The flagellated protozoan Giardia duodenalis is a worldwide parasite causing giardiasis, an acute and chronic diarrheal disease. Metabolism in G. duodenalis has a limited complexity thus making metabolic enzymes ideal targets for drug development. However, only few metabolic pathways (i.e., carbohydrates) have been described so far. Recently, the parasite homolog of the mitochondrial-like glycerol-3-phosphate dehydrogenase (gG3PD) has been identified among the interactors of the g14-3-3 protein. G3PD is involved in glycolysis, electron transport, glycerophospholipids metabolism, and hyperosmotic stress response, and is emerging as promising target in tumor treatment. In this work, we demonstrate that gG3PD is a functional flavoenzyme able to convert glycerol-3-phosphate into dihydroxyacetone phosphate and that its activity and the intracellular glycerol level increase during encystation. Taking advantage of co-immunoprecipitation assays and deletion mutants, we provide evidence that gG3PD and g14-3-3 interact at the trophozoite stage, the intracellular localization of gG3PD is stage dependent and it partially co-localizes with mitosomes during cyst development. Finally, we demonstrate that the gG3PD activity is affected by the antitumoral compound 6-(7-nitro-2,1,3-benzoxadiazol-4-ylthio)hexanol, that results more effective in vitro at killing G. duodenalis trophozoites than the reference drug metronidazole. Overall, our results highlight the involvement of gG3PD in processes crucial for the parasite survival thus proposing this enzyme as target for novel antigiardial interventions.

Purpose Truffles are colonized by a complex microbial community of bacteria, yeasts, and filamentous fungi, whose role has not yet been fully understood. The main purpose of the research was to characterize the bacterial communities associated with Tuber aestivum Vittad. fruiting bodies collected from natural truffle grounds in the Molise region (Southern Italy). Despite it is one of the Italian richest areas of truffles, little is known about truffles in Molise. Methods Six ripe fruiting bodies of Tuber aestivum Vittad. and six soil samples were collected in July 2018 at Villa San Michele in the municipality of Vastogirardi, Molise region. Then, soil and truffle microbial communities were analyzed through 16S rRNA gene sequencing on the Illumina MiSeq platform and bioinformatics analyses. Results Consistently with previous studies, the main phyla retrieved in the investigated ascocarps were Proteobacteria and Actinobacteria, with the genus Bradyrhizobium particularly represented. Nevertheless, significant differences between soil and truffle microbiota and an unexpected heterogeneity across truffles were observed. It is likely that a specific recruitment of bacteria from soil to ascocarps occurs during the truffle formation and that local-scale factors play an important role in determining the structure of the investigated truffle microbial communities. Conclusion Although further analyses (based on a larger soil and truffle sample size and aimed at defining in more detail microbial diversity, soil physical and chemical properties, microclimatic conditions, and vegetation) are required to better understand which are these factors and how they could influence the composition of truffle bacterial communities, this study represents the starting point for a deepened characterization of this economically important product.

Saliva of bloodsucking animals contains dozens to hundreds of proteins that counteract their hosts’ hemostasis, inflammation, and immunity. It was previously observed that salivary proteins involved in hematophagy are much more divergent in their primary sequence than those of housekeeping function, when comparisons were made between closely related organisms. While this pattern of evolution could result from relaxed selection or drift, it could alternatively be the result of positive selection driven by the intense pressure of the host immune system. We investigated the polymorphism of five different genes associated with blood feeding in the mosquito Anopheles gambiae and obtained evidence in four genes for sites with signatures of positive selection. These results add salivary gland genes from bloodsucking arthropods to the small list of genes driven by positive selection.

Membrane microdomains that include lipid rafts, are involved in key physiological and pathological processes and participate in the entry of endocellular pathogens. These assemblies, enriched in cholesterol and sphingolipids, form highly dynamic, liquid-ordered phases that can be separated from the bulk membranes thanks to their resistance to solubilization by nonionic detergents. To characterize complexity and dynamics of detergent-resistant membranes of sexual stages of the rodent malaria parasite , here we propose an integrated study of raft components based on proteomics, lipid analysis and bioinformatics. This analysis revealed unexpected heterogeneity and unexplored pathways associated with these specialized assemblies. Protein-protein relationships and protein-lipid co-occurrence were described through multi-component networks. The proposed approach can be widely applied to virtually every cell type in different contexts and perturbations, under physiological and/or pathological conditions.

Background: During the last decade, with the aim to solve the challenge of post-genomic and transcriptomic data mining, a plethora of tools have been developed to create, edit and analyze metabolic pathways. In particular, when a complex phenomenon is considered, the creation of a network of multiple interconnected pathways of interest could be useful to investigate the underlying biology and ultimately identify functional candidate genes affecting the trait under investigation. Results: PANEV (PAthway NEtwork Visualizer) is an R package set for gene/pathway-based network visualization. Based on information available on KEGG, it visualizes genes within a network of multiple levels (from 1 to n) of interconnected upstream and downstream pathways. The network graph visualization helps to interpret functional profiles of a cluster of genes. Conclusions: The suite has no species constraints and it is ready to analyze genomic or transcriptomic outcomes. Users need to supply the list of candidate genes, specify the target pathway(s) and the number of interconnected downstream and upstream pathways (levels) required for the investigation. The package is available at https:// github.com/vpalombo/PANEV.