Dataset Information

Geographical and Temporal Structures of Legionella pneumophila Sequence Types in Comunitat Valenciana (Spain), 1998 to 2013.

ABSTRACT: Legionella pneumophila is an accidental human pathogen associated with aerosol formation in water-related sources. High recombination rates make Legionella populations genetically diverse, and nearly 2,000 different sequence types (STs) have been described to date for this environmental pathogen. The spatial distribution of STs is extremely heterogeneous, with some variants being present worldwide and others being detected at only a local scale. Similarly, some STs have been associated with disease outbreaks, such as ST578 or ST23. Spain is among the European countries with the highest incidences of reported legionellosis cases, and specifically, Comunitat Valenciana (CV) is the second most affected area in the country. In this work, we aimed at studying the overall diversity of Legionella pneumophila populations found in the period from 1998 to 2013 in 79 localities encompassing 23 regions within CV. To do so, we performed sequence-based typing (SBT) on 1,088 L. pneumophila strains detected in the area from both environmental and clinical sources. A comparison with the genetic structuring detected in a global data set that included 20 European and 7 non-European countries was performed. Our results reveal a level of diversity in CV that can be considered representative of the diversity found in other countries worldwide.

SUBMITTER: Sanchez-Buso L

PROVIDER: S-EPMC4579446 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Publications

Geographical and Temporal Structures of Legionella pneumophila Sequence Types in Comunitat Valenciana (Spain), 1998 to 2013.

Sánchez-Busó Leonor L Coscollà Mireia M Palero Ferran F Camaró María Luisa ML Gimeno Ana A Moreno Pilar P Escribano Isabel I López Perezagua María Mar MM Colomina Javier J Vanaclocha Herme H González-Candelas Fernando F

Applied and environmental microbiology 20150731 20

Legionella pneumophila is an accidental human pathogen associated with aerosol formation in water-related sources. High recombination rates make Legionella populations genetically diverse, and nearly 2,000 different sequence types (STs) have been described to date for this environmental pathogen. The spatial distribution of STs is extremely heterogeneous, with some variants being present worldwide and others being detected at only a local scale. Similarly, some STs have been associated with dise ...[more]

PMID: 26231651

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Project description:Legionella pneumophila infects humans to produce legionellosis and Pontiac fever only from environmental sources. In order to establish control measures and study the sources of outbreaks it is essential to know extent and distribution of strain variants of this bacterium in the environment. Sporadic and outbreak-related cases of legionellosis have been historically frequent in the Comunidad Valenciana region (CV, Spain), with a high prevalence in its Southeastern-most part (BV). Environmental investigations for the detection of Legionella pneumophila are performed in this area routinely. We present a population genetics study of 87 L. pneumophila strains isolated in 13 different localities of the BV area irrigated from the same watershed and compare them to a dataset of 46 strains isolated in different points of the whole CV. Our goal was to compare environmental genetic variation at two different geographic scales, at county and regional levels. Genetic diversity, recombination and population structure were analyzed with Sequence-Based Typing data and three intergenic regions. The results obtained reveal a low, but detectable, level of genetic differentiation between both datasets, mainly, but not only, attributed to the occurrence of unusual variants of the neuA locus present in the BV populations. This differentiation is still detectable when the 10 loci considered are analyzed independently, despite the relatively high incidence of the most common genetic variant in this species, sequence type 1 (ST-1). However, when the genetic data are considered without their associated geographic information, four major groups could be inferred at the genetic level which did not show any correlation with sampling locations. The overall results indicate that the population structure of these environmental samples results from the joint action of a global, widespread ST-1 along with genetic differentiation at shorter geographic distances, which in this case are related to the common watershed for the BV localities.

Project description:Salmonella enterica subspecies enterica is one of the most important foodborne pathogens and the causative agent of salmonellosis, which affects both humans and animals producing numerous infections every year. The study and understanding of its epidemiology are key to monitoring and controlling these bacteria. With the development of whole-genome sequencing (WGS) technologies, surveillance based on traditional serotyping and phenotypic tests of resistance is being replaced by genomic surveillance. To introduce WGS as a routine methodology for the surveillance of food-borne Salmonella in the region, we applied this technology to analyze a set of 141 S. enterica isolates obtained from various food sources between 2010 and 2017 in the Comunitat Valenciana (Spain). For this, we performed an evaluation of the most relevant Salmonella typing methods, serotyping and sequence typing, using both traditional and in silico approaches. We extended the use of WGS to detect antimicrobial resistance determinants and predicted minimum inhibitory concentrations (MICs). Finally, to understand possible contaminant sources in this region and their relationship to antimicrobial resistance (AMR), we performed cluster detection combining single-nucleotide polymorphism (SNP) pairwise distances and phylogenetic and epidemiological data. The results of in silico serotyping with WGS data were highly congruent with those of serological analyses (98.5% concordance). Multi-locus sequence typing (MLST) profiles obtained with WGS information were also highly congruent with the sequence type (ST) assignment based on Sanger sequencing (91.9% coincidence). In silico identification of antimicrobial resistance determinants and minimum inhibitory concentrations revealed a high number of resistance genes and possible resistant isolates. A combined phylogenetic and epidemiological analysis with complete genome sequences revealed relationships among isolates indicative of possible common sources for isolates with separate sampling in time and space that had not been detected from epidemiological information. As a result, we demonstrate the usefulness of WGS and in silico methods to obtain an improved characterization of S. enterica enterica isolates, allowing better surveillance of the pathogen in food products and in potential environmental and clinical samples of related interest.

Dataset Information

Geographical and Temporal Structures of Legionella pneumophila Sequence Types in Comunitat Valenciana (Spain), 1998 to 2013.

Publications

Geographical and Temporal Structures of Legionella pneumophila Sequence Types in Comunitat Valenciana (Spain), 1998 to 2013.

Similar Datasets

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