Transport and bacterial interactions of three bacterial strains in saturated column experiments

Fate and transport modelling for evaluating antibiotic resistance in aquatic environments: Current knowledge and research priorities

Antibiotics have revolutionised medicine in the last century and enabled the prevention of bacterial infections that were previously deemed untreatable. However, in parallel, bacteria have increasingly developed resistance to antibiotics through various mechanisms. When resistant bacteria find their way into terrestrial and aquatic environments, animal and human exposures increase, e.g., via polluted soil, food, and water, and health risks multiply. Understanding the fate and transport of antibiotic resistant bacteria (ARB) and the transfer mechanisms of antibiotic resistance genes (ARGs) in aquatic environments is critical for evaluating and mitigating the risks of resistant-induced infections. The conceptual understanding of sources and pathways of antibiotics, ARB, and ARGs from society to the water environments is essential for setting the scene and developing an appropriate framework for modelling. Various factors and processes associated with hydrology, ecology, and climate change can significantly affect the fate and transport of ARB and ARGs in natural environments. This article reviews current knowledge, research gaps, and priorities for developing water quality models to assess the fate and transport of ARB and ARGs. The paper also provides inputs on future research needs, especially the need for new predictive models to guide risk assessment on AR transmission and spread in aquatic environments.

Taxis-mediated bacterial transport and its implication for the cometabolism of pyrene in a model aquifer

One of the main problems in contaminated soils is that many toxic substances, such as PAHs, which are found in areas close to aquifers and groundwater, are difficult to access and degrade via traditional methods of remediation. The use of controlled bacterial mobility through chemotaxis has been shown to be efficient in increasing the dispersion of pollutant-degrading organisms, increasing the biodegradation rates of pollutants. In this study, using percolation columns as model aquifers, the mobilization of the Pseudomonas putida G7 strain to a distant pyrene source was demonstrated using γ-aminobutyric acid and artificial root exudates as strong chemoeffectors. An increase in the biodegradation rates of the pollutant was observed relative to columns in which the tactic effector was not added. The presence of different metabolites was detected via a fraction collector associated with an HPLC system, providing evidence for the cometabolic capacity of strain G7. The use of chemotactic organisms can be an effective approach for the remediation of polluted sediments associated with aquifers and groundwaters, offering new possibilities for the treatment of contaminated aqueous areas.

Quantification of two-site kinetic transport parameters of polystyrene nanoplastics in porous media

In this study, a combination of column experiments, interface chemistry theory and transport model with two-site kinetics was used to systematically investigate the effect of pH on the transport of polystyrene nanoparticles (PSNPs) in porous media. The porous media containing quartz sand (QS) and three kinds of clay minerals (CMs)-kaolinite (KL), illite (IL) and montmorillonite (MT), was used in column experiments to simulate the porous media in the soil-groundwater systems. Experimental results showed that the inhibitory effect of CMs on the transport of PSNPs is weakened as pH increases. The two-dimensional (2D) surface of the DLVO interaction energy (2D-pH-DLVO) was built to calculate the interactions between PSNPs and CMs under different conditions of pH. Results suggested the inflection point of PSNP-QS, PSNP-KL, PSNP-IL and PSNP-MT are 2.42, 3.30, 2.84 and 3.69, respectively. Most importantly, there was a significant correlation between the two-site kinetic parameters related to PSNPs transport and the DLVO energy barrier (DB). The contributions of the interactions of PSNPs-PSNPs and PSNPs-minerals were determined for PSNPs transport in porous media. The critical values of pH related to the migration ability of PSNPs in porous media could be determined by a combination of column experiments, 2D-pH-DLVO and PSNPs transport model. The critical values of pH were 2.95-3.01, 3.22-3.51, 2.98-3.02, 3.31-3.33 for the migration ability of PSNPs in QS, QS + KL, QS + IL and QS + MT porous media, respectively. The stronger migration ability of PSNPs under high pH conditions is attributed to the enhanced deprotonation of the media surface and increased negative surface charge, which increases the electrostatic repulsion between PSNPs and porous media (QS, CMs). Moreover, the agglomeration of PSNPs usually is weaker and the average particle size of agglomerates is smaller under the condition of high pH, thus leading to the stronger migration ability of PSNPs under high pH conditions.

Microbially induced calcium carbonate precipitation driven by ureolysis to enhance oil recovery

Microbially induced calcium carbonate precipitation was used to improve poor volumetric sweep efficiency of water and enhance oil recovery.

Dynamics of suspended and attached aerobic toluene degraders in small-scale flow-through sediment systems under growth and starvation conditions

The microbially mediated reactions, that are responsible for field-scale natural attenuation of organic pollutants, are governed by the concurrent presence of a degrading microbial community, suitable energy and carbon sources, electron acceptors, as well as nutrients. The temporal lack of one of these essential components for microbial activity, arising from transient environmental conditions, might potentially impair in situ biodegradation. This study presents results of small scale flow-through experiments aimed at ascertaining the effects of substrate-starvation periods on the aerobic degradation of toluene by Pseudomonas putida F1. During the course of the experiments, concentrations of attached and mobile bacteria, as well as toluene and oxygen were monitored. Results from a fitted reactive-transport model, along with the observed profiles, show the ability of attached cells to survive substrate-starvation periods of up to four months and suggest a highly dynamic exchange between attached and mobile cells under growth conditions and negligible cell detachment under substrate-starvation conditions. Upon reinstatement of toluene, it was readily degraded without a significant lag period, even after a starvation period of 130 days. Our experimental and modeling results strongly suggest that aerobic biodegradation of BTEX-hydrocarbons at contaminated field sites is not hampered by intermittent starvation periods of up to four months.

Bayesian process-identification in bacteria transport in porous media

A Bayesian parameter estimation approach is developed for the estimation of joint probability distribution functions for colloid and bacterial fate and transport model parameters describing breakthrough curves (BTCs) obtained through porous media column studies, and is applied to data involving different ionic strength solutions to fit models of differing complexity. Our approach focuses on the simultaneous fitting of a number of BTCs representing different conditions, and it provides a measure of the goodness of model structure, namely Deviance Information Criteria (DIC). Comparison of DIC per model fit enables the evaluation of the significance of various processes through step-wise increases in complexity due to the addition of process model components. We use the method to investigate the transport of both flagellated and non-flagellated strains of Azotobacter vinelandii in a simulated porous media under three ionic strengths. Three different model structures are considered: one without a detachment process and with Langmuirian blocking function, one with detachment, and one with detachment and a second-order blocking function based on random sequential adsorption. First, the model was applied separately to each single BTC. Next, the model was applied comprehensively to the experiments under various ionic strengths, whereas some transport parameters including dispersivity, detachment coefficient, the fraction of cells undergoing irreversible attachment, and the coefficient of the second-order blocking term were assumed to be the same under different ionic strengths. In most cases, including detachment substantially improved the DIC as expected, whereas using the second-order blocking improved DIC for most of the cases when the method was applied to separate BTCs but not when the method was applied collectively to the three BTCs obtained under various ionic strengths. Also, comparing the outcomes of the separate applications of the parameter estimation algorithm versus the collective application indicates that the uncertainty associated with the estimated parameters is substantially smaller when the collective approach is used and also that the estimated parameters are more consistent with the expectations based on the underlying physical processes.