Biodegradation Half-lives Research Articles

Fe(III)-Aided Novosphingobium sp. ES2-1 Regulates Molecular Mechanisms of 17β-Estradiol Biodegradation.

17β-estradiol (E2) is one of the strongest environmental estrogens threatening wildlife and human health globally. Microbial degradation is an alternative strategy to remediate E2-contaminated sites and may be regulated by ubiquitous Fe(III) in eco-environments. We have previously obtained a high-efficiency E2 degrader, Novosphingobium sp. ES2-1, and investigated its metabolic pathway in connection with monooxygenase EstO1-induced ring-B opening; however, the molecular mechanisms of ring-A cleavage in E2 are sorely lacking, especially under Fe(III)-aided regulation. Here, an extradiol dioxygenase EstN1 from strain ES2-1 involved in the ring-A cleavage of E2 was reported. It catalyzed the 4,5-seco reaction of 4-hydroxyestrone (4-OH-E1, a key E2-oxidized intermediate) with the support of the electron transport chain consisting of ferredoxin EstN2 and ferredoxin reductase EstN3, resulting in a ring-A meta-cleaved product. Interestingly, Fe(III)-assisted strain ES2-1 consolidated the opening of rings A and B in E2 by reinforcing the expression of estO1 and estN1 genes, consequently enhancing E2 metabolism. Compared to Fe(III) starvation, the biodegradation half-life of E2 was sharply reduced from 1.35 to 0.59 d after Fe(III) supplementation. Simultaneously, the transcription of estO1 and estN1 genes increased clearly from 4.3 to 47.5 times and 6.6 to 246.8 times after Fe(III) induction, respectively, accompanied by remarkable improvement in the abundance of ring-A/B cleavage products and their pyridine derivatives. These findings highlight the significance of Fe(III) in regulating the microbial remediation of environmental estrogens at the molecular level.

Prioritization of monitoring compounds from SNTS identified organic micropollutants in contaminated groundwater using a machine learning optimized ToxPi model

Advanced suspect and non-target screening (SNTS) approach can identify a large number of potential hazardous micropollutants in groundwater, underscoring the need for pinpointing priority pollutants among detected chemicals. This present study therefore demonstrates a novel multi-criteria decision making (MCDM) framework utilizing machine learning (ML) algorithms coupled with toxicological prioritization index tool (i.e., ml_ToxPi) to rank 251 chemicals of interest in groundwater for subsequent targeted analysis. The MCDM framework integrated chemical analysis data (i.e., peak area and detection frequency), toxicity profiles (i.e., bioactivity ratio, human exposure metadata, and carcinogenicity metadata), as well as the environmental fate and transport information (i.e., octanol-water partition coefficient (log Kow), water solubility, biodegradation half-life, and soil adsorption coefficient (Koc)) for ranking the identified pollutants, and the random forest machine learning model was useful for systematically determining the weighting factors of each variable according to their variable importance scores (R2 = 0.808 and 0.778 for training and testing datasets, respectively, while RMSE = 0.042 in both cases). A total of 47 unique high priority compounds (i.e., ml_ToxPi score ≥ 0.55) were identified across the investigated sampling regions, which constituted diverse groups of compounds classified according to their chemical uses, such as alkylated polycyclic aromatic hydrocarbons (alkyl-PAHs), organophosphate flame retardants (OPFRs), parent PAHs, personal care products (PCPs), pesticides, pharmaceuticals, phenols, plasticizers, transformation product (TPs), and other industrial use chemicals. By incorporating relevant variables into the proposed ML-optimized ToxPi MCDM framework, the prioritization approach described here may be adopted in future SNTS assessment of environmental and biological media.

Enhanced indigenous bacteria-mediated bioremediation of aged petroleum-contaminated soil by Fenton pretreatment: Synergistic effect of soil environmental improvement and microbial community response

Due to the harsh soil environment and low microbial activity, the efficacy of indigenous bacteria-mediated bioremediation is often limited in aged petroleum-contaminated soils. In this study, Fenton pretreatment (H2O2: 200 ∼ 600 mmol/kg, H2O2: Fe2+ = 100: 1) was applied to improve the aged soil environment and rebuild the microbial community to enhance subsequent bioremediation. After pretreated by 400 mmol/kg H2O2 and 4 mmol/kg Fe2+ (T2), the removal efficiency of total petroleum hydrocarbons (TPHs) was elevated to 93.27 %, equivalent to 1.96-fold of the natural attenuation (CK). Additionally, the half-life of biodegradation was shorted to 45.57 d, representing a decrease to 0.29-fold that of CK. Correlation analysis revealed a radar plot comprising five indicators, including bacterial quantification (BQ), dehydrogenase (DHA), polyphenol oxidase (PPO), permeability coefficient (K), and bulk density coefficient (γ), all of which exhibited positive correlations with TPHs degradation. Compared to CK, Fenton pretreatment increased the richness and evenness of the microbial community during incubation, thus facilitating TPHs biodegradation. Moreover, Fenton pretreatment accelerated the shift of the dominant genus in T2 from Pseudomonas (0.599) to Pseudomonas (0.258), Nocardioides (0.109), Dietzia (0.157), and Stenotrophomonas (0.120) throughout the incubation. Based on the analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG), the metabolism and enzymatic functional genes related to the biodegradation of petroleum hydrocarbons in T2 were enhanced during incubation, accounting for the high removal efficiency of TPHs. These findings demonstrated that moderate Fenton pretreatment was an effective approach to stimulate indigenous bacteria for the enhanced biodegradation of aged petroleum-contaminated soil.

Bioremediation of crude oil polluted surface water using specialised alginate-based nanocomposite beads loaded with hydrocarbon-degrading bacteria and inorganic nutrients

This study explored the elimination of petroleum from river water using matrix-bound composites of iron oxide nanoparticles (IONPs) decorated on biochar with immobilized hydrocarbon-degrading bacteria (HCB) and monoammonium phosphate (MAP) at 10%v/v pollution levels. The beads containing biochar and IONPs (BCNP) showed better pollutant removal than those with biochar alone (BC). The treatment with beads containing biochar, IONPs, HCB and MAP had the highest removal efficiency for TPH (98.5%) and PAH (93.7%) and the lowest biodegradation half-lives. The removal efficiency for TPH and PAH was greater in the treatment microcosms than in the controls with significant differences (p ≤ 0.05) between the two groups. TPH and PAH elimination levels differed significantly (p ≤ 0.05) between systems with the BC bead and those with the BCNP beads. The study revealed a steady increase in the abundance of the total cultivable heterotrophic bacteria and cultivable hydrocarbon utilizing bacteria in the treatment microcosms after an initial decline, with strong negative correlation between bacterial abundance and TPH and PAH concentrations based on r values (0.5 − 1.0) and shared variances obtained. Bacillus, Pseudomonas and Klebsiella pneumoniae dominated as the drivers of the bioremediation process while organic acids and esters (25.0%) and ketones (14.3%) were the main biodegradation metabolite groups.

Meta-Analysis and Machine Learning Models for Anaerobic Biodegradation Rates of Organic Contaminants in Sediments and Sludge.

Anaerobic biodegradation rates (half-lives) of organic chemicals are pivotal for environmental risk assessment and remediation. Traditional experimental evaluation, constrained by prolonged, oxygen-free conditions, struggles to keep pace with emerging contaminants. Data-driven machine learning (ML) models serve as promising complements. However, reported quantitative structure-biodegradation relationships or ML models on anaerobic biodegradation are mostly based on small data sets (<100 records) and neglect experimental conditions, usually achieving compromised predictions. This work aimed to develop ML models for predicting the biodegradation half-lives of organic pollutants in anaerobic environments (i.e., sediment/soil and sludge). Focusing on important features of both chemicals and experimental conditions, we first curated two data sets, one for sediment/soil (SED) and the other for sludge (SLD), covering 978 records for 206 chemicals from the literature, and then conducted a meta-analysis. Next, we built a binary classification (half-life of 30 days as the cutoff) model with an accuracy of 81% and a regression model with R2 of 0.56 for SED based on LightGBM (80% and 0.31 for SLD based on Extra tree, respectively). The model interpretations underscored the significance of experimental conditions (e.g., temperature and inoculum dosage), as evidenced by their high feature importance, and the models were found to correctly capture the effects of chemical substructures, for example, branched structures and aromatic rings prolonged half-lives while methyl group and ortho-substitution on rings shortened half-lives. The applicability domains of the models were also defined, resulting in reasonable prediction for the half-lives of 41% (SED) or 67% (SLD) of over 4000 persistent, bioaccumulative, and toxic chemicals. Overall, this study pioneers ML models for predicting the anaerobic degradation half-lives, offering valuable support for future evaluation and implementation of chemical anaerobic biodegradation.

English

The degradation capacity of Xanthomonas campestris on crude oil, petrol, diesel and kerosene and the effect of monoammonium phosphate (MAP) addition on biodegradation efficiency were investigated in this study. X. campestris was identified using 16S rRNA sequencing while the concentration of the test compounds was determined via gas chromatography. Higher cell densities and viable bacterial counts were obtained in the presence of MAP. No significant differences (p≤0.05) were seen in counts between the two MAP application concentrations of 150 mg L-1 and 250 mg L-1. Statistically significant differences (p≤0.05) were, however, observed between the set-ups with MAP added and those without. At the end of the study, it was ascertained that addition of MAP improved the efficiency of biodegradation by up to 5.86% – 14.44% at 150 mg L-1 MAP application level and 11.11% – 15.83% at 250 mg L-1 MAP concentration. The greatest increase was seen with petrol (14.2% – 15.8%) which was also the most readily degraded of the test compounds. Biodegradation half-lives were also improved by up to 8.8 days on average in the presence of MAP. Fractions C26 – C30 proved to be the most recalcitrant based on mean removal percentages. The findings suggest that X. campestris was able to effectively breakdown the test hydrocarbon complexes and the addition of MAP enhanced its biodegradation efficiency. The bacterium may, therefore, be applied to bioremediation of environmental media polluted by crude oil or its derivative hydrocarbon fuels.

Systematic Handling of Environmental Fate Data for Model Development-Illustrated for the Case of Biodegradation Half-Life Data.

The assessment of environmental hazard indicators such as persistence, mobility, toxicity, or bioaccumulation of chemicals often results in highly variable experimental outcomes. Persistence is particularly affected due to a multitude of influencing environmental factors, with biodegradation experiments resulting in half-lives spanning several orders of magnitude. Also, half-lives may lie beyond the limits of reliable half-life quantification, and the number of available data points per substance may vary considerably, requiring a statistically robust approach for the characterization of data. Here, we apply Bayesian inference to address these challenges and characterize the distributions of reported soil half-lives. Our model estimates the mean, standard deviation, and corresponding uncertainties from a set of reported half-lives experimentally obtained for a single substance. We apply our inference model to 893 pesticides and pesticide transformation products with experimental soil half-lives of varying data quantity and quality, and we infer the half-life distribution for each compound. By estimating average half-lives, their experimental variability, and the uncertainty of the estimations, we provide a reliable data source for building predictive models, which are urgently needed by regulatory authorities to manage existing chemicals and by industry to design benign, nonpersistent chemicals. Our approach can be readily adapted for other environmental hazard indicators.

Hazard vs. exposure: Does it make a difference in identifying chemicals with persistence and mobility concerns?

Persistent and mobile (PM) chemicals are considered emerging threats to the environment and drinking water because they can be transported over long distances, penetrate natural and artificial barriers, and resist removal by traditional water treatment procedures. Current chemical regulatory frameworks raise concerns over PM chemicals due to their potential to cause high human exposure through drinking water contamination. However, the criteria used to screen and identify these chemicals often rely on hazard properties related to stability and sorption, such as biodegradation half-lives and organic-carbon-normalized sorption coefficients as respective measures of P and M. Here, we conduct a model-based assessment to examine the consistency between hazard-based and exposure-based approaches in assessing PM chemicals, by evaluating whether chemicals identified as highly P and M are consistently associated with high drinking water exposure potential (DWEP). We discover that chemicals with the top DWEPs tend to be PM chemicals, but the reverse is not always true, because DWEPs are also impacted by volatilization for air-distributed chemicals and advective particle-bound transport for particle-bound chemicals. Our findings suggest that the hazard metrics are better suited for de-prioritizing, as opposed to prioritizing, chemicals that are unlikely to result in significant human exposure through drinking water, as unfavorable values of hazard metrics are a necessary but not sufficient condition for a high DWEP. We also find that distinct mechanisms determine the DWEP in different sources of drinking water: Sorption and stability are more influential on the DWEP of chemicals in groundwater and surface water, respectively, whereas both sorption and stability equally impact water undergoing riverbank filtration. Future studies should focus on optimizing the identification of persistent and mobile chemicals to ensure that exposure potential is taken into consideration.

Occurrence and transport of N-nitrosamines in the urban water systems of the Pearl River Delta, southern China

The discharge of substantial amounts of N-nitrosamines-contained wastewater into receiving rivers can significantly deteriorate water quality, as these carcinogenic compounds can be easily transported into groundwater and drinking water systems. This study investigated the distribution of eight species of N-nitrosamines in river water, groundwater, and tap water located in the center of the Pearl River Delta (PRD), China. The results showed that three major N-nitrosamines, including N-nitrosodimethylamine (NDMA), N-nitrosodiethylamine (NDEA), and N-nitrosodibutylamine (NDBA), with concentrations of up to 64 ng/L, were observed in river water, groundwater, and tap water, whereas the other compounds occurred sporadically. In river water and groundwater, high concentrations of NDMA, NDEA, N-nitrosomorpholine (NMOR), and NDBA were found in industrial and residential lands as compared to agricultural lands owing to the influence of various human activities. The primary sources of N-nitrosamines in river water were industrial and domestic wastewater, and the infiltration of river water was responsible for the high levels of N-nitrosamines in groundwater. Among the target N-nitrosamines, NDEA and NMOR with long biodegradation half-lives (>4 days) and low LogKow values (<1) displayed the highest potential for groundwater. N-nitrosamines in groundwater and tap water pose significant potential cancer risks to residents, especially children, and juveniles, with lifetime cancer risks of over 10−4, necessitating advanced water treatments for drinking water and critical controls on primary industrial discharge in urban areas.

Exploring quantitative structure-property relationship models for environmental fate assessment of petroleum hydrocarbons.

The rate and extent of biodegradation of petroleum hydrocarbons in the different aquatic environments is an important element to address. The major avenue for removing petroleum hydrocarbons from the environment is thought to be biodegradation. The present study involves the development of predictive quantitative structure-property relationship (QSPR) models for the primary biodegradation half-life of petroleum hydrocarbons that may be used to forecast the biodegradation half-life of untested petroleum hydrocarbons within the established models' applicability domain. These models use easily computable two-dimensional (2D) descriptors to investigate important structural characteristics needed for the biodegradation of petroleum hydrocarbons in freshwater (dataset 1), temperate seawater (dataset 2), and arctic seawater (dataset 3). All the developed models follow OECD guidelines. We have used double cross-validation, best subset selection, and partial least squares tools for model development. In addition, the small dataset modeler tool has been successfully used for the dataset with very few compounds (dataset 3 with 17 compounds), where dataset division was not possible. The resultant models are robust, predictive, and mechanisticallyinterpretable based on both internal and external validation metrics (R2 range of 0.605-0.959. Q2(Loo) range of 0.509-0.904, and Q2F1 range of 0.526-0.959). The intelligent consensus predictor tool has been used for theimprovement of the prediction quality for test set compounds which provided superior outcomes to those from individual partial least squares models based on several metrics (Q2F1 = 0.808 and Q2F2 = 0.805 for dataset 1 in freshwater). Molecular size and hydrophilic factor for freshwater, frequency of two carbon atoms at topological distance 4 for temperate seawater, and electronegative atom count relative to size for arctic seawater were found to be the most significant descriptors responsible for the regulation of biodegradation half-life of petroleum hydrocarbons.

The applicability domain of EPI Suite™ for screening phytotoxins for potential to contaminate source water for drinking

BackgroundToxins produced by plants constitute a potential threat to water supplies in Europe, but have not been widely considered in systematic risk assessments. One way to begin to address potential risks of phytotoxins is to conduct screening-level assessments of known phytotoxins for their potential to contaminate source water for drinking due to persistence (P) and mobility (M). Chemical properties relevant for such an assessment (octanol–water partition coefficient KOW and biodegradation half-life) can be estimated from the structure of phytotoxins with quantitative structure–property relationship (QSPR) models found in the United States Environmental Protection Agency’s Estimation Program Interface (EPI Suite™) software, but predictions must be considered critically since these models have been developed using data for anthropogenic chemicals and many phytotoxins could lie outside their applicability domain.ResultsWe analyzed two EPI Suite™ models—KOWWIN and BIOWIN5—by evaluating the quality of property predictions for their validation sets as a function of Euclidean distances dE to the centroid of descriptor space of the models’ training sets. We identified model-specific applicability domain boundaries as local maxima in plots of the difference between root mean square error (∆RMSE) of modeled property values of validation set compounds within and outside applicability domain boundaries defined by a continuum of possible boundaries. And, we also evaluated four generic boundaries that have been suggested in literature. The ∆RMSE between validation set compounds outside and inside applicability domain boundaries had positive values for all but one of the possible boundaries we considered, indicating that properties of chemicals with dE inside the boundaries were better predicted. With our proposed model-specific boundaries, 21% of 1586 phytotoxins produced by plants found in Switzerland were out of domain of KOWWIN, and 46% of were out of domain of BIOWIN5.ConclusionsEstimates of Log KOW and biodegradation half-life of phytotoxins that lie outside the domain of applicability of the QSPR models should be viewed as extrapolations that are subject to unquantified and potentially large errors. Phytotoxins outside the domain of applicability of QSPR models should be prioritized for property measurements as a basis to expand the training sets of QSPR models and to support hazard identification for better management of drinking water quality in Europe.

Transformation and stable isotope fractionation of the urban biocide terbutryn during biodegradation, photodegradation and abiotic hydrolysis

Terbutryn is a widely used biocide in construction materials like paint and render to prevent the growth of microorganisms, algae and fungi. Terbutryn is released from the facades into the environment during rainfall, contaminating surface waters, soil and groundwater. Knowledge of terbutryn dissipation from the facades to aquatic ecosystems is scarce. Here, we examined in laboratory microcosms degradation half-lives, formation of transformation products and carbon and nitrogen isotope fractionation during terbutryn direct (UV light with λ = 254 nm and simulated sunlight) and indirect (simulated sunlight with nitrate) photodegradation, abiotic hydrolysis (pH = 1, 7 and 13), and aerobic biodegradation (stormwater pond sediment, soil and activated sludge). Biodegradation half-lives of terbutryn were high (>80 d). Photodegradation under simulated sunlight and hydrolysis at extreme pH values indicated slow degradability and accumulation in the environment. Photodegradation resulted in a variety of transformation products, whereas abiotic hydrolysis lead solely to terbutryn-2-hydroxy in acidic and basic conditions. Biodegradation indicates degradation to terbutryn-2-hydroxy through terbutryn-sulfoxide. Compound-specific isotope analysis (CSIA) of terbutryn holds potential to differentiate degradation pathways. Carbon isotope fractionation values (εC) ranged from −3.4 ± 0.3‰ (hydrolysis pH 1) to +0.8 ± 0.1‰ (photodegradation under UV light), while nitrogen isotope fractionation values ranged from −1.0 ± 0.4‰ (simulated sunlight photodegradation with nitrate) to +3.4 ± 0.2‰ (hydrolysis at pH 1). In contrast, isotope fractionation during biodegradation was insignificant. ΛN/C values ranged from −1.0 ± 0.1 (hydrolysis at pH 1) to 2.8 ± 0.3 (photodegradation under UV light), allowing to differentiate degradation pathways. Combining the formation of transformation products and stable isotope fractionation enabled identifying distinct degradation pathways. Altogether, this study highlights the potential of CSIA to follow terbutryn degradation in situ and differentiate prevailing degradation pathways, which may help to monitor urban biocide remediation and mitigation strategies.

Intelligent Consensus Predictions of Biodegradation Half-Life of Petroleum Hydrocarbons (PHCs)

The present study explores the important chemical features of diverse petroleum hydrocarbons (PHCs) responsible for their biodegradation by developing partial least squares (PLS) regression-based quantitative structure-property relationship (QSPR) models. The biodegradability is estimated in terms of biodegradation half-life (Logt1/2). All the PLS models were extensively validated by different internationally acceptable internal (R2= 0.849–0.861; Q2 = 0.833–0.849; R2adj = 0.845–0.858) and external (Q2F1= 0.825-0.848; Q2F2 = 0.822–0.845) validation parameters. The consensus predictions were also performed by using the “intelligent consensus predictor” (ICP) tool, which improves the predictive ability of individual models based on mean absolute error (MAE)-based criteria. The models suggested that the biodegradation of PHCs is dependent on the presence of substituents on the aromatic ring, 12 atom containing ring system, thiophene moiety, electron rich chemicals, large molecular size, degree of unsaturation, degree of branching, cyclization, and hydrophobicity.

Microbiome Reengineering by Heat Selection for Rapid Biodegradation of Trichloroethylene with Minimal Vinyl Chloride Formation

Trichloroethylene (TCE) was a widely used industrial solvent but is now regarded as a notorious groundwater contaminant. Both physicochemical and biological methods have been applied to remediate groundwater contaminated by TCE. For medium to low level of TCE contamination, bioremediation could be more cost-effective. However, bioremediation approaches suffer from slow degradation rates and accumulation of vinyl chloride (VC). In addition, bioaugmentation is often highly encouraged but may introduce foreign genes and increase the pace of microbial evolution. In this study, a microbiome reengineering strategy by heat selection is applied to solve these problems. Out of eight heat-treated mixed cultures, two showed a much-improved TCE degradation rate, more than 70 times higher than the untreated. The biodegradation half-life (t1/2) of TCE was 0.0627 d or shorter. No VC was detected by a gas chromatography equipped with flame ionization detector (GC-FID) and only a minimal amount by a GC-mass spectrometer (GC-MS). Ethene achieved a fairly good mass balance. Polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE) and next-generation sequencing (NGS) results showed that the heating process did not kill most bacteria, but Dehalococcoides were either not present or very scarce. Acetoanaerobium and Methanosarcina could be the most important species in this reductive dechlorination process. Kinetic study results showed that the maximum specific TCE degradation rate was approximately 1,271 nmole/min/mg cell protein, which are two orders of magnitude higher than that of the mixed cultures reported in literature. These results suggest that apart from biostimulation and bioaugmentation, microbiome reengineering could be a promising approach for rapid bioremediation of TCE-contaminated aquifers.

Biodegradation of acetaminophen and its main by-product 4-aminophenol by Trichoderma harzianum versus mixed biofilm of Trichoderma harzianum/Pseudomonas fluorescens in a fungal microbial fuel cell

Our research aimed to explore the bioremediation of acetaminophen (APAP) and 4-aminophenol (PAP), as well as energy production in a dual-chamber fungal microbial fuel cell (FMFC) device. The pure culture of fungus Trichoderma harzianum and mixed culture of bacteria and fungi (Trichoderma harzianum and Pseudomonas fluorescens) were used as bioanodes. The microorganisms were compared for the first time to examine the removal efficiency of the APAP and its main by-product (PAP). The authors have applied an electrochemical approach to follow the APAP and PAP behavior in the systems. It is interesting to mention that the mixed biofilm culture was able to completely remove the APAP and PAP at around 7 h. These experiments revealed that the biodegradation rate was enhanced in bacterial-fungal biofilms about 5 times higher than in the pure culture of fungus Trichoderma harzianum. The formation of PAP was also observed during the mixed biofilm biodegradation of APAP, which was the result of bacterial degradation. The half-life of APAP biodegradation was 7 h and 1.3 h for pure and mixed biofilm cultures, respectively. Similarly, the higher removal efficiency of PAP was also obtained for the mixed culture biofilms. The PAP biodegradation kinetic constants of 0.116 h−1 and 0.066 h−1 were observed for mixed culture and fungal biofilms, respectively. In terms of MFC performance, a power density of 1.7 mW m−2 was obtained for the FMFC system working with mixed biofilm which is at least 10 times higher than that of pure fungal biofilm (0.13 mW m−2). This work led to the conclusion that a combination of bacterial-fungal biofilm Trichoderma harzianum and Pseudomonas fluorescens could be made use of to remove APAP and PAP with simultaneous electricity production.

Low-current electro-oxidation enhanced the biodegradation of the recalcitrant naphthenic acids in oil sands process water

Combining electro-oxidation (EO) with biodegradation for real oil sands process water (OSPW) treatment was evaluated in terms of naphthenic acid (NA) biodegradation enhancement. Ion mobility spectrometry (IMS) qualitative analysis showed that EO by graphite was able to degrade the different NA clusters in OSPW including: classical, oxidized and heteroatomic NAs. Applying EO even at current density as low as 0.2 mA/cm2 was still able to reduce classical NAs and acid extractable fraction (AEF) by 19% and 7%, respectively. EO pretreatment preferentially broke long carbon chains and highly cyclic carboxylic fractions of NAs in OSPW to improve the biodegradation of NAs. Aerobic biodegradation for 40 days reduced NAs by up to 30.9% when the samples were pre-treated with EO. Applying EO at current densities below 2 mA/cm2 maintained current efficiency as high as 48% and resulted in improvement in the biodegradation rate of remaining NAs by up to 2.7 folds. It was further revealed that applying EO before biodegradation could reduce the biodegradation half-life of classical NAs by up to 4.4 folds. 16S amplicon sequencing analysis showed that the samples subjected to biodegradation had increased abundances of Sphingomonadales and Rhodocyclales with increasing applied current density for EO pre-treatments.

Metabolism of 17β-estradiol by Novosphingobium sp. ES2-1 as probed via HRMS combined with 13C3-labeling

This study investigated the biodegradation and metabolic mechanisms of 17β-estradiol (E2) by Novosphingobium sp. ES2-1 isolated from the activated sludge in a domestic sewage treatment plant (STP). It could degrade 97.1% E2 (73.5 μmol/L) in 7 d with a biodegradation half-life of 1.29 d. E2 was initially converted to estrone (E1), then to 4-hydroxyestrone (4-OH-E1), before subsequent monooxygenation reactions cleaved 4-OH-E1 into a metabolite with long-chain ketones structure (metabolite P8). However, when 4-OH-E1 was cleaved through the 4,5-seco pathway, the resulting phenol ring cleavage product could randomly condense with NH3 to yield a pyridine derivative, accompanied by the uncertain loss of a carboxy group at C4 before the condensation. The derivative was further oxidized into the metabolites with both pyridine and long-chain ketones structure (metabolite N5) through a similar formation mechanism as for P8 performed. This research presents several novel metabolites and shows that E2 can be biodegraded into the metabolite with long-chain structure through three optional pathways, thereby reducing E2 contamination.

Isolation and characterization of a novel benzophenone-3-degrading bacterium Methylophilus sp. strain FP-6

Benzophenone-3 (BP-3) is extensively applied in sunscreens and some other related cosmetic products. It is necessary to efficiently and safely remove BP-3 from environments by application of various treatment technologies. However, to the authors' knowledge, BP-3 biodegradation by a single bacterial strain has not been reported before. In this study, a Gram-negative aerobic bacterium capable of degrading BP-3 as a sole carbon source was isolated from a municipal wastewater treatment plant and classified as Methylophilus sp. FP-6 according to BIOLOG GEN III and 16S rDNA analysis. Methanol was chosen for further experiments as a co-metabolic carbon source to enhance the microbial degradation efficiency of BP-3. Orthogonal and one-way experiments were all performed to investigate the optimal culture conditions for degradation of BP-3 by Methylophilus sp. FP-6. The degradation rate of BP-3 reached about 65% after 8 days of incubation with strain FP-6 under optimal culture conditions. The half-life (t1/2) of BP-3 biodegradation by strain FP-6 was estimated as 2.95 days according to the BP-3 degradation curve. The metabolite intermediates generated during the BP-3 degradation process were analyzed by LC–MS/MS and three metabolite products were identified. According to the analysis of metabolic intermediates, three pathways for degradation of BP-3 by strain FP-6 were proposed. The results from this study gave first insights into the potential of BP-3 biodegradation by a single bacterial strain.

Biodegradability assessment of food additives using OECD 301F respirometric test.

The ready biodegradability of twenty food additives, belonging to the classes of artificial sweeteners, natural sweeteners, preservatives and colorings, was investigated using activated sludge as inoculum and OECD 301F respirometric test. According to the results, saccharin, aspartame, sodium cyclamate, xylitol, erythritol, maltitol, potassium sorbate, benzoic acid and sodium ascorbate are characterized as readily biodegradable compounds, partial biodegradation (<60% during the test) was noticed for steviol, inulin, alitame, curcumin, ponceau 4R and tartrazine, while no biodegradation was observed for the other five compounds. The duration of lag phase before the start of biodegradation varied between the target compounds, while their ultimate biodegradation half-life values ranged between 0.7 ± 0.1 days (benzoic acid) and 24.6 ± 1.0 days (curcumin). The expected removal of target compounds due to ultimate biodegradation mechanism was estimated for a biological wastewater treatment system operated at a retention time of one day and percentages higher than 40% were calculated for sodium cyclamate, potassium sorbate and benzoic acid. Higher removal percentages are expected in full-scale Sewage Treatment Plants (STPs) due to the contribution of other mechanisms such as sorption to suspended solids, (bio)transformation and co-metabolic phenomena. Further biodegradation experiments should be conducted under different experimental conditions for the food additives that did not fulfill the requirements of the applied protocol. Future studies should also focus on the occurrence and fate of food colorants and natural sweeteners in full-scale STPs.

Production and fate of fishy odorants produced by two freshwater chrysophyte species under different temperature and light conditions

Fishy odor has become one of the most often encountered aesthetic water quality problems in drinking water. While fresh water algae living in colder water can produce offensive fishy odors, their environmental behaviors remain poorly understood. In this study, two chrysophyte species (Synura uvella and Ochromonas sp.), which are often associated with fishy odor events, were selected to investigate the effect of temperature (8, 16, and 24 °C) and light intensity (10, 41, and 185 μmol photons m−2 s−1) on algal growth and odorant production. Five polyunsaturated aldehyde derivatives, including 2,4-heptadienal, 2-octenal, 2,4-octadienal, 2,4-decadienal, and 2,4,7-dectridienal, were identified as fishy/cod liver oil/fatty/rancid descriptors in the cultures of the two algae based on gas chromatography-olfactometry-mass spectrometry and comprehensive two-dimensional gas chromatography mass spectrometry. While biomass yield increased with the increase in temperature for both species, significantly higher odorant yields (production of odorants per cell) were obtained at 8 °C. The total odorant production and cell yield of the odorants decreased with the increase in light intensity from 10 to 185 μmol photons m−2 s−1. The biodegradation half-lives for the released odorants were 6–10 h at 8 °C and 2–4 h at 24 °C, whereas the volatilization half-lives were 36–97 d at 8 °C and 6–17 d at 24 °C, suggesting that temperature-dependent biodegradation was an important factor controlling the fate of fishy compounds in aquatic environments. The results of this study will help clarify why most fishy odor events occur in cooler seasons, and provide knowledge related to cold water persistence for the management of fishy odor problems associated with algae.