BackgroundFungi are among the most abundant and diverse organisms on Earth. However, a substantial amount of the species diversity, relationships, habitats, and life strategies of these microorganisms remain to be discovered and characterized. One important factor hindering progress is the difficulty in correctly identifying fungi. Morphological and molecular characteristics have been applied in such tasks. Later, DNA barcoding has emerged as a new method for the rapid and reliable identification of species. The nrITS region is considered the universal barcode of Fungi, and the ITS1 and ITS2 sub-regions have been applied as metabarcoding markers. In this study, we performed a large-scale analysis of all the available Basidiomycota sequences from GenBank. We carried out a rigorous trimming of the initial dataset based in methodological principals of DNA Barcoding. Two different approaches (PCI and barcode gap) were used to determine the performance of the complete ITS region and sub-regions.ResultsFor most of the Basidiomycota genera, the three genomic markers performed similarly, i.e., when one was considered a good marker for the identification of a genus, the others were also; the same results were observed when the performance was insufficient. However, based on barcode gap analyses, we identified genomic markers that had a superior identification performance than the others and genomic markers that were not indicated for the identification of some genera. Notably, neither the complete ITS nor the sub-regions were useful in identifying 11 of the 113 Basidiomycota genera. The complex phylogenetic relationships and the presence of cryptic species in some genera are possible explanations of this limitation and are discussed.ConclusionsKnowledge regarding the efficiency and limitations of the barcode markers that are currently used for the identification of organisms is crucial because it benefits research in many areas. Our study provides information that may guide researchers in choosing the most suitable genomic markers for identifying Basidiomycota species.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-017-0958-x) contains supplementary material, which is available to authorized users.

BackgroundSchistosomiasis remains an important parasitic disease and a major economic problem in many countries. The Schistosoma mansoni genome and predicted proteome sequences were recently published providing the opportunity to identify new drug candidates. Eukaryotic protein kinases (ePKs) play a central role in mediating signal transduction through complex networks and are considered druggable targets from the medical and chemical viewpoints. Our work aimed at analyzing the S. mansoni predicted proteome in order to identify and classify all ePKs of this parasite through combined computational approaches. Functional annotation was performed mainly to yield insights into the parasite signaling processes relevant to its complex lifestyle and to select some ePKs as potential drug targets.ResultsWe have identified 252 ePKs, which corresponds to 1.9% of the S. mansoni predicted proteome, through sequence similarity searches using HMMs (Hidden Markov Models). Amino acid sequences corresponding to the conserved catalytic domain of ePKs were aligned by MAFFT and further used in distance-based phylogenetic analysis as implemented in PHYLIP. Our analysis also included the ePK homologs from six other eukaryotes. The results show that S. mansoni has proteins in all ePK groups. Most of them are clearly clustered with known ePKs in other eukaryotes according to the phylogenetic analysis. None of the ePKs are exclusively found in S. mansoni or belong to an expanded family in this parasite. Only 16 S. mansoni ePKs were experimentally studied, 12 proteins are predicted to be catalytically inactive and approximately 2% of the parasite ePKs remain unclassified. Some proteins were mentioned as good target for drug development since they have a predicted essential function for the parasite.ConclusionsOur approach has improved the functional annotation of 40% of S. mansoni ePKs through combined similarity and phylogenetic-based approaches. As we continue this work, we will highlight the biochemical and physiological adaptations of S. mansoni in response to diverse environments during the parasite development, vector interaction, and host infection.

Vector-borne flaviviruses are emerging threats to human health. For successful transmission, the virus needs to efficiently enter mosquito cells and replicate within and escape several tissue barriers while mosquitoes elicit major transcriptional responses to flavivirus infection. This process will be affected not only by the specific mosquitopathogen pairing but also by variation in key environmental variables such as temperature. Thus far, few studies have examined the molecular responses triggered by temperature and how these responses modify infection outcomes, despite substantial evidence showing strong relationships between temperature and transmission in a diversity of systems. To define the host transcriptional changes associated with temperature variation during the early infection process, we compared the transcriptome of mosquito midgut samples from mosquitoes exposed to Zika virus (ZIKV) and nonexposed mosquitoes housed at three different temperatures (20, 28, and 36 • C). While the high-temperature samples did not show significant changes from those with standard rearing conditions (28 • C) 48 h post-exposure, the transcriptome profile of mosquitoes housed at 20 • C was dramatically different. The expression of genes most altered by the cooler temperature involved aspects of blood-meal digestion, ROS metabolism, and mosquito innate immunity. Further, we did not find significant differences in the viral RNA copy number between 24 and 48 h post-exposure at 20 • C, suggesting that ZIKV replication is limited by cold-induced changes to the mosquito midgut environment. In ZIKV-exposed mosquitoes, vitellogenin, a lipid carrier protein, was most up-regulated at 20 • C. Our results provide a deeper understanding of the temperature-triggered transcriptional changes in Aedes aegypti and can be used to further define the molecular mechanisms driven by environmental temperature variation.