Alignment of multiple metabolomics LC-MS datasets from disparate diseases to reveal fever-associated metabolites.

Acute febrile illnesses are still a major cause of mortality and morbidity globally, particularly in low to middle income countries. The aim of this study was to determine any possible metabolic commonalities of patients infected with disparate pathogens that cause fever. Three liquid chromatography-mass spectrometry (LC-MS) datasets investigating the metabolic effects of malaria, leishmaniasis and Zika virus infection were used. The retention time (RT) drift between the datasets was determined using landmarks obtained from the internal standards generally used in the quality control of the LC-MS experiments. Fitted Gaussian Process models (GPs) were used to perform a high level correction of the RT drift between the experiments, which was followed by standard peakset alignment between the samples with corrected RTs of the three LC-MS datasets. Statistical analysis, annotation and pathway analysis of the integrated peaksets were subsequently performed. Metabolic dysregulation patterns common across the datasets were identified, with kynurenine pathway being the most affected pathway between all three fever-associated datasets.

Climate services for health: predicting the evolution of the 2016 dengue season in Machala, Ecuador.

BACKGROUND: El Niño and its effect on local meteorological conditions potentially influences interannual variability in dengue transmission in southern coastal Ecuador. El Oro province is a key dengue surveillance site, due to the high burden of dengue, seasonal transmission, co-circulation of all four dengue serotypes, and the recent introduction of chikungunya and Zika. In this study, we used climate forecasts to predict the evolution of the 2016 dengue season in the city of Machala, following one of the strongest El Niño events on record. METHODS: We incorporated precipitation, minimum temperature, and Niño3·4 index forecasts in a Bayesian hierarchical mixed model to predict dengue incidence. The model was initiated on Jan 1, 2016, producing monthly dengue forecasts until November, 2016. We accounted for misreporting of dengue due to the introduction of chikungunya in 2015, by using active surveillance data to correct reported dengue case data from passive surveillance records. We then evaluated the forecast retrospectively with available epidemiological information. FINDINGS: The predictions correctly forecast an early peak in dengue incidence in March, 2016, with a 90% chance of exceeding the mean dengue incidence for the previous 5 years. Accounting for the proportion of chikungunya cases that had been incorrectly recorded as dengue in 2015 improved the prediction of the magnitude of dengue incidence in 2016. INTERPRETATION: This dengue prediction framework, which uses seasonal climate and El Niño forecasts, allows a prediction to be made at the start of the year for the entire dengue season. Combining active surveillance data with routine dengue reports improved not only model fit and performance, but also the accuracy of benchmark estimates based on historical seasonal averages. This study advances the state-of-the-art of climate services for the health sector, by showing the potential value of incorporating climate information in the public health decision-making process in Ecuador. FUNDING: European Union FP7, Royal Society, and National Science Foundation.

Evidence of diversification of dengue virus type 3 genotype III in the South American region.

In order to gain insight into the genetic variability of dengue virus type 3 (DENV-3) genotype III isolated in the Latin American region, phylogenetic analysis were carried out using envelope (E) gene sequences from 57 DENV-3 genotype III strains isolated in 11 Latin American countries. At least six different genotype III clades were observed. Amino acids substitutions were found in domain III E protein neutralization epitopes and in surface-exposed domain II and III E protein amino acid sequences.

Modeling gene sequence changes over time in type 3 dengue viruses from Ecuador.

Dengue virus (DENV) is a member of the genus Flavivirus of the family Flaviviridae. DENV-3 re-emerged in Central America in 1994, and continues to expand into the South American region. Little is known about the evolutionary rates, viral spread and population dynamics of this genotype in the Latin American region. In order to gain insight into these matters, we used a Bayesian Markov chain Monte Carlo (MCMC) approach, to analyze envelope (E) gene sequences of the DENV-3 genotype III of strains included in a monophyletic cluster composed by Ecuadorian as well as strains from Cuba, Puerto Rico and Peru. The results of these studies revealed that the expansion population growth model was the best fit to the data. The most common recent ancestor (MRCA) was placed around 1989, in agreement with the first reports of the emergence of this new DENV-3 type. A mean rate 1.033 x 10(-3) nucleotide substitution per site per year was obtained. This rate is comparatively higher than the ones obtained for DENV-2 and DENV-4 in the same region. Faster population growth and greater population dispersal may have contributed to the vigorous initial transmission dynamics of this genotype in the Latin American region.

Phylogenetic analysis of the NS5 gene of dengue viruses isolated in Ecuador.

Dengue virus (DENV) is a member of the genus Flavivirus of the family Flaviviridae. DENV causes a wide range of diseases in humans, from the acute febrile illness dengue fever (DF) to life-threatening dengue hemorrhagic fever/dengue shock syndrome (DHF/DSS). There is not knowledge of the genetic relations among DENV circulating in Ecuador. Given the emerging behaviour of DENV, a single tube RT-PCR assay using a pair of consensus primers to target the NS5 coding region has been recently validated for rapid detection of flaviviruses. In order to gain insight into the degree of genetic variation of DENV strains isolated in Ecuador, DENV NS5 sequences from 23 patients were obtained by direct sequencing of PCR fragments using the mentioned one step RT-PCR assay. Phylogenetic analysis carried out using the 23 Ecuadorian DENV NS5 sequences, as well as 56 comparable sequences from DENV strains isolated elsewhere, revealed a close genetic relation among Ecuadorian strains and DENV isolates of Caribbean origin. The use of partial NS5 gene sequences may represent a useful alternative for a rapid phylogenetic analysis of DENV outbreaks.