Project description:Here, we report the complete genome sequence characteristics of Legionella strain TUM19329, a candidate for a novel psychrotolerant species isolated from Antarctic lake sediment. The genome assembly contains a single 3,750,805-bp contig with a G+C content of 39.1% and is predicted to encode 3,538 proteins.
Project description:Legionellae are Gram-negative bacteria which are capable of causing disease, most commonly in the form of pneumonia. We describe a case of native valve endocarditis caused by a Legionella strain which by genotypic (16S rRNA and mip gene sequencing) and phenotypic analyses is unlike previously described strains of Legionella.
Project description:Legionella tunisiensis is a gammaproteobacterium from the class Legionellaceae, growing in amoebae. We sequenced the genome from strain LegM(T). It is composed of 3,508,121 bp and contains 4,747 protein-coding genes and 38 RNA genes, including 3 rRNA genes.
Project description:BACKGROUND: Legionella pneumophila subsp. pneumophila is a gram-negative gamma-Proteobacterium and the causative agent of Legionnaires' disease, a form of epidemic pneumonia. It has a water-related life cycle. In industrialized cities L. pneumophila is commonly encountered in refrigeration towers and water pipes. Infection is always via infected aerosols to humans. Although many efforts have been made to eradicate Legionella from buildings, it still contaminates the water systems. The town of Alcoy (Valencian Region, Spain) has had recurrent outbreaks since 1999. The strain "Alcoy 2300/99" is a particularly persistent and recurrent strain that was isolated during one of the most significant outbreaks between the years 1999-2000. RESULTS: We have sequenced the genome of the particularly persistent L. pneumophila strain Alcoy 2300/99 and have compared it with four previously sequenced strains known as Philadelphia (USA), Lens (France), Paris (France) and Corby (England).Pangenome analysis facilitated the identification of strain-specific features, as well as some that are shared by two or more strains. We identified: (1) three islands related to anti-drug resistance systems; (2) a system for transport and secretion of heavy metals; (3) three systems related to DNA transfer; (4) two CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) systems, known to provide resistance against phage infections, one similar in the Lens and Alcoy strains, and another specific to the Paris strain; and (5) seven islands of phage-related proteins, five of which seem to be strain-specific and two shared. CONCLUSIONS: The dispensable genome disclosed by the pangenomic analysis seems to be a reservoir of new traits that have mainly been acquired by horizontal gene transfer and could confer evolutionary advantages over strains lacking them.
Project description:Here, we report the draft genome sequence of the Legionella pneumophila Nagoya-1 strain, serogroup 4, which was isolated from a clinical sample from a patient with legionellosis. Several virulence-associated genes, including those encoding the type IV (Dot/Icm) secretion system and effector proteins, were highly conserved.
Project description:Several members of the genus Legionella cause Legionnaires' disease, a potentially debilitating form of pneumonia. Studies frequently focus on the abundant number of virulence factors present in this genus. However, what is often overlooked is the role of secondary metabolites from Legionella. Following whole genome sequencing, we assembled and annotated the Legionella parisiensis DSM 19216 genome. Together with 14 other members of the Legionella, we performed comparative genomics and analysed the secondary metabolite potential of each strain. We found that Legionella contains a huge variety of biosynthetic gene clusters (BGCs) that are potentially making a significant number of novel natural products with undefined function. Surprisingly, only a single Sfp-like phosphopantetheinyl transferase is found in all Legionella strains analyzed that might be responsible for the activation of all carrier proteins in primary (fatty acid biosynthesis) and secondary metabolism (polyketide and non-ribosomal peptide synthesis). Using conserved active site motifs, we predict some novel compounds that are probably involved in cell-cell communication, differing to known communication systems. We identify several gene clusters, which may represent novel signaling mechanisms and demonstrate the natural product potential of Legionella.
Project description:We present the genomic sequence of the human pathogen Legionella pneumophila serogroup 12 strain 570-CO-H (ATCC 43290), a clinical isolate from the Colorado Department of Health, Denver, CO. This is the first example of a genome sequence of L. pneumophila from a serogroup other than serogroup 1. We highlight the similarities and differences relative to six genome sequences that have been reported for serogroup 1 strains.
Project description:During the summer of 2012, a major Legionella pneumophila serogroup 1 outbreak occurred in Quebec City, Canada, which caused 182 declared cases of Legionnaire's disease and included 13 fatalities. Legionella pneumophila serogroup 1 isolates from 23 patients as well as from 32 cooling towers located in the vicinity of the outbreak were recovered for analysis. In addition, 6 isolates from the 1996 Quebec City outbreak and 4 isolates from patients unrelated to both outbreaks were added to allow comparison. We characterized the isolates using pulsed-field gel electrophoresis, sequence-based typing, and whole genome sequencing. The comparison of patients-isolated strains to cooling tower isolates allowed the identification of the tower that was the source of the outbreak. Legionella pneumophila strain Quebec 2012 was identified as a ST-62 by sequence-based typing methodology. Two new Legionellaceae plasmids were found only in the epidemic strain. The LVH type IV secretion system was found in the 2012 outbreak isolates but not in the ones from the 1996 outbreak and only in half of the contemporary human isolates. The epidemic strains replicated more efficiently and were more cytotoxic to human macrophages than the environmental strains tested. At least four Icm/Dot effectors in the epidemic strains were absent in the environmental strains suggesting that some effectors could impact the intracellular replication in human macrophages. Sequence-based typing and pulsed-field gel electrophoresis combined with whole genome sequencing allowed the identification and the analysis of the causative strain including its likely environmental source.
Project description:BACKGROUND: Legionella, the causative agent for Legionnaires' disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data. METHODS: Microarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in The Netherlands in the period 2002-2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental. RESULTS: Four genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme. CONCLUSIONS: The Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.
Project description:BACKGROUND: Legionella is a water and soil bacterium that can infect humans, causing a pneumonia known as Legionnaires' disease. The pneumonia is almost exclusively caused by the species L. pneumophila, of which serogroup 1 is responsible for 90% of patients. Within serogroup 1, large differences in prevalence in clinical isolates have been described. A recent study, using a Dutch Legionella strain collection, identified five virulence associated markers. In our study, we verify whether these five Dutch markers can predict the patient or environmental origin of a French Legionella strain collection. In addition, we identify new potential virulence markers and verify whether these can predict better. A total of 219 French patient isolates and environmental strains were compared using a mixed-genome micro-array. The micro-array data were analysed to identify predictive markers, using a Random Forest algorithm combined with a logistic regression model. The sequences of the identified markers were compared with eleven known Legionella genomes, using BlastN and BlastX; the functionality for each of the predictive markers was checked in the literature. RESULTS: The five Dutch markers insufficiently predicted the patient or environmental origin of the French Legionella strains. Subsequent analyses identified four predictive markers for the French collection that were used for the logistic regression model. This model showed a negative predictive value of 91%. Three of the French markers differed from the Dutch markers, one showed considerable overlap and was found in one of the Legionella genomes (Lorraine strain). This marker encodes for a structural toxin protein RtxA, described for L. pneumophila as a factor involved in virulence and entry in both human cells and amoebae. CONCLUSIONS: The combination of a mixed-genome micro-array and statistical analysis using a Random Forest algorithm has identified virulence markers in a consistent way. The Lorraine strain and related Dutch and French Legionella strains contain a marker that encodes a RtxA protein which probably is involved in the increased prevalence in clinical isolates. The current set of predictive markers is insufficient to justify its use as a reliable test in the public health field in France. Our results suggest that genetic differences in Legionella strains exist between geographically distinct entities. It may be necessary to develop region-specific mixed-genome microarrays that are constantly adapted and updated.