Factors influencing the persistence of enteropathogenic bacteria in wetland habitats and implications for water quality.

Aims: To better understand the persistence dynamics of enteropathogenic bacteria in freshwater wetland habitats, we constructed lab-scale mesocosms planted with two different wetland plant species using a subsurface flow wetland design. Mesocosms were treated with either a high-quality or a poor-quality water source to examine the effects of water quality exposure and plant species on Escherichia coli, Salmonella spp. and Enterococcus spp.

Contrasting Water Quality Treatments Result in Structural and Functional Changes to Wetland Plant-Associated Microbial Communities in Lab-Scale Mesocosms.

The impact of contrasting water quality treatments on wetland plant-associated microbial communities was investigated in this study using 12 lab-scale wetland mesocosms (subsurface flow design) planted with reed canary grass (Phalaris arundinacea) or water speedwell (Veronica anagallis-aquatica) over a 13-week period. Mesocosms received water collected from two sites along the Grand River (Ontario, Canada) designated as having either high or poor water quality according to Grand River Conservation Authority classifications. All mesocosms were established using sediment collected from the high water quality site and received water from this source pre-treatment.

E151 (sym15), a pleiotropic mutant of pea (Pisum sativum L.), displays low nodule number, enhanced mycorrhizae, delayed lateral root emergence, and high root cytokinin levels.

In legumes, the formation of rhizobial and mycorrhizal root symbioses is a highly regulated process which requires close communication between plant and microorganism. Plant mutants that have difficulties establishing symbioses are valuable tools for unravelling the mechanisms by which these symbioses are formed and regulated. Here E151, a mutant of Pisum sativum cv.

Standardized mapping of nodulation patterns in legume roots.

Optimizing nodulation in legumes is a target for crop improvement, and the spatial control of nodulation is just beginning to be unravelled. However, there is currently no method for standard phenotyping of nodulation patterns. Here we present a method and software for the quantitative analysis of nodulation phenotypes.