genes

Water conservation efforts have focused on gray water (GW) usage, especially for applications that do not require potable water quality. However, there is a need to better understand environmental pathogens and their free-living amoeba (FLA) hosts within GW, given their growth potential in stored gray water. Using synthetic gray water (sGW) we examined three strains of the water-based pathogen Legionella pneumophila and its FLA hosts Acanthamoeba polyphaga, A. castellanii, and Vermamoeba vermiformis. Exposure to sGW for 72 h resulted in significant inhibition (P < 0.0001) of amoebal encystation versus control-treated cells, with the following percentages of cysts in sGW versus controls: A. polyphaga (0.6 versus 6%), A. castellanii (2 versus 62%), and V. vermiformis (1 versus 92%), suggesting sGW induced maintenance of the actively feeding trophozoite form. During sGW exposure, L. pneumophila culturability decreased as early as 5 h (1.3 to 2.9 log10 CFU, P < 0.001) compared to controls (Δ0 to 0.1 log10 CFU) with flow cytometric analysis revealing immediate changes in membrane permeability. Furthermore, reverse transcription-quantitative PCR was performed on total RNA isolated from L. pneumophila cells at 0 to 48 h after sGW incubation, and genes associated with virulence (gacA, lirR, csrA, pla, and sidF), the type IV secretion system (lvrB and lvrE), and metabolism (ccmF and lolA) were all shown to be differentially expressed. These results suggest that conditions within GW may promote interactions between water-based pathogens and FLA hosts, through amoebal encystment inhibition and alteration of bacterial gene expression, thus warranting further exploration into FLA and L. pneumophila behavior in GW systems.

Two Fis regulators directly repress the expression of numerous effector-encoding genes in Legionella pneumophila

Legionella pneumophila is an intracellular human pathogen that utilizes the Icm/Dot type IVB secretion system to translocate a large repertoire of effectors into host cells. For most of these effectors, there is no information regarding their regulation. Therefore, the aim of this study was to examine the involvement of the three L. pneumophila Fis homologs in the regulation of effector-encoding genes. Deletion mutants constructed in the genes encoding the three Fis regulators revealed that Fis1 (lpg0542 gene) and Fis3 (lpg1743) but not Fis2 (lpg1370) are partially required for intracellular growth of L. pneumophila in Acanthamoeba castellanii. To identify pathogenesis-related genes directly regulated by Fis, we established a novel in vivo system which resulted in the discovery of numerous effector-encoding genes directly regulated by Fis. Further examination of these genes revealed that Fis1 and Fis3 repress the level of expression of effector-encoding genes during exponential phase. Three groups of effector-encoding genes were identified: (i) effectors regulated mainly by Fis1, (ii) effectors regulated mainly by Fis3, and (iii) effectors regulated by both Fis1 and Fis3. Examination of the upstream regulatory region of all of these effector-encoding genes revealed multiple putative Fis regulatory elements, and site-directed mutagenesis confirmed that a few of these sites constitute part of a repressor binding element. Furthermore, gel mobility shift assays demonstrated the direct relation between the Fis1 and Fis3 regulators and these regulatory elements. Collectively, our results demonstrate for the first time that two of the three L. pneumophila Fis regulators directly repress the expression of Icm/Dot effector-encoding genes.

Polyketide synthase (PKS) reduces fusion of Legionella pneumophila-containing vacuoles with lysosomes and contributes to bacterial competitiveness during infection

L. pneumophila-containing vacuoles (LCVs) exclude endocytic and lysosomal markers in human macrophages and protozoa. We screened a L. pneumophila mini-Tn10 transposon library for mutants, which fail to inhibit the fusion of LCVs with lysosomes by loading of the lysosomal compartment with colloidal iron dextran, mechanical lysis of infected host cells, and magnetic isolation of LCVs that have fused with lysosomes. In silico analysis of the mutated genes, D. discoideum plaque assays and infection assays in protozoa and U937 macrophage-like cells identified well established as well as novel putative L. pneumophila virulence factors. Promising candidates were further analyzed for their co-localization with lysosomes in host cells using fluorescence microscopy. This approach corroborated that the O-methyltransferase, PilY1, TPR-containing protein and polyketide synthase (PKS) of L. pneumophila interfere with lysosomal degradation. Competitive infections in protozoa and macrophages revealed that the identified PKS contributes to the biological fitness of pneumophila strains and may explain their prevalence in the epidemiology of Legionnaires' disease.

Poison domains block transit of translocated substrates via the Legionella pneumophila Icm/Dot system

Legionella pneumophila uses the Icm/Dot type 4B secretion system (T4BSS) to deliver translocated protein substrates to the host cell, promoting replication vacuole formation. The conformational state of the translocated substrates within the bacterial cell is unknown, so we sought to determine if folded substrates could be translocated via this system. Fusions of L. pneumophila Icm/Dot-translocated substrates (IDTS) to dihydrofolate reductase (DHFR) or ubiquitin (Ub), small proteins known to fold rapidly, resulted in proteins with low translocation efficiencies. The folded moieties did not cause increased aggregation of the IDTS and did not impede interaction with the adaptor protein complex IcmS/IcmW, which is thought to form a soluble complex that promotes translocation. The translocation defect was alleviated with a Ub moiety harboring mutations known to destabilize its structure, indicating that unfolded proteins are preferred substrates. Real-time analysis of translocation, following movement during the first 30 min after bacterial contact with host cells, revealed that the folded moiety caused a kinetic defect in IDTS translocation. Expression of an IDTS fused to a folded moiety interfered with the translocation of other IDTS, consistent with it causing a blockage of the translocation channel. Furthermore, the folded protein fusions also interfered with intracellular growth, consistent with inefficient or impaired translocation of proteins critical for L. pneumophila intracellular growth. These studies indicate that substrates of the Icm/Dot T4SS are translocated to the host cytosol in an unfolded conformation and that folded proteins are stalled within the translocation channel, impairing the function of the secretion system.

Methods for determining protein translocation by the Legionella pneumophila Dot/Icm type IV secretion system

Legionella pneumophila the causative agent of Legionnaires' disease, actively manipulates host cell -processes to establish a membrane-bound replication vacuole permissive for its replication. Establishment of such replication niche requires the Dot/Icm type IV secretion system which translocates a plethora of effectors into host cells. Determining whether a particular protein is a substrate of the transporter is a prerequisite for subsequent functional studies. Thus, a variety of methods have been developed in the last decade to measure Dot/Icm-dependent delivery of protein into the host cell. The combination of these methods and the appropriate screening strategies has allowed for the identification of more than 270 translocated proteins. These efforts have laid a solid foundation for further study of the roles of these proteins in the interactions between L. pneumophila and its host. Here, we summarized the experimental details of these methods.

Effector translocation by the Legionella Dot/Icm type IV secretion system

Legionella pneumophila is an opportunistic pathogen responsible for Legionnaires' disease. This bacterium survives and replicates within phagocytes by bypassing their bactericidal activity. Intracellular replication of L. pneumophila requires the Dot/Icm type IV secretion system made of approximately 27 proteins that presumably traverses the bacterial and phagosomal membranes. The perturbation of the host killing ability largely is mediated by the collective functions of the protein substrates injected into host cells via the Dot/Icm transporter. Proper protein translocation by Dot/Icm is determined by a number of factors, including signals recognizable by the translocator, chaperones that may facilitate the proper folding of substrates and transcriptional regulation and protein stability that determine the abundance and temporal transfer of the substrates. Although a large number of Dot/Icm substrates have been identified, investigation to understand the translocation is ongoing. Here we summarized the recent advancements in our understanding of the factors that determine the protein translocation activity of the Dot/Icm transporter.

Cell biology of infection by Legionella pneumophila

Professional phagocytes digest internalized microorganisms by actively delivering them into the phagolysosomal compartment. Intravacuolar bacterial pathogens have evolved a variety of effective strategies to bypass the default pathway of phagosomal maturation to create a niche permissive for their survival and propagation. Here we discuss recent progress in our understanding of the sophisticated mechanisms used by Legionella pneumophila to survive in phagocytes.

Manipulation of host vesicular trafficking and innate immune defence by Legionella Dot/Icm effectors

Legionella pneumophila, the causative agent of Legionnaires' disease, infects and replicates in macrophages and amoebas. Following internalization, L. pneumophila resides in a vacuole structure called Legionella-containing vacuole (LCV). The LCV escapes from the endocytic maturation process and avoids fusion with the lysosome, a hallmark of Legionella pathogenesis. Interference with the secretory vesicle transport and avoiding lysosomal targeting render the LCV permissive for L. pneumophila intracellular replication. Central to L. pneumophila pathogenesis is a defect in the organelle trafficking/intracellular multiplication (Dot/Icm) type IV secretion system that translocates a large number of effector proteins into host cells. Many of the Dot/Icm effectors employ diverse and sophisticated biochemical strategies to manipulate the host vesicular transport system, playing an important role in LCV biogenesis and trafficking. Similar to other bacterial pathogens, L. pneumophila also delivers effector proteins to modulate or counteract host innate immune defence pathways such as the NF-κB and apoptotic signalling. This review summarizes the known functions and mechanisms of Dot/Icm effectors that target host membrane trafficking and innate immune defence pathways.

Comprehensive identification of protein substrates of the Dot/Icm type IV transporter of Legionella pneumophila

A large number of proteins transferred by the Legionella pneumophila Dot/Icm system have been identified by various strategies. With no exceptions, these strategies are based on one or more characteristics associated with the tested proteins. Given the high level of diversity exhibited by the identified proteins, it is possible that some substrates have been missed in these screenings. In this study, we took a systematic method to survey the L. pneumophila genome by testing hypothetical orfs larger than 300 base pairs for Dot/Icm-dependent translocation. 798 of the 832 analyzed orfs were successfully fused to the carboxyl end of β-lactamase. The transfer of the fusions into mammalian cells was determined using the β-lactamase reporter substrate CCF4-AM. These efforts led to the identification of 164 proteins positive in translocation. Among these, 70 proteins are novel substrates of the Dot/Icm system. These results brought the total number of experimentally confirmed Dot/Icm substrates to 275. Sequence analysis of the C-termini of these identified proteins revealed that Lpg2844, which contains few features known to be important for Dot/Icm-dependent protein transfer can be translocated at a high efficiency. Thus, our efforts have identified a large number of novel substrates of the Dot/Icm system and have revealed the diverse features recognizable by this protein transporter.

Antibiotics and UV radiation induce competence for natural transformation in Legionella pneumophila

Natural transformation by competence is a major mechanism of horizontal gene transfer in bacteria. Competence is defined as the genetically programmed physiological state that enables bacteria to actively take up DNA from the environment. The conditions that signal competence development are multiple and elusive, complicating the understanding of its evolutionary significance. We used expression of the competence gene comEA as a reporter of competence development and screened several hundred molecules for their ability to induce competence in the freshwater living pathogen Legionella pneumophila. We found that comEA expression is induced by chronic exposure to genotoxic molecules such as mitomycin C and antibiotics of the fluoroquinolone family. These results indicated that, in L. pneumophila, competence may be a response to genotoxic stress. Sunlight-emitted UV light represents a major source of genotoxic stress in the environment and we found that exposure to UV radiation effectively induces competence development. For the first time, we show that genetic exchanges by natural transformation occur within an UV-stressed population. Genotoxic stress induces the RecA-dependent SOS response in many bacteria. However, genetic and phenotypic evidence suggest that L. pneumophila lacks a prototypic SOS response and competence development in response to genotoxic stress is RecA independent. Our results strengthen the hypothesis that competence may have evolved as a DNA damage response in SOS-deficient bacteria. This parasexual response to DNA damage may have enabled L. pneumophila to acquire and propagate foreign genes, contributing to the emergence of this human pathogen.

The E Block motif is associated with Legionella pneumophila translocated substrates

Legionella pneumophila promotes intracellular growth by moving bacterial proteins across membranes via the Icm/Dot system. A strategy was devised to identify large numbers of Icm/Dot translocated proteins, and the resulting pool was used to identify common motifs that operate as recognition signals. The 3' end of the sidC gene, which encodes a known translocated substrate, was replaced with DNA encoding 200 codons from the 3' end of 442 potential substrate-encoding genes. The resulting hybrid proteins were then tested in a high throughput assay, in which translocated SidC antigen was detected by indirect immunofluorescence. Among translocated substrates, regions of 6-8 residues called E Blocks were identified that were rich in glutamates. Analysis of SidM/DrrA revealed that loss of three Glu residues, arrayed in a triangle on an α-helical surface, totally eliminated translocation of a reporter protein. Based on this result, a second strategy was employed to identify Icm/Dot substrates having carboxyl terminal glutamates. From the fusion assay and the bioinformatic queries, carboxyl terminal sequences from 49 previously unidentified proteins were shown to promote translocation into target cells. These studies indicate that by analysing subsets of translocated substrates, patterns can be found that allow predictions of important motifs recognized by Icm/Dot.

Modulation of host cell function by Legionella pneumophila type IV effectors

Macrophages and protozoa ingest bacteria by phagocytosis and destroy these microbes using a conserved pathway that mediates fusion of the phagosome with lysosomes. To survive within phagocytic host cells, bacterial pathogens have evolved a variety of strategies to avoid fusion with lysosomes. A virulence strategy used by the intracellular pathogen Legionella pneumophila is to manipulate host cellular processes using bacterial proteins that are delivered into the cytosolic compartment of the host cell by a specialized secretion system called Dot/Icm. The proteins delivered by the Dot/Icm system target host factors that play evolutionarily conserved roles in controlling membrane transport in eukaryotic cells, which enables L. pneumophila to create an endoplasmic reticulum-like vacuole that supports intracellular replication in both protozoan and mammalian host cells. This review focuses on intracellular trafficking of L. pneumophila and describes how bacterial proteins contribute to modulation of host processes required for survival within host cells.

Legionella pneumophila strain 130b possesses a unique combination of type IV secretion systems and novel Dot/Icm secretion system effector proteins

Legionella pneumophila is a ubiquitous inhabitant of environmental water reservoirs. The bacteria infect a wide variety of protozoa and, after accidental inhalation, human alveolar macrophages, which can lead to severe pneumonia. The capability to thrive in phagocytic hosts is dependent on the Dot/Icm type IV secretion system (T4SS), which translocates multiple effector proteins into the host cell. In this study, we determined the draft genome sequence of L. pneumophila strain 130b (Wadsworth). We found that the 130b genome encodes a unique set of T4SSs, namely, the Dot/Icm T4SS, a Trb-1-like T4SS, and two Lvh T4SS gene clusters. Sequence analysis substantiated that a core set of 107 Dot/Icm T4SS effectors was conserved among the sequenced L. pneumophila strains Philadelphia-1, Lens, Paris, Corby, Alcoy, and 130b. We also identified new effector candidates and validated the translocation of 10 novel Dot/Icm T4SS effectors that are not present in L. pneumophila strain Philadelphia-1. We examined the prevalence of the new effector genes among 87 environmental and clinical L. pneumophila isolates. Five of the new effectors were identified in 34 to 62% of the isolates, while less than 15% of the strains tested positive for the other five genes. Collectively, our data show that the core set of conserved Dot/Icm T4SS effector proteins is supplemented by a variable repertoire of accessory effectors that may partly account for differences in the virulences and prevalences of particular L. pneumophila strains.

Genome-scale identification of Legionella pneumophila effectors using a machine learning approach

A large number of highly pathogenic bacteria utilize secretion systems to translocate effector proteins into host cells. Using these effectors, the bacteria subvert host cell processes during infection. Legionella pneumophila translocates effectors via the Icm/Dot type-IV secretion system and to date, approximately 100 effectors have been identified by various experimental and computational techniques. Effector identification is a critical first step towards the understanding of the pathogenesis system in L. pneumophila as well as in other bacterial pathogens. Here, we formulate the task of effector identification as a classification problem: each L. pneumophila open reading frame (ORF) was classified as either effector or not. We computationally defined a set of features that best distinguish effectors from non-effectors. These features cover a wide range of characteristics including taxonomical dispersion, regulatory data, genomic organization, similarity to eukaryotic proteomes and more. Machine learning algorithms utilizing these features were then applied to classify all the ORFs within the L. pneumophila genome. Using this approach we were able to predict and experimentally validate 40 new effectors, reaching a success rate of above 90%. Increasing the number of validated effectors to around 140, we were able to gain novel insights into their characteristics. Effectors were found to have low G+C content, supporting the hypothesis that a large number of effectors originate via horizontal gene transfer, probably from their protozoan host. In addition, effectors were found to cluster in specific genomic regions. Finally, we were able to provide a novel description of the C-terminal translocation signal required for effector translocation by the Icm/Dot secretion system. To conclude, we have discovered 40 novel L. pneumophila effectors, predicted over a hundred additional highly probable effectors, and shown the applicability of machine learning algorithms for the identification and characterization of bacterial pathogenesis determinants.

Many pathogenic bacteria exert their function by translocating a set of proteins, termed effectors, into the cytoplasm of their host cell. These effectors subvert various host cell processes for the benefit of the bacteria. Our goal in this study was to identify novel effectors in a genomic scale, towards a better understanding of the molecular mechanisms of bacterial pathogenesis. We developed a computational approach for the detection of new effectors in the intracellular pathogen Legionella pneumophila, the causative agent of the Legionnaires' disease, a severe pneumonia-like disease. The novelty of our approach for detecting effectors is the combination of state-of-the-art machine learning classification algorithms with broad biological knowledge on effector biology in a genomic scale. Applying this method, we detected and experimentally validated dozens of new effectors. Notably, our computational predictions had an exceedingly high accuracy of over 90%. In analyzing these effectors we were able to obtain new insights into the molecular mechanism of the pathogenesis system. Our results suggest, for the first time, that over 10% of the Legionella genome is dedicated to pathogenesis. Finally, our approach is general and can be utilized to study effectors in many other human pathogens.

The perplexing functions and surprising origins of Legionella pneumophila type IV secretion effectors

Only a limited number of bacterial pathogens evade destruction by phagocytic cells such as macrophages. Legionella pneumophila is a Gram-negative gamma-proteobacterial species that can infect and replicate in alveolar macrophages, causing Legionnaires' disease, a severe pneumonia. L. pneumophila uses a complex secretion system to inject host cells with effector proteins capable of disrupting or altering the host cell processes. The L. pneumophila effectors target multiple processes but are essentially aimed at modifying the properties of the L. pneumophila phagosome by altering vesicular trafficking, gradually creating a specialized vacuole in which the bacteria replicate robustly. In nature, L. pneumophila is thought to parasitize free-living protists, which may have selected for traits that promote virulence of L. pneumophila in humans. Indeed, many effector genes encode proteins with eukaryotic domains and are likely to be of protozoan origin. Sustained horizontal gene transfer events within the protozoan niche may have allowed L. pneumophila to become a professional parasite of phagocytes, simultaneously giving rise to its ability to infect macrophages, cells that constitute the first line of cellular defence against bacterial infections.

A Legionella effector acquired from protozoa is involved in sphingolipids metabolism and is targeted to the host cell mitochondria

Legionella pneumophila infects alveolar macrophages and protozoa through establishment of an intracellular replication niche. This process is mediated by bacterial effectors translocated into the host cell via the Icm/Dot type IV secretion system. Most of the effectors identified so far are unique to L. pneumophila; however, some of the effectors are homologous to eukaryotic proteins. We performed a distribution analysis of many known L. pneumophila effectors and found that several of them, mostly eukaryotic homologous proteins, are present in different Legionella species. In-depth analysis of LegS2, a L. pneumophila homologue of the highly conserved eukaryotic enzyme sphingosine-1-phosphate lyase (SPL), revealed that it was most likely acquired from a protozoan organism early during Legionella evolution. The LegS2 protein was found to translocate into host cells using a C-terminal translocation domain absent in its eukaryotic homologues. LegS2 was found to complement the sphingosine-sensitive phenotype of a Saccharomyces serevisia SPL-null mutant and this complementation depended on evolutionary conserved residues in the LegS2 catalytic domain. Interestingly, unlike the eukaryotic SPL that localizes to the endoplasmic reticulum, LegS2 was found to be targeted mainly to host cell mitochondria. Collectively, our results demonstrate the remarkable adaptations of a eukaryotic protein to the L. pneumophila pathogenesis system.