Comparison of ARIMA and Random Forest time series models for prediction of avian influenza H5N1 outbreaks

Background

Time series models can play an important role in disease prediction. Incidence data can be used to predict the future occurrence of disease events. Developments in modeling approaches provide an opportunity to compare different time series models for predictive power.

Results

We applied ARIMA and Random Forest time series models to incidence data of outbreaks of highly pathogenic avian influenza (H5N1) in Egypt, available through the online EMPRES-I system. We found that the Random Forest model outperformed the ARIMA model in predictive ability. Furthermore, we found that the Random Forest model is effective for predicting outbreaks of H5N1 in Egypt.

Conclusions

Random Forest time series modeling provides enhanced predictive ability over existing time series models for the prediction of infectious disease outbreaks. This result, along with those showing the concordance between bird and human outbreaks (Rabinowitz et al. 2012), provides a new approach to predicting these dangerous outbreaks in bird populations based on existing, freely available data. Our analysis uncovers the time-series structure of outbreak severity for highly pathogenic avain influenza (H5N1) in Egypt.     

Genome-wide prediction of discrete traits using bayesian regressions and machine learning

Background

Genomic selection has gained much attention and the main goal is to increase the predictive accuracy and the genetic gain in livestock using dense marker information. Most methods dealing with the large p (number of covariates) small n (number of observations) problem have dealt only with continuous traits, but there are many important traits in livestock that are recorded in a discrete fashion (e.g. pregnancy outcome, disease resistance). It is necessary to evaluate alternatives to analyze discrete traits in a genome-wide prediction context.

Methods

This study shows two threshold versions of Bayesian regressions (Bayes A and Bayesian LASSO) and two machine learning algorithms (boosting and random forest) to analyze discrete traits in a genome-wide prediction context. These methods were evaluated using simulated and field data to predict yet-to-be observed records. Performances were compared based on the models'' predictive ability.

Results

The simulation showed that machine learning had some advantages over Bayesian regressions when a small number of QTL regulated the trait under pure additivity. However, differences were small and disappeared with a large number of QTL. Bayesian threshold LASSO and boosting achieved the highest accuracies, whereas Random Forest presented the highest classification performance. Random Forest was the most consistent method in detecting resistant and susceptible animals, phi correlation was up to 81% greater than Bayesian regressions. Random Forest outperformed other methods in correctly classifying resistant and susceptible animals in the two pure swine lines evaluated. Boosting and Bayes A were more accurate with crossbred data.

Conclusions

The results of this study suggest that the best method for genome-wide prediction may depend on the genetic basis of the population analyzed. All methods were less accurate at correctly classifying intermediate animals than extreme animals. Among the different alternatives proposed to analyze discrete traits, machine-learning showed some advantages over Bayesian regressions. Boosting with a pseudo Huber loss function showed high accuracy, whereas Random Forest produced more consistent results and an interesting predictive ability. Nonetheless, the best method may be case-dependent and a initial evaluation of different methods is recommended to deal with a particular problem.     

Comparative analyses of Legionella species identifies genetic features of strains causing Legionnaires’ disease

Background

The genus Legionella comprises over 60 species. However, L. pneumophila and L. longbeachae alone cause over 95% of Legionnaires’ disease. To identify the genetic bases underlying the different capacities to cause disease we sequenced and compared the genomes of L. micdadei, L. hackeliae and L. fallonii (LLAP10), which are all rarely isolated from humans.

Results

We show that these Legionella species possess different virulence capacities in amoeba and macrophages, correlating with their occurrence in humans. Our comparative analysis of 11 Legionella genomes belonging to five species reveals highly heterogeneous genome content with over 60% representing species-specific genes; these comprise a complete prophage in L. micdadei, the first ever identified in a Legionella genome. Mobile elements are abundant in Legionella genomes; many encode type IV secretion systems for conjugative transfer, pointing to their importance for adaptation of the genus. The Dot/Icm secretion system is conserved, although the core set of substrates is small, as only 24 out of over 300 described Dot/Icm effector genes are present in all Legionella species. We also identified new eukaryotic motifs including thaumatin, synaptobrevin or clathrin/coatomer adaptine like domains.

Conclusions

Legionella genomes are highly dynamic due to a large mobilome mainly comprising type IV secretion systems, while a minority of core substrates is shared among the diverse species. Eukaryotic like proteins and motifs remain a hallmark of the genus Legionella. Key factors such as proteins involved in oxygen binding, iron storage, host membrane transport and certain Dot/Icm substrates are specific features of disease-related strains.

Electronic supplementary material

The online version of this article (doi:10.1186/s13059-014-0505-0) contains supplementary material, which is available to authorized users.     

Comparative genomic analysis of clinical and environmental strains provides insight into the pathogenicity and evolution of Vibrio parahaemolyticus

Background

Vibrio parahaemolyticus is a Gram-negative halophilic bacterium. Infections with the bacterium could become systemic and can be life-threatening to immunocompromised individuals. Genome sequences of a few clinical isolates of V. parahaemolyticus are currently available, but the genome dynamics across the species and virulence potential of environmental strains on a genome-scale have not been described before.

Results

Here we present genome sequences of four V. parahaemolyticus clinical strains from stool samples of patients and five environmental strains in Hong Kong. Phylogenomics analysis based on single nucleotide polymorphisms revealed a clear distinction between the clinical and environmental isolates. A new gene cluster belonging to the biofilm associated proteins of V. parahaemolyticus was found in clincial strains. In addition, a novel small genomic island frequently found among clinical isolates was reported. A few environmental strains were found harboring virulence genes and prophage elements, indicating their virulence potential. A unique biphenyl degradation pathway was also reported. A database for V. parahaemolyticus (http://kwanlab.bio.cuhk.edu.hk/vp) was constructed here as a platform to access and analyze genome sequences and annotations of the bacterium.

Conclusions

We have performed a comparative genomics analysis of clinical and environmental strains of V. parahaemolyticus. Our analyses could facilitate understanding of the phylogenetic diversity and niche adaptation of this bacterium.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1135) contains supplementary material, which is available to authorized users.     

High Prevalence,Genetic Diversity and Intracellular Growth Ability of Legionella in Hot Spring Environments

Background

Legionella is the causative agent of Legionnaires'' disease, and hot springs are a major source of outbreaks of this disease. It is important from a public health perspective to survey hot spring environments for the presence of Legionella.

Methods

Prospective surveillance of the extent of Legionella pollution was conducted at three hot spring recreational areas in Beijing, China in 2011. Pulsed-field gel electrophoresis (PFGE) and sequence-based typing (SBT) were used to describe the genetic polymorphism of isolates. The intracellular growth ability of the isolates was determined by interacting with J774 cells and plating the dilutions onto BCYE agar plates.

Results

Overall, 51.9% of spring water samples showed Legionella-positive, and their concentrations ranged from 1 CFU/liter to 2,218 CFU/liter. The positive rates of Legionella were significantly associated with a free chlorine concentration of ≥0.2 mg/L, urea concentration of ≥0.05 mg/L, total microbial counts of ≥400 CFU/ml and total coliform of ≥3 MPN/L (p<0.01). The Legionella concentrations were significantly associated with sample temperature, pH, total microbial counts and total coliform (p<0.01). Legionella pneumophila was the most frequently isolated species (98.9%), and the isolated serogroups included serogroups 3 (25.3%), 6 (23.4%), 5 (19.2%), 1 (18.5%), 2 (10.2%), 8 (0.4%), 10 (0.8%), 9 (1.9%) and 12 (0.4%). Two hundred and twenty-eight isolates were analyzed by PFGE and 62 different patterns were obtained. Fifty-seven L. pneumophila isolates were selected for SBT analysis and divided into 35 different sequence types with 5 main clonal groups. All the 57 isolates had high intracellular growth ability.

Conclusions

Our results demonstrated high prevalence and genetic polymorphism of Legionella in springs in Beijing, China, and the SBT and intracellular growth assay results suggested that the Legionella isolates of hot spring environments were pathogenic. Improved control and prevention strategies are urgently needed.     

A feature selection method for classification within functional genomics experiments based on the proportional overlapping score

Background

Microarray technology, as well as other functional genomics experiments, allow simultaneous measurements of thousands of genes within each sample. Both the prediction accuracy and interpretability of a classifier could be enhanced by performing the classification based only on selected discriminative genes. We propose a statistical method for selecting genes based on overlapping analysis of expression data across classes. This method results in a novel measure, called proportional overlapping score (POS), of a feature’s relevance to a classification task.

Results

We apply POS, along‐with four widely used gene selection methods, to several benchmark gene expression datasets. The experimental results of classification error rates computed using the Random Forest, k Nearest Neighbor and Support Vector Machine classifiers show that POS achieves a better performance.

Conclusions

A novel gene selection method, POS, is proposed. POS analyzes the expressions overlap across classes taking into account the proportions of overlapping samples. It robustly defines a mask for each gene that allows it to minimize the effect of expression outliers. The constructed masks along‐with a novel gene score are exploited to produce the selected subset of genes.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-274) contains supplementary material, which is available to authorized users.     

Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review

Introduction

The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets.

Methods

A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples.

Results

Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system.

Conclusions

The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.     

Microsatellite Typing of Clinical and Environmental Cryptococcus neoformans var. grubii Isolates from Cuba Shows Multiple Genetic Lineages

Background

Human cryptococcal infections have been associated with bird droppings as a likely source of infection. Studies toward the local and global epidemiology of Cryptococcus spp. have been hampered by the lack of rapid, discriminatory, and exchangeable molecular typing methods.

Methodology/Principal Findings

We selected nine microsatellite markers for high-resolution fingerprinting from the genome of C. neoformans var. grubii. This panel of markers was applied to a collection of clinical (n = 122) and environmental (n = 68; from pigeon guano) C. neoformans var. grubii isolates from Cuba. All markers proved to be polymorphic. The average number of alleles per marker was 9 (range 5–51). A total of 104 genotypes could be distinguished. The discriminatory power of this panel of markers was 0.993. Multiple clusters of related genotypes could be discriminated that differed in only one or two microsatellite markers. These clusters were assigned as microsatellite complexes. The majority of environmental isolates (>70%) fell into 1 microsatellite complex containing only few clinical isolates (49 environmental versus 2 clinical). Clinical isolates were segregated over multiple microsatellite complexes.

Conclusions/Significance

A large genotypic variation exists in C. neoformans var. grubii. The genotypic segregation between clinical and environmental isolates from pigeon guano suggests additional source(s) of human cryptococcal infections. The selected panel of microsatellite markers is an excellent tool to study the epidemiology of C. neoformans var. grubii.     

Whole genome characterization of the mechanisms of daptomycin resistance in clinical and laboratory derived isolates of Staphylococcus aureus

Background

Daptomycin remains one of our last-line anti-staphylococcal agents. This study aims to characterize the genetic evolution to daptomycin resistance in S. aureus.

Methods

Whole genome sequencing was performed on a unique collection of isogenic, clinical (21 strains) and laboratory (12 strains) derived strains that had been exposed to daptomycin and developed daptomycin-nonsusceptibility. Electron microscopy (EM) and lipid membrane studies were performed on selected isolates.

Results

On average, six coding region mutations were observed across the genome in the clinical daptomycin exposed strains, whereas only two mutations on average were seen in the laboratory exposed pairs. All daptomycin-nonsusceptible strains had a mutation in a phospholipid biosynthesis gene. This included mutations in the previously described mprF gene, but also in other phospholipid biosynthesis genes, including cardiolipin synthase (cls2) and CDP-diacylglycerol-glycerol-3-phosphate 3-phosphatidyltransferase (pgsA). EM and lipid membrane composition analyses on two clinical pairs showed that the daptomycin-nonsusceptible strains had a thicker cell wall and an increase in membrane lysyl-phosphatidylglycerol.

Conclusion

Point mutations in genes coding for membrane phospholipids are associated with the development of reduced susceptibility to daptomycin in S. aureus. Mutations in cls2 and pgsA appear to be new genetic mechanisms affecting daptomycin susceptibility in S. aureus.     

Neurocognitive and Clinical Predictors of Long-Term Outcome in Adolescents at Ultra-High Risk for Psychosis: A 6-Year Follow-Up

Background

Most studies aiming to predict transition to psychosis for individuals at ultra-high risk (UHR) have focused on either neurocognitive or clinical variables and have made little effort to combine the two. Furthermore, most have focused on a dichotomous measure of transition to psychosis rather than a continuous measure of functional outcome. We aimed to investigate the relative value of neurocognitive and clinical variables for predicting both transition to psychosis and functional outcome.

Methods

Forty-three UHR individuals and 47 controls completed an extensive clinical and neurocognitive assessment at baseline and participated in long-term follow-up approximately six years later. UHR adolescents who had converted to psychosis (UHR-P; n = 10) were compared to individuals who had not (UHR-NP; n = 33) and controls on clinical and neurocognitive variables. Regression analyses were performed to determine which baseline measures best predicted transition to psychosis and long-term functional outcome for UHR individuals.

Results

Low IQ was the single neurocognitive parameter that discriminated UHR-P individuals from UHR-NP individuals and controls. The severity of attenuated positive symptoms was the only significant predictor of a transition to psychosis and disorganized symptoms were highly predictive of functional outcome.

Conclusions

Clinical measures are currently the most important vulnerability markers for long-term outcome in adolescents at imminent risk of psychosis.     

Exercise-based cardiac rehabilitation in patients with chronic heart failure: a Dutch practice guideline

Rationale

To improve the quality of exercise-based cardiac rehabilitation (CR) in patients with chronic heart failure (CHF) a practice guideline from the Dutch Royal Society for Physiotherapy (KNGF) has been developed.

Guideline development

A systematic literature search was performed to formulate conclusions on the efficacy of exercise-based intervention during all CR phases in patients with CHF. Evidence was graded (1–4) according the Dutch evidence-based guideline development criteria.

Clinical and research recommendations

Recommendations for exercise-based CR were formulated covering the following topics: mobilisation and treatment of pulmonary symptoms (if necessary) during the clinical phase, aerobic exercise, strength training (inspiratory muscle training and peripheral muscle training) and relaxation therapy during the outpatient CR phase, and adoption and monitoring training after outpatient CR.

Applicability and implementation issues

This guideline provides the physiotherapist with an evidence-based instrument to assist in clinical decision-making regarding patients with CHF. The implementation of the guideline in clinical practice needs further evaluation.

Conclusion

This guideline outlines best practice standards for physiotherapists concerning exercise-based CR in CHF patients. Research is needed on strategies to improve monitoring and follow-up of the maintenance of a physical active lifestyle after supervised CR.     

Endemic Acinetobacter baumannii in a New York hospital

Background

Acinetobacter baumannii is an increasingly multidrug-resistant (MDR) cause of hospital-acquired infections, often associated with limited therapeutic options. We investigated A. baumannii isolates at a New York hospital to characterize genetic relatedness.

Methods

Thirty A. baumannii isolates from geographically-dispersed nursing units within the hospital were studied. Isolate relatedness was assessed by repetitive sequence polymerase chain reaction (rep-PCR). The presence and characteristics of integrons were assessed by PCR. Metabolomic profiles of a subset of a prevalent strain isolates and sporadic isolates were characterized and compared.

Results

We detected a hospital-wide group of closely related carbapenem resistant MDR A. baumannii isolates. Compared with sporadic isolates, the prevalent strain isolates were more likely to be MDR (p = 0.001). Isolates from the prevalent strain carried a novel Class I integron sequence. Metabolomic profiles of selected prevalent strain isolates and sporadic isolates were similar.

Conclusion

The A. baumannii population at our hospital represents a prevalent strain of related MDR isolates that contain a novel integron cassette. Prevalent strain and sporadic isolates did not segregate by metabolomic profiles. Further study of environmental, host, and bacterial factors associated with the persistence of prevalent endemic A. baumannii strains is needed to develop effective prevention strategies.     

Clinical potential of DNA methylation in gastric cancer: a meta-analysis

Background

Accumulating evidence indicates aberrant DNA methylation is involved in gastric tumourigenesis, suggesting it may be a useful clinical biomarker for the disease. The aim of this study was to consolidate and summarize published data on the potential of methylation in gastric cancer (GC) risk prediction, prognostication and prediction of treatment response.

Methods

Relevant studies were identified from PubMed using a systematic search approach. Results were summarized by meta-analysis. Mantel-Haenszel odds ratios were computed for each methylation event assuming the random-effects model.

Results

A review of 589 retrieved publications identified 415 relevant articles, including 143 case-control studies on gene methylation of 142 individual genes in GC clinical samples. A total of 77 genes were significantly differentially methylated between tumour and normal gastric tissue from GC subjects, of which data on 62 was derived from single studies. Methylation of 15, 4 and 7 genes in normal gastric tissue, plasma and serum respectively was significantly different in frequency between GC and non-cancer subjects. A prognostic significance was reported for 18 genes and predictive significance was reported for p16 methylation, although many inconsistent findings were also observed. No bias due to assay, use of fixed tissue or CpG sites analysed was detected, however a slight bias towards publication of positive findings was observed.

Conclusions

DNA methylation is a promising biomarker for GC risk prediction and prognostication. Further focused validation of candidate methylation markers in independent cohorts is required to develop its clinical potential.     

Helicobacter pylori from Gastric Cancer and Duodenal Ulcer Show Same Phylogeographic Origin in the Andean Region in Colombia

Background

A recent report has shown that the phylogenetic origin of Helicobacter pylori based on multi-locus sequence typing (MLST) was significantly associated with the severity of gastritis in Colombia. However, the potential relationship between phylogenetic origin and clinical outcomes was not examined in that study. If the phylogenetic origin rather than virulence factors were truly associated with clinical outcomes, identifying a population at high risk for gastric cancer in Colombia would be relatively straightforward. In this study, we examined the phylogenetic origins of strains from gastric cancer and duodenal ulcer patients living in Bogota, Colombia.

Methods

We included 35 gastric cancer patients and 31 duodenal ulcer patients, which are considered the variant outcomes. The genotypes of cagA and vacA were determined by polymerase chain reaction. The genealogy of these Colombian strains was analyzed by MLST. Bacterial population structure was analyzed using STRUCTURE software.

Results

H. pylori strains from gastric cancer and duodenal ulcer patients were scattered in the phylogenetic tree; thus, we did not detect any difference in phylogenetic distribution between gastric cancer and duodenal ulcer strains in the hpEurope group in Colombia. Sixty-six strains, with one exception, were classified as hpEurope irrespective of the cagA and vacA genotypes, and type of disease. STRUCTURE analysis revealed that Colombian hpEurope strains have a phylogenetic connection to Spanish strains.

Conclusions

Our study showed that a phylogeographic origin determined by MLST was insufficient for distinguishing between gastric cancer and duodenal ulcer risk among hpEurope strains in the Andean region in Colombia. Our analysis also suggests that hpEurope strains in Colombia were primarily introduced by Spanish immigrants.     

Bioactivity Guided Fractionation of Leaves Extract of Nyctanthes arbor tristis (Harshringar) against P falciparum

Background

Nyctanthes arbor-tristis (Harshringar, Night Jasmine) has been traditionally used in Ayurveda, Unani and other systems of medicine in India. The juice of its leaves has been used by various tribal populations of India in treatment of fevers resembling malaria.

Aim of the study

This work reports the antiplasmodial activity guided fractionation of Harshringar leaves extract.

Methodology

Crude ethanolic Harshringar leaves extract and its RPHPLC purified fractions were studied for antiplasmodial potency against 3D7 (CQ sensitive) and Dd2 (CQ resistant) strains of P.falciparum and subsequently subjected to bioassay guided fractionation using reverse phase chromatography to pursue the isolation of active fractions.

Principal Findings

Harshringar crude leaves extract and some of its RPHPLC purified fractions exhibited promising antiplasmodial potency against 3D7 and Dd2 strains of P.falciparum.

Conclusions

The present study has provided scientific validity to the traditional use of leaves extract of Harshringar against malaria leading to the conclusion that this plant holds promise with respect to antimalarial phytotherapy. This is the first scientific report of antiplasmodial activity of RPHPLC fractions of Harshringar leaves extract against P.falciparum strains.     

Virulence related sequences; insights provided by comparative genomics of Streptococcus uberis of differing virulence

Background

Streptococcus uberis, a Gram-positive, catalase-negative member of the family Streptococcaceae is an important environmental pathogen responsible for a significant proportion of subclinical and clinical bovine intramammary infections. Currently, the genome of only a single reference strain (0140J) has been described. Here we present a comparative analysis of complete draft genome sequences of an additional twelve S. uberis strains.

Results

Pan and core genome analysis revealed the core genome common to all strains to be 1,550 genes in 1,509 orthologous clusters, complemented by 115-246 accessory genes present in one or more S. uberis strains but absent in the reference strain 0140J. Most of the previously predicted virulent genes were present in the core genome of all 13 strains but gene gain/loss was observed between the isolates in CDS associated with clustered regularly interspaced short palindromic repeats (CRISPRs), prophage and bacteriocin production. Experimental challenge experiments confirmed strain EF20 as non-virulent; only able to infect in a transient manner that did not result in clinical mastitis. Comparison of the genome sequence of EF20 with the validated virulent strain 0140J identified genes associated with virulence, however these did not relate clearly with clinical/non-clinical status of infection.

Conclusion

The gain/loss of mobile genetic elements such as CRISPRs and prophage are a potential driving force for evolutionary change. This first “whole-genome” comparison of strains isolated from clinical vs non-clinical intramammary infections including the type virulent vs non-virulent strains did not identify simple gene gain/loss rules that readily explain, or be confidently associated with, differences in virulence. This suggests that a more complex dynamic determines infection potential and clinical outcome not simply gene content.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1512-6) contains supplementary material, which is available to authorized users.     

SNaPAfu: A Novel Single Nucleotide Polymorphism Multiplex Assay for Aspergillus fumigatus Direct Detection,Identification and Genotyping in Clinical Specimens

Objective

Early diagnosis of invasive aspergillosis is essential for positive patient outcome. Likewise genotyping of fungal isolates is desirable for outbreak control in clinical setting. We designed a molecular assay that combines detection, identification, and genotyping of Aspergillus fumigatus in a single reaction.

Methods

To this aim we combined 20 markers in a multiplex reaction and the results were seen following mini-sequencing readings. Pure culture extracts were firstly tested. Thereafter, Aspergillus-DNA samples obtained from clinical specimens of patients with possible, probable, or proven aspergillosis according to European Organization for the Research and Treatment of Cancer/Mycoses Study Group (EORTC/MSG) criteria.

Results

A new set of designed primers allowed multilocus sequence typing (MLST) gene amplification in a single multiplex reaction. The newly proposed SNaPAfu assay had a specificity of 100%, a sensitivity of 89% and detection limit of 1 ITS copy/mL (∼0.5 fg genomic Aspergillus-DNA/mL). The marker A49_F was detected in 89% of clinical samples. The SNaPAfu assay was accurately performed on clinical specimens using only 1% of DNA extract (total volume 50 µL) from 1 mL of used bronchoalveolar lavage.

Conclusions

The first highly sensitive and specific, time- and cost-economic multiplex assay was implemented that allows detection, identification, and genotyping of A. fumigatus strains in a single amplification followed by mini-sequencing reaction. The new test is suitable to clinical routine and will improve patient management.     

Isolation and Characterization of New Leptospira Genotypes from Patients in Mayotte (Indian Ocean)

Background

Leptospirosis has been implicated as a severe and fatal form of disease in Mayotte, a French-administrated territory located in the Comoros archipelago (southwestern Indian Ocean). To date, Leptospira isolates have never been isolated in this endemic region.

Methods and Findings

Leptospires were isolated from blood samples from 22 patients with febrile illness during a 17-month period after a PCR-based screening test was positive. Strains were typed using hyper-immune antisera raised against the major Leptospira serogroups: 20 of 22 clinical isolates were assigned to serogroup Mini; the other two strains belonged to serogroups Grippotyphosa and Pyrogenes, respectively. These isolates were further characterized using partial sequencing of 16S rRNA and ligB gene, Multi Locus VNTR Analysis (MLVA), and pulsed field gel electrophoresis (PFGE). Of the 22 isolates, 14 were L. borgpetersenii strains, 7 L. kirschneri strains, and 1, belonging to serogoup Pyrogenes, was L. interrogans. Results of the genotyping methods were consistent. MLVA defined five genotypes, whereas PFGE allowed the recognition of additional subgroups within the genotypes. PFGE fingerprint patterns of clinical strains did not match any of the patterns in the reference strains belonging to the same serogroup, suggesting that the strains were novel serovars.

Conclusions

Preliminary PCR screening of blood specimen allowed a high isolation frequency of leptospires among patients with febrile illness. Typing of leptospiral isolates showed that causative agents of leptospirosis in Mayotte have unique molecular features.