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Yellow fever is a vector-borne disease endemic in tropical regions of Africa, where 90% of the global burden occurs, and Latin America. It is notoriously under-reported with uncertainty arising from a complex transmission cycle including a sylvatic reservoir and non-specific symptom set. Resulting estimates of burden, particularly in Africa, are highly uncertain. We examine two established models of yellow fever transmission within a Bayesian model averaging framework in order to assess the relative evidence for each model’s assumptions and to highlight possible data gaps. Our models assume contrasting scenarios of the yellow fever transmission cycle in Africa. The first takes the force of infection in each province to be static across the observation period; this is synonymous with a constant infection pressure from the sylvatic reservoir. The second model assumes the majority of transmission results from the urban cycle; in this case, the force of infection is dynamic and defined through a fixed value of R0 in each province. Both models are coupled to a generalised linear model of yellow fever occurrence which uses environmental covariates to allow us to estimate transmission intensity in areas where data is sparse. We compare these contrasting descriptions of transmission through a Bayesian framework and trans-dimensional Markov chain Monte Carlo sampling in order to assess each model’s evidence given the range of uncertainty in parameter values. The resulting estimates allow us to produce Bayesian model averaged predictions of yellow fever burden across the African endemic region. We find strong support for the static force of infection model which suggests a higher proportion of yellow fever transmission occurs as a result of infection from an external source such as the sylvatic reservoir. However, the model comparison highlights key data gaps in serological surveys across the African endemic region. As such, conclusions concerning the most prevalent transmission routes for yellow fever will be limited by the sparsity of data which is particularly evident in the areas with highest predicted transmission intensity. Our model and estimation approach provides a robust framework for model comparison and predicting yellow fever burden in Africa. However, key data gaps increase uncertainty surrounding estimates of model parameters and evidence. As more mathematical models are developed to address new research questions, it is increasingly important to compare them with established modelling approaches to highlight uncertainty in structures and data., Author summary Yellow fever (YF) is notoriously under reported due to non-specific symptom spectrum and the true burden is highly uncertain as a result of a complex transmission cycle. As such, estimates surrounding YF burden are highly uncertain and the mechanisms behind transmission are often unclear. We assess these mechanisms and the resulting uncertainty by estimating two existing models of YF transmission within a product space framework. This allows us to produce updated estimates of transmission intensity and to compare the relative support for each model given the data. We find strong support for a model assuming a static force of infection, approximating the constant infection pressure from the sylvatic reservoir of YF. We also highlight areas where data is sparse, often the same areas estimated to have especially high transmission intensity. This is the first robust multi-model approach to applied YF modelling and provides a framework that could be extended to other disease models.

A thorough understanding of the heritability, genetic correlations and additive and non-additive variance components of tree growth and wood properties is a requisite for effective tree breeding. This knowledge is essential to maximize genetic gain, that is, the amount of increase in trait performance achieved annually through directional selection. Understanding the genetic attributes of traits targeted by breeding is also important to sustain decade-long genetic progress, that is, the progress made by increasing the average genetic value of the offspring as compared to that of the parental generation. In this study, we report quantitative genetic parameters for fifteen growth, wood chemical and physical traits for the world-famous Eucalyptus urograndis hybrid (E. grandis × E. urophylla). These traits directly impact the optimal use of wood for cellulose pulp, paper, and energy production. A population of 1,000 trees sampled in a progeny trial was phenotyped directly or following the development and use of near-infrared spectroscopy calibration models. Trees were genotyped with 33,398 SNPs and 24,001 DArT-seq genome-wide markers and genomic realized relationship matrices (GRM) were used for parameter estimation with an individual-tree additive-dominant mixed model. Wood chemical properties and wood density showed stronger genetic control than growth, cellulose and fiber traits. Additive effects are the main drivers of genetic variation for all traits, but dominance plays an equally or more important role for growth, singularly in this hybrid. GRM´s with >10,000 markers provided stable relationships estimates and more accurate parameters than pedigrees by capturing the full genetic relationships among individuals and disentangling the non-additive from the additive genetic component. Low correlations between growth and wood properties indicate that simultaneous selection for wood traits can be applied with minor effects on genetic gain for growth. Conversely, moderate to strong correlations between wood density and chemical traits exist, likely due to their interdependency on cell wall structure such that responses to selection will be connected for these traits. Our results illustrate the advantage of using genomewide marker data to inform tree breeding in general and have important consequences for operational breeding of eucalypt urograndis hybrids. Fil: de Lima, Bruno Marco. Universidade de Sao Paulo; Brasil. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil Fil: Cappa, Eduardo Pablo. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación de Recursos Naturales. Instituto de Recursos Biológicos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Silva Junior, Orzenil B.. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil. Universidade Católica de Brasília; Brasil Fil: Garcia, Carla. No especifíca; Fil: Mansfield, Shawn D.. University of British Columbia; Canadá Fil: Grattapaglia, Dario. Ministerio da Agricultura Pecuaria e Abastecimento de Brasil. Empresa Brasileira de Pesquisa Agropecuaria; Brasil. Universidade Católica de Brasília; Brasil

Background Leptospirosis is a worldwide zoonosis that is endemic in tropical areas, such as Reunion Island. The species Leptospira interrogans is the primary agent in human infections, but other pathogenic species, such as L. kirschner and L. borgpetersenii, are also associated with human leptospirosis. Methods and Findings In this study, a melting curve analysis of the products that were amplified with the primer pairs lfb1 F/R and G1/G2 facilitated an accurate species classification of Leptospira reference strains. Next, we combined an unsupervised high resolution melting (HRM) method with a new statistical approach using primers to amplify a two variable-number tandem-repeat (VNTR) for typing at the subspecies level. The HRM analysis, which was performed with ScreenClust Software, enabled the identification of genotypes at the serovar level with high resolution power (Hunter-Gaston index 0.984). This method was also applied to Leptospira DNA from blood samples that were obtained from Reunion Island after 1998. We were able to identify a unique genotype that is identical to that of the L. interrogans serovars Copenhageni and Icterohaemorrhagiae, suggesting that this genotype is the major cause of leptospirosis on Reunion Island. Conclusions Our simple, rapid, and robust genotyping method enables the identification of Leptospira strains at the species and subspecies levels and supports the direct genotyping of Leptospira in biological samples without requiring cultures.

Background Drug susceptible clinical isolates of Candida albicans frequently become highly tolerant to drugs during chemotherapy, with dreadful consequences to patient health. We used RNA sequencing (RNA-seq) to analyze the transcriptomes of a CDR (Candida Drug Resistance) strain and its isogenic drug sensitive counterpart. Results RNA-seq unveiled differential expression of 228 genes including a) genes previously identified as involved in CDR, b) genes not previously associated to the CDR phenotype, and c) novel transcripts whose function as a gene is uncharacterized. In particular, we show for the first time that CDR acquisition is correlated with an overexpression of the transcription factor encoding gene CZF1. CZF1 null mutants were susceptible to many drugs, independently of known multidrug resistance mechanisms. We show that CZF1 acts as a repressor of β-glucan synthesis, thus negatively regulating cell wall integrity. Finally, our RNA-seq data allowed us to identify a new transcribed region, upstream of the TAC1 gene, which encodes the major CDR transcriptional regulator. Conclusion Our results open new perspectives of the role of Czf1 and of our understanding of the transcriptional and post-transcriptional mechanisms that lead to the acquisition of drug resistance in C. albicans, with potential for future improvements of therapeutic strategies.

Phlebotomine sandflies are vectors of phleboviruses that cause sandfly fever or meningitis with significant implications for public health. Although several strains of these viruses had been isolated in Iran in the late 1970's, there was no recent data about the present situation at the outset of this study. Entomological investigations performed in 2009 and 2011 in Iran collected 4,770 sandflies from 10 different regions. Based on morphological identification, they were sorted into 315 pools according to species, sex, trapping station and date of capture. A phlebovirus, provisionally named Dashli virus (DASHV), was isolated from one pool of Sergentomyia spp, and subsequently DASHV RNA was detected in a second pool of Phlebotomus papatasi. Genetic and phylogenetic analyses based on complete coding genomic sequences indicated that (i) DASHV is most closely related to the Iranian isolates of Sandfly fever Sicilian virus [SFSV], (ii) there is a common ancestor to DASHV, Sandfly fever Sicilian- (SFS) and SFS-like viruses isolated in Italy, India, Turkey, and Cyprus (lineage I), (iii) DASHV is more distantly related with Corfou and Toros viruses (lineage II) although common ancestry is supported with 100% bootstrap, (iii) lineage I can be subdivided into sublineage Ia including all SFSV, SFCV and SFTV except those isolated in Iran which forms sublineage Ib (DASHV). Accordingly, we suggest to approve Sandfly fever Sicilian virus species consisting of the all aforementioned viruses. Owing that most of these viruses have been identified in human patients with febrile illness, DASHV should be considered as a potential human pathogen in Iran., Author summary Phlebotomine sandflies are vectors of phleboviruses that cause sandfly fever or meningitis with significant implications for public health. Although several strains of these viruses had been isolated in Iran in the late 1970's, there was no recent data about the present situation at the outset of this study. Entomological investigations performed in 2009 and 2011 in Iran collected 4,770 sandflies from 10 different regions. A phlebovirus, provisionally named Dashli virus (DASHV), was isolated / detected in two pools. DASHV strain was isolated in cell culture and complete genome sequence was determined. Sequence analysis indicated that (i) DASHV is most closely related to the Iranian isolates of Sandfly fever Sicilian virus [SFSV], a virus that is known to cause self-resolutive incapacitating febrile illness in humans, (ii) there is a common ancestor to DASHV and all other variants of SFSV isolated in Italy, India, Turkey, and Cyprus (lineage I), (iii) DASHV is more distantly related with Corfou and Toros viruses (lineage II) although common ancestry is supported with 100% bootstrap, (iii) lineage I can be subdivided into sublineage Ia including all SFSV strains, whereas Iranian viruses are most closely related and should be individualized as DASHV (sublineage Ib). Although discovered first in the 1940's, SFSV is still listed as "tentative species" by the International Committee for Taxonomy of Viruses. Based on the results described in this study, we propose to approve Sandfly fever Sicilian virus species. Owing that most of these viruses have been identified in human patients with febrile illness, DASHV should be considered as a potential human pathogen in Iran.