Plants can develop an enhanced defensive capacity in response to infection by arbuscular mycorrhizal fungi (AMF). This ‘mycorrhiza-induced resistance’ (MIR) provides systemic protection against a wide range of attackers and shares characteristics with systemic acquired resistance (SAR) after pathogen infection and induced systemic resistance (ISR) following root colonisation by non-pathogenic rhizobacteria. It is commonly assumed that fungal stimulation of the plant immune system is solely responsible for MIR. In this opinion article, we present a novel model of MIR that integrates different aspects of the induced resistance phenomenon. We propose that MIR is a cumulative effect of direct plant responses to mycorrhizal infection and indirect immune responses to ISR-eliciting rhizobacteria in the mycorrhizosphere.

Benzoxazinoids, such as 2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one (DIMBOA), are secondary metabolites in grasses. In addition to their function in plant defence against pests and diseases above-ground, benzoxazinoids (BXs) have also been implicated in defence below-ground, where they can exert allelochemical or antimicrobial activities. We have studied the impact of BXs on the interaction between maize and Pseudomonas putida KT2440, a competitive coloniser of the maize rhizosphere with plant-beneficial traits. Chromatographic analyses revealed that DIMBOA is the main BX compound in root exudates of maize. In vitro analysis of DIMBOA stability indicated that KT2440 tolerance of DIMBOA is based on metabolism-dependent breakdown of this BX compound. Transcriptome analysis of DIMBOA-exposed P. putida identified increased transcription of genes controlling benzoate catabolism and chemotaxis. Chemotaxis assays confirmed motility of P. putida towards DIMBOA. Moreover, colonisation essays in soil with Green Fluorescent Protein (GFP)-expressing P. putida showed that DIMBOA-producing roots of wild-type maize attract significantly higher numbers of P. putida cells than roots of the DIMBOA-deficient bx1 mutant. Our results demonstrate a central role for DIMBOA as a below-ground semiochemical for recruitment of plant-beneficial rhizobacteria during the relatively young and vulnerable growth stages of maize.

This article collates published information regarding the in vitro antibacterial activity of both metal and carbon nanoparticles. The aims are to establish a consensus regarding modes of antibacterial activity, and to evaluate the applicability of current knowledge to prediction of likely effects of nanoparticles upon important microbial processes in environmental exposures. The majority of studies suggest that nanoparticles cause disruption to bacterial membranes, probably by production of reactive oxygen species. Contact between the nanoparticle and bacterial membrane appears necessary for this activity to be manifested. Interfacial forces such as electrostatic interactions are probably important in this respect. However, the toxicity of free metal ions originating from the nanoparticles cannot be discounted. Passage of nanoparticles across intact membranes appears to be unlikely, although accumulation within the cytoplasm, probably after membrane disruption, is often observed. To date, published studies have not been designed to mimic natural systems and therefore provide poor understanding of the likely consequences of intentional or unintentional environmental release. The limited studies currently available fail to identify any significant effects at the microbial level of nanoparticles in more complex systems.

Abstract:Many water quality models use some form of the curve number (CN) equation developed by the Soil Conservation Service (SCS; U.S. Depart of Agriculture) to predict storm runoff from watersheds based on an infiltration-excess response to rainfall. However, in humid, well-vegetated areas with shallow soils, such as in the northeastern USA, the predominant runoff generating mechanism is saturation-excess on variable source areas (VSAs). We reconceptualized the SCS-CN equation for VSAs, and incorporated it into the General Watershed Loading Function (GWLF) model. The new version of GWLF, named the Variable Source Loading Function (VSLF) model, simulates the watershed runoff response to rainfall using the standard SCS-CN equation, but spatially distributes the runoff response according to a soil wetness index. We spatially validated VSLF runoff predictions and compared VSLF to GWLF for a subwatershed of the New York City Water Supply System. The spatial distribution of runoff from VSLF is more physically realistic than the estimates from GWLF. This has important consequences for water quality modeling, and for the use of models to evaluate and guide watershed management, because correctly predicting the coincidence of runoff generation and pollutant sources is critical to simulating non-point source (NPS) pollution transported by runoff.

No abstract