Influence of pH on the adsorption-desorption of doxycycline, enrofloxacin, and sulfamethoxypyridazine in soils with variable surface charge

Characterization of antibiotic resistance development of E. coli in synthetic and real wastewater

Antimicrobial resistance (AMR) is a major threat to global health and resistant bacterial populations have been observed to develop and spread in and around wastewater. However, in vitro studies on AMR development are typically conducted in ideal media conditions which can differ in composition and nutrient density from wastewater. In this study, we compare the growth and AMR development of E. coli in standard LB broth to a synthetic wastewater recipe and autoclaved wastewater samples from the Massachusetts Water Resources Authority (MWRA). We found that synthetic wastewater and real wastewater samples both supported less bacterial growth compared to LB. Additionally, bacteria grown in synthetic wastewater and real wastewater samples had differing susceptibility to antibiotic pressure from Doxycycline, Ciprofloxacin, and Streptomycin. However, AMR development over time during continuous passaging under subinhibitory antibiotic pressure was similar in fold change across all media types. Thus, we find that while LB can act as a proxy for wastewater for AMR studies in E. coli, synthetic wastewater is a more accurate predictor of both E.coli growth and antibiotic resistance development. Moreover, we also show that antibiotic resistance can develop in real wastewater samples and components within wastewater likely have synergistic and antagonistic interactions with antibiotics.

Adsorption/desorption of enrofloxacin in farmland soil as the effect of pH and coexisting ions: implications for enrofloxacin fate and risk in loess soil

Fluoroquinolone antibiotics have been extensively used in clinical treatments for human and animal diseases. However, their long-term presence in the environment increases the risk of producing resistance genes and creates a potential threat to ecosystems and the health of humans and animals. Batch equilibrium experiments were utilized to investigate the adsorption and retention behavior and mechanism of the quinolone antibiotic enrofloxacin (ENR) in farmland soil in North China. The adsorption and desorption kinetics of ENR in soil were best fitted by pseudo-second-order model (R2 > 0.999). Both the adsorption and desorption processes of ENR in soil reached equilibrium in 1 h. The desorption amounts of ENR were significantly lower than the adsorption amounts, with the hysteresis coefficient (HI) being less than 0.7. The adsorption thermodynamic process of ENR followed the Linear and Freundlich models (0.965 < R2 < 0.985). Hydrophobic distribution and heterogeneous multimolecular layer adsorption were identified as critical factors in the adsorption process. The adsorption amount of ENR gradually decreased with increasing temperature and the initial concentration of ENR. The adsorption rate of ENR was above 80%, while the desorption rate remained below 15%, indicating strong retention ability. The adsorption rate of ENR in soil decreased with increasing pH, the adsorption rate reached 98.3% at pH 3.0 but only 31.5% at pH 11. The influence of coexisting ions on adsorption primarily depended on their properties, such as ion radius, ionic strength, and hydrolysis properties, and the inhibition of adsorption increased with increasing ionic strength. These findings contribute to understanding the fate and risk of veterinary antibiotics in loess soil in North China.

Assessment of Global Antibiotic Exposure Risk for Crops: Incorporating Soil Adsorption via Machine Learning

The overuse and misuse of antibiotics could significantly increase their accumulation in soils. Consequently, antibiotics possibly enter food chain through crop uptake, posing a threat to global food security. Assessing the exposure risks of antibiotics for crops is crucial for addressing this global issue. In this study, we assessed global antibiotic exposure risk for crops, incorporating a machine learning adsorption model based on 4893 data sets from nine antibiotics. The optimized machine learning adsorption model, using the eXtreme Gradient Boosting algorithm and the class-specific modeling strategy, demonstrated relatively good performance. Notably, we introduced unsaturated soil conditions and considered spatiotemporal variations in soil moisture and temperature for the first time in such a risk assessment. Global distributions of antibiotic exposure risk for crops were predicted for March, June, September, and December. The results indicate that soil moisture significantly influences the exposure risk assessment. Relatively high exposure risk for crops was observed during months with colder local temperatures: generally June for the Southern Hemisphere and December for the Northern Hemisphere. The resulting map highlights high-risk agricultural regions, including southern Canada, western Russia, and southern Australia.

Assessing sorption of fluoroquinolone antibiotics in soils from a Kd compilation based on pure organic and mineral components

The presence of fluoroquinolone (FQ) antibiotics in soils may cause a threat to human health due to overexposure and the generation of antibiotic resistance genes. Understanding their sorption behavior in soils is important to predict subsequent FQ (bio) availability. Here, FQ sorption in pure soil organic (i.e., humic substances) and mineral (i.e., metal oxides; phyllosilicates) components is evaluated through a solid-liquid distribution coefficient (Kd (FQ)) dataset consisting of 243 entries originated from 80 different studies, to elucidate their respective contribution to the overall Kd (FQ) in bulk soils. First, different factors affecting FQ sorption and desorption in each of these soil phases are critically discussed. The strong role of pH in Kd (FQ), due to the simultaneous effect on both FQ speciation and surface charge changes, encouraged the derivation of normalized sorption coefficients for the cationic, zwitterionic and anionic FQ species in humic substances and in different phyllosilicates. Kd (FQ) in metal oxides revealed a key role of metal nature and material specific surface area due to complexation sorption mechanisms at neutral pH. Cumulative distribution functions (CDF) were applied to each dataset to establish a sorption affinity range for each phase and to derive best estimate Kd (FQ) values for those materials where normalized sorption coefficients to FQ species were unavailable. The data analysis conducted in the different soil phases set the basis for a Kd (FQ) prediction model, which combined the respective sorption affinity of each phase for FQ and phase abundance in soil to estimate Kd (FQ) in bulk soils. The model was subsequently validated with sorption data in well characterized soils compiled from the literature.

A review on carbon-based biowaste and organic polymer materials for sustainable treatment of sulfonamides from pharmaceutical wastewater

Frequent detection of sulfonamides (SAs) pharmaceuticals in wastewater has necessitated the discovery of suitable technology for their sustainable remediation. Adsorption has been widely investigated due to its effectiveness, simplicity, and availability of various adsorbent materials from natural and artificial sources. This review highlighted the potentials of carbon-based adsorbents derived from agricultural wastes such as lignocellulose, biochar, activated carbon, carbon nanotubes graphene materials as well as organic polymers such as chitosan, molecularly imprinted polymers, metal, and covalent frameworks for SAs removal from wastewater. The promising features of these materials including higher porosity, rich carbon-content, robustness, good stability as well as ease of modification have been emphasized. Thus, the materials have demonstrated excellent performance towards the SAs removal, attributed to their porous nature that provided sufficient active sites for the adsorption of SAs molecules. The modification of physico-chemical features of the materials have been discussed as efficient means for enhancing their adsorption and reusable performance. The article also proposed various interactive mechanisms for the SAs adsorption. Lastly, the prospects and challenges have been highlighted to expand the knowledge gap on the application of the materials for the sustainable removal of the SAs.

Clarithromycin as soil and environmental pollutant: Adsorption-desorption processes and influence of pH

Antibiotics pollution is a growing environmental issue, as high amounts of these compounds are found in soil, water and sediments. This work studies the adsorption/desorption of the macrolide antibiotic clarithromycin (CLA) for 17 agricultural soils with different edaphic characteristics. The research was carried out using batch-type experiments, with an additional assessment of the specific influence of pH for 6 of the soils. The results show that CLA adsorption reaches between 26 and 95%. In addition, the fit of the experimental data to adsorption models provided values between 1.9 and 19.7 Ln μmol1-n kg-1 for the KF, Freundlich affinity coefficient, and between 2.5 and 10.5 L kg-1 for Kd, distribution constant of Linear model. Regarding the linearity index, n, it varied between 0.56 and 1.34. Desorption showed lower scores than adsorption, with an average of 20%, and with values of 3.1 and 93.0 Ln μmol1-n kg-1 for KF(des) and 4.4 and 95.0 L kg-1 for Kd(des). The edaphic characteristics with the highest influence on adsorption were the silt fraction content and the exchangeable Ca content, while in the case of desorption, they were the total nitrogen, organic carbon, and exchangeable Ca and Mg contents. Regarding the pH, within the range studied (between 3 and 10), its value did not decisively affect the adsorption/desorption process. Overall, the set of these results could be of help to program appropriate measures leading to the retention/elimination of this antibiotic when it reaches the environment as a pollutant.

Adsorption kinetics studies of ciprofloxacin in soils derived from volcanic materials by electrochemical approaches and assessment of socio-economic impact on human health

The use of antibiotics in the livestock sector has resulted in the entry of these drugs into the soil matrix through the disposal of manure as an organic amendment. To define the fate of these drugs, it is necessary to evaluate kinetic aspects regarding transport in the soil-solution. The aim of this paper is to evaluate the adsorption kinetic parameters of Ciprofloxacin (CIPRO) in Ultisol and Andisol soil which allows obtaining main kinetic parameters (pseudo-first and pseudo-second order models) and to establish the solute transport mechanism by applying kinetic models such as the Elovich equation, Intraparticle diffusion (IPD) and, the Two-site non-equilibrium models (TSNE). The adsorption kinetics of this fluoroquinolone (FQ), on both soils derived from volcanic ashes, is developed using electrochemical techniques for their determination. The experimental amount of CIPRO adsorbed over time (Qt) data best fit with the pseudo-second order kinetic models; R² = 0.9855, Ɛ = 10.17% and R² = 0.9959, Ɛ = 10.77% for Ultisol and Andisol, respectively; and where CIPRO adsorption was considered time dependent for both soils but the lower adsorption capacity in Ultisol; with 17.6 ± 2.8 μmol g^-1; which could mean a greater risk in environmental. Subsequently, applying models to describe solute transport mechanisms showed differences in the CIPRO adsorption extent for the fast and slow phases. Adsorption isotherms were evaluated, where Ultisol occurs on heterogenous sites as multilayers and Andisol by monolayer with similar Q_max. Finally, the socio-economic impact of antibiotic usage is presented, giving the importance of antibiotics in the livestock sector and their effects on human health.

New Models for Estimating the Sorption of Sulfonamide and Tetracycline Antibiotics in Soils

Sulfonamides (SAs) and tetracyclines (TCs) are two classes of widely used antibiotics. There is a lack of easy models for estimating the parameters of antibiotic sorption in soils. In this work, a dataset of affinity coefficients (Kf and Kd) of seven SA/TC antibiotics (i.e., sulfachlorpyridazine, sulfamethazine, sulfadiazine, sulfamethoxazole, oxytetracycline, tetracycline, and chlortetracycline) and associated soil properties was generated. Correlation analysis of these data showed that the affinity coefficients of the SAs were predominantly affected by soil organic matter and cation exchange capacity, while those of the TCs were largely affected by soil organic matter and pH. Pedotransfer functions for estimating Kf and Kd were built by multiple linear regression analysis and were satisfactorily validated. Their performances would be better for soils having higher organic matter content and lower pH. These pedotransfer functions can be used to aid environmental risk assessment, prioritization of antibiotics and identification of vulnerable soils.