SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis.

BACKGROUND: Comparing the composition of microbial communities among groups of interest (e.g., patients vs healthy individuals) is a central aspect in microbiome research. It typically involves sequencing, data processing, statistical analysis and graphical display. Such an analysis is normally obtained by using a set of different applications that require specific expertise for installation, data processing and in some cases, programming skills. RESULTS: Here, we present SHAMAN, an interactive web application we developed in order to facilitate the use of (i) a bioinformatic workflow for metataxonomic analysis, (ii) a reliable statistical modelling and (iii) to provide the largest panel of interactive visualizations among the applications that are currently available. SHAMAN is specifically designed for non-expert users. A strong benefit is to use an integrated version of the different analytic steps underlying a proper metagenomic analysis. The application is freely accessible at http://shaman.pasteur.fr/ , and may also work as a standalone application with a Docker container (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman . Using two different datasets (a mock community sequencing and a published 16S rRNA metagenomic data), we illustrate the strengths of SHAMAN in quickly performing a complete metataxonomic analysis. CONCLUSIONS: With SHAMAN, we aim at providing the scientific community with a platform that simplifies reproducible quantitative analysis of metagenomic data.

Repellent, irritant and toxic effects of 20 plant extracts on adults of the malaria vector Anopheles gambiae mosquito.

Pyrethroid insecticides induce an excito-repellent effect that reduces contact between humans and mosquitoes. Insecticide use is expected to lower the risk of pathogen transmission, particularly when impregnated on long-lasting treated bednets. When applied at low doses, pyrethroids have a toxic effect, however the development of pyrethroid resistance in several mosquito species may jeopardize these beneficial effects. The need to find additional compounds, either to kill disease-carrying mosquitoes or to prevent mosquito contact with humans, therefore arises. In laboratory conditions, the effects (i.e., repellent, irritant and toxic) of 20 plant extracts, mainly essential oils, were assessed on adults of Anopheles gambiae, a primary vector of malaria. Their effects were compared to those of DEET and permethrin, used as positive controls. Most plant extracts had irritant, repellent and/or toxic effects on An. gambiae adults. The most promising extracts, i.e. those combining the three types of effects, were from Cymbopogon winterianus, Cinnamomum zeylanicum and Thymus vulgaris. The irritant, repellent and toxic effects occurred apparently independently of each other, and the behavioural response of adult An. gambiae was significantly influenced by the concentration of the plant extracts. Mechanisms underlying repellency might, therefore, differ from those underlying irritancy and toxicity. The utility of the efficient plant extracts for vector control as an alternative to pyrethroids may thus be envisaged.

Genetic signs of connectivity in Primula vulgaris (Primulaceae) in a hedgerow network landscape.

The effects of landscape configuration on the genetic connectivity of the heterostylous species Primula vulgaris Huds. (Primulaceae) were studied using AFLP markers. Isolation by distance pattern was shown by spatial autocorrelation analysis; moreover, hedgerow network distances were found to contribute less than Euclidian distances to spatial genetic structure. Pollen flow is probably the main factor shaping the spatial genetic structure rather than seed dispersal, which is limited in this myrmecochorous species. Detailed analysis on the genetic similarity between neighborhoods and differentiation rates showed that density of hedgerow networks impede gene flow. We therefore concluded that a high degree of habitat contiguity does not necessarily promote genetic connectivity.