Detoxification and bioaugmentation potential for acetaminophen and its derivatives using Ensifer sp. isolated from activated sludge

Delineating acetaminophen biodegradation kinetics and metabolomics using bacterial community

Acetaminophen [N-(4-hydroxyphenyl) acetamide, APAP] is an extensively and frequently consumed over-the-counter analgesic and antiphlogistic medication. It is being regarded as an emerging pollutant due to its continuous increment in the environment instigating inimical impacts on humans and the ecosystem. Considering its wide prevalence in the environment, there is an immense need of appropriate methods for the removal of APAP. The present study indulged screening and isolation of APAP degrading bacterial strains from pharmaceuticals-contaminated sites, followed by their molecular characterization via 16S rRNA sequencing. The phylogenetic analyses assigned the isolates to the genera Pseudomonas, Bacillus, Paracoccus, Agrobacterium, Brucella, Escherichia, and Enterobacter based on genetic relatedness. The efficacy of these strains in batch cultures tested through High-performance Liquid Chromatography (HPLC) revealed Paracoccus sp. and Enterobacter sp. as the most promising bacterial isolates degrading up to 88.96 and 85.92%, respectively of 300 mg L-1 of APAP within 8 days of incubation. Michaelis-Menten kinetics model parameters also elucidated the high degradation potential of these isolates. The major metabolites identified through FTIR and GC-MS analyses were 4-aminophenol, hydroquinone, and 3-hydroxy-2,4-hexadienedioic. Therefore, the outcomes of this comprehensive investigation will be of paramount significance in formulating strategies for the bioremediation of acetaminophen-contaminated sites through a natural augmentation process via native bacterial strains.

Environmental consequences of transformation products from an antibiotic mixture and their mitigation in a wastewater microbiome using an HCl-modified adsorbent

This study enhanced our understanding of antibiotic mixtures' occurrence, transformation, toxicity, and ecological risks. The role of acid-modified biochar (BC) in treating antibiotic residues was explored, shedding light on how BC influences the fate, mobility, and environmental impact of antibiotics and transformation products (TPs) in an activated sludge (AS) microbiome. A mixture of oxytetracycline and sulfamethoxazole was found to synergistically (or additively) inhibit cell growth of AS and disrupt the microbiome structure, species richness/diversity, and function. The formation of TPs with potentially higher toxicity and persistence than the original compounds was identified, explaining the microbiome disruption. Agricultural waste-derived BC was optimized for contaminant adsorption, leading to a reduction in toxicity when added to AS by sequestering TPs on its surface. This work highlighted adsorbents as a practical engineering strategy for mitigating liquid-phase contaminants' toxicological consequences, proactively controlling the fate and effects of antibiotics and TPs.

Activated sludge microbiome with H2O2-modified biochar enhances the treatment resilience and detoxification of oxytetracycline and its toxic byproducts

The widespread presence of oxytetracycline (OTC) in aquatic ecosystems poses both health risks and ecological concerns. The present study revealed the beneficial role of hydrogen peroxide (H2O2)-pretreated biochar (BC) derived from agricultural hardwood waste in an activated sludge (AS) bioprocess. The BC addition significantly enhanced the removal and detoxification of OTC and its byproducts. BC was initially modified using H2O2 to improve its OTC adsorption. Two AS reactors were then established, one with H2O2-modified BC and one without, and both were exposed to OTC. The BC-added reactor exhibited significantly higher OTC removal rates during both the start-up (0.97 d-1) and steady-state (0.98 d-1) phases than the reactor without BC (0.54 d-1 and 0.83 d-1, respectively). Two novel transformation pathways for OTC were proposed, with four byproducts originating from OTC identified, some of which were found to be more toxic than OTC itself. The BC-added reactor had significantly higher system functioning in terms of its heterotrophic activity and the reduction of the toxicity of OTC and its byproducts, as illustrated by structure-based toxicity simulations, antimicrobial susceptibility experiments, analytical chemistry, and bioinformatics analysis. Bioinformatics revealed two novel bacterial populations closely related to the known OTC-degrader Pandoraea. The ecophysiology and selective enrichment of these populations suggested their role in the enzymatic breakdown and detoxification of OTC (e.g., via demethylation and hydrogenation). Overall, the present study highlighted the beneficial role of H2O2-modified BC in combination with the AS microbiome in terms of enhancing treatment performance and resilience, reducing the toxicological disruption to biodiversity, and detoxifying micropollutants.

Predicting and improving the microbial removal of organic micropollutants during wastewater treatment: A review

Organic micropollutants (OMPs) consist of widely used chemicals such as pharmaceuticals and pesticides that can persist in surface and groundwaters at low concentrations (ng/L to μg/L) for a long time. The presence of OMPs in water can disrupt aquatic ecosystems and threaten the quality of drinking water sources. Wastewater treatment plants (WWTPs) rely on microorganisms to remove major nutrients from water, but their effectiveness at removing OMPs varies. Low removal efficiency might be the result of low concentrations, inherent stable chemical structures of OMPs, or suboptimal conditions in WWTPs. In this review, we discuss these factors, with special emphasis on the ongoing adaptation of microorganisms to degrade OMPs. Finally, recommendations are drawn to improve the prediction of OMP removal in WWTPs and to optimize the design of new microbial treatment strategies. OMP removal seems to be concentration-, compound-, and process-dependent, which poses a great complexity to develop accurate prediction models and effective microbial processes targeting all OMPs.

Recent advances in the biological treatment of wastewater rich in emerging pollutants produced by pharmaceutical industrial discharges

Pharmaceuticals and personal care products present potential risks to human health and the environment. In particular, wastewater treatment plants often detect emerging pollutants that disrupt biological treatment. The activated sludge process is a traditional biological method with a lower capital cost and limited operating requirements than more advanced treatment methods. In addition, the membrane bioreactor combines a membrane module and a bioreactor, widely used as an advanced method for treating pharmaceutical wastewater with good pollution performance. Indeed, the fouling of the membrane remains a major problem in this process. In addition, anaerobic membrane bioreactors can treat complex pharmaceutical waste while recovering energy and producing nutrient-rich wastewater for irrigation. Wastewater characterizations have shown that wastewater's high organic matter content facilitates the selection of low-cost, low-nutrient, low-surface-area, and effective anaerobic methods for drug degradation and reduces pollution. However, to improve the biological treatment, researchers have turned to hybrid processes in which all physical, chemical, and biological treatment methods are integrated to remove various emerging contaminants effectively. Hybrid systems can generate bioenergy, which helps reduce the operating costs of the pharmaceutical waste treatment system. To find the most effective treatment technique for our research, this work lists the different biological treatment techniques cited in the literature, such as activated sludge, membrane bioreactor, anaerobic treatment, and hybrid treatment, combining physicochemical and biological techniques.

Different acesulfame potassium fate and antibiotic resistance propagation pattern in nitrifying and denitrifying sludge systems

Acesulfame potassium (ACE-K) is a widely utilized sugar substitute with increasing demand, which is frequently detected in various environmental matrix due to recalcitrance. However, a general consensus on the contribution of nitrifying and denitrifying process to ACE-K removal is lacking. Therefore, ACE-K removal, its effects on antibiotic resistant genes (ARGs) propagation and microbial community in nitrifying sequencing batch reactor (N-SBR) and denitrifying sequencing batch reactor (D-SBR) inoculated with the identical activated sludge were investigated. In this study, ACE-K can be eliminated in N-SBR with satisfying removal efficiency (96.76 ± 8.33 %) after 13 d acclimation, while it remained persistent (average ACE-K removal efficiency of 2.24 ± 1.86 %) in D-SBR during 84 d exposure. Moreover, ACE-K hardly affected the performances of these two types of reactors and had little impact on nitrifying and denitrifying functional genes. However, initial contact with ACE-K would increase ARGs abundance, network analysis showed functional bacteria in each reactor were possible ARGs hosts. Potential ACE-K degrading genera Chelatococcus, Bosea and Aquamicrobium were found in both reactors. LefSe analysis showed that Phyllobacteriaceae containing Aquamicrobium genus was a differentially enriched family in N-SBR. This research might provide a perspective for better understanding factor affecting ACE-K fate in wastewater treatment process and its ecological risks.

Isolation of Novel Bacterial Strains Pseudomonas extremaustralis CSW01 and Stutzerimonas stutzeri CSW02 from Sewage Sludge for Paracetamol Biodegradation

Paracetamol is one of the most used pharmaceuticals worldwide, but due to its widespread use it is detected in various environmental matrices, such as surface and ground waters, sediments, soils or even plants, where it is introduced mainly from the discharge of wastewater and the use of sewage sludge as fertilizer in agriculture. Its accumulation in certain organisms can induce reproductive, neurotoxic or endocrine disorders, being therefore considered an emerging pollutant. This study reports on the isolation, from sewage sludge produced in wastewater treatment plants (WWTPs), of bacterial strains capable of degrading paracetamol. Up to 17 bacterial strains were isolated, but only two of them, identified as Pseudomonas stutzeri CSW02 and Pseudomonas extremaustralis CSW01, were able to degrade very high concentrations of paracetamol in solution as a sole carbon and energy source, and none of them had been previously described as paracetamol degraders. These bacteria showed the ability to degrade up to 500 mg L^-1 of paracetamol in only 6 and 4 h, respectively, much quicker than any other paracetamol-degrader strain described in the literature. The two main paracetamol metabolites, 4-aminophenol and hydroquinone, which present high toxicity, were detected during the degradation process, although they disappeared very quickly for paracetamol concentrations up to 500 mg L^-1. The IC₅₀ of paracetamol for the growth of these two isolates was also calculated, indicating that P. extremaustralis CSW01 was more tolerant than S. stutzeri CSW02 to high concentrations of paracetamol and/or its metabolites in solution, and this is the reason for the much lower paracetamol degradation by S. stutzeri CSW02 at 2000-3000 mg L^-1. These findings indicate that both bacteria are very promising candidates for their use in paracetamol bioremediation in water and sewage sludge.

Metabolomic analysis predicted changes in growth rate in Daphnia magna exposed to acetaminophen

As urbanization and the global population increases, pollutants associated with municipal wastewater such as pharmaceuticals are becoming more prevalent in aquatic environments. Acetaminophen (paracetamol) is a widely used drug worldwide and one of the most frequently detected pharmaceuticals in freshwater ecosystems. This study investigated the impact of acetaminophen on the metabolite profile of Daphnia magna at two life stages; and used these metabolomic findings to hypothesize a potential impact at a higher organismal level which was subsequently tested experimentally. Targeted polar metabolite analysis by liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to measure changes in the concentration of 51 metabolites in the neonate (> 24 h old) and adult (8 day-old) daphnids following a 48-h exposure to sub-lethal concentrations of acetaminophen. The impact of acetaminophen on the metabolic profile of neonates was widely different from adults. Also, acetaminophen exposure perturbed the abundance of nucleotides more extensively than other metabolites. The acute metabolomic experimental results led to the hypotheses that exposure to sub-lethal concentrations of acetaminophen upregulates protein synthesis in D. magna and subsequently increases growth during early life stages and has an opposite impact on adults. Accordingly, a 10 day growth rate experiment indicated that exposure to acetaminophen elevated biomass production in neonates but not in adults. These novel findings demonstrate that a targeted analysis and interpretation of the changes in the polar metabolic profile of organisms in response to environmental stressors could be used as a tool to predict changes at higher biological levels. As such, this study further emphasizes the incorporation of molecular-level platforms as critical and robust tools in environmental assessment frameworks and biomonitoring of aquatic ecosystems.

Effects of biochar addition on the fate of ciprofloxacin and its associated antibiotic tolerance in an activated sludge microbiome

This study investigated the effects of adding biochar (BC) on the fate of ciprofloxacin (CIP) and its related antibiotic tolerance (AT) in activated sludge. Three activated sludge reactors were established with different types of BC, derived from apple, pear, and mulberry tree, respectively, and one reactor with no BC. All reactors were exposed to an environmentally relevant level of CIP that acted as a definitive selective pressure significantly promoting AT to four representative antibiotics (CIP, ampicillin, tetracycline, and polymyxin B) by up to two orders of magnitude. While CIP removal was negligible in the reactor without BC, the BC-dosed reactors effectively removed CIP (70-95% removals) through primarily adsorption by BC and biodegradation/biosorption by biomass. The AT in the BC-added reactors was suppressed by 10-99%, compared to that without BC. The BC addition played a key role in sequestering CIP, thereby decreasing the selective pressure that enabled the proactive prevention of AT increase. 16S rRNA gene sequencing analysis showed that the BC addition alleviated the CIP-mediated toxicity to community diversity and organisms related to phosphorous removal. Machine learning modeling with random forest and support vector models using AS microbiome data collectively pinpointed Achromobacter selected by CIP and strongly associated with the AT increase in activated sludge. The identification of Achromobacter as an important AT bacteria revealed by the machine learning modeling with multiple models was also validated with a linear Pearson's correlation analysis. Overall, our study highlighted Achromobacter as a potential useful sentinel for monitoring AT occurring in the environment and suggested BC as a promising additive in wastewater treatment to improve micropollutant removal, mitigate potential AT propagation, and maintain community diversity against toxic antibiotic loadings.

Microbial paracetamol degradation involves a high diversity of novel amidase enzyme candidates

Pharmaceuticals are relatively new to nature and often not completely removed in wastewater treatment plants (WWTPs). Consequently, these micropollutants end up in water bodies all around the world posing a great environmental risk. One exception to this recalcitrant conversion is paracetamol, whose full degradation has been linked to several microorganisms. However, the genes and corresponding proteins involved in microbial paracetamol degradation are still elusive. In order to improve our knowledge of the microbial paracetamol degradation pathway, we inoculated a bioreactor with sludge of a hospital WWTP (Pharmafilter, Delft, NL) and fed it with paracetamol as the sole carbon source. Paracetamol was fully degraded without any lag phase and the enriched microbial community was investigated by metagenomic and metatranscriptomic analyses, which demonstrated that the microbial community was very diverse. Dilution and plating on paracetamol-amended agar plates yielded two Pseudomonas sp. isolates: a fast-growing Pseudomonas sp. that degraded 200 mg/L of paracetamol in approximately 10 h while excreting 4-aminophenol, and a slow-growing Pseudomonas sp. that degraded paracetamol without obvious intermediates in more than 90 days. Each Pseudomonas sp. contained a different highly-expressed amidase (31% identity to each other). These amidase genes were not detected in the bioreactor metagenome suggesting that other as-yet uncharacterized amidases may be responsible for the first biodegradation step of paracetamol. Uncharacterized deaminase genes and genes encoding dioxygenase enzymes involved in the catabolism of aromatic compounds and amino acids were the most likely candidates responsible for the degradation of paracetamol intermediates based on their high expression levels in the bioreactor metagenome and the Pseudomonas spp. genomes. Furthermore, cross-feeding between different community members might have occurred to efficiently degrade paracetamol and its intermediates in the bioreactor. This study increases our knowledge about the ongoing microbial evolution towards biodegradation of pharmaceuticals and points to a large diversity of (amidase) enzymes that are likely involved in paracetamol metabolism in WWTPs.

Photodegradation of Pharmaceutical Pollutants: New Photocatalytic Systems Based on 3D Printed Scaffold-Supported Ag/TiO2 Nanocomposite

Due to the release of active pharmaceutical compounds in wastewater and their persistence in the environment, dangerous consequences can develop in the aquatic and terrestrial organisms. Chitosan/Ag/TiO2 3D printed scaffolds, at different Ag nanoparticle concentrations (10, 100, 1000 ppm) are investigated here as promising materials for photocatalytic degradation under the UV–Vis irradiation of pharmaceutical compounds in wastewater. As target drugs, amoxicillin, paracetamol and their 1:1 mix were selected. Ag nanoparticles increase the photocatalytic efficiency of the system based on titanium dioxide embedded in the chitosan scaffold: in the presence of Chitosan/Ag100/TiO2, the selected pharmaceuticals (PhCs), monitored by UV–Vis spectroscopy, are completely removed in about 2 h. The photodegradation products of the PhCs were identified by Liquid Chromatography–Mass Spectroscopy and assessed for their toxicological impact on six different bacterial strains: no antibacterial activity was found towards the tested strains. This new system based on Ag/TiO2 supported on 3D chitosan scaffolds may represent an effective strategy to reduce wastewater pollution by emerging contaminants.

Bioaugmentation Technology for Treatment of Toxic and Refractory Organic Waste Water Based on Artificial Intelligence

With the development of modern chemical synthesis technology, toxic and harmful compounds increase sharply. In order to improve the removal efficiency of refractory organic matter in waste water, the method of adding powdered activated carbon (PAC) to the system for adsorption was adopted. Through the analysis of organic matter removal rule before and after waste water treatment, it can be found that PAC is easy to adsorb hydrophobic organic matter, while activated sludge is easy to remove hydrophilic and weakly hydrophobic neutral organic matter. Powdered activated carbon-activated sludge SBR system (PAC-AS) system is obviously superior to AS and PAC system in removing organic matter of hydrophilic and hydrophobic components, that is, biodegradation and PAC adsorption are additive. Compared with the control system, the Chemical Oxygen Demand (COD) removal rate of refractory substances increased by 8.36%, and PAC had a good adsorption effect on small molecular weight organic compounds, but with the increase of molecular weight of organic compounds, the adsorption effect of PAC gradually weakened, and it had no adsorption effect on macromolecular organic compounds. Based on the research of fuzzy control theory, an Agent control system for ozone oxidation process of industrial waste water based on Mobile Agent Server (MAS) theory was established, which was realized by fuzzy control method. The simulation results showed strong stability and verified the feasibility and adaptability of the distributed intelligent waste water treatment system based on MAS theory in the actual control process.

Effect of concentration and hydraulic reaction time on the removal of pharmaceutical compounds in a membrane bioreactor inoculated with activated sludge

Pharmaceuticals are often not fully removed in wastewater treatment plants (WWTPs) and are thus being detected at trace levels in water bodies all over the world posing a risk to numerous organisms. These organic micropollutants (OMPs) reach WWTPs at concentrations sometimes too low to serve as growth substrate for microorganisms; thus, co-metabolism is thought to be the main conversion mechanism. In this study, the microbial removal of six pharmaceuticals was investigated in a membrane bioreactor at increasing concentrations (4-800 nM) of the compounds and using three different hydraulic retention times (HRT; 1, 3.5 and 5 days). The bioreactor was inoculated with activated sludge from a municipal WWTP and fed with ammonium, acetate and methanol as main growth substrates to mimic co-metabolism. Each pharmaceutical had a different average removal efficiency: acetaminophen (100%) > fluoxetine (50%) > metoprolol (25%) > diclofenac (20%) > metformin (15%) > carbamazepine (10%). Higher pharmaceutical influent concentrations proportionally increased the removal rate of each compound, but surprisingly not the removal percentage. Furthermore, only metformin removal improved to 80-100% when HRT or biomass concentration was increased. Microbial community changes were followed with 16S rRNA gene amplicon sequencing in response to the increment of pharmaceutical concentration: Nitrospirae and Planctomycetes 16S rRNA relative gene abundance decreased, whereas Acidobacteria and Bacteroidetes increased. Remarkably, the Dokdonella genus, previously implicated in acetaminophen metabolism, showed a 30-fold increase in abundance at the highest concentration of pharmaceuticals applied. Taken together, these results suggest that the incomplete removal of most pharmaceutical compounds in WWTPs is dependent on neither concentration nor reaction time. Accordingly, we propose a chemical equilibrium or a growth substrate limitation as the responsible mechanisms of the incomplete removal. Finally, Dokdonella could be the main acetaminophen degrader under activated sludge conditions, and non-antibiotic pharmaceuticals might still be toxic to relevant WWTP bacteria.

Machine Learning Approach Reveals the Assembly of Activated Sludge Microbiome with Different Carbon Sources during Microcosm Startup

Activated sludge (AS) microcosm experiments usually begin with inoculating a bioreactor with an AS mixed culture. During the bioreactor startup, AS communities undergo, to some extent, a distortion in their characteristics (e.g., loss of diversity). This work aimed to provide a predictive understanding of the dynamic changes in the community structure and diversity occurring during aerobic AS microcosm startups. AS microcosms were developed using three frequently used carbon sources: acetate (A), glucose (G), and starch (S), respectively. A mathematical modeling approach quantitatively determined that 1.7–2.4 times the solid retention time (SRT) was minimally required for the microcosm startups, during which substantial divergences in the community biomass and diversity (33–45% reduction in species richness and diversity) were observed. A machine learning modeling application using AS microbiome data could successfully (>95% accuracy) predict the assembly pattern of aerobic AS microcosm communities responsive to each carbon source. A feature importance analysis pinpointed specific taxa that were highly indicative of a microcosm feed source (A, G, or S) and significantly contributed for the ML-based predictive classification. The results of this study have important implications on the interpretation and validity of microcosm experiments using AS.