No abstract

BackgroundThe impacts of man-made chemicals, in particular of persistent organic pollutants, are multifactorial as they may affect the integrity of ecosystems, alter biodiversity and have undesirable effects on many organisms. We have previously demonstrated that the belowground mycobiota of forest soils acts as a buffer against the biocide pollutant pentachlorophenol. However, the trade-offs made by mycobiota to mitigate this pollutant remain cryptic.ResultsHerein, we demonstrate using a culture-dependent approach that exposure to pentachlorophenol led to alterations in the composition and functioning of the metacommunity, many of which were not fully alleviated when most of the biocide was degraded. Proteomic and physiological analyses showed that the carbon and nitrogen metabolisms were particularly affected. This dysregulation is possibly linked to the higher pathogenic potential of the metacommunity following exposure to the biocide, supported by the secretion of proteins related to pathogenicity and reduced susceptibility to a fungicide. Our findings provide additional evidence for the silent risks of environmental pollution, particularly as it may favour the development of pathogenic trade-offs in fungi, which may impose serious threats to animals and plant hosts.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0589-y) contains supplementary material, which is available to authorized users.

This paper reports results of an investigation on the degree of influence of short-term memory mechanisms on the performance of neural classifiers when applied to robot navigation tasks. In particular, we deal with the well-known strategy of navigating by "wall-following". For this purpose, four standard neural architectures (Logistic Perceptron, Multilayer Perceptron, Mixture of Experts and Elman network) are used to associate different spatiotemporal sensory input patterns with four predetermined action categories. All stages of the experiments -data acquisition, selection and training of the architectures in a simulator and their execution on a real mobile robot -are described. The obtained results suggest that the wall-following task, formulated as a pattern classification problem, is nonlinearly separable, a result that favors the MLP network if no memory of input patters are taken into account. If short-term memory mechanisms are used, then even a linear network is able to perform the same task successfully.

Cork, the outer bark of Quercus suber, shows a unique compositional structure, a set of remarkable properties, including high recalcitrance. Cork colonisation by Ascomycota remains largely overlooked. Herein, Aspergillus nidulans secretome on cork was analysed (2DE).Proteomic data were further complemented by microscopic (SEM) and spectroscopic (ATR-FTIR) evaluation of the colonised substrate and by targeted analysis of lignin degradation compounds (UPLC-HRMS). Data showed that the fungus formed an intricate network of hyphae around the cork cell walls, which enabled polysaccharides and lignin superficial degradation, but probably not of suberin. The degradation of polysaccharides was suggested by the identification of few polysaccharide degrading enzymes (β-glucosidases and endo-1,5--L-arabinosidase).Lignin degradation, which likely evolved throughout a Fenton-like mechanism relying on the activity of alcohol oxidases, was supported by the identification of small aromatic compounds (e.g. cinnamic acid and veratrylaldehyde) and of several putative high molecular weight lignin degradation products. In addition, cork recalcitrance was corroborated by the identification of several protein species which are associated with autolysis. Finally, stringent comparative proteomics revealed that A. nidulans colonisation of cork and wood share a common set of enzymatic mechanisms. However the higher polysaccharide accessibility in cork might explain the increase of β-glucosidase in cork secretome.