Genomic evolution of ST228 SCCmec-I MRSA 10 years after a major nosocomial outbreak.

In this study, we investigated the genomic changes in a major methicillin-resistant Staphylococcus aureus (MRSA) clone following a significant outbreak at a hospital. Whole-genome sequencing of MRSA isolates was utilized to explore the genomic evolution of post-outbreak MRSA strains. The epidemicity of the clone declined over time, coinciding with the introduction of multimodal infection control measures. A genome-wide association study (GWAS) identified multiple genes significantly associated with either high or low epidemic success, indicating alterations in mobilome, virulence, and defense mechanisms. Random Forest models pinpointed a gene related to fibrinogen binding as the most influential predictor of epidemicity. The decline of the MRSA clone may be attributed to various factors, including the implementation of new infection control measures, single nucleotide polymorphisms accumulation, and the genetic drift of a given clone. This research underscores the complex dynamics of MRSA clones, emphasizing the multifactorial nature of their evolution. The decline in epidemicity seems linked to alterations in the clone's genetic profile, with a probable shift towards decreased virulence and adaptation to long-term carriage. Understanding the genomic basis for the decline of epidemic clones is crucial to develop effective strategies for their surveillance and management, as well as to gain insights into the evolutionary dynamics of pathogen genomes.

Temporal changes in fecal microbiota of patients infected with COVID-19: a longitudinal cohort.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a multifaceted disease potentially responsible for various clinical manifestations including gastro-intestinal symptoms. Several evidences suggest that the intestine is a critical site of immune cell development, gut microbiota could therefore play a key role in lung immune response. We designed a monocentric longitudinal observational study to describe the gut microbiota profile in COVID-19 patients and compare it to a pre-existing cohort of ventilated non-COVID-19 patients. METHODS: From March to December 2020, we included patients admitted for COVID-19 in medicine (43 not ventilated) or intensive care unit (ICU) (14 ventilated) with a positive SARS-CoV-2 RT-PCR assay in a respiratory tract sample. 16S metagenomics was performed on rectal swabs from these 57 COVID-19 patients, 35 with one and 22 with multiple stool collections. Nineteen non-COVID-19 ICU controls were also enrolled, among which 14 developed ventilator-associated pneumonia (pneumonia group) and five remained without infection (control group). SARS-CoV-2 viral loads in fecal samples were measured by qPCR. RESULTS: Although similar at inclusion, Shannon alpha diversity appeared significantly lower in COVID-19 and pneumonia groups than in the control group at day 7. Furthermore, the microbiota composition became distinct between COVID-19 and non-COVID-19 groups. The fecal microbiota of COVID-19 patients was characterized by increased Bacteroides and the pneumonia group by Prevotella. In a distance-based redundancy analysis, only COVID-19 presented significant effects on the microbiota composition. Moreover, patients in ICU harbored increased Campylobacter and decreased butyrate-producing bacteria, such as Lachnospiraceae, Roseburia and Faecalibacterium as compared to patients in medicine. Both the stay in ICU and patient were significant factors affecting the microbiota composition. SARS-CoV-2 viral loads were higher in ICU than in non-ICU patients. CONCLUSIONS: Overall, we identified distinct characteristics of the gut microbiota in COVID-19 patients compared to control groups. COVID-19 patients were primarily characterized by increased Bacteroides and decreased Prevotella. Moreover, disease severity showed a negative correlation with butyrate-producing bacteria. These features could offer valuable insights into potential targets for modulating the host response through the microbiota and contribute to a better understanding of the disease's pathophysiology. TRIAL REGISTRATION: CER-VD 2020-00755 (05.05.2020) & 2017-01820 (08.06.2018).

AB569, a nontoxic chemical tandem that kills major human pathogenic bacteria.

Antibiotic-resistant superbug bacteria represent a global health problem with no imminent solutions. Here we demonstrate that the combination (termed AB569) of acidified nitrite (A-NO2-) and Na2-EDTA (disodium ethylenediaminetetraacetic acid) inhibited all Gram-negative and Gram-positive bacteria tested. AB569 was also efficacious at killing the model organism Pseudomonas aeruginosa in biofilms and in a murine chronic lung infection model. AB569 was not toxic to human cell lines at bactericidal concentrations using a basic viability assay. RNA-Seq analyses upon treatment of P. aeruginosa with AB569 revealed a catastrophic loss of the ability to support core pathways encompassing DNA, RNA, protein, ATP biosynthesis, and iron metabolism. Electrochemical analyses elucidated that AB569 produced more stable SNO proteins, potentially explaining one mechanism of bacterial killing. Our data implicate that AB569 is a safe and effective means to kill pathogenic bacteria, suggesting that simple strategies could be applied with highly advantageous therapeutic/toxicity index ratios to pathogens associated with a myriad of periepithelial infections and related disease scenarios.

Antibody response and intra-host viral evolution after plasma therapy in COVID-19 patients pre-exposed or not to B-cell-depleting agents.

Administration of plasma therapy may contribute to viral control and survival of COVID-19 patients receiving B-cell-depleting agents that impair humoral immunity. However, little is known on the impact of anti-CD20 pre-exposition on the kinetics of SARS-CoV-2-specific antibodies. Here, we evaluated the relationship between anti-spike immunoglobulin G (IgG) kinetics and the clinical status or intra-host viral evolution after plasma therapy in 36 eligible hospitalized COVID-19 patients, pre-exposed or not to B-cell-depleting treatments. The majority of anti-CD20 pre-exposed patients (14/17) showed progressive declines of anti-spike IgG titres following plasma therapy, contrasting with the 4/19 patients who had not received B-cell-depleting agents (p = 0.0006). Patients with antibody decay also depicted prolonged clinical symptoms according to the World Health Organization (WHO) severity classification (p = 0.0267) and SARS-CoV-2 viral loads (p = 0.0032) before complete virus clearance. Moreover, they had higher mutation rates than patients able to mount an endogenous humoral response (p = 0.015), including three patients with one to four spike mutations, potentially associated with immune escape. No relevant differences were observed between patients treated with plasma from convalescent and/or mRNA-vaccinated donors. Our study emphasizes the need for an individualized clinical care and follow-up in the management of COVID-19 patients with B-cell lymphopenia.

External Quality Assessment of SARS-CoV-2 Sequencing: an ESGMD-SSM Pilot Trial across 15 European Laboratories.

This first pilot trial on external quality assessment (EQA) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whole-genome sequencing, initiated by the European Society of Clinical Microbiology and Infectious Diseases (ESCMID) Study Group for Genomic and Molecular Diagnostics (ESGMD) and the Swiss Society for Microbiology (SSM), aims to build a framework between laboratories in order to improve pathogen surveillance sequencing. Ten samples with various viral loads were sent out to 15 clinical laboratories that had free choice of sequencing methods and bioinformatic analyses. The key aspects on which the individual centers were compared were the identification of (i) single nucleotide polymorphisms (SNPs) and indels, (ii) Pango lineages, and (iii) clusters between samples. The participating laboratories used a wide array of methods and analysis pipelines. Most were able to generate whole genomes for all samples. Genomes were sequenced to various depths (up to a 100-fold difference across centers). There was a very good consensus regarding the majority of reporting criteria, but there were a few discrepancies in lineage and cluster assignments. Additionally, there were inconsistencies in variant calling. The main reasons for discrepancies were missing data, bioinformatic choices, and interpretation of data. The pilot EQA was overall a success. It was able to show the high quality of participating laboratories and provide valuable feedback in cases where problems occurred, thereby improving the sequencing setup of laboratories. A larger follow-up EQA should, however, improve on defining the variables and format of the report. Additionally, contamination and/or minority variants should be a further aspect of assessment.

Building up a clinical microbiota profiling: a quality framework proposal.

Extensive characterization of the human microbiota has revealed promising relationships between microbial composition and health or disease, generating interest in biomarkers derived from microbiota profiling. However, microbiota complexity and technical challenges strongly influencing the results limit the generalization of microbiota profiling and question its clinical utility. In addition, no quality management scheme has been adapted to the specificities of microbiota profiling, notably due to the heterogeneity in methods and results. In this review, we discuss possible adaptation of classical quality management tools routinely used in diagnostic laboratories to microbiota profiling and propose a specific framework. Multiple quality controls are needed to cover all steps, from sampling to data processing. Standard operating procedures, primarily developed for wet lab analyses, must be adapted to the use of bioinformatic tools. Finally, requirements for test validation and proficiency testing must take into account expected discrepancies in results due to the heterogeneity of the processes. The proposed quality management framework should support the implementation of routine microbiota profiling by clinical laboratories to support patient care. Furthermore, its use in research laboratories would improve publication reproducibility as well as transferability of methods and results to routine practice.

ChlamDB: a comparative genomics database of the phylum Chlamydiae and other members of the Planctomycetes-Verrucomicrobiae-Chlamydiae superphylum.

ChlamDB is a comparative genomics database containing 277 genomes covering the entire Chlamydiae phylum as well as their closest relatives belonging to the Planctomycetes-Verrucomicrobiae-Chlamydiae (PVC) superphylum. Genomes can be compared, analyzed and retrieved using accessions numbers of the most widely used databases including COG, KEGG ortholog, KEGG pathway, KEGG module, Pfam and InterPro. Gene annotations from multiple databases including UniProt (curated and automated protein annotations), KEGG (annotation of pathways), COG (orthology), TCDB (transporters), STRING (protein-protein interactions) and InterPro (domains and signatures) can be accessed in a comprehensive overview page. Candidate effectors of the Type III secretion system (T3SS) were identified using four in silico methods. The identification of orthologs among all PVC genomes allows users to perform large-scale comparative analyses and to identify orthologs of any protein in all genomes integrated in the database. Phylogenetic relationships of PVC proteins and their closest homologs in RefSeq, comparison of transmembrane domains and Pfam domains, conservation of gene neighborhood and taxonomic profiles can be visualized using dynamically generated graphs, available for download. As a central resource for researchers working on chlamydia, chlamydia-related bacteria, verrucomicrobia and planctomyces, ChlamDB facilitates the access to comprehensive annotations, integrates multiple tools for comparative genomic analyses and is freely available at https://chlamdb.ch/. Database URL: https://chlamdb.ch/.

Assessment of SARS-CoV-2 Genome Sequencing: Quality Criteria and Low-Frequency Variants.

Although many laboratories worldwide have developed their sequencing capacities in response to the need for SARS-CoV-2 genome-based surveillance of variants, only a few reported some quality criteria to ensure sequence quality before lineage assignment and submission to public databases. Hence, we aimed here to provide simple quality control criteria for SARS-CoV-2 sequencing to prevent erroneous interpretation of low-quality or contaminated data. We retrospectively investigated 647 SARS-CoV-2 genomes obtained over 10 tiled amplicons sequencing runs. We extracted 26 potentially relevant metrics covering the entire workflow from sample selection to bioinformatics analysis. Based on data distribution, critical values were established for 11 selected metrics to prompt further quality investigations for problematic samples, in particular those with a low viral RNA quantity. Low-frequency variants (<70% of supporting reads) can result from PCR amplification errors, sample cross contaminations, or presence of distinct SARS-CoV2 genomes in the sample sequenced. The number and the prevalence of low-frequency variants can be used as a robust quality criterion to identify possible sequencing errors or contaminations. Overall, we propose 11 metrics with fixed cutoff values as a simple tool to evaluate the quality of SARS-CoV-2 genomes, among which are cycle thresholds, mean depth, proportion of genome covered at least 10×, and the number of low-frequency variants combined with mutation prevalence data.

Microbial genomic island discovery, visualization and analysis.

Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.

Improved genomic island predictions with IslandPath-DIMOB.

Motivation: Genomic islands (GIs) are clusters of genes of probable horizontal origin that play a major role in bacterial and archaeal genome evolution and microbial adaptability. They are of high medical and industrial interest, due to their enrichment in virulence factors, some antimicrobial resistance genes and adaptive metabolic pathways. The development of more sensitive but precise prediction tools, using either sequence composition-based methods or comparative genomics, is needed as large-scale analyses of microbial genomes increase. Results: IslandPath-DIMOB, a leading GI prediction tool in the IslandViewer webserver, has now been significantly improved by modifying both the decision algorithm to determine sequence composition biases, and the underlying database of HMM profiles for associated mobility genes. The accuracy of IslandPath-DIMOB and other major software has been assessed using a reference GI dataset predicted by comparative genomics, plus a manually curated dataset from literature review. Compared to the previous version (v0.2.0), this IslandPath-DIMOB v1.0.0 achieves 11.7% and 5.3% increase in recall and precision, respectively. IslandPath-DIMOB has the highest Matthews correlation coefficient among individual prediction methods tested, combining one of the highest recall measures (46.9%) at high precision (87.4%). The only method with higher recall had notably lower precision (55.1%). This new IslandPath-DIMOB v1.0.0 will facilitate more accurate studies of GIs, including their key roles in microbial adaptability of medical, environmental and industrial interest. Availability and implementation: IslandPath-DIMOB v1.0.0 is freely available through the IslandViewer webserver {{http://www.pathogenomics.sfu.ca/islandviewer/}} and as standalone software {{https://github.com/brinkmanlab/islandpath/}} under the GNU-GPLv3. Supplementary information: Supplementary data are available at Bioinformatics online.

Phylogenomics reveal that Mycobacterium kansasii subtypes are species-level lineages. Description of Mycobacterium pseudokansasii sp. nov., Mycobacterium innocens sp. nov. and Mycobacterium attenuatum sp. nov.

Among the species Mycobacterium kansasii, seven subtypes have been previously reported based on the PCR and the restriction fragment length polymorphism of the gene hsp65. Here, we used whole-genome sequencing to refine M. kansasii taxonomy and correct multiple inconsistencies. Average nucleotide identity (ANI) values between M. kansasii subtypes ranged from 88.4 to 94.2 %, lower than the accepted 95-96 % cut-off for species delineation. In addition, Mycobacterium gastri was closer to the M. kansasii subtypes 1, 2, 3, 4 and 5 than M. kansasii subtype 6. The recently described species Mycobacterium persicum shared 99.77 % ANI with M. kansasii subtype 2. Consistent with the ANI results, the digital DNA-DNA hybridization value was below the 70 % threshold for species delineation between subtypes and above it within subtypes as well as between subtype 2 and M. persicum. Furthermore, core-genome phylogeny confirmed the current M. kansasii species to be polyphyletic. Hence, we propose (i) Mycobacterium pseudokansasii sp. nov., replacing subtype 3, with the type strain MK142T(=CCUG 72128T=DSM 107152T), (ii) Mycobacterium innocens sp. nov., replacing subtype 5, with the type strain MK13T (=CCUG 72126T=DSM 107161T), and (iii) Mycobacterium attenuatum sp. nov., replacing subtype 6, with the type strain MK41T(=CCUG 72127T=DSM 107153T). Subtype 4 represents a new species-level lineage based on the genomic data but no strain was available. No genome sequence or strain was available for subtype 7. The proposed nomenclature will facilitate the identification of the most pathogenic subtype 1 as M. kansasii by clinicians while the new species names suggest the attenuated pathogenicity of the other subtypes.

IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets.

IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.

EDGAR 2.0: an enhanced software platform for comparative gene content analyses.

The rapidly increasing availability of microbial genome sequences has led to a growing demand for bioinformatics software tools that support the functional analysis based on the comparison of closely related genomes. By utilizing comparative approaches on gene level it is possible to gain insights into the core genes which represent the set of shared features for a set of organisms under study. Vice versa singleton genes can be identified to elucidate the specific properties of an individual genome. Since initial publication, the EDGAR platform has become one of the most established software tools in the field of comparative genomics. Over the last years, the software has been continuously improved and a large number of new analysis features have been added. For the new version, EDGAR 2.0, the gene orthology estimation approach was newly designed and completely re-implemented. Among other new features, EDGAR 2.0 provides extended phylogenetic analysis features like AAI (Average Amino Acid Identity) and ANI (Average Nucleotide Identity) matrices, genome set size statistics and modernized visualizations like interactive synteny plots or Venn diagrams. Thereby, the software supports a quick and user-friendly survey of evolutionary relationships between microbial genomes and simplifies the process of obtaining new biological insights into their differential gene content. All features are offered to the scientific community via a web-based and therefore platform-independent user interface, which allows easy browsing of precomputed datasets. The web server is accessible at http://edgar.computational.bio.

Cedratvirus lausannensis - digging into Pithoviridae diversity.

Amoeba-infecting viruses have raised scientists' interest due to their novel particle morphologies, their large genome size and their genomic content challenging previously established dogma. We report here the discovery and the characterization of Cedratvirus lausannensis, a novel member of the Megavirales, with a 0.75-1 µm long amphora-shaped particle closed by two striped plugs. Among numerous host cell types tested, the virus replicates only in Acanthamoeba castellanii leading to host cell lysis within 24 h. C. lausannensis was resistant to ethanol, hydrogen peroxide and heating treatments. Like 30 000-year-old Pithovirus sibericum, C. lausannensis enters by phagocytosis, releases its genetic content by fusion of the internal membrane with the inclusion membrane and replicates in intracytoplasmic viral factories. The genome encodes 643 proteins that confirmed the grouping of C. lausannensis with Cedratvirus A11 as phylogenetically distant members of the family Pithoviridae. The 575,161 bp AT-rich genome is essentially devoid of the numerous repeats harbored by Pithovirus, suggesting that these non-coding repetitions might be due to a selfish element rather than particular characteristics of the Pithoviridae family. The discovery of C. lausannensis confirms the contemporary worldwide distribution of Pithoviridae members and the characterization of its genome paves the way to better understand their evolution.

Bifidobacterium longum bacteremia in preterm infants receiving probiotics.

Administration of probiotics to premature newborns has been shown to prevent necrotizing enterocolitis and reduce all-cause mortality. In our hospital, we documented 2 cases of Bifidobacterium longum subspecies infantis bacteremia in newborns receiving probiotics. By comparative genomics, we confirmed that the strains isolated from each patient originated from the probiotics.

Comparative genome analysis of Pseudomonas knackmussii†B13, the first bacterium known to degrade chloroaromatic compounds.

Pseudomonas knackmussii B13 was the first strain to be isolated in 1974 that could degrade chlorinated aromatic hydrocarbons. This discovery was the prologue for subsequent characterization of numerous bacterial metabolic pathways, for genetic and biochemical studies, and which spurred ideas for pollutant bioremediation. In this study, we determined the complete genome sequence of B13 using next generation sequencing technologies and optical mapping. Genome annotation indicated that B13 has a variety of metabolic pathways for degrading monoaromatic hydrocarbons including chlorobenzoate, aminophenol, anthranilate and hydroxyquinol, but not polyaromatic compounds. Comparative genome analysis revealed that B13 is closest to Pseudomonas denitrificans and Pseudomonas aeruginosa. The B13 genome contains at least eight genomic islands [prophages and integrative conjugative elements (ICEs)], which were absent in closely related pseudomonads. We confirm that two ICEs are identical copies of the 103 kb self-transmissible element ICEclc that carries the genes for chlorocatechol metabolism. Comparison of ICEclc showed that it is composed of a variable and a 'core' region, which is very conserved among proteobacterial genomes, suggesting a widely distributed family of so far uncharacterized ICE. Resequencing of two spontaneous B13 mutants revealed a number of single nucleotide substitutions, as well as excision of a large 220 kb region and a prophage that drastically change the host metabolic capacity and survivability.

Taxogenomics of the order Chlamydiales.

Bacterial classification is a long-standing problem for taxonomists and species definition itself is constantly debated among specialists. The classification of strict intracellular bacteria such as members of the order Chlamydiales mainly relies on DNA- or protein-based phylogenetic reconstructions because these organisms exhibit few phenotypic differences and are difficult to culture. The availability of full genome sequences allows the comparison of the performance of conserved protein sequences to reconstruct Chlamydiales phylogeny. This approach permits the identification of markers that maximize the phylogenetic signal and the robustness of the inferred tree. In this study, a set of 424 core proteins was identified and concatenated to reconstruct a reference species tree. Although individual protein trees present variable topologies, we detected only few cases of incongruence with the reference species tree, which were due to horizontal gene transfers. Detailed analysis of the phylogenetic information of individual protein sequences (i) showed that phylogenies based on single randomly chosen core proteins are not reliable and (ii) led to the identification of twenty taxonomically highly reliable proteins, allowing the reconstruction of a robust tree close to the reference species tree. We recommend using these protein sequences to precisely classify newly discovered isolates at the family, genus and species levels.

Comparative genomics of koala, cattle and sheep strains of Chlamydia pecorum.

BACKGROUND: Chlamydia pecorum is an important pathogen of domesticated livestock including sheep, cattle and pigs. This pathogen is also a key factor in the decline of the koala in Australia. We sequenced the genomes of three koala C. pecorum strains, isolated from the urogenital tracts and conjunctiva of diseased koalas. The genome of the C. pecorum VR629 (IPA) strain, isolated from a sheep with polyarthritis, was also sequenced. RESULTS: Comparisons of the draft C. pecorum genomes against the complete genomes of livestock C. pecorum isolates revealed that these strains have a conserved gene content and order, sharing a nucleotide sequence similarity > 98%. Single nucleotide polymorphisms (SNPs) appear to be key factors in understanding the adaptive process. Two regions of the chromosome were found to be accumulating a large number of SNPs within the koala strains. These regions include the Chlamydia plasticity zone, which contains two cytotoxin genes (toxA and toxB), and a 77 kbp region that codes for putative type III effector proteins. In one koala strain (MC/MarsBar), the toxB gene was truncated by a premature stop codon but is full-length in IPTaLE and DBDeUG. Another five pseudogenes were also identified, two unique to the urogenital strains C. pecorum MC/MarsBar and C. pecorum DBDeUG, respectively, while three were unique to the koala C. pecorum conjunctival isolate IPTaLE. An examination of the distribution of these pseudogenes in C. pecorum strains from a variety of koala populations, alongside a number of sheep and cattle C. pecorum positive samples from Australian livestock, confirmed the presence of four predicted pseudogenes in koala C. pecorum clinical samples. Consistent with our genomics analyses, none of these pseudogenes were observed in the livestock C. pecorum samples examined. Interestingly, three SNPs resulting in pseudogenes identified in the IPTaLE isolate were not found in any other C. pecorum strain analysed, raising questions over the origin of these point mutations. CONCLUSIONS: The genomic data revealed that variation between C. pecorum strains were mainly due to the accumulation of SNPs, some of which cause gene inactivation. The identification of these genetic differences will provide the basis for further studies to understand the biology and evolution of this important animal pathogen.