The role of root exuded low molecular weight organic anions in facilitating petroleum hydrocarbon degradation: current knowledge and future directions

Rhizoremediation is a bioremediation technique whereby enhanced microbial degradation of organic contaminants occurs within the plant root zone (rhizosphere). It is considered an effective and affordable ‘green technology’ for remediating soils contaminated with petroleum hydrocarbons (PHCs). This paper critically reviews the potential role of root exuded compounds in rhizoremediation, with emphasis on commonly exuded low molecular weight aliphatic organic acid anions (carboxylates). The extent to which remediation is achieved shows wide disparity among plant species. Therefore, plant selection is crucial for the advancement and widespread adoption of this technology. Root exudation is speculated to be one of the predominant factors leading to microbial changes in the rhizosphere and thus the potential driver behind enhanced petroleum biodegradation. Carboxylates can form a significant component of the root exudate mixture and are hypothesised to enhance petroleum biodegradation by: i) providing an easily degradable energy source; ii) increasing phosphorus supply; and/or iii) enhancing the contaminant bioavailability. These differing hypotheses, which are not mutually exclusive, require further investigation to progress our understanding of plant–microbe interactions with the aim to improve plant species selection and the efficacy of rhizoremediation.

Characterization of para-Nitrophenol-degrading bacterial communities in river water by using functional markers and stable isotope probing

Microbial degradation is a major determinant of the fate of pollutants in the environment. para-Nitrophenol (PNP) is an EPA listed priority pollutant with a wide environmental distribution, but little is known about the microorganisms that degrade it in the environment. We studied the diversity of active PNP-degrading bacterial populations in river water using a novel functional marker approach coupled with [13C6]PNP stable isotope probing (SIP). Culturing together with culture-independent terminal restriction fragment length polymorphism analysis of 16S rRNA gene amplicons identified Pseudomonas syringae to be the major driver of PNP degradation in river water microcosms. This was confirmed by SIP-pyrosequencing of amplified 16S rRNA. Similarly, functional gene analysis showed that degradation followed the Gram-negative bacterial pathway and involved pnpA from Pseudomonas spp. However, analysis of maleylacetate reductase (encoded by mar), an enzyme common to late stages of both Gram-negative and Gram-positive bacterial PNP degradation pathways, identified a diverse assemblage of bacteria associated with PNP degradation, suggesting that mar has limited use as a specific marker of PNP biodegradation. Both the pnpA and mar genes were detected in a PNP-degrading isolate, P. syringae AKHD2, which was isolated from river water. Our results suggest that PNP-degrading cultures of Pseudomonas spp. are representative of environmental PNP-degrading populations.

A laboratory incubation method for determining the rate of microbiological degradation of skeletal muscle tissue in soil

A controlled laboratory experiment is described, in principle and practice, which can be used for the of determination the rate of tissue decomposition in soil. By way of example, an experiment was conducted to determine the effect of temperature (12°C, 22°C) on the aerobic decomposition of skeletal muscle tissue (Organic Texel × Suffolk lamb (Ovis aries)) in a sandy loam soil. Measurements of decomposition processes included muscle tissue mass loss, microbial CO2 respiration, and muscle tissue carbon (C) and nitrogen (N). Muscle tissue mass loss at 22°C always was greater than at 12°C (p < 0.001). Microbial respiration was greater in samples incubated at 22°C for the initial 21 days of burial (p < 0.01). All buried muscle tissue samples demonstrated changes in C and N content at the end of the experiment. A significant correlation (p < 0.001) was demonstrated between the loss of muscle tissue-derived C (C1) and microbially-respired C (Cm) demonstrating CO2 respiration may be used to predict mass loss and hence biodegradation. In this experiment Q10 (12°C - 22°C) = 2.0. This method is recommended as a useful tool in determining the effect of environmental variables on the rate of decomposition of various tissues and associated materials.

Assessment and improvement of biotransfer models to cow’s milk and beef used in exposure assessment tools for organic pollutants

The aim of this study was to assess and improve the accuracy of biotransfer models for the organic pollutants (PCBs, PCDD/Fs, PBDEs, PFCAs, and pesticides) into cow’s milk and beef used in human exposure assessment. Metabolic rate in cattle is known as a key parameter for this biotransfer, however few experimental data and no simulation methods are currently available. In this research, metabolic rate was estimated using existing QSAR biodegradation models of microorganisms (BioWIN) and fish (EPI-HL and IFS-HL). This simulated metabolic rate was then incorporated into the mechanistic cattle biotransfer models (RAIDAR, ACC-HUMAN, OMEGA, and CKow). The goodness of fit tests showed that RAIDAR, ACC-HUMAN, OMEGA model performances were significantly improved using either of the QSARs when comparing the new model outputs to observed data. The CKow model is the only one that separates the processes in the gut and liver. This model showed the lowest residual error of all the models tested when the BioWIN model was used to represent the ruminant metabolic process in the gut and the two fish QSARs were used to represent the metabolic process in the liver. Our testing included EUSES and CalTOX which are KOW-regression models that are widely used in regulatory assessment. New regressions based on the simulated rate of the two metabolic processes are also proposed as an alternative to KOW-regression models for a screening risk assessment. The modified CKow model is more physiologically realistic, but has equivalent usability to existing KOW-regression models for estimating cattle biotransfer of organic pollutants.