Prevalence of antibiotic resistance and virulence genes in the biofilms from an aquifer recharged with stormwater.

An improved understanding of the diversity and composition of microbial communities carrying antibiotic resistance genes (ARGs) and virulence genes (VGs) in aquifers recharged with stormwater is essential to comprehend potential human health risks from water reuse. A high-throughput functional gene array was used to study the prevalence of ARGs and VGs in aquifer biofilms (n = 27) taken from three boreholes over three months. Bacterial genera annotated as opportunistic pathogens such as Aeromonas, Burkholderia, Pseudomonas, Shewanella, and Vibrio were ubiquitous and abundant in all biofilms. Bacteria from clinically relevant genera, Campylobacter, Enterobacter, Klebsiella, Mycobacterium, Mycoplasma, and Salmonella were detected in biofilms. The mean travel time of stormwater from the injection well to P1 and P3 boreholes was 260 and 360 days respectively. The presence of ARGs and VGs in the biofilms from these boreholes suggest a high spatial movement of ARGs and VGs in the aquifer. The ARGs with the highest abundance were small multidrug resistance efflux pumps (SMR) and multidrug efflux (Mex) followed by ß-lactamase C genes. ß- lactamase C encoding genes were primarily detected in Enterobacteriaceae, Pseudomonadaceae, Bacillaceae, and Rhodobacteraceae families. The VGs encoding siderophores, including aerobactin (iro and iuc genes), followed by pilin, hemolysin, and type III secretion were ubiquitous. Canonical correspondence analysis suggested that Total Organic Carbon (TOC), Dissolved Organic Carbon (DOC), turbidity, and Fe concentration has a significant impact on the microbial community structure of bacteria carrying ARGs and VGs. Post abstraction treatment of groundwater may be prudent to improve water security and reduce potential health risks.

Fungal community structure in disease suppressive soils assessed by 28S LSU gene sequencing.

Natural biological suppression of soil-borne diseases is a function of the activity and composition of soil microbial communities. Soil microbe and phytopathogen interactions can occur prior to crop sowing and/or in the rhizosphere, subsequently influencing both plant growth and productivity. Research on suppressive microbial communities has concentrated on bacteria although fungi can also influence soil-borne disease. Fungi were analyzed in co-located soils 'suppressive' or 'non-suppressive' for disease caused by Rhizoctonia solani AG 8 at two sites in South Australia using 454 pyrosequencing targeting the fungal 28S LSU rRNA gene. DNA was extracted from a minimum of 125 g of soil per replicate to reduce the micro-scale community variability, and from soil samples taken at sowing and from the rhizosphere at 7 weeks to cover the peak Rhizoctonia infection period. A total of ∼ 994,000 reads were classified into 917 genera covering 54% of the RDP Fungal Classifier database, a high diversity for an alkaline, low organic matter soil. Statistical analyses and community ordinations revealed significant differences in fungal community composition between suppressive and non-suppressive soil and between soil type/location. The majority of differences associated with suppressive soils were attributed to less than 40 genera including a number of endophytic species with plant pathogen suppression potentials and mycoparasites such as Xylaria spp. Non-suppressive soils were dominated by Alternaria, Gibberella and Penicillum. Pyrosequencing generated a detailed description of fungal community structure and identified candidate taxa that may influence pathogen-plant interactions in stable disease suppression.

The effect of Penicillium fungi on plant growth and phosphorus mobilization in neutral to alkaline soils from southern Australia.

The phosphate solubilizing fungi Penicillium radicum, Penicillium bilaiae (strain RS7B-SD1), and an unidentified Penicillium sp. designated strain KC6-W2 were tested for their ability to increase the growth and phosphorus (P) nutrition of wheat, medic, and lentil in three soils of neutral to alkaline pH reaction. The strongest plant growth promoting (PGP) strain was Penicillium sp. KC6-W2, which stimulated significant increases in shoot growth and dry mass in seven of the nine experiments conducted. Levels of PGP by Penicillium sp. KC6-W2 ranged from 6.6% to 19% and were associated with increased uptake of P to the shoot. The PGP properties of Penicillium sp. KC6-W2 were evident on each of the three different plant species and soil types, a level of reliability not observed in other strains tested. Inoculation of seed with P. radicum increased lentil growth by 5.5% (P < 0.05) in soil from Tarlee but did not affect plant growth in the eight other experiments. Inoculation of plant seed with P. bilaiae RS7B-SD1 resulted in significant PGP in two of the nine experiments conducted. However, when significant, stimulation of PGP by P. bilaiae RS7B-SD1 was strong and resulted in increases in medic dry matter (19%) and lentil shoot dry matter (15%). A soil microcosm experiment investigated the effect of Penicillium fungi on cycling of soil P. Penicillium bilaiae RS7B-SD1 was the only fungus to significantly increase HCO3-extractable P (23% increase; P < 0.05). Production of phosphatase enzymes was not associated with increased HCO3-extractable P. Addition of carbon in the form of ryegrass seed significantly increased microbial respiration and movement of P to the microbial biomass (P < 0.05), but these parameters were irrespective of Penicillium treatment. This work has established the potential for use of Penicillium inoculants to increase plant growth on alkaline soils in Australia. The role of Penicillium fungi in plant P uptake and soil P cycling requires further exploration.

Identifying hazards in complex ecological systems. Part 3: Hierarchical Holographic Model for herbicide tolerant oilseed rape.

This paper is the third in a series designed to demonstrate the application of rigorous, systematic hazard identification techniques to ecological systems. Here we use Hierarchical Holographic Modelling to identify the potential ecological hazards associated with the commercial release of herbicide tolerant oilseed rape. Hierarchical Holographic Models decompose complex systems into a series of sub-systems and consider interactions between the components and processes of these sub-systems in order to identify hazards. In this example we considered 1356 potential interactions between the biological, chemical and physical components and processes of the herbicide tolerant oilseed rape environment, and identified 152 potential hazards, grouped into 14 categories. The hazards were subsequently scored for degree of concern and plausibility, and then compared with an equivalent list of hazards generated independently by a checklist approach. The incidence of herbicide tolerant volunteers (and weeds) both on and off the farm had the highest average score of all the ecological hazard categories. The checklist based approach identified or implied 44% of the hazards identified in the Hierarchical Holographic Model, including nine of the ten hazards ranked most important. The checklist approach focussed almost exclusively on the phenotypic and genotypic hazards associated with herbicide tolerant oilseed rape and largely ignored the hazards associated with the circumstances surrounding its use. As a result the checklist identified only 6 out of the 79 potential hazards associated with changes to farming practice. The commercial release of herbicide tolerant oilseed rape will be associated with changes in tillage and the application of post-emergent herbicides. It may also lead to changes in spray schedules of insecticide and fungicide. Many of the environmental hazards identified with these changes are plausible and may warrant further investigation or targeted monitoring.