Evolutionary studies on dengue virus have frequently focused on intra-serotype diversity or on specific epidemics. In this study, we compiled a comprehensive data set of the envelope gene of dengue virus serotypes and conducted an extensive comparative study of evolutionary molecular epidemiology. We found that substitution rates are homogeneous among dengue serotypes, although their population dynamics have differed over the past few years as inferred by Bayesian coalescent methods. On a global scale, DENV-2 is the serotype with the highest effective population size. The genealogies also showed geographical structure within the serotypes. Finally, we also explored the causes of dengue virus serotype diversification by investigating the plausibility that it was driven by adaptive changes. Our results suggest that the envelope gene is under significant purifying selection and the hypothesis that dengue virus serotype diversification was the result of stochastic events cannot be ruled out.

The cervical microbiota composition and diversity of HIV-positive women in the postpartum period is unknown. Using a high-throughput bacterial 16S rRNA gene sequencing, we identified four community state types (CSTs). CST III (Lactobacillusdominant) and CST IV (IV-A, IV-B.1, IV-B.2; high-diversity) were found in 41% and 59% of samples, respectively. We did not find association of any CST to postpartum period (six or twelve months), HPV infection or cytology (normal or lesion). However, five bacterial genera were associated with cervical lesions (Gardnerella, Aerococcus, Schlegelella, Moryella and Bifidobacterium), with significant odds ratio (OR) of 40 (2.28–706) for the presence of Moryella and 3.5 (1.36–8.9) for Schlegelella. Longitudinal analysis of samples at postpartum that regressed (lesion to normal), progressed (normal to lesion) and maintained the cytology (lesion or normal) evidenced Gardnerella with a significantly higher abundance in regressing lesions. In the current study, we report the first data on the cervical microbiota of HIV-positive women in the postpartum period. Consistent with previous studies of HIV-negative cohorts, HIV-positive women present a stable cervical microbiota of high-diversity in the postpartum period. Our results highlight that specific microbiota species may serve as sensors for changes in the cervical microenvironment associated with cervical lesions.

The human papillomavirus (HPV) is present in a significant fraction of head-and-neck squamous cell cancer (HNSCC). The main goal of this study was to identify distinct co-expression patterns between HPV+ and HPV− HNSCC and to provide insights into potential regulatory mechanisms/effects within the analyzed networks. We selected cases deposited in The Cancer Genome Atlas database comprising data of gene expression, methylation profiles and mutational patterns, in addition to clinical information. The intersection among differentially expressed and differentially methylated genes showed the negative correlations between the levels of methylation and expression, suggesting that these genes have their expression levels regulated by methylation alteration patterns in their promoter. Weighted correlation network analysis was used to identify co-expression modules and a systematic approach was applied to refine them and identify key regulatory elements integrating results from the other omics. Three distinct co-expression modules were associated with HPV status and molecular signatures. Validation using independent studies reporting biological experimental data converged for the most significant genes in all modules. This study provides insights into complex genetic and epigenetic particularities in the development and progression of HNSCC according to HPV status, and contribute to unveiling specific genes/pathways as novel therapeutic targets in HNSCC.

The unprecedented size of the human population, along with its associated economic activities, has an ever‐increasing impact on global environments. Across the world, countries are concerned about the growing resource consumption and the capacity of ecosystems to provide resources. To effectively conserve biodiversity, it is essential to make indicators and knowledge openly available to decision‐makers in ways that they can effectively use them. The development and deployment of tools and techniques to generate these indicators require having access to trustworthy data from biological collections, field surveys and automated sensors, molecular data, and historic academic literature. The transformation of these raw data into synthesized information that is fit for use requires going through many refinement steps. The methodologies and techniques applied to manage and analyze these data constitute an area usually called biodiversity informatics. Biodiversity data follow a life cycle consisting of planning, collection, certification, description, preservation, discovery, integration, and analysis. Researchers, whether producers or consumers of biodiversity data, will likely perform activities related to at least one of these steps. This article explores each stage of the life cycle of biodiversity data, discussing its methodologies, tools, and challenges. This article is categorized under: Algorithmic Development > Biological Data Mining

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