Trends in predictive biodegradation for sustainable mitigation of environmental pollutants: Recent progress and future outlook

Evaluation of suitability and biodegradability of the organophosphate insecticides to mitigate insecticide pollution in onion farming

Organophosphates constitute a major class of pesticides widely employed in agriculture to manage insect pests. Their toxicity is attributed to their ability to inhibit the functioning of acetylcholinesterase (AChE), an essential enzyme for normal nerve transmission. Organophosphates, especially chlorpyrifos, have been a key component of the integrated pest management (IPM) in onions, effectively controlling onion maggot Delia antiqua, a severe pest of onions. However, the growing concerns over the use of this insecticide on human health and the environment compelled the need for an alternative organophosphate and a potential microbial agent for bioremediation to mitigate organophosphate pesticide pollution. In the present study, chloropyrifos along with five other organophosphate insecticides, phosmet, primiphos-methyl, isofenphos, iodofenphos and tribuphos, were screened against the target protein AChE of D. antiqua using molecular modeling and docking techniques. The results revealed that iodofenphos showed the best interaction, while tribuphos had the lowest interaction with the AChE based on comparative binding energy values. Further, protein-protein interaction analysis conducted using the STRING database and Cytoscap software revealed that AChE is linked with a network of 10 different proteins, suggesting that the function of AChE is disrupted through interaction with insecticides, potentially leading to disruption within the network of associated proteins. Additionally, an in silico study was conducted to predict the binding efficiency of two organophosphate degrading enzymes, organophosphohydrolase (OpdA) from Agrobacterium radiobacter and Trichoderma harzianum paraoxonase 1 like (ThPON1-like) protein from Trichoderma harzianum, with the selected insecticides. The analysis revealed their potential to degrade the pesticides, offering a promising alternative before going for cumbersome onsite remediation.

Evaluation of surfactant-aided polycyclic aromatic hydrocarbon biodegradation by molecular docking and molecular dynamic simulation in the marine environment

Marine oil spills directly cause polycyclic aromatic hydrocarbons (PAHs) pollution and affect marine organisms due to their toxic property. Chemical and bio-based dispersants composed of surfactants and solvents are considered effective oil spill-treating agents. Dispersants enhance oil biodegradation in the marine environment by rapidly increasing their solubility in the water column. However, the effect of dispersants, especially surfactants, on PAHs degradation by enzymes produced by microorganisms has not been studied at the molecular level. The role of the cytochrome P450 (CYP) enzyme in converting contaminants into reactive metabolites during the biodegradation process has been evidenced, but the activity in the presence of surfactants is still ambiguous. Thus, this study focused on the evaluation of the impact of chemical and bio-surfactants (i.e., Tween 80 (TWE) and Surfactin (SUC)) on the biodegradation of naphthalene (NAP), chrysene (CHR), and pyrene (PYR), the representative components of PAHs, with CYP enzyme from microalgae Parachlorella kessleri using molecular docking and molecular dynamics (MD) simulation. The molecular docking analysis revealed that PAHs bound to residues at the CYP active site through hydrophobic interactions for biodegradation. The MD simulation showed that the surfactant addition changed the enzyme conformation in the CYP-PAH complexes to provide more interactions between the enzyme and PAHs. This led to an increase in the enzyme's capability to degrade PAHs. Binding free energy (ΔG‌‌Bind) calculations confirmed that surfactant treatment could enhance PAHs degradation by the enzyme. The SUC gave a better result on NAP and PYR biodegradation based on ΔG‌‌Bind, while TWE facilitated the biodegradation of CHR. The research outputs could greatly facilitate evaluating the behaviors of oil spill-treating agents and oil spill response operations in the marine environment.

Predicting Hydrocarbon Primary Biodegradation in Soil and Sediment Systems Using System Parameterization and Machine Learning

Technical complexity associated with biodegradation testing, particularly for substances of unknown or variable composition, complex reaction products, or biological materials (UVCB), necessitates the advancement of non-testing methods such as quantitative structure-property relationships (QSPRs). Models for describing the biodegradation of petroleum hydrocarbons (HCs) have been previously developed. A critical limitation of available models is their inability to capture the variability in biodegradation rates associated with variable test systems and environmental conditions. Recently, the Hydrocarbon Biodegradation System Integrated Model (HC-BioSIM) was developed to characterize the biodegradation of HCs in aquatic systems with the inclusion of key test system variables. The present study further expands the HC-BioSIM methodology to soil and sediment systems using a database of 2195 half-life (i.e., degradation time [DT]50) entries for HCs in soil and sediment. Relevance and reliability criteria were defined based on similarity to standard testing guidelines for biodegradation testing and applied to all entries in the database. The HC-BioSIM soil and sediment models significantly outperformed the existing biodegradation HC half-life (BioHCWin) and virtual evaluation of chemical properties and toxicities (VEGA) quantitative Mario Negri Institute for Pharmacological Research (IRFMN) models in soil and sediment. Average errors in predicted DT50s were reduced by up to 6.3- and 8.7-fold for soil and sediment, respectively. No significant bias as a function of HC class, carbon number, or test system parameters was observed. Model diagnostics demonstrated low variability in performance and high consistency of parameter usage/importance and rule structure, supporting the generalizability and stability of the models for application to external data sets. The HC-BioSIM provides improved accuracy of Persistence categorization, with correct classification rates of 83.9%, and 90.6% for soil and sediment, respectively, demonstrating a significant improvement over the existing BioHCWin (70.7% and 58.6%) and VEGA (59.5% and 18.5%) models. Environ Toxicol Chem 2024;43:1352-1363. © 2024 Concawe. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Using UV/peracetic acid as pretreatment for subsequent bio-treatment of antibiotic-containing wastewater treatment: Mitigating microbial inhibition and antibiotic resistance genes proliferation

UV/peracetic acid (PAA) treatment presents a promising approach for antibiotic removal, but its effects on microbial community and proliferation of antibiotic resistance genes (ARGs) during the subsequent bio-treatment remain unclear. Thus, we evaluated the effects of the UV/PAA on tetracycline (TTC) degradation, followed by introduction of the treated wastewater into the bio-treatment system to monitor changes in ARG expression and biodegradability. Results demonstrated effective TTC elimination by the UV/PAA system, with carbon-centered radicals playing a significant role. Crucially, the UV/PAA system not only eliminated antibacterial activity but also inhibited potential ARG host growth, thereby minimizing the emergence and dissemination of ARGs during subsequent bio-treatment. Additionally, the UV/PAA system efficiently removed multi-antibiotic resistant bacteria and ARGs from the bio-treatment effluent, preventing ARGs from being released into the environment. Hence, we propose a multi-barrier strategy for treating antibiotic-containing wastewater, integrating UV/PAA pre-treatment and post-disinfection with bio-treatment. The inhibition of ARGs transmission by the integrated system was verified through actual soil testing, confirming its effectiveness in preventing ARGs dissemination in the surrounding natural ecosystem. Overall, the UV/PAA treatment system offers a promising solution for tackling ARGs challenges by controlling ARGs proliferation at the source and minimizing their release at the end of the treatment process.

Exploring pollutant joint effects in disease through interpretable machine learning

Identifying the impact of pollutants on diseases is crucial. However, assessing the health risks posed by the interplay of multiple pollutants is challenging. This study introduces the concept of Pollutants Outcome Disease, integrating multidisciplinary knowledge and employing explainable artificial intelligence (AI) to explore the joint effects of industrial pollutants on diseases. Using lung cancer as a representative case study, an extreme gradient boosting predictive model that integrates meteorological, socio-economic, pollutants, and lung cancer statistical data is developed. The joint effects of industrial pollutants on lung cancer are identified and analyzed by employing the SHAP (Shapley Additive exPlanations) interpretable machine learning technique. Results reveal substantial spatial heterogeneity in emissions from CPG and ILC, highlighting pronounced nonlinear relationships among variables. The model yielded strong predictions (an R of 0.954, an RMSE of 4283, and an R2 of 0.911) and emphasized the impact of pollutant emission amounts on lung cancer responses. Diverse joint effects patterns were observed, varying in terms of patterns, regions (frequency), and the extent of antagonistic and synergistic effects among pollutants. The study provides a new perspective for exploring the joint effects of pollutants on diseases and demonstrates the potential of AI technology to assist scientific discovery.

In Silico Insights into the Arsenic Binding Mechanism Deploying Application of Computational Biology-Based Toolsets

An assortment of environmental matrices includes arsenic (As) in its different oxidation states, which is often linked to concerns that pose a threat to public health worldwide. The current difficulty lies in addressing toxicological concerns and achieving sustained detoxification of As. Multiple conventional degradation methods are accessible; however, they are indeed labor-intensive, expensive, and reliant on prolonged laboratory evaluations. Molecular interaction and atomic level degradation mechanisms for enzyme-As exploration are, however, underexplored in those approaches. A feasible approach in this case for tackling this accompanying concern of As might be to cope with undertaking multivalent computational methodologies and tools. This work aimed to provide molecular-level insight into the enzyme-aided As degradation mechanism. AutoDock Vina, CABS-flex 2.0, and Desmond high-performance molecular dynamics simulation (MDS) were utilized in the current investigation to simulate multivalent molecular processes on two protein sets: arsenate reductase (ArsC) and laccase (LAC) corresponding arsenate (ART) and arsenite (AST), which served as model ligands to comprehend binding, conformational, and energy attributes. The structural configurations of both proteins exhibited variability in flexibility and structure framework within the range of 3.5-4.5 Å. The LAC-ART complex exhibited the lowest calculated binding affinity, measuring -5.82 ± 0.01 kcal/mol. Meanwhile, active site residues ILE-200 and HIS-206 were demonstrated to engage in H-bonding with the ART ligand. In contrast to ArsC, the ligand binding affinity of this bound complex was considerably greater. Additional validation of docked complexes was carried out by deploying Desmond MDS of 100 ns to capture protein and ligand conformation behavior. The system achieved stability during the 100 ns simulation run, as confirmed by the average P-L RMSD, which was ∼1 Å. As a preliminary test of the enzyme's ability to catalyze As species, corresponding computational insights might be advantageous for bridging gaps and regulatory consideration.

Covalent organic frameworks: Pioneering remediation solutions for organic pollutants

Covalent Organic Frameworks (COFs) have emerged as a promising class of crystalline porous materials with customizable structures, high surface areas, and tunable functionalities. Their unique properties make them attractive candidates for addressing environmental contamination caused by pharmaceuticals, pesticides, industrial chemicals, persistent organic pollutants (POPs), and endocrine disruptors (EDCs). This review article provides a comprehensive overview of recent advancements and applications of COFs in removing and remedying various environmental contaminants. We delve into the synthesis, properties, and performance of COFs and their potential limitations and future prospects.

Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation

Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.

Improving predictions and understanding of primary and ultimate biodegradation rates with machine learning models

This study aimed to develop machine learning based quantitative structure biodegradability relationship (QSBR) models for predicting primary and ultimate biodegradation rates of organic chemicals, which are essential parameters for environmental risk assessment. For this purpose, experimental primary and ultimate biodegradation rates of high consistency were compiled for 173 organic compounds. A significant number of descriptors were calculated with a collection of quantum/computational chemistry software and tools to achieve comprehensive representation and interpretability. Following a pre-screening process, multiple QSBR models were developed for both primary and ultimate endpoints using three algorithms: extreme gradient boosting (XGBoost), support vector machine (SVM), and multiple linear regression (MLR). Furthermore, a unified QSBR model was constructed using the knowledge transfer technique and XGBoost. Results demonstrated that all QSBR models developed in this study had good performance. Particularly, SVM models exhibited high level of goodness of fit (coefficient of determination on the training set of 0.973 for primary and 0.980 for ultimate), robustness (leave-one-out cross-validated coefficient of 0.953 for primary and 0.967 for ultimate), and external predictive ability (external explained variance of 0.947 for primary and 0.958 for ultimate). The knowledge transfer technique enhanced model performance by learning from properties of two biodegradation endpoints. Williams plots were used to visualize the application domains of the models. Through SHapley Additive exPlanations (SHAP) analysis, this study identified key features affecting biodegradation rates. Notably, MDEO-12, APC2D1_C_O, and other features contributed to primary biodegradation, while AATS0v, AATS2v, and others inhibited it. For ultimate biodegradation, features like No. of Rotatable Bonds, APC2D1_C_O, and minHBa were contributors, while C1SP3, Halogen Ratio, GGI4, and others hindered the process. Also, the study quantified the contributions of each feature in predictions for individual chemicals. This research provides valuable tools for predicting both primary and ultimate biodegradation rates while offering insights into the mechanisms.

Bio-mitigation of organic pollutants using horseradish peroxidase as a promising biocatalytic platform for environmental sustainability

A wide array of environmental pollutants is often generated and released into the ecosystem from industrial and human activities. Antibiotics, phenolic compounds, hydroquinone, industrial dyes, and Endocrine-Disrupting Chemicals (EDCs) are prevalent pollutants in water matrices. To promote environmental sustainability and minimize the impact of these pollutants, it is essential to eliminate such contaminants. Although there are multiple methods for pollutants removal, many of them are inefficient and environmentally unfriendly. Horseradish peroxidase (HRP) has been widely explored for its ability to oxidize the aforementioned pollutants, both alone and in combination with other peroxidases, and in an immobilized way. Numerous positive attributes make HRP an excellent biocatalyst in the biodegradation of diverse environmentally hazardous pollutants. In the present review, we underlined the major advancements in the HRP for environmental research. Numerous immobilization and combinational studies have been reviewed and summarized to comprehend the degradability, fate, and biotransformation of pollutants. In addition, a possible deployment of emerging computational methodologies for improved catalysis has been highlighted, along with future outlook and concluding remarks.

Toxicity assessment of a novel biopesticide guvermectin and identification of its transformation products in soils

Guvermectin is a novel biopesticide often used as seed soaking to promote the rice yield. However, its biotoxicity and degradation behavior in soils were still not disclosed, which posed a knowledge gap to guide its rational application. Therefore, the degradation behaviors of guvermectin in four typical soils under aerobic and anaerobic conditions were investigated in the laboratory. The results showed that guvermectin was degraded fast with DT50 ranging from 0.95 to 10.10 d, and the degradation rate was higher in aerobic condition than that in anaerobic condition. Eight transformation products were screened using UPLC-QTOF/MS. The acute toxicities tests of guvermectin to Coturnix coturnix japonica and Apis mellifera were measured by biological laboratory experiments, and the acute and chronic toxicities of transformation products to Danio rerio, Daphnia magna Straus and Green algae were predicted by ECOSAR software. The results showed that guvermectin has low toxic to quail and honeybee (LD50 2000 mg a.i./kg body weight, LD50 ˃ 100 μg a.i./bee), and its transformation products were also low toxic class to Danio rerio, Daphnia magna Straus and Green algae (LC50/EC50 > 100 mg a.i./L). However, the nucleoside-like metabolites may pose a potential risk due to their similarity to genetic material, which should be concerned. The findings provided important environmental risk assessment data for the rational use of guvermectin.

Combining computational tools and experimental studies towards endocrine disruptors mitigation: A review of biocatalytic and adsorptive processes

The endocrine disruptors (EDCs) are an important group of emerging contaminants, and their mitigation has been a huge challenge due to their chemistry complexity and variety of these compounds. The traditional treatments are inefficient to completely remove EDCs, and adsorptive processes are the major alternative investigated on their removal. Also, the use of EDCs degrading enzymes has been encouraged due to ecofriendly approach of biocatalytic processes. This paper highlights the occurrence, classification, and toxicity of EDCs with special focus in the use of enzyme-based and adsorptive technologies in the elimination of EDCs from ambiental matrices. Numerous prior reviews have focused on the discussions toward these technologies. However, the literature lacks theoretical discussions about important aspects of these methods such as the mechanisms of EDCs adsorption on the adsorbent surface or the interactions between degrading enzymes - EDCs. In this sense, theoretical calculations combined to experimental studies may help in the development of more efficient technologies to EDCs mitigation. In this review, we point out how computational tools such as molecular docking and molecular dynamics have to contribute to the design of new adsorbents and efficient catalytic processes towards endocrine disruptors mitigation.

Bioremediation of contaminated soil and groundwater by in situ biostimulation

Bioremediation by in situ biostimulation is an attractive alternative to excavation of contaminated soil. Many in situ remediation methods have been tested with some success; however, due to highly variable results in realistic field conditions, they have not been implemented as widely as they might deserve. To ensure success, methods should be validated under site-analogous conditions before full scale use, which requires expertise and local knowledge by the implementers. The focus here is on indigenous microbial degraders and evaluation of their performance. Identifying and removing biodegradation bottlenecks for degradation of organic pollutants is essential. Limiting factors commonly include: lack of oxygen or alternative electron acceptors, low temperature, and lack of essential nutrients. Additional factors: the bioavailability of the contaminating compound, pH, distribution of the contaminant, and soil structure and moisture, and in some cases, lack of degradation potential which may be amended with bioaugmentation. Methods to remove these bottlenecks are discussed. Implementers should also be prepared to combine methods or use them in sequence. Chemical/physical means may be used to enhance biostimulation. The review also suggests tools for assessing sustainability, life cycle assessment, and risk assessment. To help entrepreneurs, decision makers, and methods developers in the future, we suggest founding a database for otherwise seldom reported unsuccessful interventions, as well as the potential for artificial intelligence (AI) to assist in site evaluation and decision-making.

Unlocking secrets of microbial ecotoxicology: recent achievements and future challenges

Environmental pollution is one of the main challenges faced by humanity. By their ubiquity and vast range of metabolic capabilities, microorganisms are affected by pollution with consequences on their host organisms and on the functioning of their environment. They also play key roles in the fate of pollutants through the degradation, transformation, and transfer of organic or inorganic compounds. Thus, they are crucial for the development of nature-based solutions to reduce pollution and of bio-based solutions for environmental risk assessment of chemicals. At the intersection between microbial ecology, toxicology, and biogeochemistry, microbial ecotoxicology is a fast-expanding research area aiming to decipher the interactions between pollutants and microorganisms. This perspective paper gives an overview of the main research challenges identified by the Ecotoxicomic network within the emerging One Health framework and in the light of ongoing interest in biological approaches to environmental remediation and of the current state of the art in microbial ecology. We highlight prevailing knowledge gaps and pitfalls in exploring complex interactions among microorganisms and their environment in the context of chemical pollution and pinpoint areas of research where future efforts are needed.

Gelatin Methacryloyl Hydrogel, from Standardization, Performance, to Biomedical Application

Gelatin methacryloyl (GelMA), a photocurable hydrogel, is widely used in 3D culture, particularly in 3D bioprinting, due to its high biocompatibility, tunable physicochemical properties, and excellent formability. However, as the properties and performances of GelMA vary under different synthetic conditions, there is a lack of standardization, leading to conflicting results. In this study, a uniform standard is established to understand and enhance GelMA applications. First, the basic concept of GelMA and the density of the molecular network (DMN) are defined. Second, two properties, degrees of substitution and ratio of solid content, as the main measurable parameters determining the DMN are used. Third, the mechanisms and relationships between DMN and its performance in various applications in terms of porosity, viscosity, formability, mechanical strength, swelling, biodegradation, and cytocompatibility are theoretically explained. The main questions that are answered: what does performance mean, why is it important, how to optimize the basic parameters to improve the performance, and how to characterize it reasonably and accurately? Finally, it is hoped that this knowledge will eliminate the need for researchers to conduct tedious and repetitive pre-experiments, enable easy communication for achievements between groups under the same standard, and fully explore the potential of the GelMA hydrogel.

Assessment of the Presence of Transformation Products of Certain Pharmaceutical Products (Psychotropic Family) by Suspect and Non-Targeted HRMS Screening in Wastewater Treatment Plants

Aquatic environments are the final receptors of human emissions and are therefore contaminated by molecules, such as pharmaceuticals. After use, these compounds and their metabolites are discharged to wastewater treatment plants (WWTPs). During wastewater treatment, compounds may be eliminated or degraded into transformation products (TPs) or may be persistent. The aim of this study was to develop an analytical method based on high resolution mass spectrometry (HRMS) for the identification of six psychotropic drugs that are widely consumed in France and present in WWTPs, as well as their potential associated metabolites and TPs. Four out of six psychotropic drugs and between twenty-five and thirty-seven potential TPs were detected in wastewater, although this was based on full scan data. TPs not reported in the literature and specific to the study sites and therefore to the wastewater treatment processes were tentatively identified. For the selected drugs, most known and present TPs were identified, such as desmethylvenlafaxine or norcitalopram. Moreover, the short fragmentation study led rather to the identification of several TPs of carbamazepine as ubiquitous persistent TPs.

Combining predictive and analytical methods to elucidate pharmaceutical biotransformation in activated sludge

While man-made chemicals in the environment are ubiquitous and a potential threat to human health and ecosystem integrity, the environmental fate of chemical contaminants such as pharmaceuticals is often poorly understood. Biodegradation processes driven by microbial communities convert chemicals into transformation products (TPs) that may themselves have adverse ecological effects. The detection of TPs formed during biodegradation has been continuously improved thanks to the development of TP prediction algorithms and analytical workflows. Here, we contribute to this advance by (i) reviewing past applications of TP identification workflows, (ii) applying an updated workflow for TP prediction to 42 pharmaceuticals in biodegradation experiments with activated sludge, and (iii) benchmarking 5 different pathway prediction models, comprising 4 prediction models trained on different datasets provided by enviPath, and the state-of-the-art EAWAG pathway prediction system. Using the updated workflow, we could tentatively identify 79 transformation products for 31 pharmaceutical compounds. Compared to previous works, we have further automatized several steps that were previously performed by hand. By benchmarking the enviPath prediction system on experimental data, we demonstrate the usefulness of the pathway prediction tool to generate suspect lists for screening, and we propose new avenues to improve their accuracy. Moreover, we provide a well-documented workflow that can be (i) readily applied to detect transformation products in activated sludge and (ii) potentially extended to other environmental studies.

Pesticide pestilence: Global scenario and recent advances in detection and degradation methods

Increased anthropogenic activities are confronted as the main cause for rising environmental and health concerns globally, presenting an indisputable threat to both environment and human well-being. Modern-day industrialization has given rise to a cascade of concurrent environmental and health challenges. The global human population is growing at an alarming rate, posing tremendous pressure on future food security, and healthy and environmentally sustainable diets for all. To feed all, the global food production needs to increase by 50% by 2050, but this increase has to occur from the limited arable land, and under the present-day climate variabilities. Pesticides have become an integral component of contemporary agricultural system, safeguarding crops from pests and diseases and their use must be reduce to fulfill the SDG (Sustainable Development Goals) agenda . However, their indiscriminate use, lengthy half-lives, and high persistence in soil and aquatic ecosystems have impacted global sustainability, overshot the planetary boundaries and damaged the pure sources of life with severe and negative impacts on environmental and human health. Here in this review, we have provided an overview of the background of pesticide use and pollution status and action strategies of top pesticide-using nations. Additionally, we have summarized biosensor-based methodologies for the rapid detection of pesticide residue. Finally, omics-based approaches and their role in pesticide mitigation and sustainable development have been discussed qualitatively. The main aim of this review is to provide the scientific facts for pesticide management and application and to provide a clean, green, and sustainable environment for future generations.

Microbe-Plant Interactions Targeting Metal Stress: New Dimensions for Bioremediation Applications

In the age of industrialization, numerous non-biodegradable pollutants like plastics, HMs, polychlorinated biphenyls, and various agrochemicals are a serious concern. These harmful toxic compounds pose a serious threat to food security because they enter the food chain through agricultural land and water. Physical and chemical techniques are used to remove HMs from contaminated soil. Microbial-metal interaction, a novel but underutilized strategy, might be used to lessen the stress caused by metals on plants. For reclaiming areas with high levels of heavy metal contamination, bioremediation is effective and environmentally friendly. In this study, the mechanism of action of endophytic bacteria that promote plant growth and survival in polluted soils-known as heavy metal-tolerant plant growth-promoting (HMT-PGP) microorganisms-and their function in the control of plant metal stress are examined. Numerous bacterial species, such as Arthrobacter, Bacillus, Burkholderia, Pseudomonas, and Stenotrophomonas, as well as a few fungi, such as Mucor, Talaromyces, Trichoderma, and Archaea, such as Natrialba and Haloferax, have also been identified as potent bioresources for biological clean-up. In this study, we additionally emphasize the role of plant growth-promoting bacteria (PGPB) in supporting the economical and environmentally friendly bioremediation of heavy hazardous metals. This study also emphasizes future potential and constraints, integrated metabolomics approaches, and the use of nanoparticles in microbial bioremediation for HMs.

Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology-A review

Lignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization of lignin, oxidative cleavage of xenobiotics and phenolics. LMEs implementation in the biotechnological and industrial sectors has sparked significant attention, although its potential future applications remain underexploited. To understand the mechanism of LMEs in sustainable pollution mitigation, several studies have been undertaken to assess the feasibility of LMEs in correlating to diverse pollutants for binding and intermolecular interactions at the molecular level. However, further investigation is required to fully comprehend the underlying mechanism. In this review we presented the key structural and functional features of LMEs, including the computational aspects, as well as the advanced applications in biotechnology and industrial research. Furthermore, concluding remarks and a look ahead, the use of LMEs coupled with computational frameworks, built upon artificial intelligence (AI) and machine learning (ML), has been emphasized as a recent milestone in environmental research.

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.

Phytotoxicity and cytotoxicity attributes of immobilized Bacillus cereus treated and untreated textile effluents on Vigna mungo seeds and Artemia franciscana larvae

The physicochemical attributes of textile effluents collected from secondary treatment stage was investigated in this study and also assess the biosorption potential of membrane immobilized Bacillus cereus and free form of Bacillus cereus on textile effluent through bioreactor model study to find a sustainable solution to manage the textile effluent as vital need. Furthermore, the phytotoxicity and cytotoxicity nature of treated and untreated textile effluents on Vigna mungo and Artemia franciscana larvae under laboratory conditions as a novel approach. The textile effluent physicochemical parameter analysis results showed that the properties such as colour (Hazen unit), pH, turbidity, As, Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Cd, Cl, Cr, Cu, Hg, Ni, Pb, SO₄^2-, and Zn were beyond the acceptable limits. Bacillus cereus immobilized on a polyethylene membrane eliminated greater amounts of dye (25.0 ± 1.3, 56.5 ± 1.8, 57.18 ± 1.5, and 54.34 ± 1.7 Hazen unit from An1, Ae2, Ve3, and So4 respectively) and pollutants (As: 0.9-2.0, Cd: 6-8, Cr: 300-450, Cu: 5-7, Hg: 0.1-0.7, Ni: 8-14, Pb: 4-5, and Zn: 4-8 mg L^-1) from textile effluent in a week of biosorption investigation using a bioreactor model (batch type) compared to a free form of B. cereus on textile effluent. The phytotoxicity and cytotoxicity study results revealed that the membrane immobilized B. cereus treated textile effluent exposure showed reduced phytotoxicity and minimal cytotoxicity (including mortality) percentage compared with free form B. cereus treated and untreated textile effluents. These entire results conclude that the membrane immobilized B. cereus may considerably minimize/detoxify the harmful pollutants from the textile effluents. A large scale level biosorption approach need to be performed to validate the maximum pollutants removing potential of this membrane immobilized bacteria species and optimal conditions for effective remediation.

Deciphering the recent trends in pesticide bioremediation using genome editing and multi-omics approaches: a review

Pesticide pollution in recent times has emerged as a grave environmental problem contaminating both aquatic and terrestrial ecosystems owing to their widespread use. Bioremediation using gene editing and system biology could be developed as an eco-friendly and proficient tool to remediate pesticide-contaminated sites due to its advantages and greater public acceptance over the physical and chemical methods. However, it is indispensable to understand the different aspects associated with microbial metabolism and their physiology for efficient pesticide remediation. Therefore, this review paper analyses the different gene editing tools and multi-omics methods in microbes to produce relevant evidence regarding genes, proteins and metabolites associated with pesticide remediation and the approaches to contend against pesticide-induced stress. We systematically discussed and analyzed the recent reports (2015-2022) on multi-omics methods for pesticide degradation to elucidate the mechanisms and the recent advances associated with the behaviour of microbes under diverse environmental conditions. This study envisages that CRISPR-Cas, ZFN and TALEN as gene editing tools utilizing Pseudomonas, Escherichia coli and Achromobacter sp. can be employed for remediation of chlorpyrifos, parathion-methyl, carbaryl, triphenyltin and triazophos by creating gRNA for expressing specific genes for the bioremediation. Similarly, systems biology accompanying multi-omics tactics revealed that microbial strains from Paenibacillus, Pseudomonas putida, Burkholderia cenocepacia, Rhodococcus sp. and Pencillium oxalicum are capable of degrading deltamethrin, p-nitrophenol, chlorimuron-ethyl and nicosulfuron. This review lends notable insights into the research gaps and provides potential solutions for pesticide remediation by using different microbe-assisted technologies. The inferences drawn from the current study will help researchers, ecologists, and decision-makers gain comprehensive knowledge of value and application of systems biology and gene editing in bioremediation assessments.

The essential role of GSTP1 I105V polymorphism in the prediction of CDNB metabolism and toxicity: In silico and in vitro insights

Humans are continuously exposed to toxic chemicals such as nitro-chlorobenzene (CDNB) through occupation, water, and even the air we breathe. Due to the severe toxicity caused by the high electrophilicity of CDNB, occupational and environmental exposure to CDNB can produce toxic effects that ultimately lead to cell damage. CDNB can be eliminated from organisms by binding to GSH, the catalytic product of glutathione S-transferase P1 (GSTP1). Therefore, GSTP1 plays an important role in the detoxification of CDNB. However, subtle variations in GSTP1 can result in single nucleotide polymorphisms (SNPs). Indeed, the correlation between the clinical outcome of the disease and certain genotypes of GSTP1 has been extensively studied, however, their impact on the metabolic detoxification of toxicants such as CDNB remains to be elucidated. Among the various SNPs of GSTP1, I105V has a significant effect on the catalytic activity of GSTP1. In this paper, a GSTP1 I105V polymorphism model was successfully established, and its effect on CDNB metabolism and toxicity was studied by computer analysis including molecular docking and molecular dynamics simulation. The result demonstrated that the binding capacity of CDNB decreases with the I105V mutation of GSTP1(p < 0.001), indicating the changes in its detoxification efficacy in CDNB-induced cell damage. Organisms expressing GSTP1 V105 are more susceptible to cell damage caused by CDNB than individuals expressing GSTP1 I105 (p < 0.001). In sum, the data in this study provide prospective insights into the mechanism and capacity of CDNB detoxification in the GSTP1 allele, extending the CDNB-mediated toxicological profile. In addition, the heterogeneity of the GSTP1 allele should be included in toxicological studies of individuals exposed to CDNB.

Multi-omics approach reveals elevated potential of bacteria for biodegradation of imidacloprid

The residual imidacloprid, a widely used insecticide is causing serious environmental concerns. Knowledge of its biodegradation will help in assessing its residual mass in soil. In view of this, a soil microcosm-based study was performed to test the biodegradation potential of Agrobacterium sp. InxBP2. It achieved ∼88% degradation in 20 days and followed the pseudo-first-order kinetics (k = 0.0511 day^-1 and t_1/2=7 days). Whole genome sequencing of Agrobacterium sp. InxBP2 revealed a genome size of 5.44 Mbp with 5179 genes. Imidacloprid degrading genes at loci K7A42_07110 (ABC transporter substrate-binding protein), K7A42_07270 (amidohydrolase family protein), K7A42_07385 (ABC transporter ATP-binding protein), K7A42_16,845 (nitronate monooxygenase family protein), and K7A42_20,660 (FAD-dependent monooxygenase) having sequence and functional similarity with known counterparts were identified. Molecular docking of proteins encoded by identified genes with their respective degradation pathway intermediates exhibited significant binding energies (-6.56 to -4.14 kcal/mol). Molecular dynamic simulation discovered consistent interactions and binding depicting high stability of docked complexes. Proteome analysis revealed differential protein expression in imidacloprid treated versus untreated samples which corroborated with the in-silico findings. Further, the detection of metabolites proved the bacterial degradation of imidacloprid. Thus, results provided a mechanistic link between imidacloprid and associated degradative genes/enzymes of Agrobacterium sp. InxBP2. These findings will be of immense significance in carrying out the lifecycle analysis and formulating strategies for the bioremediation of soils contaminated with insecticides like imidacloprid.

Sustainable Design of Structural and Functional Polymers for a Circular Economy

To achieve a sustainable circular economy, polymer production must start transitioning to recycled and biobased feedstock and accomplish CO₂ emission neutrality. This is not only true for structural polymers, such as in packaging or engineering applications, but also for functional polymers in liquid formulations, such as adhesives, lubricants, thickeners or dispersants. At their end of life, polymers must be either collected and recycled via a technical pathway, or be biodegradable if they are not collectable. Advances in polymer chemistry and applications, aided by computational material science, open the way to addressing these issues comprehensively by designing for recyclability and biodegradability. This Review explores how scientific progress, together with emerging regulatory frameworks, societal expectations and economic boundary conditions, paint pathways for the transformation towards a circular economy of polymers.

Petroleum Hydrocarbon Catabolic Pathways as Targets for Metabolic Engineering Strategies for Enhanced Bioremediation of Crude-Oil-Contaminated Environments

Anthropogenic activities and industrial effluents are the major sources of petroleum hydrocarbon contamination in different environments. Microbe-based remediation techniques are known to be effective, inexpensive, and environmentally safe. In this review, the metabolic-target-specific pathway engineering processes used for improving the bioremediation of hydrocarbon-contaminated environments have been described. The microbiomes are characterised using environmental genomics approaches that can provide a means to determine the unique structural, functional, and metabolic pathways used by the microbial community for the degradation of contaminants. The bacterial metabolism of aromatic hydrocarbons has been explained via peripheral pathways by the catabolic actions of enzymes, such as dehydrogenases, hydrolases, oxygenases, and isomerases. We proposed that by using microbiome engineering techniques, specific pathways in an environment can be detected and manipulated as targets. Using the combination of metabolic engineering with synthetic biology, systemic biology, and evolutionary engineering approaches, highly efficient microbial strains may be utilised to facilitate the target-dependent bioprocessing and degradation of petroleum hydrocarbons. Moreover, the use of CRISPR-cas and genetic engineering methods for editing metabolic genes and modifying degradation pathways leads to the selection of recombinants that have improved degradation abilities. The idea of growing metabolically engineered microbial communities, which play a crucial role in breaking down a range of pollutants, has also been explained. However, the limitations of the in-situ implementation of genetically modified organisms pose a challenge that needs to be addressed in future research.

Understanding the biodegradation pathways of azo dyes by immobilized white-rot fungus, Trametes hirsuta D7, using UPLC-PDA-FTICR MS supported by in silico simulations and toxicity assessment

No biodegradation methods are absolute in the treatment of all textile dyes, which leads to structure-dependent degradation. In this study, biodegradation of three azo dyes, reactive black 5 (RB5), acid blue 113 (AB113), and acid orange 7 (AO7), was investigated using an immobilized fungus, Trametes hirsuta D7. The degraded metabolites were identified using UPLC-PDA-FTICR MS and the biodegradation pathway followed was proposed. RB5 (92%) and AB113 (97%) were effectively degraded, whereas only 30% of AO7 was degraded. Molecular docking simulations were performed to determine the reason behind the poor degradation of AO7. Weak binding affinity, deficiency in H-bonding interactions, and the absence of interactions between the azo (-NN-) group and active residues of the model laccase enzyme were responsible for the low degradation efficiency of AO7. Furthermore, cytotoxicity and genotoxicity assays confirmed that the fungus-treated dye produced non-toxic metabolites. The observations of this study will be useful for understanding and further improving enzymatic dye biodegradation.

Assessing chemical hazard and unraveling binding affinity of priority pollutants to lignin modifying enzymes for environmental remediation

Lignin-modifying enzymes (LMEs) are impactful biocatalysts in environmental remediation applications. However, LMEs-assisted experimental degradation neglects the molecular basis of pollutant degradation. Furthermore, throughout the remediation process, the inherent hazards of environmental pollutants remain untapped for in-depth toxicological endpoints. In this investigation, a predictive toxicological framework and a computational framework adopting LMEs were employed to assess the hazards of Priority Pollutants (PP) and its possible LMEs-assisted catalytic screening. The potential hazardous outcomes of PP were assessed using Quantitative structure-activity relationship (QSARs)-based techniques including Toxtree, ECOSAR, and T.E.S.T. tools. Toxicological findings revealed positive outcomes in a multitude of endpoints for all PP. The PP compound 2,3,7,8-TCDD (dioxin) was found to exhibit the lowest concentration of aquatic toxicity implementing aquatic model systems; LC₅₀ as 0.01, 0.01, 0.04 (mg L^-1) for Fish (96 H), Daphnid (48 H), Green algae (96 H) respectively. T.E.S.T. results revealed that chloroform, and 2-chlorophenol both seem to be developmental toxicants. Subsequently, LMEs-assisted docking procedure was employed in predictive mitigation of PP. The docking approach as predicted degradation revealed the far lowest docking energy score for Versatile peroxidase (VP)- 2,3,7,8-TCDD docked complex with a binding energy of -9.2 (kcal mol^-1), involved PHE-46, PRO-139, PRO-141, ILE-148, LEU-165, HIS-169, LEU-228, MET-262, and MET-265 as key interacting amino acid residues. Second most ranked but lesser than VP, Lignin peroxidase (LiP)- 2,3,7,8-TCDD docked complex exhibited a rather lower binding affinity score (-8.8 kcal mol^-1). Predictive degradation screening employing comparative docking revealed varying binding affinities, portraying that each LMEs member has independent feasibility to bind PP as substrate. Predictive findings endorsed the hazardous nature of associated PP in a multitude of endpoints, which could be attenuated by undertaking LMEs as a predictive approach to protect the environment and implement it in regulatory considerations.

In vivo degradation of polyethylene terephthalate using microbial isolates from plastic polluted environment

Accumulation of plastics alarms a risk to the environment worldwide. As polyethylene pterephthalate (PET) degrades slowly and produces hazardous substances, therefore, it is now essential to eliminate plastic wastes from the environment. Given that, the current study is concerned with PET degradation potential of naturally occurring microbial strains isolated from plastic waste dumping sites, Sarcina aurantiaca (TB3), Bacillus subtilis (TB8), Aspergillus flavus (STF1), Aspergillus niger (STF2). To test the biodegradability of PET films, the films were incubated for 60 days at 37 °C with the microorganisms designated as TB3, TB8, STF1, STF2 and the microbial consortium (TB3+TB8+STF1+STF2) in Minimal Salt Medium and Bushnell Hass Broth. Hydrophobicity, viability, and total protein content of isolates were investigated. Using Field Emission Scanning Electron Microscopy and Fourier Transform Infrared Spectrophotometry to measure variations in functional groups and carbonyl index on PET surface, biodegradation process was affirmed by fissures and modified surfaces. Results revealed that the microbial consortium (S. aurantiaca + B. subtilis + A. flavus + A. niger) that the weight loss of PET films was 28.78%. The microbial consortium could be used to treat PET waste, posing no health or environmental risks. The developed microbial consortium has the potential to degrade PET, hence can be employed for eliminating PET in plastic contaminated sites.

Latest eco-friendly approaches for pesticides decontamination using microorganisms and consortia microalgae: A comprehensive insights, challenges, and perspectives

Pesticides are chemical compounds that are considered toxic to many organisms, including humans. Their elimination from polluted sites attracted the attention of Scientifics in the last decade; Among the various methods used to decontaminate pesticides from the environment, the microbial-algae consortium is a promising bioremediation technology, which implies several advantages as an eco-friendly process that generate biomass produced that could be valorized in the form of bioenergy, In this review, we will discuss the latest eco-friendly approaches using microorganisms to remediate sites contaminated by pesticides, and shows the ability of microbial, algae and their consortium to remove pesticides and the role of different enzymes in degradation processes.

Recent advances in assessment methods and mechanism of microbe-mediated chlorpyrifos remediation

Chlorpyrifos (CP) is one of the Organophosphorus pesticides (OPs) primarily used in agriculture to safeguard crops from pests and diseases. The pervasive use of chlorpyrifos is hazardous to humans and the environment as it inhibits the receptor for acetylcholinesterase activity, leading to abnormalities linked to the central nervous system. Hence, there is an ardent need to develop an effective and sustainable approach to the on-site degradation of chlorpyrifos. The role of microbes in the remediation of pesticides is considered the most effective and eco-friendly approach, as they have strong degradative potential due to their gene and enzymes naturally adapted to these sites. Several reports have previously been published on exploring the role of microbes in the degradation of CP. However, detection of CP as an environmental contaminant is an essential prerequisite for developing an efficient microbial-mediated biodegradation method with less harmful intermediates. Most of the articles published to date discuss the fate and impact of CP in the environment along with its degradation mechanism but still fail to discuss the analytical portion. This review is focused on the latest developments in the field of bioremediation of CP along with its physicochemical properties, toxicity, fate, and conventional (UV-Visible spectrophotometer, FTIR, NMR, GC-MS, etc) and advanced detection methods (Biosensors and immunochromatography-based methods) from different environmental samples. Apart from it, this review explores the role of metagenomics, system biology, in-silico tools, and genetic engineering in facilitating the bioremediation of CP. One of the objectives of this review is to educate policymakers with scientific data that will enable the development of appropriate strategies to reduce pesticide exposure and the harmful health impacts on both Human and other environmental components. Moreover, this review provides up-to-date developments related to the sustainable remediation of CP.

Bioremediation of Endocrine Disrupting Chemicals- Advancements and Challenges

Endocrine Disrupting Chemicals (EDCs), major group of recalcitrant compounds, poses a serious threat to the health and future of millions of human beings, and other flora and fauna for years to come. A close analysis of various xenobiotics undermines the fact that EDC is structurally diverse chemical compounds generated as a part of anthropogenic advancements as well as part of their degradation. Regardless of such structural diversity, EDC is common in their ultimate drastic effect of impeding the proper functioning of the endocrinal system, basic physiologic systems, resulting in deregulated growth, malformations, and cancerous outcomes in animals as well as humans. The current review outlines an overview of various EDCs, their toxic effects on the ecosystem and its inhabitants. Conventional remediation methods such as physico-chemical methods and enzymatic approaches have been put into action as some form of mitigation measures. However, the last decade has seen the hunt for newer technologies and methodologies at an accelerated pace. Genetically engineered microbial degradation, gene editing strategies, metabolic and protein engineering, and in-silico predictive approaches - modern day's additions to our armamentarium in combating the EDCs are addressed. These additions have greater acceptance socially with lesser dissonance owing to reduced toxic by-products, lower health trepidations, better degradation, and ultimately the prevention of bioaccumulation. The positive impact of such new approaches on controlling the menace of EDCs has been outlaid. This review will shed light on sources of EDCs, their impact, significance, and the different remediation and bioremediation approaches, with a special emphasis on the recent trends and perspectives in using sustainable approaches for bioremediation of EDCs. Strict regulations to prevent the release of estrogenic chemicals to the ecosystem, adoption of combinatorial methods to remove EDC and prevalent use of bioremediation techniques should be followed in all future endeavors to combat EDC pollution. Moreover, the proper development, growth and functioning of future living forms relies on their non-exposure to EDCs, thus remediation of such chemicals present even in nano-concentrations should be addressed gravely.

Exolaccase-boosted humification for agricultural applications

Globally, phenolic contaminants have posed a considerable threat to agro-ecosystems. Exolaccase-boosted humification may be an admirable strategy for phenolic detoxification by creating multifunctional humic-like products (H-LPs). Nonetheless, the potential applicability of the formed H-LPs in agricultural production is still overlooked. This review describes immobilized exolaccase-enabled humification in eliminating phenolic pollutants and producing artificial H-LPs. The similarities and differences between artificial H-LPs and natural humic substances (HSs) in chemical properties are compared. In particular, the agronomic effects of these reproducible artificial H-LPs are highlighted. On the basis of the above summary, the granulation process is employed to prepare granular humic-like organic fertilizers, which can be applied to field crops by mechanical side-deep fertilization. Finally, the challenges and perspectives of exolaccase-boosted humification for practical applications are also discussed. This review is a first step toward a more profound understanding of phenolic detoxification, soil improvement, and agricultural production by exolaccase-boosted humification.

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Exolaccase-initiated humification is conductive to phenolic detoxification

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Multiple humic-like products are created in exolaccase-boosted humification

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Similarities and differences between artificial and natural humus are disclosed

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Humic-like products can be used to sustain soil health and increase crop yield

Classification and Regression Machine Learning Models for Predicting Aerobic Ready and Inherent Biodegradation of Organic Chemicals in Water

Machine learning (ML) is viewed as a promising tool for the prediction of aerobic biodegradation, one of the most important elimination pathways of organic chemicals from the environment. However, available models only have small datasets (<3200 records), make binary classification predictions, evaluate ready biodegradability, and do not incorporate experimental conditions (e.g., system setup and reaction time). This study addressed all these limitations by first compiling a large database of 12,750 records, considering both ready and inherent biodegradation under different conditions, and then developing regression and classification models using different chemical representations and ML algorithms. The best regression model (R² = 0.54 and root mean square error of 0.25) and classification model (the prediction accuracy from 85.1%) achieved very good performance. The model interpretation indicated that the models correctly captured the effects of chemical substructures, following the order of C═O > O═C-O > OH > CH₃ > halogen > branching > N > 6-member ring. The consideration of chemical speciation based on pK_a and α notations did not affect the regression model performance but significantly improved the classification model performance (the accuracy increased to 87.6%). The models also showed large applicability domains and provided reasonable predictions for more than 98% of over 850,000 environmentally relevant chemicals in the Distributed Structure-Searchable Toxicity database. These robust, trustable models were finally made widely accessible through two free online predictors with graphical user interface.

Carbon-based nanocomposite materials with multifunctional attributes for environmental remediation of emerging pollutants

Carbon-based materials are among the most biosynthesized nanocomposites with excellent tunability and multifunctionality features, that other materials fail to demonstrate. Naturally occurring materials, such as alginate (Alg), can be combined and modified by linking the active moieties of various carbon-based materials of interest, such as graphene oxide (GO), carbon nanotubes (CNTs), and mesoporous silica nanocomposite (MSN), among others. Thus, several types of robust nanocomposites have been fabricated and deployed for environmental remediation of emerging pollutants, such as pharmaceutical compounds, toxic dyes, and other environmentally hazardous contaminants of emerging concern. Considering the above critiques and added features of carbon-based nanocomposites, herein, an effort has been made to spotlight the synergies of GO, CNTs, and MSN with Alg and their role in mitigating emerging pollutants. From the information presented in this work, it can be concluded that Alg is a material that has excellent potential. However, its use still requires further tests in different areas and other materials to carry out a holistic investigation that exploits its versatility for environmental remediation purposes.

Robust strategies to eliminate endocrine disruptive estrogens in water resources

The widespread occurrence and ubiquitous distribution of estrogens, i.e., estrone (E1), estradiol (E2), and estriol (E3) in our water matrices, is an issue of global concern. Public and regulatory authorities are concerned and placing joint efforts to eliminate estrogens and related environmentally hazardous compounds, due to their toxic influences on the environmental matrices, ecology, and human health, even at low concentrations. However, most of the available literature is focused on the occurrence of estrogens in different water environments with limited treatment options. Thus, a detailed review to fully cover the several treatment processes is needed. This review comprehensively and comparatively discusses many physical, chemical, and biological-based treatments to eliminate natural estrogens, i.e., estrone (E1), estradiol (E2), and estriol (E3) and related synthetic estrogens, e.g., 17α-ethinylestradiol (EE2) and other related hazardous compounds. The covered techniques include adsorption, nanofiltration, ultrafiltration, ultrasonication, photocatalysis of estrogenic compounds, Fenton, Fenton-like and photo-Fenton degradation of estrogenic compounds, electro-Fenton degradation of estrogenic compounds, ozonation, and biological methods for the removal of estrogenic compounds are thoroughly discussed with suitable examples. The studies revealed that treatment plants based on chemical and biological approaches are cost-friendly for removing estrogenic pollutants. Further, there is a need to properly monitor and disposal of the usage of estrogenic drugs in humans and animals. Additional studies are required to explore a robust and more advanced oxidation treatment strategy that can contribute effectively to industrial-scale applications. This review may assist future investigations, monitoring, and removing estrogenic compounds from various environmental matrices. In concluding remarks, a way forward and future perspectives focusing on bridging knowledge gaps in estrogenic compounds removal are also proposed.

Nano-remediation technologies for the sustainable mitigation of persistent organic pollutants

The absence of novel and efficient methods for the elimination of persistent organic pollutants (POPs) from the environment is a serious concern in the society. The pollutants release into the atmosphere by means of industrialization and urbanization is a massive global hazard. Although, the eco-toxicity associated with nanotechnology is still being debated, nano-remediation is a potentially developing tool for dealing with contamination of the environment, particularly POPs. Nano-remediation is a novel strategy to the safe and long-term removal of POPs. This detailed review article presents an important perspective on latest innovations and future views of nano-remediation methods used for environmental decontamination, like nano-photocatalysis and nanosensing. Different kinds of nanomaterials including nanoscale zero-valent iron (nZVI), carbon nanotubes (CNTs), magnetic and metallic nanoparticles, silica (SiO₂) nanoparticles, graphene oxide, covalent organic frameworks (COFs), and metal organic frameworks (MOFs) have been summarized for the mitigation of POPs. Furthermore, the long-term viability of nano-remediation strategies for dealing with legacy contamination was considered, with a particular emphasis on environmental and health implications. The assessment goes on to discuss the environmental consequences of nanotechnology and offers consensual recommendations on how to employ nanotechnology for a greater present and a more prosperous future.

In silico homology modeling, docking and sequence analysis of some bacterial laccases to unravel enzymatic specificity towards lignin biodegradation

Laccase is a delignifying enzyme that belongs to the oxidoreductase family, and it has long been investigated as a pretreatment agent in biofuel production. In this study, amino acid sequences of five bacterial laccases from Bifidobacterium breve, Klebsiella pneumonia, Pseudodesulfovibrio hydrargyri, Pseudomonas aeruginosa and Veillonella rodentium have been retrieved from UniProtKB for sequence alignment, phylogenetic analysis using MEGA 7.0 and 3 D structure prediction by homology modeling in SWISS-MODEL. Multiple sequence alignment between all the bacterial laccase sequences revealed a similar structural fold, although the overall protein sequence varied greatly with the substrate binding sites. Further molecular docking in AutoDock Vina and MD stimulation (MDS) in GROMACS for those modelled enzymes were performed considering both apo and ligand bound structures considering both apo and its ligand bound form. Investigation of molecular interaction utilizing docking of five bacterial laccases with three substrates (ABTS, DMP and Guaiacol) revealed that ABTS with K. pneumoniae laccase had the highest binding energy of -7.00 kcal/mol. In the current MDS investigation, bacterial laccases demonstrated greater binding and substrate energy in the ligand bound complex than in the apo form for ABTS, DMP and Guaiacol. In most cases of bacterial laccase, MDS revealed that DMP bound complex was more stable within an average RMSD value lower than 0.5 nm throughout 100 ns time scale. Thus, in silico studies undertaken in this work will be useful in determining the stable enzyme-substrate complex which further might improve the enzymatic catalysis of bacterial laccases for lignin breakdown and biofuel generation.

Bisphenol A Analogs Induce Cellular Dysfunction in Human Trophoblast Cells in a Thyroid Hormone Receptor-Dependent Manner: In Silico and In Vitro Analyses

Bisphenol A (BPA) and its analogs are frequently detected in human daily necessities and environmental media. Placental thyroid hormone plays an important role in fetal development. Herein, we followed the adverse outcome pathway (AOP) to explore the toxic mechanisms of BPA and its analogs toward placental thyroid hormone receptor (TR). First, the TOX21 database was used, and the interactions between BPA analogs and the ligand-binding domains (LBDs) of two subtypes of TR (TRα and TRβ) were subjected to in silico screening using molecular docking (MD) and molecular dynamics simulation (MDS). Fluorescence spectra and circular dichroism (CD) showed that BPA and its analogs interfere with TRs as a molecular initiation event (MIE), including static fluorescence quenching and secondary structural content changes in TR-LBDs. Key events (KEs) of the AOP, including the toxicity induced in placental chorionic trophoblast cells (HTR-8/SVneo) by an inverted U-shaped dose effect and changes in ROS levels, were tested in vitro. BPA, BPB, and BPAF significantly changed the expression level of TRβ, and only BPAF significantly downregulated the expression level of TRα. In conclusion, our study contributes to the health risk assessment of BPA and its analogs regarding placental adverse outcomes (AOs).

A predictive toolset for the identification of degradation pattern and toxic hazard estimation of multimeric hazardous compounds persists in water bodies

An array of industrial processing units generates many multimeric hazardous compounds, such as complex technical lignin and its toxic derivatives, thereby persist in expelled water bodies. The inclusion of some group of motifs in the complex technical lignin structure helps it resist degrade biologically, most often even recalcitrant. Relatively small concentrations of lignin are harmful to aquatic organisms and can trigger environmental hazards. Sadly, the entire biotransformation pathway and insightful information about these toxic derivatives are incomplete and missing in the literature. This is mainly because the current conventional treatments often fail to identify all transformed compounds and their environmental fate. Thus, a robust toolset is much needed to cover this literature gap. Inadequate performance of conventional remediation processes and biological degradation patterns can be maximally optimized with the aid of predictive toolset methods that could offer better degradability and complete transformed compound information. A predictive toolset-assisted biodegradation pattern determination is a multifaceted and reliable analytical technique that can help to overcome existing shortcomings by providing an entire transformation pathway. Considering the above critiques, this work reports on the degradation pattern, and toxicological endpoints of five hazardous compounds, i.e., 2-chlorosyringaldehyde, 5-chlorovanillin, catechol, guaiacyl 4-O-5 guaiacyl, and syringyl β-O-4 syringyl β-O-4 sinapyl alcohol, that persists in water matrices. The predictive transformation pattern was revealed notably less complex end-products of catechol as; succinate, and 2-Oxo-4-pentenoate. The gastrointestinal (GI) absorption rate was found high for all tested compounds, excluding trimer compound, i.e., syringyl β-O-4 syringyl β-O-4 sinapyl alcohol. The toxicity and persistence profile tested via Toxtree showed that the Cramer Rules, Verhaar Scheme, and Structural Alerts for Reactivity, (START) biodegradation ability as positive, and all five target compounds were found as class-II persistent compounds. Furthermore, the Ecological Structure-Activity Relationships (ECOSAR)assisted testing specifies that all tested derivatives have multiple aquatic toxic levels. In summary, the current findings endorse the hazardous compounds and undertake prescreening of the deprivation policy to protect the environment.

An improved opposition-based crow search algorithm for biodegradable material classification

The development of a reliable quantitative structure-activity relationship (QSAR) classification model with a small number of molecular descriptors is a crucial step in chemometrics. In this study, an improvement of crow search algorithm (CSA) is proposed by adapting the opposite-based learning (OBL) approach, which is named as OBL-CSA, to improve the exploration and exploitation capability of the CSA in quantitative structure-biodegradation relationship (QSBR) modelling of classifying the biodegradable materials. The results reveal that the performance of OBL-CSA not only manifest in improving the classification performance, but also in reduced computational time required to complete the process when compared to the standard CSA and other four optimization algorithms tested, which are the particle swarm algorithm (PSO), black hole algorithm (BHA), grey wolf algorithm (GWA), and whale optimization algorithm (WOA). In conclusion, the OBL-CSA could be a valuable resource in the classification of biodegradable materials.

Microbial bioremediation strategies with wastewater treatment potentialities - A review

The demand for innovative waste treatment techniques has arisen because of the establishment and operation of rigorous waste discharge guidelines into the environment. Due to the rapid increase in the human population, wastewater treatment is a procedure of increasing significance. As a result, wastewater treatment systems are intended to sustain high activities and densities of such microorganisms which meet the different purification requirements. The waste produced by the pharmaceutical industry, if not adequately treated, has harmful repercussions for the environment as well as public health. Bioremediation is an innovative and optimistic technology that can be used to remove and reduce heavy metals from polluted water and contaminated soil. Because of cost-effectiveness and environmental compatibility, bioremediation using microorganisms has an excellent potential for future development. A diverse range of microorganisms, including algae, fungi, yeasts, and bacteria, can function as biologically active methylators, capable of modifying toxic species. Microorganisms play a crucial role in heavy metal bioremediation. Nanotechnology may minimize industry expenses by producing environmentally friendly nanomaterials to alleviate these contaminants. The use of microorganisms in nanoparticle synthesis gives green biotechnology a positive impetus to cost reduction and sustainable production as a developing nanotechnology sector.

Emerging frontiers in microbe-mediated pesticide remediation: Unveiling role of omics and In silico approaches in engineered environment

The overuse of pesticides for augmenting agriculture productivity always comes at the cost of environment, biodiversity, and human health and has put the land, water, and environmental footprints under severe threat throughout the globe. Underpinning and maximizing the microbiome functions in pesticide-contaminated environments has become a prerequisite for a sustainable environment and resilient agriculture. It is imperative to elucidate the metabolic network of the microbial communities and environmental variables at the contaminated site to predict the best strategy for remediation and soil microbe-pesticide interactions. High throughput next-generation sequencing and in silico analysis allow us to identify and discern the members and characteristics of core microbiomes at the contaminated site. Integration of modern high throughput multi-omics investigations and informatics pipelines provide novel approaches and pathways to capitalize on the core microbiomes for enhancing environmental functioning and mitigation. The role of eco-genomics tools in visualising the microbial network, taxonomy, functional potential, and environmental variables in contaminated habitats is discussed in this review. The integrated role of the potential microbe identification as individual or consortia, mechanistic approach for pesticide degradation, identification of responsible enzymes/genes, and in silico approach is emphasized for the prospects of the area.

In silico analytical toolset for predictive degradation and toxicity of hazardous pollutants in water sources

Different phenolic compounds, including multimeric lignin derivatives in the β-O-4 form, are among the most prevalent compounds in wastewater, often generated from paper industries. Relatively small concentrations of lignin are hazardous to aquatic organisms and can trigger severe environmental hazards. Herein, we present a predictive toolset to insight the induced toxic hazards prediction, and their Lignin peroxidase (LiP)-assisted degradation mechanism of selected multimeric lignin model compounds. T.E.ST and Toxtree toolset were deployed for toxic hazards estimation in different endpoints. To minimize the concerning hazards, we screened multimeric compounds for binding affinity with LiP. The binding affinity was found to be significantly lower than the reference compound. An Extra precision (XP) Glide score of -6.796 kcal/mol was found for dimer (guaiacyl 4-O-5 guaiacyl) complex as lowest compared to reference compound (-4.007 kcal/mol). The active site residues ASP-153, HIP-226, VAL-227, ARG-244, GLU-215, 239, PHE-261 were identified as site-specific key binding AA residues actively involved with corresponding ligands, forming Hydrophobic, H-Bond, π-Stacking, π-π type interactions. The DESMOND-assisted molecular dynamics simulation's (MDS) trajectories of protein-ligand revealed the considerable binding behavior and attained stability and system equilibrium state. Such theoretical and predictive conclusions indicted the feasibility of LiP assisted sustainable mitigation of lignin-based compounds, and such could be used to protect the environment from the potential hazards posed by recognized similar pollutants.

Analytical and regulatory considerations to mitigate highly hazardous toxins from environmental matrices

The ubiquitous occurrence, toxicological influence, and bioaccumulation of toxic entities, e.g., pesticides and toxic elements in the environment, biota, and humans, directly or indirectly, are posing severe social, ecological, and human health concerns. Much attention has been given to the rising bioaccumulation of toxins and their adverse impact on various environmental matrices. For example, the inappropriate and exacerbated use of xenobiotics and related hazardous substances have caused the deterioration of the agricultural environment, e.g., fertile soils where plants are grown. Moreover, the harmful toxins have negatively impacted human health through the trophic chains. However, the analytical and regulatory considerations to effectively monitor and mitigate any or many pesticides and toxic elements from environmental matrices are still lacking in the existing literature. For decades, the scientific community has overseen the consequences caused by pollutants, however, the improvement of analytical detection methods and regulatory considerations are not yet fully covered. This review covers the notable literature gap by stressing the development and deployment of robust analytical and regulatory considerations for an efficient abatement of hazardous substances. Following detailed information on occurrence, toxicological influence, and bioaccumulation of pesticides and toxic elements, the most relevant analytical detection tools and regulatory measures are given herein, with suitable examples, to mitigate or reduce the damage caused by these pollutants.

Covalent organic frameworks-based smart materials for mitigation of pharmaceutical pollutants from aqueous solution

Covalent organic frameworks (COFs) are an emergent group of crystalline porous materials that have gained incredible interest in recent years. With foreseeable controllable functionalities and structural configurations, the constructions and catalytic properties of these organic polymeric materials can be controlled to fabricate targeted materials. The specified monomer linkers and pre-designed architecture of COFs facilitate the post-synthetic modifications for introducing novel functions and useful properties. By virtue of inherent porosity, robust framework, well-ordered geometry, functionality, higher stability, and amenability to functionalization, COFs and COFs-based composites are regarded as prospective nanomaterials for environmental clean-up and remediation. This report spotlights the state-of-the-art advances and progress in COFs-based materials to efficiently mitigate pharmaceutical-based environmental pollutants from aqueous solutions. Synthesis approaches, structure, functionalization, and sustainability aspects of COFs are discussed. Moreover, the adsorptive and photocatalytic potential of COFs and their derived nanocomposites for removal and degradation of pharmaceuticals are thoroughly vetted. In addition to deciphering adsorption mechanism/isotherms, the stability, regeneratability and reproducibility are also delineated. Lastly, the outcomes are summed up, and new directions are proposed to widen the promise of COF-based smart materials in diverse fields.

Tapping the Role of Microbial Biosurfactants in Pesticide Remediation: An Eco-Friendly Approach for Environmental Sustainability

Pesticides are used indiscriminately all over the world to protect crops from pests and pathogens. If they are used in excess, they contaminate the soil and water bodies and negatively affect human health and the environment. However, bioremediation is the most viable option to deal with these pollutants, but it has certain limitations. Therefore, harnessing the role of microbial biosurfactants in pesticide remediation is a promising approach. Biosurfactants are the amphiphilic compounds that can help to increase the bioavailability of pesticides, and speeds up the bioremediation process. Biosurfactants lower the surface area and interfacial tension of immiscible fluids and boost the solubility and sorption of hydrophobic pesticide contaminants. They have the property of biodegradability, low toxicity, high selectivity, and broad action spectrum under extreme pH, temperature, and salinity conditions, as well as a low critical micelle concentration (CMC). All these factors can augment the process of pesticide remediation. Application of metagenomic and in-silico tools would help by rapidly characterizing pesticide degrading microorganisms at a taxonomic and functional level. A comprehensive review of the literature shows that the role of biosurfactants in the biological remediation of pesticides has received limited attention. Therefore, this article is intended to provide a detailed overview of the role of various biosurfactants in improving pesticide remediation as well as different methods used for the detection of microbial biosurfactants. Additionally, this article covers the role of advanced metagenomics tools in characterizing the biosurfactant producing pesticide degrading microbes from different environments.

Occurrence, environmental fate, ecological issues, and redefining of endocrine disruptive estrogens in water resources

The growing persistence of estrogenic pollutants in water resources is a worrying concern because of their endocrine disrupting activities and potentially hazardous consequences on the environmental matrices, ecology, and human health, even at low concentration. The long-term persistence of steroidal estrogens leads to their bioaccumulation in aquatic organisms that can further reach to humans via food chain route. Considering the toxicity of steroidal estrogens, it is important to mitigate these environmentally related hazardous contaminants. So far, several treatment methods, like adsorption, oxidation, irradiation, and electrochemical techniques have been proposed to eliminate estrogens from aqueous ecosystems. Nevertheless, high operational costs, insufficient removal, generation of toxic sludge, and the necessity of skilled maintenance and operating workers are the major hindrances associated with large scale applications. Bioremediation of steroidal estrogens using enzyme-based biocatalytic system has recently emerged as a promising alternative to remove and bio-transform estrogens from aqueous systems. However, the current literature lacks a critique focusing specifically and comprehensively on steroidal estrogens. The presented review is a critical assessment of the existing literature on steroid-based endocrine disruptive estrogens. A detailed description about the occurrence and eco-fate of steroidal estrogens is given with representative examples. The later half of the review stresses on the redefining (removal) of endocrine disruptive estrogens in water resources with particular reference to enzyme-based approaches.