Next Article in Journal
Potential Linkage between Heavy Metal Pollution Risk Assessment and Dissolved Organic Matter Spectra in the WWTPs-River Integrated Area-Case Study from Ashi River
Next Article in Special Issue
(Micro)Plastics Are Toxic Pollutants
Previous Article in Journal
Cysteine Attenuates the Impact of Bisphenol A-Induced Oxidative Damage on Growth Performance and Intestinal Function in Piglets
Previous Article in Special Issue
Dithiocarbamates: Properties, Methodological Approaches and Challenges to Their Control
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Insights in Pharmaceutical Pollution: The Prospective Role of eDNA Metabarcoding

by
Charikleia Papaioannou
1,†,
George Geladakis
1,†,
Vasiliki Kommata
1,†,
Costas Batargias
1,* and
George Lagoumintzis
2,*
1
Department of Biology, University of Patras, 26504 Patras, Greece
2
Department of Pharmacy, University of Patras, 26504 Patras, Greece
*
Authors to whom correspondence should be addressed.
These authors contributed equally to this work.
Toxics 2023, 11(11), 903; https://doi.org/10.3390/toxics11110903
Submission received: 11 October 2023 / Revised: 30 October 2023 / Accepted: 2 November 2023 / Published: 5 November 2023
(This article belongs to the Special Issue The 10th Anniversary of Toxics)

Abstract

:
Environmental pollution is a growing threat to natural ecosystems and one of the world’s most pressing concerns. The increasing worldwide use of pharmaceuticals has elevated their status as significant emerging contaminants. Pharmaceuticals enter aquatic environments through multiple pathways related to anthropogenic activity. Their high consumption, insufficient waste treatment, and the incapacity of organisms to completely metabolize them contribute to their accumulation in aquatic environments, posing a threat to all life forms. Various analytical methods have been used to quantify pharmaceuticals. Biotechnology advancements based on next-generation sequencing (NGS) techniques, like eDNA metabarcoding, have enabled the development of new methods for assessing and monitoring the ecotoxicological effects of pharmaceuticals. eDNA metabarcoding is a valuable biomonitoring tool for pharmaceutical pollution because it (a) provides an efficient method to assess and predict pollution status, (b) identifies pollution sources, (c) tracks changes in pharmaceutical pollution levels over time, (d) assesses the ecological impact of pharmaceutical pollution, (e) helps prioritize cleanup and mitigation efforts, and (f) offers insights into the diversity and composition of microbial and other bioindicator communities. This review highlights the issue of aquatic pharmaceutical pollution while emphasizing the importance of using modern NGS-based biomonitoring actions to assess its environmental effects more consistently and effectively.

1. Introduction

Human activities such as industrialization, urbanization, and economic development contribute synergistically to increased environmental pollution in aquatic habitats, such as rivers, lakes, and marine environments [1]. Chemical pollutants, such as heavy metals and industrial and pharmaceutical chemicals, can disrupt the balance of essential nutrients and oxygen levels, impair water quality, and make toxic or unsuitable conditions for aquatic life [2]. Water pollution can also harm biodiversity and disrupt photosynthesis in aquatic plants, significantly impacting ecosystems relying on these plants [3]. Both terrestrial and aquatic plants can absorb pollutants from water (as their main nutrient source) and transfer them through the food chain to animals and humans [4]. Pharmaceutical drugs and their metabolites contribute to water pollution by entering water bodies, disrupting the normal biological processes of aquatic organisms, and leading to the development of drug-resistant strains of bacteria [5]. In aquatic environments, including surface water, urban wastewater, wastewater treatment plants, groundwater, drinking water, and even seawater, the concentration range of predominant individual pharmaceutical compounds is typically observed to be between nanograms per liter (ng/L) to micrograms per liter (μg/L). Nevertheless, effluent from treatment plants that receive waste from pharmaceutical manufacturing facilities has been documented to contain concentrations as high as several milligrams per liter (mg/L) [6]. Furthermore, the distribution of pharmaceuticals in aquatic environments is geographically specific and contingent upon drug use patterns [7].
In recent decades, a major concern has arisen due to the increasing use of pharmaceutical products and their detrimental effects on the environment, wildlife, and humans [8]. Hignite and Azarnoff were the pioneering authors who initially documented the existence of pharmaceutical compounds in both wastewater and natural water during the late 1970s [9]. Since then, our comprehension of pharmaceuticals’ origins, fate, and ecotoxicity has advanced [10,11,12]. Pharmaceuticals are chemicals for diagnosing, preventing, and treating humans and animals [13]. They are vital to modern human and veterinary medicine, and their use is rising worldwide because of population increase, aging demographics, economic expansion, and the rising demand for animal protein in intensified food production [8,14]. Pharmaceuticals are one of the few chemical groups explicitly designed to act on living organisms. Pharmaceutical active chemicals (PhACs) are the biologically active components of pharmaceutical medications. These PhACs may be natural or synthetic chemical compounds typically found in therapeutic and veterinary medicines.
Over the past twenty years, the negative effects of pharmaceutical products on the environment, wildlife, and humans have been recognized as a serious problem that must be addressed globally [8,15,16,17,18,19]. Slowly degradable or non-degradable PhACs pose a unique risk when they enter, remain, or disperse in the environment and are thus considered environmentally persistent pharmaceutical pollutants (EPPPs). The extensive consumption of numerous pharmaceutical products results in their subsequent release into the environment, making them serious emerging contaminants. [5,12,20]. Multiple mechanisms and pathways aid PhACs and their metabolites enter aquatic environments such as seas, rivers, and aquaculture facilities [21,22,23,24]. These pathways include the excessive use of pharmaceutical products like antibiotics, β-blockers, psychoactive substances, endocrine disruptors, analgesics, anticancer drugs, and non-steroidal anti-inflammatory drugs (NSAIDs), as well as processes such as oxidation, photolysis, wastewater treatment plants, pharmaceutical manufacturing, and improper medication disposal [6,19,25,26,27]. Additively, microplastics can also carry pharmaceutical elements and metabolites, increasing environmental exposure [28]. Due to their massive global consumption and the inability of organisms to completely metabolize drugs [29,30,31], pharmaceutical residues in aquatic environments and their long-term toxic effects on living organisms are becoming more of a concern [21,26,30,32,33].
According to the existing literature, antibiotics are the most frequently identified pharmaceuticals in aquatic environments, followed by non-steroidal anti-inflammatory drugs (NSAIDs) and psychotropic substances [34]. Antibiotics are chemical compounds that can eradicate or impede the proliferation of pathogens. Consequently, they have been extensively employed in the management, regulation, and prevention of infectious diseases in humans, animals, and plants [35,36]. Multiple antibiotics have been documented to exhibit high levels of toxicity towards various aquatic organisms, as indicated by toxicity unit values above 100 for acute toxicity and 1000 for chronic toxicity. Erythromycin exhibited the highest level of toxicity among the antibiotics, as indicated by its elevated acute and chronic toxicity unit values [37,38].
Analgesics and NSAIDs are PhACs that are extensively utilized on a global scale [39]. These substances are commonly prescribed for analgesic purposes in human medical treatment. However, they are also frequently available for purchase without a prescription, commonly referred to as “over-the-counter” medications. Certain NSAIDs may not elicit immediate physiological responses but instead exert long-term effects on specific organisms. As an example, Cleuvers [40] reported that naproxen exhibited an EC50 (half maximal effective concentration) value of 174 mg/L and a NOEC (no-observed-effect concentration) value of 0.15 mg/L for Daphnia magna. Based on studies conducted by Martins et al. [41] and Załeska-Radziwiłl et al. [42], ciprofloxacin exhibited an EC50 value of 65.3 mg/L for Daphnia magna, while the NOEC value was 0.156 mg/L.
Psychiatric medications are pharmacological agents that possess psychoactive properties, influencing the internal neurochemical processes of the brain and the central nervous system. Therefore, these pharmaceuticals manage mental and neurological disorders [43,44]. In aquatic environments, the most frequently identified psychiatric pharmaceuticals include antidepressants, anxiolytics, and antiepileptic drugs (AEDs). According to Duarte et al. [45], the administration of fluoxetine, a psychiatric medication, resulted in significant DNA damage in meagre (Argyrosomus regius) when exposed to a concentration of 3 μg/L, as compared to the control group. Additionally, Aguirre-Martínez et al. [46] emphasized the significant DNA damage caused by carbamazepine, a psychiatric medication, to Corbicula fluminea. Notably, even at the lowest dose examined (0.1 μg/L) and after an exposure period of 21 days, carbamazepine had a considerable impact on DNA integrity.
Pharmaceuticals exhibit significant diversity in their physicochemical qualities, resulting in a wide range of biological variances. The water solubility, hydrophobicity, volatility, and other similar properties of substances can significantly influence their actions and ultimate destiny within aquatic ecosystems. The fate of pharmaceuticals is influenced by various factors, including dissociation constants (pKa), solid–water distribution coefficients (Kd), organic carbon-based sorption coefficients (log Koc), and octanol-water partition coefficients (Kow). These factors play a role in determining the extent of sorption, partitioning, hydrolysis, photodegradation, and biodegradation processes [47,48,49]. Furthermore, it should be noted that numerous pharmaceuticals possess acidic and/or basic functional groups, hence allowing for the existence of anionic, cationic, neutral, or zwitterionic forms under varying pH values [50]. The variability of these factors is contingent upon the pKa and Kow values of the molecule, as stated by Patel et al. [6]. The significance of chirality in relation to the environmental destiny of pharmaceuticals is noteworthy, because approximately 50% of pharmaceutical products are marketed and distributed as individual enantiomers [51]. Enantioselective reactions involve the subjection of a certain enantiomer to distinct biotransformations compared to its enantiomeric counterpart [52].
To evaluate the environmental hazards associated with pharmaceuticals, it is imperative to consider many factors, such as the quantities in which they are used, their physicochemical characteristics, and their potential for ecotoxicity. The necessity for conducting risk assessment analysis arises from several factors, including the high solubility of the substance in water, its ability to persist in the environment, its tendency to accumulate in organisms, and its potential to induce toxicity and carcinogenicity. Indeed, this endeavor has a significant level of difficulty. Low concentrations of pharmaceutical environmental residues can potentially cause acute and chronic impacts on microorganisms, flora, and fauna. The observed effects encompass a spectrum of metabolic alterations and disruptions in hormonal equilibrium. Organisms other than the specified target species may experience adverse effects. Although present in tiny amounts, below the established threshold, certain pharmaceutical substances have the potential to inflict serious adverse effects due to the intricate interactions exhibited by diverse pharmaceutical mixes within the environment [6].
For the quantification of PhACs in water or soil sediments, various analytical biochemical methods have been utilized, including liquid chromatography-mass spectrometry (LC-MS), gas chromatography-MS (GC-MS), solid-phase extraction (SPE), hydrophilic interaction liquid chromatography (HILIC), and high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) [53,54]. Nevertheless, in recent decades, technological advances in molecular biotechnology have improved the measurement and monitoring of pharmaceutical compounds’ ecotoxicological effects on water quality by applying and validating new biological indicators, such as bioassays and biomarkers [8,55,56,57,58,59,60,61,62].
The impact of human activities on different ecosystems is widely recognized, resulting in significant changes that include species extinction and biodiversity alterations. Cardinale et al. [63] highlighted that these changes can negatively affect ecosystem functioning. Hence, there is a demand for non-invasive assessments of biodiversity. According to Shim et al. [64], all living organisms release genetic material into the environment via various means, such as feces, urine, gametes, and epidermal cells, leaving detectable remnants of their DNA. In this context, biotechnological techniques based on next-generation sequencing (NGS), such as environmental DNA (eDNA) metabarcoding, can serve as a powerful bioindicator for detecting and evaluating the impacts of various pollutants, such as pharmaceutical compounds, on the diversity and composition of bacterial communities and other microorganisms such as microalgae (phytoplankton), protista, and metazoa [65,66,67,68,69]. Such techniques may also prove helpful for estimating the composition of animal and plant communities, including the genetic diversity of these species and their response to disease outbreaks resulting from changes in pathogen fitness and genotype–environment interactions due to the presence of specific PhACs [70]. The technique of eDNA metabarcoding entails an in-depth, thorough analysis of DNA sequences derived from environmental samples within a particular ecosystem [62,71,72,73,74]. The novel concept of eDNA metabarcoding, which offers to bypass many of the problems of thorough conventional research, is gaining traction as an effective and powerful approach to measuring biodiversity, albeit with pros and cons.
This review aims to provide an extensive overview of the emerging concept of pharmaceutical environmental pollution, focusing on the infiltration pathways of several PhACs into aquatic environments. Considering the ecotoxicological impacts of PhACs on organisms, this study highlights the significance of utilizing eDNA metabarcoding as a robust bioindicator method for evaluating these effects. More specifically, two primary facets were examined. Firstly, the issue of aquatic pharmaceutical pollution: the different categories of pharmaceutical pollutants were reviewed, emphasizing the characteristics, sources, fate, treatment methods, and impacts on the aquatic environment. Secondly, the importance of using eDNA metabarcoding as a biomonitoring tool to evaluate pharmaceutical environmental effects more consistently and effectively: the use of aquatic species as bioindicators to evaluate the implications of pharmaceutical pollution and the application of eDNA metabarcoding as a surveillance method of altered microbial communities, invertebrates, plants, and fishes were analyzed, thus contributing to more robust monitoring approaches and improved risk assessments. The eDNA metabarcoding methodology is presented comprehensively, encompassing technical details and analyzing its advantages and disadvantages.
The present study conducted a thorough examination of the existing literature using the established PRISMA principles [75]. A comprehensive literature review was performed using various search phrases in the ScienceDirect, Scopus, and PubMed databases. The inclusion criteria were restricted to studies published in English in peer-reviewed journals. The main focus was on research conducted between 2010 and 2023. Nevertheless, efforts have been undertaken to incorporate all relevant and significant reviews and full-length original articles that substantially contribute to the field, irrespective of the year of publication. The titles, abstracts, and keywords were subjected to a thorough examination to eliminate items that were not relevant to the study. The significance of this review is made evident by the author’s endeavor to incorporate, analyze, enhance understanding, and emphasize all the pertinent yet diverse and emerging research findings about the field of environmental pollution, biomonitoring, and eDNA metabarcoding.

2. Pharmaceuticals and Pollution: Routes and Pathways

Many PhACs and byproducts exist in rivers, lakes, and groundwater [26]. Due to their widespread use, persistence, and bioaccumulation potential, several classes of PhACs have been identified as hazards to human and environmental health. They primarily infiltrate waterways through wastewater treatment plants, improper drug disposal, and human and animal waste (Figure 1).
PhACs can alter aquatic systems’ nutrient cycling, energy transmission, and microbial community composition, resulting in altered reproduction and development, as well as changing the behavior and survivability of almost all aquatic vertebrates and invertebrates [50,76]. Moreover, low antibiotic concentrations are associated with the survival and spread of antibiotic-resistant bacteria (ARBs) and antibiotic resistance genes (ARGs), which endanger human and animal health. Indeed, chronic exposure to trace amounts of PhACs in potable water or the consumption of contaminated aquatic organisms may result in medication resistance. To reduce PhACs’ contamination of water bodies and soil, upgrading treatment facilities or implementing new treatment methods is imperative. Depending on persistence, bioaccumulation, and exposure, pharmaceutical pollution varies by region and water body. Nevertheless, it is important to note that while conventional pollution typically has a more detrimental impact on hosts or pathogens when present in higher quantities, emerging pollutants such as pharmaceuticals can often exert their effects even at lower doses, usually after long-term exposure [6,77,78]. This phenomenon can be attributed to the specific manner in which these chemicals target conserved pathways [79]. The sensitization of the public, proper use and disposal, waste management, and purification have been proposed as essential measures to reduce pharmaceutical pollution and its potential adverse health and environmental effects [80]. Table 1 summarizes the main sources and the corresponding effects of these PhACs.

2.1. Antibiotics

Antibiotics are frequently employed in human as well as animal medicine for the purpose of treating bacterial infections. Penicillins, cephalosporins, lincosamides, macrolides, tetracyclines, sulfonamides, and quinolones are among the most frequently utilized classes of antibiotics in human medicine [89]. After ingestion, humans and animals frequently excrete antibiotics. Antibiotics and their constituents can also be released from untreated or inadequately treated effluents if conventional wastewater treatment methods are ineffective at removing them [35,36]. The excessive utilization of agricultural practices, such as farming and raising livestock, may be another source that contributes to the release of antibiotics into the surrounding environment.
Due to their vast utilization, the discharge of antibiotic-containing effluent into rivers, lakes, or other water bodies contributes significantly to pharmaceutical pollution [81,84,87,88,91,116]. Despite utilizing advanced treatment methods like activated carbon adsorption, ozone treatment, or other advanced methods, completely eradicating antibiotic residues from enriched wastes may not be achievable. Furthermore, the persistence of antibiotics in the environment can be attributed to their resistance to degradation [86]. Hence, antibiotics in the environment can potentially contribute to developing and spreading antibiotic resistance in microorganisms, posing significant challenges in treating infections. It can also exert selective pressure by disturbing the equilibrium of microbial communities in water bodies, thereby affecting nutrient cycling and the overall ecosystem functioning. This disturbance contributes to the emergence and dissemination of antibiotic-resistant bacteria (ARBs) and antibiotic resistance genes (ARGs) [82,83].

2.2. Hormones and Endocrine-Disrupting Chemicals

Endocrine-disrupting chemicals (EDCs) are naturally occurring or artificially produced compounds that interfere with the normal functioning of hormones in the body. Hormones such as estrogen are integral endocrine system components [117]. According to the United States Environmental Protection Agency (EPA), an EDC is an exogenous substance that possesses the capacity to interfere with the synthesis, secretion, transport, metabolism, receptor binding, or clearance of endogenous hormones, thereby inducing modifications in the endocrine and homeostatic systems [118,119]. EDCs are commonly found in a variety of everyday products, such as human and animal medications (e.g., diethylstilbestrol), cosmetics (e.g., triclosan), food and beverage packaging (e.g., perfluorochemicals, bisphenol A, phthalates), toys (e.g., lead and cadmium), industrial solvents or oils and their by-products (e.g., dioxins and polychlorinated biphenyls), and pesticides (e.g., dichlorodiphenyltrichloroethane and chlorpyrifos) [120,121,122]. EDCs can be classified into four distinct groups based on their source: industrial (e.g., dioxins, polychlorinated biphenyls, and alkylphenols), agricultural (including pesticides, insecticides, herbicides, phytoestrogens, and fungicides), residential (such as phthalates, polybrominated biphenyls, and bisphenol A), and pharmaceutical (including birth control pills, hormone replacement therapy, and parabens) [118,123,124].
Pharmaceutical EDCs can enter the environment through excretion and improper disposal [92,96,98]. Since hormones regulate human and animal physiological processes, their release into the environment through agricultural and livestock manure runoff can contribute to environmental pollution and ultimately disrupt the endocrine systems of aquatic organisms, resulting in reproductive and developmental abnormalities, altered sex ratios, and stunted growth and development [93,94,95,97,99,100]. Estrogenic hormones, such as estradiol and ethinyl estradiol (i.e., a synthetic estrogen present in contraceptive medications), are of special concern. The presence of these hormones has been linked to the occurrence of feminization effects in fish populations. Exposure to these hormones can induce the development of intersex traits, characterized by both male and female characteristics within a single individual, as well as the disturbance of normal reproductive processes. Fish feminization can have significant implications for population dynamics and reproductive success. It can sometimes lead to population declines or the extinction of endangered species [125,126].
Although the direct impact of hormone-contaminated water on human health is not yet fully understood, scientists continue to investigate the potential risks since it is believed that chronic exposure to low levels of hormone contaminants in potable water or consuming contaminated aquatic organisms may subtly affect human endocrine systems [127].

2.3. Analgesics and Nonsteroidal Anti-Inflammatory Drugs

Analgesics and nonsteroidal anti-inflammatory drugs (NSAIDs) are commonly employed to manage pain and inflammation. The detection of analgesics and NSAIDs in both ground and surface water, such as lakes and rivers, has become prevalent due to their extensive utilization. Minute amounts of NSAIDs have been identified in various environmental matrices such as soil, wastewater, surface water, groundwater, sediments, snow, and drinking water [39,104]. Despite negligible detectable environmental concentrations, NSAIDs have long-lasting ecotoxic impacts on the biotic components of ecosystems [103,104]. According to Feng et al. [128], daily NSAID consumption exceeds 30 million doses and is rising swiftly. Due to their stability and resistance to degradation, these compounds can persist in the environment and accumulate over time. NSAIDs can enter the environment through various routes, but human excretion is the most common. The inappropriate disposal of unused medications further contributes to NSAID pollution [129]. Additionally, pharmaceutical manufacturing and healthcare facility effluent discharges can release NSAIDs into the environment. NSAIDs can influence organisms’ behavior, reproduction, growth, and development. For instance, NSAIDs such as ibuprofen and diclofenac have been associated with impaired reproduction and aberrant development in fish. In addition, repeated exposure to NSAIDs may cause bioaccumulation in aquatic organisms. Bioaccumulation can occur through the food chain, leading to elevated levels of NSAIDs in predators that consume contaminated prey. NSAIDs can influence the microbial communities of aquatic ecosystems by inhibiting the development and activity of beneficial bacteria, resulting in population imbalances among microorganisms and disruption of essential ecological processes [101,102].

2.4. Psychotropic and Antiepileptic Drugs

Psychotropic medications and AEDs are commonly employed in managing mental health disorders, such as anxiety and depression, addiction, seizures and convulsions, and chronic pain management. Researchers have discovered traces of psychotropics and AEDs in aquatic environments, implying their widespread presence. Psychotropic and AED drugs infiltrate the environment primarily through human excretion following their use as medications. The active compounds of psychotropic medications are metabolized within the body, and the residues are excreted through urine and feces. Also, these drugs can infiltrate wastewater systems via sewage or septic tanks [43,44,108]. Studies have demonstrated that exposure to psychotropic medications can induce alterations in the behavior, reproductive patterns, and physiological functions of fish, invertebrates, and other aquatic organisms [106,107], contributing to further disrupting the natural ecological processes and aquatic ecosystem populations.

2.5. β-Blockers

β-blockers are a class of pharmaceutical drugs (competitive antagonists) that inhibit the activity of adrenergic β-receptors in the sympathetic nervous system. The broad range of pathologies for which β-blockers are prescribed has resulted in an annual consumption increase of more than treble [130,131]. Although β-blockers have significant therapeutic value, they can potentially contribute to pharmaceutical pollution and have environmental effects. The increased consumption of β-blockers has led to increased tracing in the environment, and their presence has been detected in several bodies of water [132,133]. The administration of β-blockers has the potential to exert adverse effects on fish, as evidenced by their ability to induce alterations in pulse rate and other cardiovascular-related physiological processes. They have been found to have various impacts on aquatic organisms, such as causing disruption in testosterone levels, reducing fertility and reproduction rates, and inducing abnormal behavior [109,110,111]. β-blockers can alter the activities and functions of microorganisms involved in decomposing organic matter during treatment within wastewater treatment facilities [112].

2.6. Chemotherapy and Anticancer Drugs

Chemotherapy and anticancer medications may pose risks as pharmaceutical pollutants when discharged into the environment [115]. Human excretion is the primary source after administering these medications to cancer patients. However, the incorrect disposal of unused medicines can contribute to chemotherapy drug pollution. Typically, conventional wastewater purification processes are ineffective at removing chemotherapy drugs. Thus, these drugs can enter the environment through treated effluents [114,134]. Certain chemotherapy drugs are designed to be exceedingly robust and resistant to degradation to exert their therapeutic effects on the human body. This stability will also allow them to endure for extended periods in the environment and, consequently, may accumulate over time, resulting in long-term exposure in particular regions [114,135]. Chemotherapeutic medications may adversely affect aquatic organisms and other non-target species [113]. They can affect the growth, development, and reproduction of organisms exposed to them by interfering with normal cell division and DNA replication. Several investigations have demonstrated toxic effects at environmental concentrations on fish, invertebrates, and other aquatic organisms [114]. Additionally, chemotherapy drugs can disrupt the growth and activity of soil and water microbial communities in the environment, leading to population imbalances and disturbances in ecological processes.

3. Treatment Methods for Pharmaceutical Pollution

Mitigating pharmaceutical contamination necessitates a comprehensive strategy encompassing regulatory measures, appropriate disposal practices, and effective treatment methodologies. Traditional water treatment facilities employ a multifaceted approach encompassing several physical, chemical, and/or biological techniques to enhance water quality (Table 2). However, it is important to note that most treatment approaches exhibit certain drawbacks, including secondary pollution, elevated maintenance expenses, and intricate procedures involved in the treatment process [136]. Conventional treatment techniques, such as chlorination, filtration, and coagulation–flocculation, exhibit limited efficacy in eliminating pharmaceuticals [137]. The ineffectiveness of these technologies in maintaining appropriate levels of water safety and quality has become evident due to the increasing presence of pharmaceuticals in environmental waters. Hence, there is a pressing need to develop more efficient and sophisticated water treatment technologies to mitigate the potential risks associated with pharmaceuticals in water. These technologies should integrate traditional methods’ strengths while incorporating novel and innovative solutions [138,139]. Several studies have provided evidence that various treatment approaches, including membrane bioreactors [140], bacterial or fungal treatments [141,142], adsorption, nanofiltration, and reverse osmosis, have proven to be successful in the removal of contaminants [143,144,145]. In recent times, the utilization of electrochemical oxidation, in conjunction with other advanced oxidation processes (AOP), has emerged as an up-and-coming method for eliminating pharmaceuticals from water and wastewater [146]. AOPs encompass the production of highly reactive species that can break down or fully mineralize specific chemical contaminants, even when present in minute concentrations. Over the past few decades, extensive research has been conducted on various AOPs for water and wastewater remediation. These processes encompass photolytic, chemical, photochemical, physical, and photocatalytic mechanisms [147]. Among these, the photocatalytic process is of particular significance, with the choice of photocatalyst being a crucial factor. Notably, TiO2 has been widely employed for degrading pharmaceutical compounds and other chemical pollutants [148,149,150,151]. Table 2 below provides comparative information on the efficiency of different treatment methods for removing major pharmaceutical compounds from water and wastewater.

4. Methods of Analysis, Detecting, and Monitoring of Pharmaceutical Pollution

For the analysis and quantification of EPPPs and PhACs in aquatic environments, numerous sophisticated chromatographic and spectroscopic methodologies and instrumentation, such as LC-MS, GC-MS, SPE, HILIC, and HPLC-MS, are commonly employed, which have allowed for the high-throughput monitoring of hundreds of chemicals even at exceedingly low quantities [53,54,195,196,197,198,199,200,201,202,203,204,205,206,207,208,209,210]. HPLC is widely recognized as the predominant analytical technique in the field. This method is employed to analyze diverse environmental pollutants, such as PhACs, which typically exhibit polarity and instability across various sample types. The utilization of LC techniques has been found to offer an effective stationary phase through particle size reduction. This reduction in the particle size leads to improved fixation and a decrease in the duration of the process [211]. Consequently, in the majority of instances, ultra-high-performance liquid chromatography (UHPLC) has been employed instead of conventional HPLC. Also, GC is a widely employed analytical technique to classify, analyze, and identify chemical constituents in diverse samples. When used in conjunction with MS, the GC method is considered the most systematic approach, as it can produce precise and reliable results. GC is preferred over LC for determining the most polar contaminants, such as those found in pharmaceuticals [212]. Due to the high polarity and low flexibility of analytes such as hydroxyl, phenolic endocrine-disrupting chemicals, amines, and amides, the utilization of alternative output is required in the GC method to enhance the chromatographic behavior of analysts [213].
Although the chemical analysis of the environment matrix is the most straightforward method to uncover the presence of pharmaceutical pollution in the environment, this approach alone may not provide compelling evidence regarding the comprehensive impact and potential toxicity of such pollution on organisms and the ecosystem as a whole.

4.1. Bio-Monitoring and Pharmaceutical Surveillance Methods

The risk characterization of aquatic ecosystems is highly important and involves assessing potential damage to freshwater and/or marine organisms and the effects on humans [214]. The significance of biomonitoring studies in aquatic ecosystems lies in its role in evaluating the response of these ecosystems to disruptions and in unraveling the intricate relationships among physical, chemical, and biological factors [215]. These studies are essential for assessing aquatic ecosystem well-being since organisms excel as indicators of environmental conditions, frequently providing insights beyond what conventional water quality measurements can reveal [216,217,218,219].
The integration of field and traditional laboratory investigations is of paramount importance in the field of ecotoxicology. However, relying only on either approach may only sometimes yield comprehensive results in terms of identifying and quantifying the potential ecological risk posed by chemical stressors. The evaluation of the detrimental impacts of pollutants on ecosystem processes can be conducted through the utilization of experimental systems, such as sediment [220] and stream microcosms or mesocosms [221,222]. In addition, novel approaches exist for evaluating ecological well-being, including stressor-specific indicators like pollution-induced community tolerance (PICT) [223], multivariate diagnostic tools for assessing the responses of microbial communities to pollutants [224], and the SPEcies AT Risk index (SPEAR) for detecting the adverse effects of toxic stress on macroinvertebrate communities [225]. These methods prove to be valuable in assessing ecological health. Furthermore, the evaluation of chemicals might extend beyond their direct harmful effects on individual species, encompassing their potential indirect impacts on community structure [226], population dynamics, and ecosystem services [227,228]. It has been demonstrated that community ecology models (e.g., food web modeling) are effective for evaluating ecologically significant adverse effects in aquatic ecosystems [229]. Yet, ecotoxicologists are still wondering how to safeguard all biodiversity from the variety of chemicals they are now exposed to, when we know relatively little about real-world exposures and even less about the flora and fauna that we want to protect [230].

4.1.1. Bioindicator Species: Methods and Platforms

Scientists utilize biological markers to detect environmental contamination, ranging from plants and animals to microorganisms [231]. It is common practice to use microorganisms, primarily bacteria, as markers of the overall health of both marine and terrestrial ecosystems. Bacterial pharmaceutical pollution indicators specifically include measuring the composition of the entire microbial community, quantifying several sole bacterial species (e.g., Escherichia, Pseudomonas, Acinetobacter, Rhodococcus spp., etc.), or groups (e.g., bioluminescent, or nitrifying bacteria), and assessing the abundance in selective ARBs communities [232]. In polluted environments, measuring the abundance of specific genetic (e.g., ARGs) or protein bacterial indicators (e.g., metabolic biochemical markers) is also employed to assist in identifying particular pharmaceutical pollutants and their consequences [233].
Several effect-based methods and technological interventions can be used in monitoring routine and investigative endeavors to assess the ecological condition related to pollution burden [234,235,236]. Microbial biosensors (cell-free and whole-cell-based) [237,238,239] metagenomic and metatranscriptomic methods, such as high-throughput sequencing of organisms exposed to chemicals [240,241,242,243], have the potential to improve the efficacy of structure-based ecosystem analyses. These approaches can establish more explicit links between chemicals, their modes of action, and ecological functions [244]. Table 3 outlines examples of bacteria indicators coupled to different experimental sets and platforms associated with several types of pharmaceutical pollution (directly or indirectly).

4.1.2. eDNA Metabarcoding

Over the past few years, eDNA metabarcoding has gained widespread popularity as a means to assess the ecological effects of pharmaceutical pollution on natural aquatic ecosystems by unveiling the phylogenetic diversity of specific species (e.g., [269,270,271,272]), as well as on the structures and co-occurrence patterns of multi-trophic communities [273,274,275]. eDNA refers to the genetic material obtained from various environmental sources, such as soil, water, and air, without the requirement of isolating specific target organisms beforehand [276]. It has a wide temporal persistence range, spanning from a few weeks to many thousands of years, thus permitting its utilization in various fields such as molecular biology, ecology, paleontology, and environmental sciences [277]. In contemporary times, the methodologies employed in eDNA investigation, specifically eDNA metabarcoding, have made significant progress, enabling the evaluation of entire ecological communities through the analysis of a solitary sample. This is achieved by utilizing high-throughput NGS techniques to discern the species composition within the sample [277].
Using eDNA analysis to detect and quantify the biodiversity of micro- and macro-organisms enables the research community to study an ecosystem without requiring physical capture or visual surveys [278]. Consequently, it can address the limitations of other labor-intensive conventional methods and investigate the presence of organisms at a location by identifying eDNA in environmental samples [279]. Pont et al. [280] suggested a quantitative approach to aquatic community analysis using eDNA methods, which appeared more suitable for biomonitoring and bioassessment purposes than other traditional methods. By combining qPCR analysis and eDNA metabarcoding, using 12S rRNA, they allowed for the estimation of species diversity and abundance in the Danube River, overall detecting 86 fish taxa [280]. Similarly, Yang et al. [281] proposed an unsupervised biological assessment framework based on multi-gene eDNA metabarcoding for the health evaluation of Lake Taihu. This framework could allow consistent evaluation across various ecosystems and seasons, thereby supporting environmental management and decision-making. They were able to describe a total of 478 species using 18S rRNA, while COI and 12S rRNA identified 99 and 66 species, respectively, including algae, protists, zooplankton, and fish. In their study, the limitations of traditional supervised assessment methods and the need for more standardized indicators and assessment methods were highlighted, emphasizing the potential of eDNA technology for efficient and non-invasive biomonitoring [281].
eDNA metabarcoding can serve as a practical and highly sensitive tool for biodiversity monitoring [282], offering several key advantages in aquatic research [283,284]. It can effectively identify a wide range of freshwater and marine species, often outperforming traditional survey methods in species detection [285,286,287]. It can detect rare and cryptic species often missed by conventional survey techniques, including endangered and invasive species [288,289,290]. eDNA collection requires only tiny amounts of water and basic filtering techniques [291,292], making it accessible even in remote locations by individuals with limited training. eDNA eliminates the need for diving, enhancing worker safety [284,293], and it is cost-effective and has the potential for automation [294,295], enabling remote sample collection and efficient high-throughput lab processing. Lastly, the complex disruptions arising from a combination of natural and human-induced factors, as well as the increasing rate of biodiversity decline and the diminishing ecological function in aquatic ecosystems, reinforce the need for using eDNA metabarcoding as a dependable approach for assessing the influence of pollutants, e.g., pharmaceuticals, on aquatic organisms [66,275,296].
The experimental procedure steps for the development of eDNA metabarcoding surveys have been extensively described in various studies [277,297,298] and comprise a selection of specific gene(s) and primers for targeting particular taxa [299,300], the compilation or creation of extensive barcode reference databases [299,301], the implementation of stringent decontamination pipelines based on site occupancy (e.g., [302,303]), initial investigations performance to characterize spatial and temporal variations in eDNA (e.g., [304,305,306]) and the storage of samples, extracts, and raw sequence data for future reference (e.g., [307,308,309]).
Even though the application of eDNA metabarcoding has grown enormously, there are also concerns regarding its strengths and limitations. The effectiveness of this method in aquatic environments depends on its ability to detect species even at low abundance levels, as well as cryptic, rare, or elusive organisms [310]. A key point in ecological assessments and biodiversity monitoring is sensitivity, as it enables researchers to reveal the hidden aspects of aquatic ecosystems and track changes in species composition over time [311,312]. Various factors, such as sample collection methods, DNA extraction protocols, and the choice of genetic markers, which play a crucial role in maximizing the method’s detection capabilities, need to be taken into consideration to reach the desirable levels of sensitivity in eDNA metabarcoding [312].
Another crucial point for the application of this method is accuracy, as it directly affects the reliability of species identification and community assessments within aquatic environments [311,313]. Ensuring precision and reducing the risk of false positive and negative identifications in ecological data is essential in species detection [314]. Optimal accuracy depends on the proper selection of genetic markers, the utilization of suitable primer sets, robust bioinformatic pipelines for data analysis, and updated databases for correct species recognition [315]. Precise eDNA metabarcoding enhances our comprehension of aquatic ecosystem biodiversity and establishes a valid basis for informed decisions in conservation and management [316].
As with any other method, it may not work, or when it does, it might not provide the requisite information. Challenges relating to imperfect detection, quantifying abundance, assigning taxonomies, understanding the spatial and temporal dynamics of eDNA, analyzing and interpreting data, and assessing ecological conditions have all proven to be significant hurdles [279,317]. These challenges and limitations of eDNA metabarcoding have been the subject of various biodiversity and monitoring studies [314,318,319]. However, before its adoption, researchers have focused on addressing and overcoming the disadvantages of the method (e.g., [320,321,322]).
Overall, this method provides a powerful supplement or alternative to traditional survey methods in measuring and monitoring the biodiversity and health of aquatic ecosystems at unprecedented resolution and scale [66,311,323,324,325]. Nowadays, it constitutes one of the primary surveys employed by researchers and public agencies towards ecosystem conservation and meeting many resource management issues across nations [322,326,327].

5. Environmental Impact of Different Sources of Pharmaceutical Pollution

Industrialization, urbanization, and economic development damage rivers, lakes, and oceans [328]. Nutrient pollution can induce toxic algal overgrowth, fish deaths, waterborne disease outbreaks, and eutrophication, which pollutes and depletes oxygen [329,330]. The increasing use of pharmaceuticals and their persistent occurrence in aquatic environments significantly impact various species across different taxonomic levels [331]. These effects extend from microbial communities and aquatic plants to macro-invertebrates, fishes, and humans. In the following sections, the main implications of pharmaceuticals on the different aquatic organisms were described, as well as the utilization of eDNA metabarcoding as a reliable methodology for examining the impacts of pollutants, specifically pharmaceuticals, on aquatic ecosystems [332,333,334,335]. Table 4 summarizes the main implications of PhACs and the role of eDNA metabarcoding as a bio-monitoring surveillance method for environmental/pharmaceutical pollution. In the following Section 5.1, Section 5.2 and Section 5.3, we elaborate on the effects of pharmaceutical pollution and the potential role of eDNA metabarcoding in evaluating these effects.

5.1. Alteration of Microbial Communities Due to Pharmaceutical Contamination

Multiple research studies have investigated the impact of pharmaceutical substances on microbial communities in aquatic environments. The synthesis of these studies reveals that pharmaceutical contaminants can induce alterations in the structure, metabolic activity, composition, and formation of microbial biofilms [5,336]. These modifications can potentially impact the equilibrium of nutrients in surface waters, soil, and marine ecosystems and contribute to microbiological concerns in potable water. Furthermore, the primary emphasis in studying the influence of pharmaceuticals on microbial communities in the environment lies in investigating the consequences of minimal levels of antibiotics. At the same time, attention is also given to other emerging contaminants that are not antibiotics, such as NSAIDs. These emerging contaminants have the potential to exert selective pressure and facilitate the proliferation of antimicrobial resistance [336].
The primary purpose of antibiotics is to combat pathogenic bacteria. Nonetheless, the potential impact of byproducts and residues on non-target species, such as algae and cyanobacteria, which play a crucial role as primary producers in aquatic ecosystems, cannot be overlooked [338,377]. The perturbations in these photoautotrophic organisms’ populations can significantly impact higher trophic levels. The literature has extensively examined the toxic effects of antibiotics as individual pharmaceuticals, as well as their biodegradation products, in diverse aquatic environments [14,35,339,340]. Through the utilization of various bioassays, researchers have demonstrated that most microorganisms exhibit susceptibility to prolonged exposure to varying concentrations of antibiotics, with cyanobacteria emerging as the most probable candidate.
This fortuitous encounter suggests that the administration of antibiotics has the potential to disrupt the balance of microbial populations, leading to an increase in ARBs and ARGs. In recent years, there has been a notable emergence of ARBs and ARGs as environmental contaminants with the capacity for rapid global dissemination [90]. ARGs, along with mobile genetic elements (MGEs) such as plasmids, integrons, and transposons, have the ability to disseminate through horizontal gene transfer. This process is facilitated by three mechanisms: transformation, conjugation, and transduction [85].
DNA-based techniques, e.g., polymerase chain reaction (PCR) and quantitative PCR (qPCR), are required to investigate the possible transmission of ARBs and ARGs within microbial communities, as well as their transfer to higher organisms. In the past decade, by utilizing these techniques, researchers have demonstrated the presence of bacteria and the existence of genes associated with resistance to different antibiotics and antimicrobial drugs in samples from various water sources, such as water treatment facilities [378,379,380,381], residential areas [379,382], hospitals [379], lakes [383], rivers [384,385], and aquaculture facilities [386]. These findings indicate that regions characterized by human exploitation significantly contribute to the spread of microbial antibiotic resistance.
In addition to conventional DNA-based methodologies such as PCR and qPCR, which allow for the targeted detection of particular microbial species, the application of metabarcoding techniques has facilitated the assessment of changes in the composition and diversity of microbial communities resulting from specific PhACs [342,345]. Examining microbial communities’ structure and identifying potential hazards, such as bacterial contamination in water sources, are of utmost importance. In this regard, Cruz et al. [343] employed the sequencing of the 16S rRNA gene amplicon to analyze the DNA of bacterial communities in diverse water sources, including treated and untreated hospital wastewater, fish culture sites, lakes, and urban waste canals, situated in Sri Lanka and the Philippines. The bacterial communities’ composition and abundance were found to be influenced by the water source, with untreated wastewater samples exhibiting higher bacterial richness. This finding underscores the significance of comprehending bacterial communities in assessing water quality.
Romero et al. [344] utilized 16S rRNA metabarcoding to examine microbiota in various sub-basins of the Rimac River, which serves as the primary water source for Lima, Peru. The investigation focused on areas with persistent multidirectional water pollution and aimed to compare the diversity patterns between the Andean and Metropolitan regions. The higher prevalence of bacteria in samples collected from lower altitudes and the high occurrence of Arcobacter cryaerophilus, a pathogen associated with fecal contamination and antibiotic resistance, underscores the necessity for utilizing NGS techniques to augment pathogen surveillance. In a similar investigation, Chonova et al. [333] effectively employed metabarcoding to analyze diatom communities’ spatial and temporal dynamics. The study aimed to evaluate these communities’ ecological responses, growth patterns, and behavioral tendencies in environments containing diverse pharmaceutical pollutants, including β-blockers, NSAIDs, and antibiotics.
Other recent reports also suggest that eDNA methods could provide valuable insights into predicting pollution levels and identifying the key factors influencing ecological networks. Li et al. [66] employed eDNA metabarcoding to effectively characterize a diverse array of bacteria and ascertain the primary source of contamination in rivers, encompassing multiple anthropogenic pollutants such as excessive nutrients, heavy metals, pesticides, and pharmaceuticals. In another study, Lyu et al. [275] identified the occurrence of 91 antibiotics in water and sediment samples obtained from the Nei River. Additionally, they utilized eDNA metabarcoding to investigate the observed fluctuations in bacterial communities. Significant inverse associations were observed between antibiotic concentrations and the relative abundances of vital metabolic pathways in bacterial populations.
Furthermore, the increase in urbanization and land use poses a significant threat to freshwater ecosystems due to the release of various chemical contaminants [387], which can affect organismal dispersal and nutrient transport in water [388,389]. Xie et al. [341], by examining freshwater sediments from the Nanfei River in Anhui Province, China, suggested that eDNA metabarcoding on in situ eukaryotic communities can be a valuable method for biomonitoring and detecting chemical pollution originating from diverse land use types, such as agricultural and industrial areas. All these findings highlight how eDNA analysis is an effective tool for providing comprehensive data regarding the influence of pharmaceutical pollutants on aquatic microbial diversity.

5.2. Effects of Pharmaceuticals on Aquatic Invertebrates, Plants, and Fishes

Despite typically occurring at low concentrations in aquatic environments, pharmaceutical compounds exhibit considerable biological activity, often coupled with remarkable stability [390]. As a result, there is increasing concern about their potential ecotoxicological effects on aquatic fauna and flora, especially over extended periods of exposure [34]. To develop a comprehensive understanding of the potential risks that pharmaceuticals may pose to aquatic life, it is crucial to assess their prevalence across various organisms, including plants and algae, invertebrates, and fish [53].
Photosynthetic organisms, including phytoplankton and macrophytes, constitute a significant proportion of the overall biomass present in aquatic ecosystems [347]. Primary producers release oxygen and constitute key carbon sources, nutrients, and trace elements [391]. They also provide food and shelter for many aquatic species, affecting water flow patterns and reducing sediment erosion [347]. Accumulating emerging contaminants in water bodies (e.g., pesticides) has been shown to induce harmful effects during plant development [346] and impair aquatic plant photosynthesis and biodiversity [3]. Among various PhACs, antibiotics have an antichloroplastic activity in cyanobacteria, green algae, and other aquatic plants, primarily due to the similarity of their target sites for toxic action with those of bacteria [347]. However, micro- and macrophytes could provide important environmental services by bioremediating pollutants in natural environments [392]. They are equipped with multiple detoxification mechanisms that aid in mitigating the deleterious effects of pollutants and counteracting the toxicity of various exogenous substances [393]. Following Bala et al. [394], contaminants can undergo partial or complete degradation, broad metabolism, or be transformed into less toxic compounds. These transformed compounds can then be incorporated into plant tissues in a form that cannot be easily extracted [395].
The role of aquatic invertebrates (e.g., sponges, corals, worms, echinoderms, crustaceans, and shellfish) in nutrient cycling, processing substantial amounts of organic matter, and serving as a food source for numerous organisms makes them crucial for the functioning of aquatic ecosystems [396]. The existing literature indicates that pharmaceutical pollution can notably affect macroinvertebrates, mainly in terms of growth, behavior, and reproduction [357]. However, the absorption and bioaccumulation of pharmaceuticals in these organisms are subject to considerable variability, contingent upon habitat conditions (both abiotic and biotic factors) and their physiological attributes, encompassing chemical and biological elements [397]. The task of making reliable inferences about the bioaccumulation of pharmaceuticals in invertebrates is considerably more complex, primarily attributable to the inconsistent presence of pharmaceutical compounds in benthic species across diverse sampling sites [398]. Furthermore, the bioaccumulation process is intricately linked to the species’ type, distribution, and abundance, which can vary spatially and temporally within aquatic ecosystems [399].
Relative to the effects of PhACs in aquatic vertebrates, extensive research has been conducted on fish, primarily due to their role as a reliable indicator of aquatic pollution. This is attributed to their ability to accumulate contaminants from the surrounding water and their vulnerability to experiencing adverse effects [358]. The predominant chronic adverse impacts of pharmaceuticals on fish species primarily manifest as locomotor and reproductive dysfunctions, hematological and hormonal imbalances, immunotoxicity, disruption of endocrine function, genotoxicity, oxidative stress, physical deformities, teratogenic effects, and a deterioration in the overall physiological state of the organisms [39,358,359,360,361]. The initial exposure of fish to xenobiotics in aquatic environments occurs via their gills, leading to potential structural impairments and physiological changes in these tissues [400,401]. However, the degree of consequences of pharmaceutical substances in the various health aspects of fish depends on species, sex, and the phase of the life cycle, as well as on the dose and duration of the substances [361,402,403]. Furthermore, the presence of pharmaceuticals in aquatic environments has also been observed to influence the behavior of fish, comprising alterations in activity, sociality, and feeding rate, as well as aggression and reproductive behaviors [362,363,364,365].
Identifying species abundance and diversity changes can provide valuable insights into the ecological consequences of pharmaceutical exposure. In aquatic ecosystems, conventional biotic indices, such as morphological identification, are insufficient to accurately represent the actual population structure, since species in these environments may remain concealed underwater, and their detection through traditional means could be challenging [348,350]. Therefore, the utilization of eDNA in ecological research, biomonitoring, and environmental management can be beneficial and bring about a transformative impact on the field of conservation science [404]. Several studies have reported the use of eDNA analysis to investigate the biotic composition, abundance, and distribution of aquatic species, such as macroinvertebrates, plants, fishes, and others in freshwater and marine ecosystems [348,349,350,351,352,353,354].
Fish comprise more than one quarter of the world’s vertebrate species and are also one of the most threatened taxonomic groups [405]. They are the most frequently targeted taxa in species-specific metabarcoding studies, probably due to their economic importance [406]. Alterations in fish composition and abundance as bioindicators of aquatic systems subjected to anthropogenic stressors suggest that eDNA technology could be used to revolutionize fish monitoring, foster biodiversity, conservation, and fishery management that transcends both geographical and temporal boundaries [355,356].
Although eDNA surveys for groups like fishes are being standardized, this differs for other aquatic taxa such as macroinvertebrates [407] and plants [408]. Humanization processes like water pollution and habitat fragmentation lead to a decline in macroinvertebrate populations, highlighting the importance of rapid, precise, and homogeneous eDNA monitoring for species survival [409,410,411]. Following Pawlowski et al. [412] and Pochon et al. [413], the application of metabarcoding techniques has shown that fish farming significantly impacts benthic foraminifera communities, indicating alterations in species richness near aquaculture facilities. However, they mentioned the need for the replication of samples and the interpretation of read abundance data. To overcome these biases and limitations, more experimental studies are needed to improve the accuracy and reliability of NGS metabarcoding as well as the taxonomic assignment of NGS reads, enhancing the effectiveness of NGS metabarcoding as a biomonitoring tool for macroinvertebrates [412]. Finally, the absence of single universal plant barcodes hinders the use of metabarcoding for studying contemporary marine plants. However, recent studies show promising results in assessing plant biodiversity monitoring in aquatic ecosystems [408]. Overall, the necessity for sensitive biomonitoring tools to support conservation initiatives aimed at safeguarding these susceptible organisms is paramount.

5.3. Bioaccumulation and Trophic Transfer of Pharmaceuticals in Aquatic Food Webs

The bioaccumulation of pharmaceuticals is a critical concern, potentially with significant implications for aquatic life and human health. As these pharmaceutical compounds enter aquatic ecosystems through various pathways, they can be taken up and stored in the tissues of aquatic organisms [366,367]. Subsequently, these contaminants can be transferred through the food web, leading to higher concentrations in higher trophic levels (namely biomagnification), including fish and macroinvertebrates [368]. Given the widespread consumption and cost-effectiveness of aquatic organisms (mainly fish) as a protein source in various global regions, it is plausible that pharmaceutical substances could be introduced into the human body through trophic transfer, potentially posing risks to human health [358]. Due to their complex nature, food webs cannot be easily understood by merely considering the sum of their constituent elements (e.g., fish play a significant role within aquatic food webs, moving between trophic levels during their ontogeny) [414], the understanding of the dynamics of trophic transfer and bioaccumulation of pharmaceuticals in different aquatic species is essential for assessing and mitigating potential health hazards associated with these emerging contaminants [367].
Pharmaceuticals are being detected more frequently in environmental samples, yet our understanding of their movement through aquatic food webs, known as trophic transfer, still needs to be fully resolved [367]. Using conventional methods, scientists have already studied the bioaccumulation of such substances at various trophic levels [415,416]. In this field, however, multiple challenges need to be addressed. A comprehensive understanding of ecology is essential to gain insights into the accumulation and dispersion of pharmaceuticals in aquatic food webs [417]. The successful management and preservation of ecosystems necessitate a comprehensive worldwide endeavor to consistently monitor the biological communities’ composition and diversity [418]. Current ecological assessment methods are constrained by their reliance on traditional morpho-taxonomic approaches, the assumption of environmental sorting of communities, and the identification of species by proficient analysts, methods that cannot keep up with the growing need for swift assessments [369].
eDNA data for biomonitoring provide distinct advantages over current methods as they may detect a broader spectrum of taxa and indicator groups that traditional taxonomic identification may miss, leading to more accurate assessments, particularly when comparing nearby locations or evaluating moderate environmental changes [369]. Its use in ecotoxicology has also become a crucial advancement in recent years, allowing for the detection and quantification of the effects of toxic substances on ecological communities [370]. DNA metabarcoding is being used for various applications like identifying individual species and assessing community compositions in aquatic ecosystems [369], investigating biodiversity [313,373], characterizing prey in gut contents or fecal samples [374,375], and analyzing food web dynamics [376]. It can also provide valuable insights into the impacts of chemical stressors on freshwater ecosystems and allows for identifying keystone species and monitoring shifts in microbial functional groups, which can help predict potential changes in ecosystem functionality [317]. Anagnostopoulos et al. [371] used metabarcoding analysis to assess bacterial communities and potential pathogens in water and fish flesh sampled from various locations within Lake Karla (Eastern mainland Greece). This approach offered a comprehensive view of the microbial composition and diversity within the samples, revealing the impact of agricultural and industrial activities on both water quality and fish safety. Li et al. [372] utilized DNA metabarcoding to assess the impact of paroxetine (SSRI antidepressants) on multi-trophic microorganisms and nitrogen transformation in river sediments. This study underscores the significance of this approach in offering valuable insights into the composition and dynamics of microbial communities responding to the tested pharmaceutical [372]. Despite the numerous potential benefits of eDNA-based assessment, such as enhanced sensitivity, broader spatial and temporal coverage, and reduced personnel demands [348,419], it still requires validation as a reliable alternative to existing biomonitoring protocols [369].

6. Future Perspectives

Ecosystems worldwide are changing as they enter a new geological era in which human interventions (e.g., climate change, habitat destruction, environmental pollution) dramatically affect the environment [420,421]. Among the various global environmental challenges, a notable rise of contaminants, including pharmaceuticals, personal care products, pesticides, and microplastics, has been noted in aquatic ecosystems worldwide over the past few decades [6]. Environmental pharmaceutical pollution has garnered international attention over the past two decades [422] in light of significant global issues such as rising antimicrobial resistance and the lack of new antibiotic molecules [5]. Pharmaceuticals can negatively affect aquatic ecosystems and wildlife. However, the complete scope of ecological impacts must be comprehended, including the short- and long-term effects on various species and habitats. It is anticipated that pharmaceutical pollution will continue to rise exponentially and globally due to population growth, aging populations, and increased access to healthcare, all of which will increase pharmaceutical consumption and its potential release into the environment.
Global pharmaceutical pollution necessitates developing and implementing effective strategies for monitoring, mitigating, and preventing pharmaceutical pollution by multiple parties [423]. Governments and non-government organizations are attempting to combat the pollution caused by pharmaceuticals (e.g., Environmental Risk Assessment–ERA) [14]. The overall scheme of these proposed—but not yet fully managed and implemented—efforts includes the ethical use of antibiotics, which refers to the responsible administration of antibiotics in human and veterinary medicine, the understanding of the path that these medications take in the environment and how they are transported, the raising of awareness about the negative effects that pharmaceuticals have on the environment, the promoting of the safe disposal of unused prescription drugs, and the supporting of the safe disposal of unused pharmaceuticals. These combined efforts and approaches aim to reduce the pollution caused by a broad range of pharmaceutical products and limit the potential impact of some PhACs on the surrounding environment [8,424].
The utilization of sophisticated molecular biology techniques and traditional biochemical methods enables us to efficiently degrade or accumulate harmful substances from the environment, thereby mitigating pharmaceutical pollution. Microorganisms and plants possessing biosynthetic pathways for the degradation or accumulation of environmental pollutants in soil and water have the potential to mitigate environmental pollution, including that induced by pharmaceutical compounds. Nevertheless, the limited presence of distinct genetic elements in microorganisms and plants hampers their ability to break down or accumulate pollutants effectively. In recent years, significant progress has been made in the field of CRISPR-Cas9 technology, which has facilitated the manipulation of genetic material in microorganisms and plants. This has been employed to enhance the effectiveness of reducing the degradation and accumulation of environmental pollutants [425,426]. Although welcomed and alleviative, these approaches are far from efficient enough, and more holistic approaches are needed.
Hence, the observation (biomonitoring) and understanding the dynamics and shifts (biodiversity) of various types of species’ pollution remain crucial, as well as the need for more innovative solutions to address pharmaceutical pollution effectively. To achieve this objective, biomonitoring can be carried out qualitatively through observing and documenting alterations in organisms or quantitatively by assessing the accumulation of compounds within the tissues of organisms. Through the process of observing or measuring the impacts of the environment on native organisms, it becomes possible to raise suspicions or make inferences about pollution. Consequently, appropriate actions can be prioritized based on these findings [284].
eDNA metabarcoding shows great potential as a novel strategy for comprehensively assessing and monitoring aquatic ecosystems [66,404]. The application of metabarcoding in studying the impacts of pharmaceuticals on aquatic ecosystems has been demonstrated as an effective and valuable methodology [427]. Certain medications can alter microbial communities in soil, water, and detritus, and metabarcoding can assist in identifying these alterations, thereby serving as an early warning system for pharmaceutical contamination. Thus, through metabarcoding and high-throughput NGS, eDNA can rapidly, repeatedly, and affordably survey community biodiversity [283]. By integrating eDNA metabarcoding with other complementary methodologies, such as biochemical analysis and conventional ecotoxicological assessments, scientists can synergistically gain insight into the ecological consequences of pharmaceutical pollution and design effective management strategies. In addition, metabarcoding can be used to monitor the effectiveness of pharmaceutical pollution mitigation measures. By comparing the composition and diversity of microbial communities before and after the implementation of interventions, such as improved effluent treatment or regulatory measures, researchers can evaluate the effectiveness of these interventions. Furthermore, metabarcoding enables the detection of emergent contaminants that may not be included in standard monitoring programs. It allows for the identification of unknown or novel pharmaceuticals that may have contaminated the environment and aids in prioritizing research and regulatory efforts to combat these emergent threats.
Despite the several benefits of species detection and community monitoring that have been mentioned, several important considerations need to be made before employing eDNA techniques [428]. The accuracy of the assessment is significantly dependent on the sampled material type. eDNA detection is typically more efficient in aquatic environments than in detritus or soil [429]. The sample’s quality and quantity are also crucial factors. This aspect is closely related to the quantity of DNA released into the environment by each species. For instance, species such as fish and amphibians tend to discharge substantial amounts of DNA [316,430]. In addition, certain habitats, particularly those that are difficult to access, hinder species tracking more than others [431]. Consequently, the assessment of species assembly in aquatic environments was more effective in small, stationary freshwater habitats, such as lakes and ponds, than in large, moving waterways, such as streams and rivers [432]. Lastly, accurate species identification is impacted by species abundance within the studied medium and eDNA changes over time and space [73,433]. Nonetheless, obstacles, including PCR inhibition, eDNA capture, and representative sampling, impede the discovery of complete species diversity in aquatic environments. In addition to the specificity of primers and the quality of the reference database, the level of taxonomic expertise influences the success of species identification. Measuring species abundance, associating species detections with the actual species composition of the ecosystem and determining species interaction are additional challenges in implementing eDNA-based approaches [279].

7. Conclusions

In conclusion, to effectively manage pharmaceutical pollution, governments, regulatory bodies, pharmaceutical producers, healthcare professionals, scientists, and the general public must cooperate in an efficient and productive manner. By implementing the methods mentioned above, we may make strides in lowering the environmental and health risks of pharmaceutical pollution and promoting a more sustainable approach to the consumption of medications and their disposal. Despite any limitations and obstacles, the novel idea of eDNA metabarcoding, which bypasses many of the difficulties associated with conducting extensive conventional environmental research, is gaining traction as a means of measuring and monitoring biodiversity alterations due to pharmaceutical pollution, indicating the presence of pharmaceuticals, assessing ecological impacts, and tracking the efficacy of mitigation efforts. These benefits further advance our knowledge of the scope and effects of pharmaceutical pollution and help us make informed further decisions about mitigating its negative impact on the environment. Harnessing technological innovations, eDNA metabarcoding emerges as a highly promising approach for assessing communities across a spectrum of applications, spanning from ecosystem restoration to human health, underscoring its pivotal role in the future of molecular research.

Author Contributions

All authors contributed to the investigation and the initial drafting of the manuscript. C.P., G.G. and V.K. contributed equally to this manuscript. G.L. and C.B. conceptualized, supervised, and performed the final drafting and editing of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

The research of G.L. has been financed by the funding program “MEDICUS” of the University of Patras (Number: 82443).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Goel, P.K. Water Pollution: Causes, Effects and Control; New Age International: New Delhi, India, 2006. [Google Scholar]
  2. Gautam, P.K.; Gautam, R.K.; Banerjee, S.; Chattopadhyaya, M.C.; Pandey, J.D. Heavy Metals in the Environment: Fate, Transport, Toxicity and Remediation Technologies. In Heavy Metals: Sources, Toxicity and Remediation Techniques; Pathania, S., Ed.; Nova Science Publishers: Hauppauge, NY, USA, 2016; ISBN 9781634847407. [Google Scholar]
  3. Obinnaa, I.B.; Ebere, E.C. A Review: Water Pollution by Heavy Metal and Organic Pollutants: Brief Review of Sources, Effects and Progress on Remediation with Aquatic Plants. Anal. Methods Environ. Chem. J. 2019, 2, 5–38. [Google Scholar] [CrossRef]
  4. Tongesayi, T.; Fedick, P.; Lechner, L.; Brock, C.; Le Beau, A.; Bray, C. Daily Bioaccessible Levels of Selected Essential but Toxic Heavy Metals from the Consumption of Non-Dietary Food Sources. Food Chem. Toxicol. 2013, 62, 142–147. [Google Scholar] [CrossRef] [PubMed]
  5. Świacka, K.; Maculewicz, J.; Kowalska, D.; Grace, M.R. Do Pharmaceuticals Affect Microbial Communities in Aquatic Environments? A Review. Front. Environ. Sci. 2023, 10, 1093920. [Google Scholar] [CrossRef]
  6. Patel, M.; Kumar, R.; Kishor, K.; Mlsna, T.; Pittman, C.U.; Mohan, D. Pharmaceuticals of Emerging Concern in Aquatic Systems: Chemistry, Occurrence, Effects, and Removal Methods. Chem. Rev. 2019, 119, 3510–3673. [Google Scholar] [CrossRef] [PubMed]
  7. Carlsson, C.; Johansson, A.K.; Alvan, G.; Bergman, K.; Kühler, T. Are Pharmaceuticals Potent Environmental Pollutants? Part I: Environmental Risk Assessments of Selected Active Pharmaceutical Ingredients. Sci. Total Environ. 2006, 364, 67–87. [Google Scholar] [CrossRef]
  8. Kock, A.; Glanville, H.C.; Law, A.C.; Stanton, T.; Carter, L.J.; Taylor, J.C. Emerging Challenges of the Impacts of Pharmaceuticals on Aquatic Ecosystems: A Diatom Perspective. Sci. Total Environ. 2023, 878, 162939. [Google Scholar] [CrossRef]
  9. Hignite, C.; Azarnoff, D.L. Drugs and Drug Metabolites as Environmental Contaminants: Chlorophenoxyisobutyrate and Salicyclic Acid in Sewage Water Effluent. Life Sci. 1977, 20, 337–342. [Google Scholar] [CrossRef]
  10. Cardoso, O.; Porcher, J.M.; Sanchez, W. Factory-Discharged Pharmaceuticals Could Be a Relevant Source of Aquatic Environment Contamination: Review of Evidence and Need for Knowledge. Chemosphere 2014, 115, 20–30. [Google Scholar] [CrossRef]
  11. Pozzebon, E.A.; Seifert, L. Emerging Environmental Health Risks Associated with the Land Application of Biosolids: A Scoping Review. Environ. Health 2023, 22, 57. [Google Scholar] [CrossRef]
  12. Nguyen, M.K.; Lin, C.; Nguyen, H.L.; Hung, N.T.Q.; La, D.D.; Nguyen, X.H.; Chang, S.W.; Chung, W.J.; Nguyen, D.D. Occurrence, Fate, and Potential Risk of Pharmaceutical Pollutants in Agriculture: Challenges and Environmentally Friendly Solutions. Sci. Total Environ. 2023, 899, 165323. [Google Scholar] [CrossRef]
  13. aus der Beek, T.; Weber, F.A.; Bergmann, A.; Hickmann, S.; Ebert, I.; Hein, A.; Küster, A. Pharmaceuticals in the Environment-Global Occurrences and Perspectives. Environ. Toxicol. Chem. 2016, 35, 823–835. [Google Scholar] [CrossRef]
  14. Kovalakova, P.; Cizmas, L.; McDonald, T.J.; Marsalek, B.; Feng, M.; Sharma, V.K. Occurrence and Toxicity of Antibiotics in the Aquatic Environment: A Review. Chemosphere 2020, 251, 126351. [Google Scholar] [CrossRef]
  15. Valdez-Carrillo, M.; Abrell, L.; Ramírez-Hernández, J.; Reyes-López, J.A.; Carreón-Diazconti, C. Pharmaceuticals as Emerging Contaminants in the Aquatic Environment of Latin America: A Review. Environ. Sci. Pollut. Res. 2020, 27, 44863–44891. [Google Scholar] [CrossRef]
  16. Hughes, S.R.; Kay, P.; Brown, L.E. Global Synthesis and Critical Evaluation of Pharmaceutical Data Sets Collected from River Systems. Environ. Sci. Technol. 2013, 47, 661–677. [Google Scholar] [CrossRef]
  17. Kolpin, D.W.; Furlong, E.T.; Meyer, M.T.; Thurman, E.M.; Zaugg, S.D.; Barber, L.B.; Buxton, H.T. Pharmaceuticals, Hormones, and Other Organic Wastewater Contaminants in U.S. Streams, 1999-2000: A National Reconnaissance. Environ. Sci. Technol. 2002, 36, 1202–1211. [Google Scholar] [CrossRef] [PubMed]
  18. Fekadu, S.; Alemayehu, E.; Dewil, R.; Van der Bruggen, B. Pharmaceuticals in Freshwater Aquatic Environments: A Comparison of the African and European Challenge. Sci. Total Environ. 2019, 654, 324–337. [Google Scholar] [CrossRef] [PubMed]
  19. Hussain, A.; Ashique, S.; Zaheen Hassan, M.; Afzal, O.; Asiri, Y.I.; Kumar, P.; Dua, K.; Webster, T.J.; Altamimi, A.S.A.; Altamimi, M.A. Pharmaceutical Contaminants in Aquatic Systems, Conventional and Green Strategies, Recent Updates, Challenges and Policies, and Potential Outcomes. J. Mol. Liq. 2023, 389, 122905. [Google Scholar] [CrossRef]
  20. Mahapatra, I.; Clark, J.R.A.; Dobson, P.J.; Owen, R.; Lynch, I.; Lead, J.R. Expert Perspectives on Potential Environmental Risks from Nanomedicines and Adequacy of the Current Guideline on Environmental Risk Assessment. Environ. Sci. Nano 2018, 5, 1873–1889. [Google Scholar] [CrossRef]
  21. Wilkinson, J.L.; Boxall, A.B.A.; Kolpin, D.W.; Leung, K.M.Y.; Lai, R.W.S.; Galbán-Malagón, C.; Adell, A.D.; Mondon, J.; Metian, M.; Marchant, R.A.; et al. Pharmaceutical Pollution of the World’s Rivers. Proc. Natl. Acad. Sci. USA 2022, 119, e2113947119. [Google Scholar] [CrossRef]
  22. Feckler, A.; Wolfram, J.; Schulz, R.; Bundschuh, M. Reducing Pollution to Levels Not Harming Biodiversity and Ecosystem Functions: A Perspective on the Post-2020 Global Biodiversity Framework. Curr. Opin. Environ. Sci. Health 2023, 35, 100495. [Google Scholar] [CrossRef]
  23. Fatimazahra, S.; Latifa, M.; Laila, S.; Monsif, K. Review of Hospital Effluents: Special Emphasis on Characterization, Impact, and Treatment of Pollutants and Antibiotic Resistance. Environ. Monit. Assess. 2023, 195, 393. [Google Scholar] [CrossRef]
  24. Fernandes, J.P.; Almeida, C.M.R.; Salgado, M.A.; Carvalho, M.F.; Mucha, A.P. Pharmaceutical Compounds in Aquatic Environments— Occurrence, Fate and Bioremediation Prospective. Toxics 2021, 9, 257. [Google Scholar] [CrossRef]
  25. Salimi, M.; Esrafili, A.; Gholami, M.; Jonidi Jafari, A.; Rezaei Kalantary, R.; Farzadkia, M.; Kermani, M.; Sobhi, H.R. Contaminants of Emerging Concern: A Review of New Approach in AOP Technologies. Environ. Monit. Assess. 2017, 189, 414. [Google Scholar] [CrossRef] [PubMed]
  26. Ortúzar, M.; Esterhuizen, M.; Olicón-Hernández, D.R.; González-López, J.; Aranda, E. Pharmaceutical Pollution in Aquatic Environments: A Concise Review of Environmental Impacts and Bioremediation Systems. Front. Microbiol. 2022, 13, 869332. [Google Scholar] [CrossRef]
  27. Lin, J.Y.; Zhang, Y.; Bian, Y.; Zhang, Y.X.; Du, R.Z.; Li, M.; Tan, Y.; Feng, X.S. Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) in the Environment: Recent Updates on the Occurrence, Fate, Hazards and Removal Technologies. Sci. Total Environ. 2023, 904, 166897. [Google Scholar] [CrossRef] [PubMed]
  28. Santos, L.H.M.L.M.; Rodríguez-Mozaz, S.; Barceló, D. Microplastics as Vectors of Pharmaceuticals in Aquatic Organisms—An Overview of Their Environmental Implications. Case Stud. Chem. Environ. Eng. 2021, 3, 100079. [Google Scholar] [CrossRef]
  29. Prestinaci, F.; Pezzotti, P.; Pantosti, A. Antimicrobial Resistance: A Global Multifaceted Phenomenon. Pathog. Glob. Health 2015, 109, 309–318. [Google Scholar] [CrossRef]
  30. Świacka, K.; Maculewicz, J.; Kowalska, D.; Caban, M.; Smolarz, K.; Świeżak, J. Presence of Pharmaceuticals and Their Metabolites in Wild-Living Aquatic Organisms—Current State of Knowledge. J. Hazard. Mater. 2022, 424, 127350. [Google Scholar] [CrossRef] [PubMed]
  31. Rios-Miguel, A.B.; van Bergen, T.J.H.M.; Zillien, C.; Ragas, A.M.J.; van Zelm, R.; Jetten, M.S.M.; Hendriks, A.J.; Welte, C.U. Predicting and Improving the Microbial Removal of Organic Micropollutants during Wastewater Treatment: A Review. Chemosphere 2023, 333, 138908. [Google Scholar] [CrossRef]
  32. Pinheiro, M.; Martins, I.; Raimundo, J.; Caetano, M.; Neuparth, T.; Santos, M.M. Stressors of Emerging Concern in Deep-Sea Environments: Microplastics, Pharmaceuticals, Personal Care Products and Deep-Sea Mining. Sci. Total Environ. 2023, 876, 162557. [Google Scholar] [CrossRef]
  33. Bethke, K.; Kropidłowska, K.; Stepnowski, P.; Caban, M. Review of Warming and Acidification Effects to the Ecotoxicity of Pharmaceuticals on Aquatic Organisms in the Era of Climate Change. Sci. Total Environ. 2023, 877, 162829. [Google Scholar] [CrossRef]
  34. Hejna, M.; Kapuścińska, D.; Aksmann, A. Pharmaceuticals in the Aquatic Environment: A Review on Eco-Toxicology and the Remediation Potential of Algae. Int. J. Environ. Res. Public Health 2022, 19, 7717. [Google Scholar] [CrossRef] [PubMed]
  35. Carvalho, I.T.; Santos, L. Antibiotics in the Aquatic Environments: A Review of the European Scenario. Environ. Int. 2016, 94, 736–757. [Google Scholar] [CrossRef]
  36. Nannou, C.; Ofrydopoulou, A.; Evgenidou, E.; Heath, D.; Heath, E.; Lambropoulou, D. Antiviral Drugs in Aquatic Environment and Wastewater Treatment Plants: A Review on Occurrence, Fate, Removal and Ecotoxicity. Sci. Total Environ. 2020, 699, 134322. [Google Scholar] [CrossRef] [PubMed]
  37. Eguchi, K.; Nagase, H.; Ozawa, M.; Endoh, Y.S.; Goto, K.; Hirata, K.; Miyamoto, K.; Yoshimura, H. Evaluation of Antimicrobial Agents for Veterinary Use in the Ecotoxicity Test Using Microalgae. Chemosphere 2004, 57, 1733–1738. [Google Scholar] [CrossRef] [PubMed]
  38. González-Pleiter, M.; Gonzalo, S.; Rodea-Palomares, I.; Leganés, F.; Rosal, R.; Boltes, K.; Marco, E.; Fernández-Piñas, F. Toxicity of Five Antibiotics and Their Mixtures towards Photosynthetic Aquatic Organisms: Implications for Environmental Risk Assessment. Water Res. 2013, 47, 2050–2064. [Google Scholar] [CrossRef]
  39. Świacka, K.; Michnowska, A.; Maculewicz, J.; Caban, M.; Smolarz, K. Toxic Effects of NSAIDs in Non-Target Species: A Review from the Perspective of the Aquatic Environment. Environ. Pollut. 2021, 273, 115891. [Google Scholar] [CrossRef]
  40. Cleuvers, M. Mixture Toxicity of the Anti-Inflammatory Drugs Diclofenac, Ibuprofen, Naproxen, and Acetylsalicylic Acid. Ecotoxicol. Environ. Saf. 2004, 59, 309–315. [Google Scholar] [CrossRef]
  41. Martins, N.; Pereira, R.; Abrantes, N.; Pereira, J.; Gonçalves, F.; Marques, C.R. Ecotoxicological Effects of Ciprofloxacin on Freshwater Species: Data Integration and Derivation of Toxicity Thresholds for Risk Assessment. Ecotoxicology 2012, 21, 1167–1176. [Google Scholar] [CrossRef]
  42. Załęska-Radziwiłł, M.; Łebkowska, M.; Affek, K.; Zarzeczna, A. Environmental Risk Assessment of Selected Pharmaceuticals Present in Surface Waters in Relation to Animals. Arch. Environ. Prot. 2011, 37, 31–42. [Google Scholar]
  43. Hartwig, C.; Muth-Köhne, E.; Düring, R.A. Screening for Ecotoxicological Effects of Antiepileptic Drugs in Biologically Treated Waste Water Originating from an Epilepsy Ward by Danio Rerio Embryos. Environ. Sci. Eur. 2013, 25, 29. [Google Scholar] [CrossRef]
  44. Argaluza, J.; Domingo-Echaburu, S.; Orive, G.; Medrano, J.; Hernandez, R.; Lertxundi, U. Environmental Pollution with Psychiatric Drugs. World J. Psychiatry 2021, 11, 791–804. [Google Scholar] [CrossRef] [PubMed]
  45. Duarte, I.A.; Reis-Santos, P.; Novais, S.C.; Rato, L.D.; Lemos, M.F.L.; Freitas, A.; Pouca, A.S.V.; Barbosa, J.; Cabral, H.N.; Fonseca, V.F. Depressed, Hypertense and Sore: Long-Term Effects of Fluoxetine, Propranolol and Diclofenac Exposure in a Top Predator Fish. Sci. Total Environ. 2020, 712, 136564. [Google Scholar] [CrossRef]
  46. Aguirre-Martínez, G.V.; Del Valls, T.A.; Martín-Díaz, M.L. Identification of Biomarkers Responsive to Chronic Exposure to Pharmaceuticals in Target Tissues of Carcinus Maenas. Mar. Environ. Res. 2013, 87–88, 1–11. [Google Scholar] [CrossRef]
  47. Yamamoto, H.; Nakamura, Y.; Moriguchi, S.; Nakamura, Y.; Honda, Y.; Tamura, I.; Hirata, Y.; Hayashi, A.; Sekizawa, J. Persistence and Partitioning of Eight Selected Pharmaceuticals in the Aquatic Environment: Laboratory Photolysis, Biodegradation, and Sorption Experiments. Water Res. 2009, 43, 351–362. [Google Scholar] [CrossRef] [PubMed]
  48. Pal, A.; Gin, K.Y.H.; Lin, A.Y.C.; Reinhard, M. Impacts of Emerging Organic Contaminants on Freshwater Resources: Review of Recent Occurrences, Sources, Fate and Effects. Sci. Total Environ. 2010, 408, 6062–6069. [Google Scholar] [CrossRef]
  49. Lapworth, D.J.; Baran, N.; Stuart, M.E.; Ward, R.S. Emerging Organic Contaminants in Groundwater: A Review of Sources, Fate and Occurrence. Environ. Pollut. 2012, 163, 287–303. [Google Scholar] [CrossRef]
  50. Kummerer, K. Pharmaceuticals in the Environment. Annu. Rev. Environ. Resour. 2010, 35, 57–75. [Google Scholar] [CrossRef]
  51. Kasprzyk-Hordern, B. Pharmacologically Active Compounds in the Environment and Their Chirality. Chem. Soc. Rev. 2010, 39, 4466–4503. [Google Scholar] [CrossRef]
  52. Kasprzyk-Hordern, B.; Baker, D.R. Estimation of Community-Wide Drugs Use via Stereoselective Profiling of Sewage. Sci. Total Environ. 2012, 423, 142–150. [Google Scholar] [CrossRef] [PubMed]
  53. Miller, T.H.; Bury, N.R.; Owen, S.F.; MacRae, J.I.; Barron, L.P. A Review of the Pharmaceutical Exposome in Aquatic Fauna. Environ. Pollut. 2018, 239, 129–146. [Google Scholar] [CrossRef] [PubMed]
  54. Wilkinson, J.L.; Boxall, A.B.A.; Kolpin, D.W. A Novel Method to Characterise Levels of Pharmaceutical Pollution in Large-Scale Aquatic Monitoring Campaigns. Appl. Sci. 2019, 9, 1368. [Google Scholar] [CrossRef]
  55. Kontana, A.; Papadimitriou, C.A.; Samaras, P.; Zdragas, A.; Yiangou, M. Bioassays and Biomarkers for Ecotoxicological Assessment of Reclaimed Municipal Wastewater. Water Sci. Technol. 2008, 57, 947–953. [Google Scholar] [CrossRef]
  56. Maranho, L.A.; Baena-Nogueras, R.M.; Lara-Martín, P.A.; DelValls, T.A.; Martín-Díaz, M.L. Bioavailability, Oxidative Stress, Neurotoxicity and Genotoxicity of Pharmaceuticals Bound to Marine Sediments. The Use of the Polychaete Hediste Diversicolor as Bioindicator Species. Environ. Res. 2014, 134, 353–365. [Google Scholar] [CrossRef]
  57. Mercado, S.A.S.; Galvis, D.G.V. Paracetamol Ecotoxicological Bioassay Using the Bioindicators Lens Culinaris Med. and Pisum Sativum L. Environ. Sci. Pollut. Res. 2023, 30, 61965–61976. [Google Scholar] [CrossRef] [PubMed]
  58. Rodrigues, S.; Pinto, I.; Martins, F.; Formigo, N.; Antunes, S.C. Can Biochemical Endpoints Improve the Sensitivity of the Biomonitoring Strategy Using Bioassays with Standard Species, for Water Quality Evaluation? Ecotoxicol. Environ. Saf. 2021, 215, 112151. [Google Scholar] [CrossRef]
  59. Gavrilescu, M.; Demnerová, K.; Aamand, J.; Agathos, S.; Fava, F. Emerging Pollutants in the Environment: Present and Future Challenges in Biomonitoring, Ecological Risks and Bioremediation. New Biotechnol. 2015, 32, 147–156. [Google Scholar] [CrossRef] [PubMed]
  60. Chauhan, B.; Dodamani, S.; Malik, S.; Almalki, W.H.; Haque, S.; Sayyed, R.Z. Microbial Approaches for Pharmaceutical Wastewater Recycling and Management for Sustainable Development: A Multicomponent Approach. Environ. Res. 2023, 237, 116983. [Google Scholar] [CrossRef]
  61. Mishra, S.; Singh, A.K.; Cheng, L.; Hussain, A.; Maiti, A. Occurrence of Antibiotics in Wastewater: Potential Ecological Risk and Removal through Anaerobic–Aerobic Systems. Environ. Res. 2023, 226, 115678. [Google Scholar] [CrossRef]
  62. Lin, Y.; Zhong, W.; Zhang, X.; Zhou, X.; He, L.; Lv, J.; Zhao, Z. Environmental DNA Metabarcoding Revealed the Impacts of Anthropogenic Activities on Phytoplankton Diversity in Dianchi Lake and Its Three Inflow Rivers. Ecol. Evol. 2023, 13, e10088. [Google Scholar] [CrossRef]
  63. Cardinale, B.J.; Duffy, J.E.; Gonzalez, A.; Hooper, D.U.; Perrings, C.; Venail, P.; Narwani, A.; MacE, G.M.; Tilman, D.; Wardle, D.A.; et al. Biodiversity Loss and Its Impact on Humanity. Nature 2012, 486, 59–67. [Google Scholar] [CrossRef]
  64. Shim, K.Y.; Shin, H.; Yeo, I.C.; Kim, K.R.; Kwak, I.S.; Jeong, C.B. Environmental DNA Surveillance of Biocontamination in a Drinking Water Treatment Plant. J. Hazard. Mater. 2023, 456, 131656. [Google Scholar] [CrossRef] [PubMed]
  65. Bernhard, A.E.; Field, K.G. Identification of Nonpoint Sources of Fecal Pollution in Coastal Waters by Using Host-Specific 16S Ribosomal DNA Genetic Markers from Fecal Anaerobes. Appl. Environ. Microbiol. 2000, 66, 1587–1594. [Google Scholar] [CrossRef] [PubMed]
  66. Li, F.; Peng, Y.; Fang, W.; Altermatt, F.; Xie, Y.; Yang, J.; Zhang, X. Application of Environmental DNA Metabarcoding for Predicting Anthropogenic Pollution in Rivers. Environ. Sci. Technol. 2018, 52, 11708–11719. [Google Scholar] [CrossRef]
  67. Wang, S.; Zhang, P.; Zhang, D.; Chang, J. Evaluation and Comparison of the Benthic and Microbial Indices of Biotic Integrity for Urban Lakes Based on Environmental DNA and Its Management Implications. J. Environ. Manag. 2023, 341, 118026. [Google Scholar] [CrossRef] [PubMed]
  68. Zan, R.; Blackburn, A.; Plaimart, J.; Acharya, K.; Walsh, C.; Stirling, R.; Kilsby, C.G.; Werner, D. Environmental DNA Clarifies Impacts of Combined Sewer Overflows on the Bacteriology of an Urban River and Resulting Risks to Public Health. Sci. Total Environ. 2023, 889, 164282. [Google Scholar] [CrossRef] [PubMed]
  69. Zhang, L.; Yang, J.; Zhang, Y.; Shi, J.; Yu, H.; Zhang, X. eDNAeDNA Biomonitoring Revealed the Ecological Effects of Water Diversion Projects between Yangtze River and Tai Lake. Water Res. 2022, 210, 117994. [Google Scholar] [CrossRef]
  70. Aulsebrook, L.C.; Wong, B.B.M.; Hall, M.D. Can Pharmaceutical Pollution Alter the Spread of Infectious Disease? A Case Study Using Fluoxetine. Philos. Trans. R. Soc. B Biol. Sci. 2023, 378, 20220010. [Google Scholar] [CrossRef]
  71. Barnes, M.A.; Turner, C.R.; Jerde, C.L.; Renshaw, M.A.; Chadderton, W.L.; Lodge, D.M. Environmental Conditions Influence eDNA Persistence in Aquatic Systems. Environ. Sci. Technol. 2014, 48, 1819–1827. [Google Scholar] [CrossRef]
  72. Greco, M.; Lejzerowicz, F.; Reo, E.; Caruso, A.; Maccotta, A.; Coccioni, R.; Pawlowski, J.; Frontalini, F. Environmental RNA Outperforms eDNA Metabarcoding in Assessing Impact of Marine Pollution: A Chromium-Spiked Mesocosm Test. Chemosphere 2022, 298, 134239. [Google Scholar] [CrossRef] [PubMed]
  73. Jerde, C.L.; Olds, B.P.; Shogren, A.J.; Andruszkiewicz, E.A.; Mahon, A.R.; Bolster, D.; Tank, J.L. Influence of Stream Bottom Substrate on Retention and Transport of Vertebrate Environmental DNA. Environ. Sci. Technol. 2016, 50, 8770–8779. [Google Scholar] [CrossRef]
  74. Suarez-Menendez, M.; Planes, S.; Garcia-Vazquez, E.; Ardura, A. Early Alert of Biological Risk in a Coastal Lagoon Through eDNA Metabarcoding. Front. Ecol. Evol. 2020, 8, 9. [Google Scholar] [CrossRef]
  75. Moher, D.; Liberati, A.; Tetzlaff, J.; Altman, D.G.; Antes, G.; Atkins, D.; Barbour, V.; Barrowman, N.; Berlin, J.A.; Clark, J.; et al. Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement. PLoS Med. 2009, 6, e1000097. [Google Scholar] [CrossRef]
  76. Barra Caracciolo, A.; Topp, E.; Grenni, P. Pharmaceuticals in the Environment: Biodegradation and Effects on Natural Microbial Communities. A Review. J. Pharm. Biomed. Anal. 2015, 106, 25–36. [Google Scholar] [CrossRef] [PubMed]
  77. Arnold, K.E.; Brown, A.R.; Brown, A.R.; Ankley, G.T.; Sumpter, J.P. Medicating the Environment: Assessing Risks of Pharmaceuticals to Wildlife and Ecosystems. Philos. Trans. R. Soc. B Biol. Sci. 2014, 369, 20130569. [Google Scholar] [CrossRef] [PubMed]
  78. Grenni, P.; Ancona, V.; Barra Caracciolo, A. Ecological Effects of Antibiotics on Natural Ecosystems: A Review. Microchem. J. 2018, 136, 25–39. [Google Scholar] [CrossRef]
  79. King, K.C.; Hall, M.D.; Wolinska, J. Infectious Disease Ecology and Evolution in a Changing World. Philos. Trans. R. Soc. B Biol. Sci. 2023, 378, 20220002. [Google Scholar] [CrossRef]
  80. Caban, M.; Stepnowski, P. How to Decrease Pharmaceuticals in the Environment? A Review. Environ. Chem. Lett. 2021, 19, 3115–3138. [Google Scholar] [CrossRef]
  81. Bilal, M.; Mehmood, S.; Rasheed, T.; Iqbal, H.M.N. Antibiotics Traces in the Aquatic Environment: Persistence and Adverse Environmental Impact. Curr. Opin. Environ. Sci. Health 2020, 13, 68–74. [Google Scholar] [CrossRef]
  82. Bondarczuk, K.; Piotrowska-Seget, Z. Microbial Diversity and Antibiotic Resistance in a Final Effluent-Receiving Lake. Sci. Total Environ. 2019, 650, 2951–2961. [Google Scholar] [CrossRef]
  83. Lai, C.C.; Chen, S.Y.; Ko, W.C.; Hsueh, P.R. Increased Antimicrobial Resistance during the COVID-19 Pandemic. Int. J. Antimicrob. Agents 2021, 57, 106324. [Google Scholar] [CrossRef]
  84. López-Serna, R.; Jurado, A.; Vázquez-Suñé, E.; Carrera, J.; Petrović, M.; Barceló, D. Occurrence of 95 Pharmaceuticals and Transformation Products in Urban Groundwaters Underlying the Metropolis of Barcelona, Spain. Environ. Pollut. 2013, 174, 305–315. [Google Scholar] [CrossRef] [PubMed]
  85. Michaelis, C.; Grohmann, E. Horizontal Gene Transfer of Antibiotic Resistance Genes in Biofilms. Antibiotics 2023, 12, 328. [Google Scholar] [CrossRef]
  86. Mukhtar, A.; Manzoor, M.; Gul, I.; Zafar, R.; Jamil, H.I.; Niazi, A.K.; Ali, M.A.; Park, T.J.; Arshad, M. Phytotoxicity of Different Antibiotics to Rice and Stress Alleviation upon Application of Organic Amendments. Chemosphere 2020, 258, 127353. [Google Scholar] [CrossRef] [PubMed]
  87. Peng, X.; Yu, Y.; Tang, C.; Tan, J.; Huang, Q.; Wang, Z. Occurrence of Steroid Estrogens, Endocrine-Disrupting Phenols, and Acid Pharmaceutical Residues in Urban Riverine Water of the Pearl River Delta, South China. Sci. Total Environ. 2008, 397, 158–166. [Google Scholar] [CrossRef]
  88. Peng, X.; Zhang, K.; Tang, C.; Huang, Q.; Yu, Y.; Cui, J. Distribution Pattern, Behavior, and Fate of Antibacterials in Urban Aquatic Environments in South China. J. Environ. Monit. 2011, 13, 446–454. [Google Scholar] [CrossRef]
  89. Samal, K.; Mahapatra, S.; Hibzur Ali, M. Pharmaceutical Wastewater as Emerging Contaminants (EC): Treatment Technologies, Impact on Environment and Human Health. Energy Nexus 2022, 6, 100076. [Google Scholar] [CrossRef]
  90. Serwecińska, L. Antimicrobials and Antibiotic-Resistant Bacteria: A Risk to the Environment and to Public Health. Water 2020, 12, 3313. [Google Scholar] [CrossRef]
  91. Valcárcel, Y.; González Alonso, S.; Rodríguez-Gil, J.L.; Gil, A.; Catalá, M. Detection of Pharmaceutically Active Compounds in the Rivers and Tap Water of the Madrid Region (Spain) and Potential Ecotoxicological Risk. Chemosphere 2011, 84, 1336–1348. [Google Scholar] [CrossRef] [PubMed]
  92. Andrade-Eiroa, A.; Canle, M.; Leroy-Cancellieri, V.; Cerdà, V. Solid-Phase Extraction of Organic Compounds: A Critical Review (Part I). Trends Anal. Chem. 2016, 80, 641–654. [Google Scholar] [CrossRef]
  93. Braun, J.M. Early-Life Exposure to EDCs: Role in Childhood Obesity and Neurodevelopment. Nat. Rev. Endocrinol. 2017, 13, 161–173. [Google Scholar] [CrossRef]
  94. Forte, M.; Di Lorenzo, M.; Carrizzo, A.; Valiante, S.; Vecchione, C.; Laforgia, V.; De Falco, M. Nonylphenol Effects on Human Prostate Non Tumorigenic Cells. Toxicology 2016, 357–358, 21–32. [Google Scholar] [CrossRef] [PubMed]
  95. Forte, M.; Di Lorenzo, M.; Iachetta, G.; Mita, D.G.; Laforgia, V.; De Falco, M. Nonylphenol Acts on Prostate Adenocarcinoma Cells via Estrogen Molecular Pathways. Ecotoxicol. Environ. Saf. 2019, 180, 412–419. [Google Scholar] [CrossRef] [PubMed]
  96. Gröger, T.M.; Käfer, U.; Zimmermann, R. Gas Chromatography in Combination with Fast High-Resolution Time-of-Flight Mass Spectrometry: Technical Overview and Perspectives for Data Visualization. Trends Anal. Chem. 2020, 122, 115677. [Google Scholar] [CrossRef]
  97. Heindel, J.J.; Newbold, R.; Schug, T.T. Endocrine Disruptors and Obesity. Nat. Rev. Endocrinol. 2015, 11, 653–661. [Google Scholar] [CrossRef]
  98. Li, C.; Wei, Y.; Zhang, S.; Tan, W. Advanced Methods to Analyze Steroid Estrogens in Environmental Samples. Environ. Chem. Lett. 2020, 18, 543–559. [Google Scholar] [CrossRef]
  99. Marotta, V.; Russo, G.; Gambardella, C.; Grasso, M.; La Sala, D.; Chiofalo, M.G.; D’Anna, R.; Puzziello, A.; Docimo, G.; Masone, S.; et al. Human Exposure to Bisphenol AF and Diethylhexylphthalate Increases Susceptibility to Develop Differentiated Thyroid Cancer in Patients with Thyroid Nodules. Chemosphere 2019, 218, 885–894. [Google Scholar] [CrossRef]
  100. Nadal, A.; Quesada, I.; Tudurí, E.; Nogueiras, R.; Alonso-Magdalena, P. Endocrine-Disrupting Chemicals and the Regulation of Energy Balance. Nat. Rev. Endocrinol. 2017, 13, 536–546. [Google Scholar] [CrossRef]
  101. Izadi, P.; Izadi, P.; Salem, R.; Papry, S.A.; Magdouli, S.; Pulicharla, R.; Brar, S.K. Non-Steroidal Anti-Inflammatory Drugs in the Environment: Where Were We and How Far We Have Come? Environ. Pollut. 2020, 267, 115370. [Google Scholar] [CrossRef] [PubMed]
  102. Jan-Roblero, J.; Cruz-Maya, J.A. Ibuprofen: Toxicology and Biodegradation of an Emerging Contaminant. Molecules 2023, 28, 2097. [Google Scholar] [CrossRef]
  103. Parolini, M. Toxicity of the Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) Acetylsalicylic Acid, Paracetamol, Diclofenac, Ibuprofen and Naproxen towards Freshwater Invertebrates: A Review. Sci. Total Environ. 2020, 740, 140043. [Google Scholar] [CrossRef] [PubMed]
  104. Tyumina, E.A.; Bazhutin, G.A.; Cartagena Gómez, A.d.P.; Ivshina, I.B. Nonsteroidal Anti-Inflammatory Drugs as Emerging Contaminants. Microbiology 2020, 89, 148–163. [Google Scholar] [CrossRef]
  105. Huynh, N.C.; Nguyen, T.T.T.; Nguyen, D.T.C.; Tran, T. Van Occurrence, Toxicity, Impact and Removal of Selected Non-Steroidal Anti-Inflammatory Drugs (NSAIDs): A Review. Sci. Total Environ. 2023, 898, 165317. [Google Scholar] [CrossRef] [PubMed]
  106. Gao, S.; Yang, F. Behavioral Changes and Neurochemical Responses in Chinese Rare Minnow Exposed to Four Psychoactive Substances. Sci. Total Environ. 2022, 808, 152100. [Google Scholar] [CrossRef]
  107. Gupta, I.; Clauder-Münster, S.; Klaus, B.; Järvelin, A.I.; Aiyar, R.S.; Benes, V.; Wilkening, S.; Huber, W.; Pelechano, V.; Steinmetz, L.M. Alternative Polyadenylation Diversifies Post-Transcriptional Regulation by Selective RNA-Protein Interactions. Mol. Syst. Biol. 2014, 10, 719. [Google Scholar] [CrossRef] [PubMed]
  108. Mousel, D.; Bastian, D.; Firk, J.; Palmowski, L.; Pinnekamp, J. Removal of Pharmaceuticals from Wastewater of Health Care Facilities. Sci. Total Environ. 2021, 751, 141310. [Google Scholar] [CrossRef]
  109. Huggett, D.B.; Brooks, B.W.; Peterson, B.; Foran, C.M.; Schlenk, D. Toxicity of Select Beta Adrenergic Receptor-Blocking Pharmaceuticals (B-Blockers) on Aquatic Organisms. Arch. Environ. Contam. Toxicol. 2002, 43, 229–235. [Google Scholar] [CrossRef] [PubMed]
  110. Maszkowska, J.; Stolte, S.; Kumirska, J.; Łukaszewicz, P.; Mioduszewska, K.; Puckowski, A.; Caban, M.; Wagil, M.; Stepnowski, P.; Białk-Bielińska, A. Beta-Blockers in the Environment: Part II. Ecotoxicity Study. Sci. Total Environ. 2014, 493, 1122–1126. [Google Scholar] [CrossRef]
  111. De Oliveira, L.L.D.; Antunes, S.C.; Gonçalves, F.; Rocha, O.; Nunes, B. Acute and Chronic Ecotoxicological Effects of Four Pharmaceuticals Drugs on Cladoceran Daphnia Magna. Drug Chem. Toxicol. 2016, 39, 13–21. [Google Scholar] [CrossRef]
  112. Rutere, C.; Posselt, M.; Ho, A.; Horn, M.A. Biodegradation of Metoprolol in Oxic and Anoxic Hyporheic Zone Sediments: Unexpected Effects on Microbial Communities. Appl. Microbiol. Biotechnol. 2021, 105, 6103–6115. [Google Scholar] [CrossRef]
  113. Li, D.; Chen, H.; Liu, H.; Schlenk, D.; Mu, J.; Lacorte, S.; Ying, G.G.; Xie, L. Anticancer Drugs in the Aquatic Ecosystem: Environmental Occurrence, Ecotoxicological Effect and Risk Assessment. Environ. Int. 2021, 153, 106543. [Google Scholar] [CrossRef]
  114. Nassour, C.; Barton, S.J.; Nabhani-Gebara, S.; Saab, Y.; Barker, J. Occurrence of Anticancer Drugs in the Aquatic Environment: A Systematic Review. Environ. Sci. Pollut. Res. 2020, 27, 1339–1347. [Google Scholar] [CrossRef]
  115. Rowney, N.C.; Johnson, A.C.; Williams, R.J. Cytotoxic Drugs in Drinking Water: A Prediction and Risk Assessment Exercise for the Thames Catchment in the United Kingdom. Environ. Toxicol. Chem. 2009, 28, 2733–2743. [Google Scholar] [CrossRef] [PubMed]
  116. Kümmerer, K. Antibiotics in the Aquatic Environment—A Review—Part I. Chemosphere 2009, 75, 417–434. [Google Scholar] [CrossRef]
  117. Gore, A.C.; Chappell, V.A.; Fenton, S.E.; Flaws, J.A.; Nadal, A.; Prins, G.S.; Toppari, J.; Zoeller, R.T. Executive Summary to EDC-2: The Endocrine Society’s Second Scientific Statement on Endocrine-Disrupting Chemicals. Endocr. Rev. 2015, 36, 593–602. [Google Scholar] [CrossRef] [PubMed]
  118. Kabir, E.R.; Rahman, M.S.; Rahman, I. A Review on Endocrine Disruptors and Their Possible Impacts on Human Health. Environ. Toxicol. Pharmacol. 2015, 40, 241–258. [Google Scholar] [CrossRef]
  119. Kiyama, R.; Wada-Kiyama, Y. Estrogenic Endocrine Disruptors: Molecular Mechanisms of Action. Environ. Int. 2015, 83, 11–40. [Google Scholar] [CrossRef]
  120. Gore, A.C.; Crews, D.; Doan, L.L.; Merrill, M.L.; Patisaul, H.; Zota, A. Introduction to Endocrine Disrupting Chemicals (EDCs): A Guide for Public Interest Organizations and Policymakers; IPEN: Göteborg, Sweden, 2014; pp. 21–22. [Google Scholar]
  121. Tijani, J.O.; Fatoba, O.O.; Babajide, O.O.; Petrik, L.F. Pharmaceuticals, Endocrine Disruptors, Personal Care Products, Nanomaterials and Perfluorinated Pollutants: A Review. Environ. Chem. Lett. 2016, 14, 27–49. [Google Scholar] [CrossRef]
  122. Huang, S.; Qi, Z.; Ma, S.; Li, G.; Long, C.; Yu, Y. A Critical Review on Human Internal Exposure of Phthalate Metabolites and the Associated Health Risks. Environ. Pollut. 2021, 279, 116941. [Google Scholar] [CrossRef]
  123. De Coster, S.; Van Larebeke, N. Endocrine-Disrupting Chemicals: Associated Disorders and Mechanisms of Action. J. Environ. Public Health 2012, 2012, 713696. [Google Scholar] [CrossRef]
  124. Monneret, C. What Is an Endocrine Disruptor? Comptes Rendus. Biol. 2017, 340, 403–405. [Google Scholar] [CrossRef] [PubMed]
  125. Akhbarizadeh, R.; Russo, G.; Rossi, S.; Golianova, K.; Moore, F.; Guida, M.; De Falco, M.; Grumetto, L. Emerging Endocrine Disruptors in Two Edible Fish from the Persian Gulf: Occurrence, Congener Profile, and Human Health Risk Assessment. Mar. Pollut. Bull. 2021, 166, 112241. [Google Scholar] [CrossRef]
  126. Vieira, W.T.; de Farias, M.B.; Spaolonzi, M.P.; da Silva, M.G.C.; Vieira, M.G.A. Removal of Endocrine Disruptors in Waters by Adsorption, Membrane Filtration and Biodegradation. A Review. Environ. Chem. Lett. 2020, 18, 1113–1143. [Google Scholar] [CrossRef]
  127. Gonsioroski, A.; Mourikes, V.E.; Flaws, J.A. Endocrine Disruptors in Water and Their Effects on the Reproductive System. Int. J. Mol. Sci. 2020, 21, 1929. [Google Scholar] [CrossRef]
  128. Feng, L.; van Hullebusch, E.D.; Rodrigo, M.A.; Esposito, G.; Oturan, M.A. Removal of Residual Anti-Inflammatory and Analgesic Pharmaceuticals from Aqueous Systems by Electrochemical Advanced Oxidation Processes. A Review. Chem. Eng. J. 2013, 228, 944–964. [Google Scholar] [CrossRef]
  129. Azmi Hassali, M.; Shakeel, S. Unused and Expired Medications Disposal Practices among the General Public in Selangor, Malaysia. Pharmacy 2020, 8, 196. [Google Scholar] [CrossRef]
  130. Vieno, N.; Tuhkanen, T.; Kronberg, L. Elimination of Pharmaceuticals in Sewage Treatment Plants in Finland. Water Res. 2007, 41, 1001–1012. [Google Scholar] [CrossRef] [PubMed]
  131. Xu, J.; Sun, H.; Zhang, Y.; Alder, A.C. Occurrence and Enantiomer Profiles of β-Blockers in Wastewater and a Receiving Water Body and Adjacent Soil in Tianjin, China. Sci. Total Environ. 2019, 650, 1122–1130. [Google Scholar] [CrossRef] [PubMed]
  132. Godoy, A.A.; Kummrow, F.; Pamplin, P.A.Z. Occurrence, Ecotoxicological Effects and Risk Assessment of Antihypertensive Pharmaceutical Residues in the Aquatic Environment—A Review. Chemosphere 2015, 138, 281–291. [Google Scholar] [CrossRef] [PubMed]
  133. Maszkowska, J.; Stolte, S.; Kumirska, J.; Łukaszewicz, P.; Mioduszewska, K.; Puckowski, A.; Caban, M.; Wagil, M.; Stepnowski, P.; Białk-Bielińska, A. Beta-Blockers in the Environment: Part I. Mobility and Hydrolysis Study. Sci. Total Environ. 2014, 493, 1112–1121. [Google Scholar] [CrossRef]
  134. Heath, E.; Filipič, M.; Kosjek, T.; Isidori, M. Fate and Effects of the Residues of Anticancer Drugs in the Environment. Environ. Sci. Pollut. Res. 2016, 23, 14687–14691. [Google Scholar] [CrossRef] [PubMed]
  135. Wormington, A.M.; De María, M.; Kurita, H.G.; Bisesi, J.H.; Denslow, N.D.; Martyniuk, C.J. Antineoplastic Agents: Environmental Prevalence and Adverse Outcomes in Aquatic Organisms. Environ. Toxicol. Chem. 2020, 39, 967–985. [Google Scholar] [CrossRef]
  136. Grassi, M.; Kaykioglu, G.; Belgiorno, V.; Lofrano, G. Removal of Emerging Contaminants from Water and Wastewater by Adsorption Process. In Emerging Compounds Removal from Wastewater Natural and Solar Based Treatments; Lofrano, G., Ed.; Springer: Salerno, Italy, 2012; pp. 15–37. [Google Scholar]
  137. Falisse, E.; Voisin, A.S.; Silvestre, F. Impacts of Triclosan Exposure on Zebrafish Early-Life Stage: Toxicity and Acclimation Mechanisms. Aquat. Toxicol. 2017, 189, 97–107. [Google Scholar] [CrossRef]
  138. Khan, F.I.; Husain, T.; Hejazi, R. An Overview and Analysis of Site Remediation Technologies. J. Environ. Manag. 2004, 71, 95–122. [Google Scholar] [CrossRef]
  139. Kuppusamy, S.; Palanisami, T.; Megharaj, M.; Venkateswarlu, K.; Naidu, R. In-Situ Remediation Approaches for the Management of Contaminated Sites: A Comprehensive Overview. In Reviews of Environmental Contamination and Toxicology; de Voogt, P., Ed.; Springer: New York, NY, USA, 2016; Volume 236, pp. 1–115. [Google Scholar]
  140. Chang, C.Y.; Chang, J.S.; Vigneswaran, S.; Kandasamy, J. Pharmaceutical Wastewater Treatment by Membrane Bioreactor Process—A Case Study in Southern Taiwan. Desalination 2008, 234, 393–401. [Google Scholar] [CrossRef]
  141. Madukasi, E.I.; Dai, X.; He, C.; Zhou, J. Potentials of Phototrophic Bacteria in Treating Pharmaceutical Wastewater. Int. J. Environ. Sci. Technol. 2010, 7, 165–174. [Google Scholar] [CrossRef]
  142. Spina, F.; Anastasi, A.E.; Prigione, V.P.; Tigini, V.; Varese, G. Biological Treatment of Industrial Wastewaters: A Fungal Approach. Chem. Eng. Trans. 2012, 27, 175–180. [Google Scholar]
  143. Haq, I.; Raj, A. Endocrine-Disrupting Pollutants in Industrial Wastewater and Their and Detoxification. In Emerging and Eco-Friendly Approaches for Waste Management; Bharagava, R.N., Chowdhary, P., Eds.; Springer: Singapore, 2019; pp. 121–142. ISBN 9789811086694. [Google Scholar]
  144. Leusch, F.D.L.; Neale, P.A.; Busetti, F.; Card, M.; Humpage, A.; Orbell, J.D.; Ridgway, H.F.; Stewart, M.B.; van de Merwe, J.P.; Escher, B.I. Transformation of Endocrine Disrupting Chemicals, Pharmaceutical and Personal Care Products during Drinking Water Disinfection. Sci. Total Environ. 2019, 657, 1480–1490. [Google Scholar] [CrossRef]
  145. Abd El-Gawad, S.A.; Abd ElAziz, H.M. Effective Removal of Chemical Oxygen Demand and Phosphates from Aqueous Medium Using Entrapped Activated Carbon in Alginate. MOJ Biol. Med. 2018, 3, 227–236. [Google Scholar] [CrossRef]
  146. Martín de Vidales, M.J.; Rua, J.; de Juan, J.L.M.; Fernández-Martínez, F.; Dos Santos-García, A.J. Degradation of Contaminants of Emerging Concern by Electrochemical Oxidation: Coupling of Ultraviolet and Ultrasound Radiations. Materials 2020, 13, 5551. [Google Scholar] [CrossRef]
  147. Qin, K.; Zhao, Q.; Yu, H.; Xia, X.; Li, J.; He, S.; Wei, L.; An, T. A Review of Bismuth-Based Photocatalysts for Antibiotic Degradation: Insight into the Photocatalytic Degradation Performance, Pathways and Relevant Mechanisms. Environ. Res. 2021, 199, 111360. [Google Scholar] [CrossRef]
  148. An, T.; Yang, H.; Li, G.; Song, W.; Cooper, W.J.; Nie, X. Kinetics and Mechanism of Advanced Oxidation Processes (AOPs) in Degradation of Ciprofloxacin in Water. Appl. Catal. B 2010, 94, 288–294. [Google Scholar] [CrossRef]
  149. Chen, J.; Luo, H.; Shi, H.; Li, G.; An, T. Anatase TiO2 Nanoparticles-Carbon Nanotubes Composite: Optimization Synthesis and the Relationship of Photocatalytic Degradation Activity of Acyclovir in Water. Appl. Catal. A Gen. 2014, 485, 188–195. [Google Scholar] [CrossRef]
  150. Li, G.; Nie, X.; Chen, J.; Wong, P.K.; An, T.; Yamashita, H.; Zhao, H. Enhanced Simultaneous PEC Eradication of Bacteria and Antibiotics by Facilely Fabricated High-Activity {001} Facets TiO2 Mounted onto TiO2 Nanotubular Photoanode. Water Res. 2016, 101, 597–605. [Google Scholar] [CrossRef]
  151. Khan, J.A.; He, X.; Khan, H.M.; Shah, N.S.; Dionysiou, D.D. Oxidative Degradation of Atrazine in Aqueous Solution by UV/H2O2/Fe2+, UV/S2 O 8 2 /Fe2+ and UV/HS O 5 /Fe2+ Processes: A Comparative Study. Chem. Eng. J. 2013, 218, 376–383. [Google Scholar] [CrossRef]
  152. Stadlmair, L.F.; Letzel, T.; Drewes, J.E.; Grassmann, J. Enzymes in Removal of Pharmaceuticals from Wastewater: A Critical Review of Challenges, Applications and Screening Methods for Their Selection. Chemosphere 2018, 205, 649–661. [Google Scholar] [CrossRef] [PubMed]
  153. Burke, V.; Duennbier, U.; Massmann, G. The Effect of Aeration on the Removal of Wastewater-Derived Pharmaceutical Residues from Groundwater ⋯ A Laboratory Study. Water Sci. Technol. 2013, 67, 658–666. [Google Scholar] [CrossRef] [PubMed]
  154. Adams, C.; Asce, M.; Wang, Y.; Loftin, K.; Meyer, M. Removal of Antibiotics from Surface and Distilled Water in Conventional Water Treatment Processes. J. Environ. Eng. 2002, 128, 253–260. [Google Scholar] [CrossRef]
  155. Ternes, T.A.; Meisenheimer, M.; McDowell, D.; Sacher, F.; Brauch, H.J.; Haist-Gulde, B.; Preuss, G.; Wilme, U.; Zulei-Seibert, N. Removal of Pharmaceuticals during Drinking Water Treatment. Environ. Sci. Technol. 2002, 36, 3855–3863. [Google Scholar] [CrossRef]
  156. Westerhoff, P.; Yoon, Y.; Snyder, S.; Wert, E. Fate of Endocrine-Disruptor, Pharmaceutical, and Personal Care Product Chemicals during Simulated Drinking Water Treatment Processes. Environ. Sci. Technol. 2005, 39, 6649–6663. [Google Scholar] [CrossRef]
  157. Ferreira, R.C.; De Lima, H.H.C.; Cândido, A.A.; Junior, O.C.; Arroyo, P.A.; De Carvalho, K.Q.; Gauze, G.F.; Barros, M.A.S.D. Adsorption of Paracetamol Using Activated Carbon of Dende and Babassu Coconut Mesocarp. Int. J. Biotechnol. Bioeng. 2015, 9, 717–722. [Google Scholar] [CrossRef]
  158. Mukoko, T.; Mupa, M.; Guyo, U.; Dziike, F. Preparation of Rice Hull Activated Carbon for the Removal of Selected Pharmaceutical Waste Compounds in Hospital Effluent. J. Environ. Anal. Toxicol. 2015, s7, 1–9. [Google Scholar] [CrossRef]
  159. Nazari, G.; Abolghasemi, H.; Esmaieli, M. Batch Adsorption of Cephalexin Antibiotic from Aqueous Solution by Walnut Shell-Based Activated Carbon. J. Taiwan. Inst. Chem. Eng. 2016, 58, 357–365. [Google Scholar] [CrossRef]
  160. Ahmadi, S.; Banach, A.; Kord Mostafapour, F.; Balarak, D. Study Survey of Cupric Oxide Nanoparticles in Removal Efficiency of Ciprofloxacin Antibiotic from Aqueous Solution: Adsorption Isotherm Study. Desalination Water Treat. 2017, 89, 297–303. [Google Scholar] [CrossRef]
  161. Prasannamedha, G.; Kumar, P.S.; Mehala, R.; Sharumitha, T.J.; Surendhar, D. Enhanced Adsorptive Removal of Sulfamethoxazole from Water Using Biochar Derived from Hydrothermal Carbonization of Sugarcane Bagasse. J. Hazard. Mater. 2021, 407, 124825. [Google Scholar] [CrossRef]
  162. Richter, D.; Massmann, G.; Dünnbier, U. Behaviour and Biodegradation of Sulfonamides (p-TSA, o-TSA, BSA) during Drinking Water Treatment. Chemosphere 2008, 71, 1574–1581. [Google Scholar] [CrossRef] [PubMed]
  163. Meffe, R.; Kohfahl, C.; Holzbecher, E.; Massmann, G.; Richter, D.; Dünnbier, U.; Pekdeger, A. Modelling the Removal of P-TSA (Para-Toluenesulfonamide) during Rapid Sand Filtration Used for Drinking Water Treatment. Water Res. 2010, 44, 205–213. [Google Scholar] [CrossRef] [PubMed]
  164. Prasse, C.; Wagner, M.; Schulz, R.; Ternes, T.A. Biotransformation of the Antiviral Drugs Acyclovir and Penciclovir in Activated Sludge Treatment. Environ. Sci. Technol. 2011, 45, 2761–2769. [Google Scholar] [CrossRef]
  165. Zearley, T.L.; Summers, R.S. Removal of Trace Organic Micropollutants by Drinking Water Biological Filters. Environ. Sci. Technol. 2012, 46, 9412–9419. [Google Scholar] [CrossRef]
  166. Helbling, D.E.; Hollender, J.; Kohler, H.P.E.; Singer, H.; Fenner, K. High-Throughput Identification of Microbial Transformation Products of Organic Micropollutants. Environ. Sci. Technol. 2010, 44, 6621–6627. [Google Scholar] [CrossRef]
  167. Zhao, S.; Ba, C.; Yao, Y.; Zheng, W.; Economy, J.; Wang, P. Removal of Antibiotics Using Polyethylenimine Cross-Linked Nanofiltration Membranes: Relating Membrane Performance to Surface Charge Characteristics. Chem. Eng. J. 2018, 335, 101–109. [Google Scholar] [CrossRef]
  168. Mallakpour, S.; Azadi, E. Nanofiltration Membranes for Food and Pharmaceutical Industries. Emergent Mater. 2022, 5, 1329–1343. [Google Scholar] [CrossRef]
  169. Nayak, V.; Cuhorka, J.; Mikulášek, P. Separation of Drugs by Commercial Nanofiltration Membranes and Their Modelling. Membranes 2022, 12, 528. [Google Scholar] [CrossRef] [PubMed]
  170. Radjenović, J.; Petrović, M.; Ventura, F.; Barceló, D. Rejection of Pharmaceuticals in Nanofiltration and Reverse Osmosis Membrane Drinking Water Treatment. Water Res. 2008, 42, 3601–3610. [Google Scholar] [CrossRef] [PubMed]
  171. Urtiaga, A.M.; Pérez, G.; Ibáñez, R.; Ortiz, I. Removal of Pharmaceuticals from a WWTP Secondary Effluent by Ultrafiltration/Reverse Osmosis Followed by Electrochemical Oxidation of the RO Concentrate. Desalination 2013, 331, 26–34. [Google Scholar] [CrossRef]
  172. Hollman, J.; Khan, M.F.; Dominic, J.A.; Achari, G. Pilot-Scale Treatment of Neutral Pharmaceuticals in Municipal Wastewater Using Reverse Osmosis and Ozonation. J. Environ. Eng. 2020, 146, 04020121. [Google Scholar] [CrossRef]
  173. Urase, T.; Kikuta, T. Separate Estimation of Adsorption and Degradation of Pharmaceutical Substances and Estrogens in the Activated Sludge Process. Water Res. 2005, 39, 1289–1300. [Google Scholar] [CrossRef]
  174. Krah, D.; Ghattas, A.K.; Wick, A.; Bröder, K.; Ternes, T.A. Micropollutant Degradation via Extracted Native Enzymes from Activated Sludge. Water Res. 2016, 95, 348–360. [Google Scholar] [CrossRef]
  175. Hena, S.; Znad, H. Membrane Bioreactor for Pharmaceuticals and Personal Care Products Removal from Wastewater. In Comprehensive Analytical Chemistry; Elsevier B.V.: Amsterdam, The Netherlands, 2018; Volume 81, pp. 201–256. ISBN 9780444640642. [Google Scholar]
  176. de Wilt, A.; Butkovskyi, A.; Tuantet, K.; Leal, L.H.; Fernandes, T.V.; Langenhoff, A.; Zeeman, G. Micropollutant Removal in an Algal Treatment System Fed with Source Separated Wastewater Streams. J. Hazard. Mater. 2016, 304, 84–92. [Google Scholar] [CrossRef]
  177. Peng, F.Q.; Ying, G.G.; Yang, B.; Liu, S.; Lai, H.J.; Liu, Y.S.; Chen, Z.F.; Zhou, G.J. Biotransformation of Progesterone and Norgestrel by Two Freshwater Microalgae (Scenedesmus obliquus and Chlorella pyrenoidosa): Transformation Kinetics and Products Identification. Chemosphere 2014, 95, 581–588. [Google Scholar] [CrossRef]
  178. Sathishkumar, P.; Chae, J.C.; Unnithan, A.R.; Palvannan, T.; Kim, H.Y.; Lee, K.J.; Cho, M.; Kamala-Kannan, S.; Oh, B.T. Laccase-Poly(Lactic-Co-Glycolic Acid) (PLGA) Nanofiber: Highly Stable, Reusable, and Efficacious for the Transformation of Diclofenac. Enzym. Microb. Technol. 2012, 51, 113–118. [Google Scholar] [CrossRef] [PubMed]
  179. Sathishkumar, P.; Mythili, A.; Hadibarata, T.; Jayakumar, R.; Kanthimathi, M.S.; Palvannan, T.; Ponraj, M.; Salim, M.R.; Mohd Yusoff, A.R. Laccase Mediated Diclofenac Transformation and Cytotoxicity Assessment on Mouse Fibroblast 3T3-L1 Preadipocytes. RSC Adv. 2014, 4, 11689–11697. [Google Scholar] [CrossRef]
  180. Touahar, I.E.; Haroune, L.; Ba, S.; Bellenger, J.P.; Cabana, H. Characterization of Combined Cross-Linked Enzyme Aggregates from Laccase, Versatile Peroxidase and Glucose Oxidase, and Their Utilization for the Elimination of Pharmaceuticals. Sci. Total Environ. 2014, 481, 90–99. [Google Scholar] [CrossRef] [PubMed]
  181. Acero, J.L.; Benitez, F.J.; Real, F.J.; Roldan, G. Kinetics of Aqueous Chlorination of Some Pharmaceuticals and Their Elimination from Water Matrices. Water Res. 2010, 44, 4158–4170. [Google Scholar] [CrossRef]
  182. Quintana, J.B.; Rodil, R.; López-Mahía, P.; Muniategui-Lorenzo, S.; Prada-Rodríguez, D. Investigating the Chlorination of Acidic Pharmaceuticals and By-Product Formation Aided by an Experimental Design Methodology. Water Res. 2010, 44, 243–255. [Google Scholar] [CrossRef]
  183. Gagnon, C.; Lajeunesse, A.; Cejka, P.; Gagné, F.; Hausler, R. Degradation of Selected Acidic and Neutral Pharmaceutical Products in a Primary-Treated Wastewater by Disinfection Processes. Ozone Sci. Eng. 2008, 30, 387–392. [Google Scholar] [CrossRef]
  184. Broséus, R.; Vincent, S.; Aboulfadl, K.; Daneshvar, A.; Sauvé, S.; Barbeau, B.; Prévost, M. Ozone Oxidation of Pharmaceuticals, Endocrine Disruptors and Pesticides during Drinking Water Treatment. Water Res. 2009, 43, 4707–4717. [Google Scholar] [CrossRef]
  185. Guo, Y.; Zhu, S.; Wang, B.; Huang, J.; Deng, S.; Yu, G.; Wang, Y. Modelling of Emerging Contaminant Removal during Heterogeneous Catalytic Ozonation Using Chemical Kinetic Approaches. J. Hazard. Mater. 2019, 380, 120888. [Google Scholar] [CrossRef]
  186. Elmolla, E.S.; Chaudhuri, M. The Feasibility of Using Combined TiO2 Photocatalysis-SBR Process for Antibiotic Wastewater Treatment. Desalination 2011, 272, 218–224. [Google Scholar] [CrossRef]
  187. Malato, S.; Giménez, J.; Oller, I.; Agüera, A.; Sánchez Pérez, J.A. Removal and Degradation of Pharmaceutically Active Compounds (PhACs) in Wastewaters by Solar Advanced Oxidation Processes. In The Handbook of Environmental Chemistry; Rodriguez-Mozaz, S., Blánquez Cano, P., Adroguer, M.S., Eds.; Springer: Berlin/Heidelberg, Germany, 2020; Volume 108, pp. 299–326. [Google Scholar]
  188. Singh, S.; Kumar, V.; Anil, A.G.; Kapoor, D.; Khasnabis, S.; Shekar, S.; Pavithra, N.; Samuel, J.; Subramanian, S.; Singh, J.; et al. Adsorption and Detoxification of Pharmaceutical Compounds from Wastewater Using Nanomaterials: A Review on Mechanism, Kinetics, Valorization and Circular Economy. J. Environ. Manag. 2021, 300, 113569. [Google Scholar] [CrossRef]
  189. Torres-Pinto, A.; Díez, A.M.; Silva, C.G.; Faria, J.L.; Sanromán, M.Á.; Silva, A.M.T.; Pazos, M. Photoelectrocatalytic Degradation of Pharmaceuticals Promoted by a Metal-Free G-C3N4 Catalyst. Chem. Eng. J. 2023, 476, 146761. [Google Scholar] [CrossRef]
  190. Liu, R.; Gao, C.; Zhao, Y.G.; Wang, A.; Lu, S.; Wang, M.; Maqbool, F.; Huang, Q. Biological Treatment of Steroidal Drug Industrial Effluent and Electricity Generation in the Microbial Fuel Cells. Bioresour. Technol. 2012, 123, 86–91. [Google Scholar] [CrossRef]
  191. Li, H.; Zhang, S.; Yang, X.L.; Yang, Y.L.; Xu, H.; Li, X.N.; Song, H.L. Enhanced Degradation of Bisphenol A and Ibuprofen by an Up-Flow Microbial Fuel Cell-Coupled Constructed Wetland and Analysis of Bacterial Community Structure. Chemosphere 2019, 217, 599–608. [Google Scholar] [CrossRef] [PubMed]
  192. Zhang, S.; Song, H.L.; Cao, X.; Li, H.; Guo, J.; Yang, X.L.; Singh, R.P.; Liu, S. Inhibition of Methanogens Decreased Sulfadiazine Removal and Increased Antibiotic Resistance Gene Development in Microbial Fuel Cells. Bioresour. Technol. 2019, 281, 188–194. [Google Scholar] [CrossRef] [PubMed]
  193. Ondon, B.S.; Li, S.; Zhou, Q.; Li, F. Simultaneous Removal and High Tolerance of Norfloxacin with Electricity Generation in Microbial Fuel Cell and Its Antibiotic Resistance Genes Quantification. Bioresour. Technol. 2020, 304, 122984. [Google Scholar] [CrossRef] [PubMed]
  194. Wu, C.; Ge, J.; Gu, F.; Bai, L. Electrochemical Oxidation Technique to Pharmaceutical Pollutants Removal. Chemosphere 2023, 337, 139373. [Google Scholar] [CrossRef]
  195. Branchet, P.; Arpin-Pont, L.; Piram, A.; Boissery, P.; Wong-Wah-Chung, P.; Doumenq, P. Pharmaceuticals in the Marine Environment: What Are the Present Challenges in Their Monitoring? Sci. Total Environ. 2021, 766, 142644. [Google Scholar] [CrossRef] [PubMed]
  196. Rathi, B.S.; Kumar, P.S.; Vo, D.V.N. Critical Review on Hazardous Pollutants in Water Environment: Occurrence, Monitoring, Fate, Removal Technologies and Risk Assessment. Sci. Total Environ. 2021, 797, 149134. [Google Scholar] [CrossRef]
  197. Aminot, Y.; Litrico, X.; Chambolle, M.; Arnaud, C.; Pardon, P.; Budzinski, H. Development and Application of a Multi-Residue Method for the Determination of 53 Pharmaceuticals in Water, Sediment, and Suspended Solids Using Liquid Chromatography-Tandem Mass Spectrometry. Anal. Bioanal. Chem. 2015, 407, 8585–8604. [Google Scholar] [CrossRef]
  198. Justo-Vega, A.; Jinadasa, K.K.; Jayasinghe, G.D.T.M.; Álvarez-Freire, I.; Bermejo, A.M.; Bermejo-Barrera, P.; Moreda-Piñeiro, A. Ultrasound Assisted Membrane-Assisted Solvent Extraction for the Simultaneous Assessment of Some Drugs Involved in Drug-Facilitated Sexual Assaults by Liquid Chromatography-Tandem Mass Spectrometry. J. Chromatogr. A 2023, 1706, 464284. [Google Scholar] [CrossRef]
  199. Díaz, A.; Peña-Alvarez, A. A Simple Method for the Simultaneous Determination of Pharmaceuticals and Personal Care Products in River Sediment by Ultrasound-Assisted Extraction Followed by Solid-Phase Microextraction Coupled with Gas Chromatography-Mass Spectrometry. J. Chromatogr. Sci. 2017, 55, 946–953. [Google Scholar] [CrossRef] [PubMed]
  200. Qin, H.; Liu, H.; Liu, Y.; Di, S.; Bao, Y.; Zhai, Y.; Zhu, S. Recent Advances in Sample Preparation and Chromatographic Analysis of Pharmaceuticals and Personal Care Products in Environment. TrAC—Trends Anal. Chem. 2023, 164, 117112. [Google Scholar] [CrossRef]
  201. Ramos, S.; Homem, V.; Santos, L. Simultaneous Determination of Synthetic Musks and UV-Filters in Water Matrices by Dispersive Liquid-Liquid Microextraction Followed by Gas Chromatography Tandem Mass-Spectrometry. J. Chromatogr. A 2019, 1590, 47–57. [Google Scholar] [CrossRef]
  202. Li, Y.; Niu, X.; Yao, C.; Yang, W.; Lu, G. Distribution, Removal, and Risk Assessment of Pharmaceuticals and Their Metabolites in Five Sewage Plants. Int. J. Environ. Res. Public Health 2019, 16, 4729. [Google Scholar] [CrossRef] [PubMed]
  203. Rice, S.L.; Mitra, S. Microwave-Assisted Solvent Extraction of Solid Matrices and Subsequent Detection of Pharmaceuticals and Personal Care Products (PPCPs) Using Gas Chromatography-Mass Spectrometry. Anal. Chim. Acta 2007, 589, 125–132. [Google Scholar] [CrossRef]
  204. Trujillo-Rodríguez, M.J.; Nan, H.; Anderson, J.L. Expanding the Use of Polymeric Ionic Liquids in Headspace Solid-Phase Microextraction: Determination of Ultraviolet Filters in Water Samples. J. Chromatogr. A 2018, 1540, 11–20. [Google Scholar] [CrossRef]
  205. Fawzy, M.G.; Said, M.A. Valuation of Environmental Influence of Recently Invented High-Performance Liquid Chromatographic Method for Hypoglycemic Mixtures of Gliflozins and Metformin in the Presence of Melamine Impurities: Application of Molecular Modeling Simulation Approach. J. Sep. Sci. 2023, 46, e2300267. [Google Scholar] [CrossRef] [PubMed]
  206. Goeury, K.; Vo Duy, S.; Munoz, G.; Prévost, M.; Sauvé, S. Assessment of Automated Off-Line Solid-Phase Extraction LC-MS/MS to Monitor EPA Priority Endocrine Disruptors in Tap Water, Surface Water, and Wastewater. Talanta 2022, 241, 123216. [Google Scholar] [CrossRef]
  207. Chen, L.; Yan, X.; Zhou, X.; Peng, P.; Sun, Q.; Zhao, F. Advances in the On-Line Solid-Phase Extraction-Liquid Chromatography-Mass Spectrometry Analysis of Emerging Organic Contaminants. TrAC—Trends Anal. Chem. 2023, 160, 116976. [Google Scholar] [CrossRef]
  208. Mthiyane, Z.L.; Makhubela, N.; Nyoni, H.; Madikizela, L.M.; Maseko, B.R.; Ncube, S. Determination of Antibiotics during Treatment of Hospital Wastewater Using Automated Solid-Phase Extraction Followed by UHPLC-MS: Occurrence, Removal and Environmental Risks. Environ. Technol. 2023, 1–11. [Google Scholar] [CrossRef]
  209. Restrepo-Vieira, L.H.; Busetti, F.; Linge, K.L.; Joll, C.A. Development and Validation of a Direct Injection Liquid Chromatography-Tandem Mass Spectrometry Method for the Analysis of Illicit Drugs and Psychopharmaceuticals in Wastewater. J. Chromatogr. A 2022, 1685, 463562. [Google Scholar] [CrossRef]
  210. Zhi, S.; Zhou, J.; Zhang, Z.; Zhang, K. Determination of 38 Antibiotics in Raw and Treated Wastewater from Swine Farms Using Liquid Chromatography-Mass Spectrometry. J. Sep. Sci. 2022, 45, 1525–1537. [Google Scholar] [CrossRef]
  211. Hernández, F.; Ibáñez, M.; Bade, R.; Bijlsma, L.; Sancho, J.V. Investigation of Pharmaceuticals and Illicit Drugs in Waters by Liquid Chromatography-High-Resolution Mass Spectrometry. TrAC—Trends Anal. Chem. 2014, 63, 140–157. [Google Scholar] [CrossRef]
  212. Martín-Pozo, L.; de Alarcón-Gómez, B.; Rodríguez-Gómez, R.; García-Córcoles, M.T.; Çipa, M.; Zafra-Gómez, A. Analytical Methods for the Determination of Emerging Contaminants in Sewage Sludge Samples. A Review. Talanta 2019, 192, 508–533. [Google Scholar] [CrossRef] [PubMed]
  213. Poole, C.F. Alkylsilyl Derivatives for Gas Chromatography. J. Chromatogr. A 2013, 1296, 2–14. [Google Scholar] [CrossRef] [PubMed]
  214. Jones, S.J.; Lassiter, M.G. Environmental Toxicology: Aquatic. In Information Resources in Toxicology; Wexler, P., Ed.; Elsevier: Amsterdam, The Netherlands, 2020; pp. 263–278. [Google Scholar]
  215. Sumudumali, R.G.I.; Jayawardana, J.M.C.K. A Review of Biological Monitoring of Aquatic Ecosystems Approaches: With Special Reference to Macroinvertebrates and Pesticide Pollution. Environ. Manag. 2021, 67, 263–276. [Google Scholar] [CrossRef] [PubMed]
  216. Adeyemo, O.K.; Sogbanmu, T.O.; Alarape, S.A.; Denslow, N.D. Biomonitoring of Aquatic Pollution: Status and Trends from Genomics to Populations. Proc. Niger. Acad. Sci. 2021, 13, 2s. [Google Scholar] [CrossRef]
  217. de Mello, K.; Taniwaki, R.H.; Macedo, D.R.; Leal, C.G.; Randhir, T.O. Biomonitoring for Watershed Protection from a Multiscale Land-Use Perspective. Diversity 2023, 15, 636. [Google Scholar] [CrossRef]
  218. Fabbri, E.; Valbonesi, P.; Moon, T.W. Pharmaceuticals in the Marine Environment: Occurrence, Fate, and Biological Effects. In Contaminants of Emerging Concern in the Marine Environment; León, V.M., Bellas, J., Eds.; Elsevier: Amsterdam, The Netherlands, 2023; pp. 11–71. [Google Scholar]
  219. Kuehne, L.M.; Dickens, C.; Tickner, D.; Messager, M.L.; Olden, J.D.; O’Brien, G.; Lehner, B.; Eriyagama, N. The Future of Global River Health Monitoring. PLOS Water 2023, 2, e0000101. [Google Scholar] [CrossRef]
  220. Jeppe, K.J.; Yang, J.; Long, S.M.; Carew, M.E.; Zhang, X.; Pettigrove, V.; Hoffmann, A.A. Detecting Copper Toxicity in Sediments: From the Subindividual Level to the Population Level. J. Appl. Ecol. 2017, 54, 1331–1342. [Google Scholar] [CrossRef]
  221. King, R.S.; Brain, R.A.; Back, J.A.; Becker, C.; Wright, M.V.; Toteu Djomte, V.; Scott, W.C.; Virgil, S.R.; Brooks, B.W.; Hosmer, A.J.; et al. Effects of Pulsed Atrazine Exposures on Autotrophic Community Structure, Biomass, and Production in Field-Based Stream Mesocosms. Environ. Toxicol. Chem. 2016, 35, 660–675. [Google Scholar] [CrossRef] [PubMed]
  222. Van Straalen, N.M. Ecotoxicology Becomes Stress Ecology. Environ. Sci. Technol. 2003, 37, 324A–330A. [Google Scholar] [CrossRef] [PubMed]
  223. Bundschuh, M.; Mesquita-Joanes, F.; Rico, A.; Camacho, A. Understanding Ecological Complexity in a Chemical Stress Context: A Reflection on Recolonization, Recovery, and Adaptation of Aquatic Populations and Communities. Environ. Toxicol. Chem. 2023, 42, 1857–1866. [Google Scholar] [CrossRef] [PubMed]
  224. Morin, S.; Artigas, J. Twenty Years of Research in Ecosystem Functions in Aquatic Microbial Ecotoxicology. Environ. Toxicol. Chem. 2023, 42, 1867–1888. [Google Scholar] [CrossRef] [PubMed]
  225. Enns, D.; Cunze, S.; Baker, N.J.; Oehlmann, J.; Jourdan, J. Flushing Away the Future: The Effects of Wastewater Treatment Plants on Aquatic Invertebrates. Water Res. 2023, 243, 120388. [Google Scholar] [CrossRef]
  226. Mcmahon, T.A.; Halstead, N.T.; Johnson, S.; Raffel, T.R.; Romansic, J.M.; Crumrine, P.W.; Rohr, J.R. Fungicide-Induced Declines of Freshwater Biodiversity Modify Ecosystem Functions and Services. Ecol. Lett. 2012, 15, 714–722. [Google Scholar] [CrossRef]
  227. Halstead, N.T.; Mcmahon, T.A.; Johnson, S.A.; Raffel, T.R.; Romansic, J.M.; Crumrine, P.W.; Rohr, J.R. Community Ecology Theory Predicts the Effects of Agrochemical Mixtures on Aquatic Biodiversity and Ecosystem Properties. Ecol. Lett. 2014, 17, 932–941. [Google Scholar] [CrossRef]
  228. Rodrigues, A.C.M.; Machado, A.L.; Bordalo, M.D.; Saro, L.; Simão, F.C.P.; Rocha, R.J.M.; Golovko, O.; Žlábek, V.; Barata, C.; Soares, A.M.V.M.; et al. Invasive Species Mediate Insecticide Effects on Community and Ecosystem Functioning. Environ. Sci. Technol. 2018, 52, 4889–4900. [Google Scholar] [CrossRef]
  229. De Laender, F.; Rohr, J.R.; Ashauer, R.; Baird, D.J.; Berger, U.; Eisenhauer, N.; Grimm, V.; Hommen, U.; Maltby, L.; Meliàn, C.J.; et al. Reintroducing Environmental Change Drivers in Biodiversity–Ecosystem Functioning Research. Trends Ecol. Evol. 2016, 31, 905–915. [Google Scholar] [CrossRef]
  230. Hermens, J.L.M.; Ankley, G.T.; Sumpter, J.P. Ecotoxicology—A Multidisciplinary, Problem-Driven Science. Environ. Sci. Technol. 2004, 38, 446A–447A. [Google Scholar] [CrossRef]
  231. Zaghloul, A.; Saber, M.; Gadow, S.; Awad, F. Biological Indicators for Pollution Detection in Terrestrial and Aquatic Ecosystems. Bull. Natl. Res. Cent. 2020, 44, 127. [Google Scholar] [CrossRef]
  232. Huang, C.W.; Lin, C.; Nguyen, M.K.; Hussain, A.; Bui, X.T.; Ngo, H.H. A Review of Biosensor for Environmental Monitoring: Principle, Application, and Corresponding Achievement of Sustainable Development Goals. Bioengineered 2023, 14, 58–80. [Google Scholar] [CrossRef]
  233. Kulik, K.; Lenart-Boroń, A.; Wyrzykowska, K. Impact of Antibiotic Pollution on the Bacterial Population within Surface Water with Special Focus on Mountain Rivers. Water 2023, 15, 975. [Google Scholar] [CrossRef]
  234. Yusuf, A.; O’Flynn, D.; White, B.; Holland, L.; Parle-Mcdermott, A.; Lawler, J.; McCloughlin, T.; Harold, D.; Huerta, B.; Regan, F. Monitoring of Emerging Contaminants of Concern in the Aquatic Environment: A Review of Studies Showing the Application of Effect-Based Measures. Anal. Methods 2021, 13, 5120–5143. [Google Scholar] [CrossRef] [PubMed]
  235. Arroyo, C.L.; Dionela, M.; Ann Bautista, M.G.; Concepcion, R.; Vicerra, R.R.; Duarte, B. Biomonitoring Technologies Used in Aquatic Ecosystems: A Systematic and Trend Analysis. In Proceedings of the 2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2022, Boracay Island, Philippines, 1–4 December 2022. [Google Scholar]
  236. Justino, C.I.L.; Duarte, A.C.; Rocha-Santos, T.A.P. Recent Progress in Biosensors for Environmental Monitoring: A Review. Sensors 2017, 17, 2918. [Google Scholar] [CrossRef]
  237. Daunert, S.; Barrett, G.; Feliciano, J.S.; Shetty, R.S.; Shrestha, S.; Smith-Spencer, W. Genetically Engineered Whole-Cell Sensing Systems: Coupling Biological Recognition with Reporter Genes. Chem. Rev. 2000, 100, 2705–2738. [Google Scholar] [CrossRef] [PubMed]
  238. Rogers, K.R. Recent Advances in Biosensor Techniques for Environmental Monitoring. Anal. Chim. Acta 2006, 568, 222–231. [Google Scholar] [CrossRef] [PubMed]
  239. Kaur, H.; Kumar, R.; Babu, J.N.; Mittal, S. Advances in Arsenic Biosensor Development—A Comprehensive Review. Biosens. Bioelectron. 2015, 63, 533–545. [Google Scholar] [CrossRef]
  240. Rather, R.A.; Ara, S.; Padder, S.A.; Sharma, S.; Pathak, S.P.; Baba, T.R. Seasonal Fluctuation of Water Quality and Ecogenomic Phylogeny of Novel Potential Microbial Pollution Indicators of Veshaw River Kashmir-Western Himalaya. Environ. Pollut. 2023, 320, 121104. [Google Scholar] [CrossRef]
  241. Machuca-Sepúlveda, J.; Miranda, J.; Lefin, N.; Pedroso, A.; Beltrán, J.F.; Farias, J.G. Current Status of Omics in Biological Quality Elements for Freshwater Biomonitoring. Biology 2023, 12, 923. [Google Scholar] [CrossRef]
  242. Mielecki, D.; Grzesiuk, E.; Bednarska, A.; Garbicz, D.; Świderska, B.; Grzesiuk, M. Contamination of Aquatic Environment with Anticancer Reagents Influences Daphnia Magna—Ecotoxicogenomics Approach. Ecotoxicol. Environ. Saf. 2023, 249, 114372. [Google Scholar] [CrossRef] [PubMed]
  243. Pham, K.; Ho, L.; D’Incal, C.P.; De Cock, A.; Berghe, W.V.; Goethals, P. Epigenetic Analytical Approaches in Ecotoxicological Aquatic Research. Environ. Pollut. 2023, 330, 121737. [Google Scholar] [CrossRef] [PubMed]
  244. Brack, W.; Escher, B.I.; Müller, E.; Schmitt-Jansen, M.; Schulze, T.; Slobodnik, J.; Hollert, H. Towards a Holistic and Solution-Oriented Monitoring of Chemical Status of European Water Bodies: How to Support the EU Strategy for a Non-Toxic Environment? Environ. Sci. Eur. 2018, 30, 33. [Google Scholar] [CrossRef] [PubMed]
  245. Amorim, C.L.; Alves, M.; Castro, P.M.L.; Henriques, I. Bacterial Community Dynamics within an Aerobic Granular Sludge Reactor Treating Wastewater Loaded with Pharmaceuticals. Ecotoxicol. Environ. Saf. 2018, 147, 905–912. [Google Scholar] [CrossRef] [PubMed]
  246. Marchlewicz, A.; Domaradzka, D.; Guzik, U.; Wojcieszyńska, D. Bacillus Thuringiensis B1(2015b) Is a Gram-Positive Bacteria Able to Degrade Naproxen and Ibuprofen. Water Air Soil. Pollut. 2016, 227, 197. [Google Scholar] [CrossRef]
  247. Zhou, N.A.; Lutovsky, A.C.; Andaker, G.L.; Gough, H.L.; Ferguson, J.F. Cultivation and Characterization of Bacterial Isolates Capable of Degrading Pharmaceutical and Personal Care Products for Improved Removal in Activated Sludge Wastewater Treatment. Biodegradation 2013, 24, 813–827. [Google Scholar] [CrossRef]
  248. Lin, B.; Lyu, J.; Lyu, X.J.; Yu, H.Q.; Hu, Z.; Lam, J.C.W.; Lam, P.K.S. Characterization of Cefalexin Degradation Capabilities of Two Pseudomonas Strains Isolated from Activated Sludge. J. Hazard. Mater. 2015, 282, 158–164. [Google Scholar] [CrossRef]
  249. Esplugas, M.; González, O.; Sans, C. Bacterial Community Characterization of a Sequencing Batch Reactor Treating Pre-Ozonized Sulfamethoxazole in Water. Environ. Technol. 2013, 34, 1583–1591. [Google Scholar] [CrossRef]
  250. Sauvêtre, A.; Schröder, P. Uptake of Carbamazepine by Rhizomes and Endophytic Bacteria of Phragmites Australis. Front. Plant Sci. 2015, 6, 83. [Google Scholar] [CrossRef]
  251. Hirth, N.; Topp, E.; Dörfler, U.; Stupperich, E.; Munch, J.C.; Schroll, R. An Effective Bioremediation Approach for Enhanced Microbial Degradation of the Veterinary Antibiotic Sulfamethazine in an Agricultural Soil. Chem. Biol. Technol. Agric. 2016, 3, 29. [Google Scholar] [CrossRef]
  252. D’Alessio, M.; Yoneyama, B.; Kirs, M.; Kisand, V.; Ray, C. Pharmaceutically Active Compounds: Their Removal during Slow Sand Filtration and Their Impact on Slow Sand Filtration Bacterial Removal. Sci. Total Environ. 2015, 524–525, 124–135. [Google Scholar] [CrossRef] [PubMed]
  253. Forrez, I.; Carballa, M.; Boon, N.; Verstraete, W. Biological Removal of 17α-Ethinylestradiol (EE2) in an Aerated Nitrifying Fixed Bed Reactor during Ammonium Starvation. J. Chem. Technol. Biotechnol. 2009, 84, 119–125. [Google Scholar] [CrossRef]
  254. Pauwels, B.; Wille, K.; Noppe, H.; De Brabander, H.; Van De Wiele, T.; Verstraete, W.; Boon, N. 17α-Ethinylestradiol Cometabolism by Bacteria Degrading Estrone, 17β-Estradiol and Estriol. Biodegradation 2008, 19, 683–693. [Google Scholar] [CrossRef] [PubMed]
  255. Wang, H.; Hu, C.; Shen, Y.; Shi, B.; Zhao, D.; Xing, X. Response of Microorganisms in Biofilm to Sulfadiazine and Ciprofloxacin in Drinking Water Distribution Systems. Chemosphere 2019, 218, 197–204. [Google Scholar] [CrossRef] [PubMed]
  256. Proia, L.; Lupini, G.; Osorio, V.; Pérez, S.; Barceló, D.; Schwartz, T.; Amalfitano, S.; Fazi, S.; Romaní, A.M.; Sabater, S. Response of Biofilm Bacterial Communities to Antibiotic Pollutants in a Mediterranean River. Chemosphere 2013, 92, 1126–1135. [Google Scholar] [CrossRef] [PubMed]
  257. Rosi-Marshall, E.J.; Kincaid, D.W.; Bechtold, H.A.; Royer, T.V.; Rojas, M.; Kelly, J.J. Pharmaceuticals Suppress Algal Growth and Microbial Respiration and Alter Bacterial Communities in Stream Biofilms. Ecol. Appl. 2013, 23, 583–593. [Google Scholar] [CrossRef]
  258. Suleiman, M.; Demaria, F.; Zimmardi, C.; Kolvenbach, B.A.; Corvini, P.F.X. Analyzing Microbial Communities and Their Biodegradation of Multiple Pharmaceuticals in Membrane Bioreactors. Appl. Microbiol. Biotechnol. 2023, 107, 5545–5554. [Google Scholar] [CrossRef] [PubMed]
  259. Leiviskä, T.; Risteelä, S. Analysis of Pharmaceuticals, Hormones and Bacterial Communities in a Municipal Wastewater Treatment Plant—Comparison of Parallel Full-Scale Membrane Bioreactor and Activated Sludge Systems. Environ. Pollut. 2022, 292, 118433. [Google Scholar] [CrossRef]
  260. Yang, Y.; Li, B.; Zou, S.; Fang, H.H.; Zhang, T. Fate of Antibiotic Resistance Genes in Sewage Treatment Plant Revealed by Metagenomic Approach. Water Res. 2014, 62, 97–106. [Google Scholar] [CrossRef] [PubMed]
  261. Berendonk, T.U.; Manaia, C.M.; Merlin, C.; Fatta-Kassinos, D.; Cytryn, E.; Walsh, F.; Bürgmann, H.; Sørum, H.; Norström, M.; Pons, M.N.; et al. Tackling Antibiotic Resistance: The Environmental Framework. Nat. Rev. Microbiol. 2015, 13, 310–317. [Google Scholar] [CrossRef]
  262. Araújo, S.; Silva, I.A.T.; Tacão, M.; Patinha, C.; Alves, A.; Henriques, I. Characterization of Antibiotic Resistant and Pathogenic Escherichia Coli in Irrigation Water and Vegetables in Household Farms. Int. J. Food Microbiol. 2017, 257, 192–200. [Google Scholar] [CrossRef] [PubMed]
  263. Heitzer, A.; Malachowsky, K.; Thonnard, J.E.; Bienkowski, P.R.; White, D.C.; Sayleri, G.S. Optical Biosensor for Environmental On-Line Monitoring of Naphthalene and Salicylate Bioavailability with an Immobilized Bioluminescent Catabolic Reporter Bacterium. Appl. Environ. Microbiol. 1994, 60, 1487–1494. [Google Scholar] [CrossRef]
  264. Valtonen, S.J.; Kurittu, J.S.; Karp, M.T. A Luminescent Escherichia Coli Biosensor for the High Throughput Detection of β-Lactams. J. Biomol. Screen. 2002, 7, 127–134. [Google Scholar] [CrossRef]
  265. Shemer, B.; Belkin, S. Microbial Biosensors for the Detection of Organic Pollutants. In Handbook of Cell Biosensors; Thouand, G., Ed.; Springer International Publishing: Cham, Switzerland, 2019; pp. 1–24. [Google Scholar]
  266. Lautenschläger, N.; Popp, P.F.; Mascher, T. Development of a Novel Heterologous β-Lactam-Specific Whole-Cell Biosensor in Bacillus Subtilis. J. Biol. Eng. 2020, 14, 21. [Google Scholar] [CrossRef]
  267. Yin, J.; Zhu, Y.; Liang, Y.; Luo, Y.; Lou, J.; Hu, X.; Meng, Q.; Zhu, T.; Yu, Z. Development of Whole-Cell Biosensors for Screening of Peptidoglycan-Targeting Antibiotics in a Gram-Negative Bacterium. Appl. Environ. Microbiol. 2022, 88, e0084622. [Google Scholar] [CrossRef]
  268. Yin, J.; Cheng, D.; Zhu, Y.; Liang, Y.; Yu, Z. Development of a Whole-Cell Biosensor for Detection of Antibiotics Targeting Bacterial Cell Envelope in Bacillus Subtilis. Appl. Microbiol. Biotechnol. 2022, 106, 789–798. [Google Scholar] [CrossRef]
  269. Minamoto, T.; Yamanaka, H.; Takahara, T.; Honjo, M.N.; Kawabata, Z. Surveillance of Fish Species Composition Using Environmental DNA. Limnology 2012, 13, 193–197. [Google Scholar] [CrossRef]
  270. Wilcox, T.M.; McKelvey, K.S.; Young, M.K.; Jane, S.F.; Lowe, W.H.; Whiteley, A.R.; Schwartz, M.K. Robust Detection of Rare Species Using Environmental DNA: The Importance of Primer Specificity. PLoS ONE 2013, 8, e59520. [Google Scholar] [CrossRef]
  271. Ardura, A.; Zaiko, A.; Martinez, J.L.; Samulioviene, A.; Semenova, A.; Garcia-Vazquez, E. eDNA and Specific Primers for Early Detection of Invasive Species—A Case Study on the Bivalve Rangia Cuneata, Currently Spreading in Europe. Mar. Environ. Res. 2015, 112, 48–55. [Google Scholar] [CrossRef] [PubMed]
  272. Roy, M.; Belliveau, V.; Mandrak, N.E.; Gagné, N. Development of Environmental DNA (eDNA) Methods for Detecting High-Risk Freshwater Fishes in Live Trade in Canada. Biol. Invasions 2018, 20, 299–314. [Google Scholar] [CrossRef]
  273. Stat, M.; Huggett, M.J.; Bernasconi, R.; Dibattista, J.D.; Berry, T.E.; Newman, S.J.; Harvey, E.S.; Bunce, M. Ecosystem Biomonitoring with eDNA: Metabarcoding across the Tree of Life in a Tropical Marine Environment. Sci. Rep. 2017, 7, 12240. [Google Scholar] [CrossRef]
  274. Djurhuus, A.; Closek, C.J.; Kelly, R.P.; Pitz, K.J.; Michisaki, R.P.; Starks, H.A.; Walz, K.R.; Andruszkiewicz, E.A.; Olesin, E.; Hubbard, K.; et al. Environmental DNA Reveals Seasonal Shifts and Potential Interactions in a Marine Community. Nat. Commun. 2020, 11, 254. [Google Scholar] [CrossRef] [PubMed]
  275. Lyu, Y.; Xu, X.; Yuan, Y.; Wang, Z.; Hu, J.; Chen, Q.; Sun, W. Antibiotic Profiles and Their Relationships with Multitrophic Aquatic Communities in an Urban River. Sci. Total Environ. 2023, 868, 161678. [Google Scholar] [CrossRef] [PubMed]
  276. Taberlet, P.; Coissac, E.; Hajibabaei, M.; Rieseberg, L.H. Environmental DNA. Mol. Ecol. 2012, 21, 1789–1793. [Google Scholar] [CrossRef] [PubMed]
  277. Ruppert, K.M.; Kline, R.J.; Rahman, M.S. Past, Present, and Future Perspectives of Environmental DNA (eDNA) Metabarcoding: A Systematic Review in Methods, Monitoring, and Applications of Global eDNA. Glob. Ecol. Conserv. 2019, 17, e00547. [Google Scholar] [CrossRef]
  278. Tsuji, S.; Takahara, T.; Doi, H.; Shibata, N.; Yamanaka, H. The Detection of Aquatic Macroorganisms Using Environmental DNA Analysis—A Review of Methods for Collection, Extraction, and Detection. Environ. DNA 2019, 1, 99–108. [Google Scholar] [CrossRef]
  279. Beng, K.C.; Corlett, R.T. Applications of Environmental DNA (eDNA) in Ecology and Conservation: Opportunities, Challenges and Prospects. Biodivers. Conserv. 2020, 29, 2089–2121. [Google Scholar] [CrossRef]
  280. Pont, D.; Meulenbroek, P.; Bammer, V.; Dejean, T.; Erős, T.; Jean, P.; Lenhardt, M.; Nagel, C.; Pekarik, L.; Schabuss, M.; et al. Quantitative Monitoring of Diverse Fish Communities on a Large Scale Combining eDNA Metabarcoding and QPCR. Mol. Ecol. Resour. 2023, 23, 396–409. [Google Scholar] [CrossRef]
  281. Yang, J.; Zhang, L.; Mu, Y.; Wang, J.; Yu, H.; Zhang, X. Unsupervised Biological Integrity Assessment by eDNA Biomonitoring of Multi-Trophic Aquatic Taxa. Environ. Int. 2023, 175, 107950. [Google Scholar] [CrossRef]
  282. Deiner, K.; Yamanaka, H.; Bernatchez, L. The Future of Biodiversity Monitoring and Conservation Utilizing Environmental DNA. Environ. DNA 2021, 3, 3–7. [Google Scholar] [CrossRef]
  283. Deiner, K.; Bik, H.M.; Mächler, E.; Seymour, M.; Lacoursière-Roussel, A.; Altermatt, F.; Creer, S.; Bista, I.; Lodge, D.M.; de Vere, N.; et al. Environmental DNA Metabarcoding: Transforming How We Survey Animal and Plant Communities. Mol. Ecol. 2017, 26, 5872–5895. [Google Scholar] [CrossRef] [PubMed]
  284. Gold, Z.; Sprague, J.; Kushner, D.J.; Marin, E.Z.; Barber, P.H. eDNA Metabarcoding as a Biomonitoring Tool for Marine Protected Areas. PLoS ONE 2021, 16, e0238557. [Google Scholar] [CrossRef]
  285. McElroy, M.E.; Dressler, T.L.; Titcomb, G.C.; Wilson, E.A.; Deiner, K.; Dudley, T.L.; Eliason, E.J.; Evans, N.T.; Gaines, S.D.; Lafferty, K.D.; et al. Calibrating Environmental DNA Metabarcoding to Conventional Surveys for Measuring Fish Species Richness. Front. Ecol. Evol. 2020, 8, 276. [Google Scholar] [CrossRef]
  286. Prié, V.; Valentini, A.; Lopes-Lima, M.; Froufe, E.; Rocle, M.; Poulet, N.; Taberlet, P.; Dejean, T. Environmental DNA Metabarcoding for Freshwater Bivalves Biodiversity Assessment: Methods and Results for the Western Palearctic (European Sub-Region). Hydrobiologia 2021, 848, 2931–2950. [Google Scholar] [CrossRef]
  287. Svenningsen, A.K.N.; Pertoldi, C.; Bruhn, D. eDNA Metabarcoding Benchmarked towards Conventional Survey Methods in Amphibian Monitoring. Animals 2022, 12, 763. [Google Scholar] [CrossRef]
  288. Rees, H.C.; Maddison, B.C.; Middleditch, D.J.; Patmore, J.R.M.; Gough, K.C. The Detection of Aquatic Animal Species Using Environmental DNA—A Review of eDNA as a Survey Tool in Ecology. J. Appl. Ecol. 2014, 51, 1450–1459. [Google Scholar] [CrossRef]
  289. Senapati, D.; Bhattacharya, M.; Kar, A.; Chini, D.S.; Das, B.K.; Patra, B.C. Environmental DNA (eDNA): A Promising Biological Survey Tool for Aquatic Species Detection. Proc. Zool. Soc. 2019, 72, 211–228. [Google Scholar] [CrossRef]
  290. Rey, A.; Carney, K.J.; Quinones, L.E.; Pagenkopp Lohan, K.M.; Ruiz, G.M.; Basurko, O.C.; Rodríguez-Ezpeleta, N. Environmental DNA Metabarcoding: A Promising Tool for Ballast Water Monitoring. Environ. Sci. Technol. 2019, 53, 11849–11859. [Google Scholar] [CrossRef]
  291. Majaneva, M.; Diserud, O.H.; Eagle, S.H.C.; Boström, E.; Hajibabaei, M.; Ekrem, T. Environmental DNA Filtration Techniques Affect Recovered Biodiversity. Sci. Rep. 2018, 8, 4682. [Google Scholar] [CrossRef]
  292. Takasaki, K.; Aihara, H.; Imanaka, T.; Matsudaira, T.; Tsukahara, K.; Usui, A.; Osaki, S.; Doi, H. Water Pre-Filtration Methods to Improve Environmental DNA Detection by Real-Time PCR and Metabarcoding. PLoS ONE 2021, 16, e0250162. [Google Scholar] [CrossRef]
  293. Alexander, J.B.; Bunce, M.; White, N.; Wilkinson, S.P.; Adam, A.A.S.; Berry, T.; Stat, M.; Thomas, L.; Newman, S.J.; Dugal, L.; et al. Development of a Multi-Assay Approach for Monitoring Coral Diversity Using eDNA Metabarcoding. Coral Reefs 2020, 39, 159–171. [Google Scholar] [CrossRef]
  294. Sepulveda, A.J.; Birch, J.M.; Barnhart, E.P.; Merkes, C.M.; Yamahara, K.M.; Marin, R.; Kinsey, S.M.; Wright, P.R.; Schmidt, C. Robotic Environmental DNA Bio-Surveillance of Freshwater Health. Sci. Rep. 2020, 10, 14389. [Google Scholar] [CrossRef]
  295. Hendricks, A.; Mackie, C.M.; Luy, E.; Sonnichsen, C.; Smith, J.; Grundke, I.; Tavasoli, M.; Furlong, A.; Beiko, R.G.; LaRoche, J.; et al. Compact and Automated eDNA Sampler for in Situ Monitoring of Marine Environments. Sci. Rep. 2023, 13, 5210. [Google Scholar] [CrossRef]
  296. Xiong, W.; Huang, X.; Chen, Y.; Fu, R.; Du, X.; Chen, X.; Zhan, A. Zooplankton Biodiversity Monitoring in Polluted Freshwater Ecosystems: A Technical Review. Environ. Sci. Ecotechnology 2020, 1, 100008. [Google Scholar] [CrossRef]
  297. Lawson Handley, L. How Will the “molecular Revolution” Contribute to Biological Recording? Biol. J. Linn. Soc. 2015, 115, 750–766. [Google Scholar] [CrossRef]
  298. Gold, Z.; Wall, A.R.; Schweizer, T.M.; Pentcheff, N.D.; Curd, E.E.; Barber, P.H.; Meyer, R.S.; Wayne, R.; Stolzenbach, K.; Prickett, K.; et al. A Manager’s Guide to Using eDNA Metabarcoding in Marine Ecosystems. PeerJ 2022, 10, e14071. [Google Scholar] [CrossRef]
  299. García-Machado, E.; Normandeau, E.; Côté, G.; Bernatchez, L. How eDNA Data Filtration, Sequence Coverage, and Primer Selection Influence Assessment of Fish Communities in Northern Temperate Lakes. Environ. DNA 2023, 00, 1–18. [Google Scholar] [CrossRef]
  300. Wang, Z.; Liu, X.; Liang, D.; Wang, Q.; Zhang, L.; Zhang, P. VertU: Universal Multilocus Primer Sets for eDNA Metabarcoding of Vertebrate Diversity, Evaluated by Both Artificial and Natural Cases. Front. Ecol. Evol. 2023, 11, 1164206. [Google Scholar] [CrossRef]
  301. Weigand, H.; Beermann, A.J.; Čiampor, F.; Costa, F.O.; Csabai, Z.; Duarte, S.; Geiger, M.F.; Grabowski, M.; Rimet, F.; Rulik, B.; et al. DNA Barcode Reference Libraries for the Monitoring of Aquatic Biota in Europe: Gap-Analysis and Recommendations for Future Work. Sci. Total Environ. 2019, 678, 499–524. [Google Scholar] [CrossRef]
  302. Abbott, C.; Coulson, M.; Gagné, N.; Lacoursière-Roussel, A.; Parent, G.J.; Bajno, R.; Dietrich, C.; May-Mcnally, S. Guidance on the Use of Targeted Environmental DNA (eDNA) Analysis for the Management of Aquatic Invasive Species and Species at Risk; Canadian Science Advisory Secretariat (CSAS): Ottawa, ON, Canada, 2021.
  303. Huszarik, M.; Röder, N.; Eberhardt, L.; Kennedy, S.; Krehenwinkel, H.; Schwenk, K.; Entling, M.H. External DNA Contamination and Efficiency of Bleach Decontamination for Arthropod Diet Analysis. Environ. DNA 2023, 5, 540–550. [Google Scholar] [CrossRef]
  304. Beentjes, K.K.; Speksnijder, A.G.C.L.; Schilthuizen, M.; Hoogeveen, M.; Van Der Hoorn, B.B. The Effects of Spatial and Temporal Replicate Sampling on eDNA Metabarcoding. PeerJ 2019, 2019, e7335. [Google Scholar] [CrossRef] [PubMed]
  305. Troth, C.R.; Sweet, M.J.; Nightingale, J.; Burian, A. Seasonality, DNA Degradation and Spatial Heterogeneity as Drivers of eDNA Detection Dynamics. Sci. Total Environ. 2021, 768, 144466. [Google Scholar] [CrossRef] [PubMed]
  306. Wee, A.K.S.; Salmo, S.G.; Sivakumar, K.; Then, A.Y.H.; Basyuni, M.; Fall, J.; Habib, K.A.; Isowa, Y.; Leopardas, V.; Peer, N.; et al. Prospects and Challenges of Environmental DNA (eDNA) Metabarcoding in Mangrove Restoration in Southeast Asia. Front. Mar. Sci. 2023, 10, 1033258. [Google Scholar] [CrossRef]
  307. Spens, J.; Evans, A.R.; Halfmaerten, D.; Knudsen, S.W.; Sengupta, M.E.; Mak, S.S.T.; Sigsgaard, E.E.; Hellström, M. Comparison of Capture and Storage Methods for Aqueous Macrobial eDNA Using an Optimized Extraction Protocol: Advantage of Enclosed Filter. Methods Ecol. Evol. 2017, 8, 635–645. [Google Scholar] [CrossRef]
  308. Jarman, S.N.; Berry, O.; Bunce, M. The Value of Environmental DNA Biobanking for Long-Term Biomonitoring. Nat. Ecol. Evol. 2018, 2, 1192–1193. [Google Scholar] [CrossRef]
  309. Xing, Y.; Gao, W.; Shen, Z.; Zhang, Y.; Bai, J.; Cai, X.; Ouyang, J.; Zhao, Y. A Review of Environmental DNA Field and Laboratory Protocols Applied in Fish Ecology and Environmental Health. Front. Environ. Sci. 2022, 10, 725360. [Google Scholar] [CrossRef]
  310. Evans, N.T.; Lamberti, G.A. Freshwater Fisheries Assessment Using Environmental DNA: A Primer on the Method, Its Potential, and Shortcomings as a Conservation Tool. Fish. Res. 2018, 197, 60–66. [Google Scholar] [CrossRef]
  311. Pascher, K.; Švara, V.; Jungmeier, M. Environmental DNA-Based Methods in Biodiversity Monitoring of Protected Areas: Application Range, Limitations, and Needs. Diversity 2022, 14, 463. [Google Scholar] [CrossRef]
  312. Fonseca, V.G.; Davison, P.I.; Creach, V.; Stone, D.; Bass, D.; Tidbury, H.J. The Application of eDNA for Monitoring Aquatic Non-Indigenous Species: Practical and Policy Considerations. Diversity 2023, 15, 631. [Google Scholar] [CrossRef]
  313. Valentini, A.; Taberlet, P.; Miaud, C.; Civade, R.; Herder, J.; Thomsen, P.F.; Bellemain, E.; Besnard, A.; Coissac, E.; Boyer, F.; et al. Next-Generation Monitoring of Aquatic Biodiversity Using Environmental DNA Metabarcoding. Mol. Ecol. 2016, 25, 929–942. [Google Scholar] [CrossRef]
  314. Rishan, S.T.; Kline, R.J.; Rahman, M.S. Applications of Environmental DNA (eDNA) to Detect Subterranean and Aquatic Invasive Species: A Critical Review on the Challenges and Limitations of eDNA Metabarcoding. Environ. Adv. 2023, 12, 100370. [Google Scholar] [CrossRef]
  315. Macher, T.-H.; Schütz, R.; Yildiz, A.; Beermann, A.J.; Leese, F. Evaluating Five Primer Pairs for Environmental DNA Metabarcoding of Central European Fish Species Based on Mock Communities. Metabarcoding Metagenom 2023, 7, e103856. [Google Scholar] [CrossRef]
  316. Bálint, M.; Nowak, C.; Márton, O.; Pauls, S.U.; Wittwer, C.; Aramayo, J.L.; Schulze, A.; Chambert, T.; Cocchiararo, B.; Jansen, M. Accuracy, Limitations and Cost Efficiency of eDNA-Based Community Survey in Tropical Frogs. Mol. Ecol. Resour. 2018, 18, 1415–1426. [Google Scholar] [CrossRef] [PubMed]
  317. Bani, A.; Randall, K.C.; Clark, D.R.; Gregson, B.H.; Henderson, D.K.; Losty, E.C.; Ferguson, R.M.W. Mind the Gaps: What Do We Know about How Multiple Chemical Stressors Impact Freshwater Aquatic Microbiomes? In Advances in Ecological Research; Academic Press Inc.: Cambridge, MA, USA, 2022; Volume 67, pp. 331–377. ISBN 9780323985932. [Google Scholar]
  318. Hansen, B.K.; Bekkevold, D.; Clausen, L.W.; Nielsen, E.E. The Sceptical Optimist: Challenges and Perspectives for the Application of Environmental DNA in Marine Fisheries. Fish. Fish. 2018, 19, 751–768. [Google Scholar] [CrossRef]
  319. Harper, L.R.; Buxton, A.S.; Rees, H.C.; Bruce, K.; Brys, R.; Halfmaerten, D.; Read, D.S.; Watson, H.V.; Sayer, C.D.; Jones, E.P.; et al. Prospects and Challenges of Environmental DNA (eDNA) Monitoring in Freshwater Ponds. Hydrobiologia 2019, 826, 25–41. [Google Scholar] [CrossRef]
  320. Hunter, M.E.; Ferrante, J.A.; Meigs-Friend, G.; Ulmer, A. Improving eDNA Yield and Inhibitor Reduction through Increased Water Volumes and Multi-Filter Isolation Techniques. Sci. Rep. 2019, 9, 5259. [Google Scholar] [CrossRef]
  321. Bernos, T.A.; Yates, M.C.; Docker, M.F.; Fitzgerald, A.; Hanner, R.; Heath, D.; Imrit, A.; Livernois, J.; Myler, E.; Patel, K.; et al. Environmental DNA (eDNA) Applications in Freshwater Fisheries Management and Conservation in Canada: Overview of Current Challenges and Opportunities. Can. J. Fish. Aquat. Sci. 2023, 80, 1170–1186. [Google Scholar] [CrossRef]
  322. Capurso, G.; Carroll, B.; Stewart, K.A. Transforming Marine Monitoring: Using eDNA Metabarcoding to Improve the Monitoring of the Mediterranean Marine Protected Areas Network. Mar. Policy 2023, 156, 105807. [Google Scholar] [CrossRef]
  323. Frontalini, F.; Greco, M.; Di Bella, L.; Lejzerowicz, F.; Reo, E.; Caruso, A.; Cosentino, C.; Maccotta, A.; Scopelliti, G.; Nardelli, M.P.; et al. Assessing the Effect of Mercury Pollution on Cultured Benthic Foraminifera Community Using Morphological and eDNA Metabarcoding Approaches. Mar. Pollut. Bull. 2018, 129, 512–524. [Google Scholar] [CrossRef] [PubMed]
  324. Chang, J. Monitoring Biodiversity and Water Pollution via High-Throughput eDNA Metabarcoding. Berkeley Sci. J. 2020, 24, 50–58. [Google Scholar] [CrossRef]
  325. Lee, V.M. Validation of eDNA Metabarcoding: A Comparison to Traditional Survey Methods in Ozark Streams. Master’s Thesis, Missouri University of Science and Technology, Rolla, MI, USA, 2022. [Google Scholar]
  326. Miya, M. Environmental DNA Metabarcoding: A Novel Method for Biodiversity Monitoring of Marine Fish Communities. Annu. Rev. Mar. Sci. 2021, 14, 161–185. [Google Scholar] [CrossRef] [PubMed]
  327. Kelly, R.P.; Lodge, D.M.; Lee, K.N.; Theroux, S.; Sepulveda, A.J.; Scholin, C.A.; Craine, J.M.; Andruszkiewicz Allan, E.; Nichols, K.M.; Parsons, K.M.; et al. Toward a National eDNA Strategy for the United States. Environ. DNA 2023, 1–10. [Google Scholar] [CrossRef]
  328. Ebenstein, A. The Consequences of Industrialization: Evidence from Water Pollution and Digestive Cancers in China. Rev. Econ. Stat. 2012, 94, 186–201. [Google Scholar] [CrossRef]
  329. Chaudhry, F.N.; Malik, M.F. Factors Affecting Water Pollution: A Review. J. Ecosyst. Ecography 2017, 7, 225. [Google Scholar] [CrossRef]
  330. Schmidt, J.R.; Shaskus, M.; Estenik, J.F.; Oesch, C.; Khidekel, R.; Boyer, G.L. Variations in the Microcystin Content of Different Fish Species Collected from a Eutrophic Lake. Toxins 2013, 5, 992–1009. [Google Scholar] [CrossRef] [PubMed]
  331. Ebele, A.J.; Abou-Elwafa Abdallah, M.; Harrad, S. Pharmaceuticals and Personal Care Products (PPCPs) in the Freshwater Aquatic Environment. Emerg. Contam. 2017, 3, 1–16. [Google Scholar] [CrossRef]
  332. Brix, K.V.; Blust, R.; Mertens, J.; Baken, S.; Middleton, E.T.; Cooper, C. Evaluation of Effects-Based Methods as Monitoring Tools for Assessing Ecological Impacts of Metals in Aquatic Ecosystems. Integr. Environ. Assess. Manag. 2023, 19, 24–31. [Google Scholar] [CrossRef]
  333. Chonova, T.; Kurmayer, R.; Rimet, F.; Labanowski, J.; Vasselon, V.; Keck, F.; Illmer, P.; Bouchez, A. Benthic Diatom Communities in an Alpine River Impacted by Waste Water Treatment Effluents as Revealed Using DNA Metabarcoding. Front. Microbiol. 2019, 10, 653. [Google Scholar] [CrossRef]
  334. Kajtar, A. Environmental DNA Plumes: Linking Fish Farm eDNA to Microbial Communities and Novel Detection of Transgenic eDNA. Master’s Thesis, Great Lakes Institute for Environmental Research, Windsor, ON, Canada, 2021. [Google Scholar]
  335. Shi, P.; Jia, S.; Zhang, X.X.; Zhang, T.; Cheng, S.; Li, A. Metagenomic Insights into Chlorination Effects on Microbial Antibiotic Resistance in Drinking Water. Water Res. 2013, 47, 111–120. [Google Scholar] [CrossRef]
  336. Pinto, I.; Simões, M.; Gomes, I.B. An Overview of the Impact of Pharmaceuticals on Aquatic Microbial Communities. Antibiotics 2022, 11, 1700. [Google Scholar] [CrossRef]
  337. Ebert, I.; Bachmann, J.; Kühnen, U.; Küster, A.; Kussatz, C.; Maletzki, D.; Schlüter, C. Toxicity of the Fluoroquinolone Antibiotics Enrofloxacin and Ciprofloxacin to Photoautotrophic Aquatic Organisms. Environ. Toxicol. Chem. 2011, 30, 2786–2792. [Google Scholar] [CrossRef] [PubMed]
  338. Sehnal, L.; Brammer-Robbins, E.; Wormington, A.M.; Blaha, L.; Bisesi, J.; Larkin, I.; Martyniuk, C.J.; Simonin, M.; Adamovsky, O. Microbiome Composition and Function in Aquatic Vertebrates: Small Organisms Making Big Impacts on Aquatic Animal Health. Front. Microbiol. 2021, 12, 567408. [Google Scholar] [CrossRef] [PubMed]
  339. Binh, V.N.; Dang, N.; Anh, N.T.K.; Ky, L.X.; Thai, P.K. Antibiotics in the Aquatic Environment of Vietnam: Sources, Concentrations, Risk and Control Strategy. Chemosphere 2018, 197, 438–450. [Google Scholar] [CrossRef]
  340. Välitalo, P.; Kruglova, A.; Mikola, A.; Vahala, R. Toxicological Impacts of Antibiotics on Aquatic Micro-Organisms: A Mini-Review. Int. J. Hyg. Environ. Health 2017, 220, 558–569. [Google Scholar] [CrossRef]
  341. Xie, Y.; Wang, J.; Yang, J.; Giesy, J.P.; Yu, H.; Zhang, X. Environmental DNA Metabarcoding Reveals Primary Chemical Contaminants in Freshwater Sediments from Different Land-Use Types. Chemosphere 2017, 172, 201–209. [Google Scholar] [CrossRef] [PubMed]
  342. Stoeck, T.; Pan, H.; Dully, V.; Forster, D.; Jung, T. Towards an eDNA Metabarcode-Based Performance Indicator for Full-Scale Municipal Wastewater Treatment Plants. Water Res. 2018, 144, 322–331. [Google Scholar] [CrossRef]
  343. Cruz, A.F.; Wijesekara, R.G.S.; Jinadasa, K.B.S.N.; Gonzales, B.J.; Ohura, T.; Guruge, K.S. Preliminary Investigation of Microbial Community in Wastewater and Surface Waters in Sri Lanka and the Philippines. Front. Water 2021, 3, 730124. [Google Scholar] [CrossRef]
  344. Romero, P.E.; Calla-Quispe, E.; Castillo-Vilcahuaman, C.; Yokoo, M.; Fuentes-Rivera, H.L.; Ramirez, J.L.; Ampuero, A.; Ibáñez, A.J.; Wong, P. From the Andes to the Desert: 16S RRNA Metabarcoding Characterization of Aquatic Bacterial Communities in the Rimac River, the Main Source of Water for Lima, Peru. PLoS ONE 2021, 16, e0250401. [Google Scholar] [CrossRef]
  345. Bouchali, R.; Marjolet, L.; Mondamert, L.; Chonova, T.; Ribun, S.; Laurent, E.; Bouchez, A.; Labanowski, J.; Cournoyer, B. Evidence of Bacterial Community Coalescence between Freshwater and Discharged Tpm-Harboring Bacterial Taxa from Hospital and Domestic Wastewater Treatment Plants among Epilithic Biofilms. Microorganisms 2023, 11, 922. [Google Scholar] [CrossRef] [PubMed]
  346. Pathak, V.M.; Verma, V.K.; Rawat, B.S.; Kaur, B.; Babu, N.; Sharma, A.; Dewali, S.; Yadav, M.; Kumari, R.; Singh, S.; et al. Current Status of Pesticide Effects on Environment, Human Health and It’s Eco-Friendly Management as Bioremediation: A Comprehensive Review. Front. Microbiol. 2022, 13, 962619. [Google Scholar] [CrossRef]
  347. Brain, R.A.; Hanson, M.L.; Solomon, K.R.; Brooks, B.W. Aquatic Plants Exposed to Pharmaceuticals: Effects and Risks. In Reviews of Environmental Contamination and Toxicology; Springer: New York, NY, USA, 2008; Volume 192, pp. 67–115. [Google Scholar]
  348. Pawlowski, J.; Kelly-Quinn, M.; Altermatt, F.; Apothéloz-Perret-Gentil, L.; Beja, P.; Boggero, A.; Borja, A.; Bouchez, A.; Cordier, T.; Domaizon, I.; et al. The Future of Biotic Indices in the Ecogenomic Era: Integrating (e)DNA Metabarcoding in Biological Assessment of Aquatic Ecosystems. Sci. Total Environ. 2018, 637–638, 1295–1310. [Google Scholar] [CrossRef] [PubMed]
  349. Ji, F.; Yan, L.; Yan, S.; Qin, T.; Shen, J.; Zha, J. Estimating Aquatic Plant Diversity and Distribution in Rivers from Jingjinji Region, China, Using Environmental DNA Metabarcoding and a Traditional Survey Method. Environ. Res. 2021, 199, 111348. [Google Scholar] [CrossRef]
  350. Liu, Q.; Zhang, Y.; Wu, H.; Liu, F.; Peng, W.; Zhang, X.; Chang, F.; Xie, P.; Zhang, H. A Review and Perspective of Edna Application to Eutrophication and Hab Control in Freshwater and Marine Ecosystems. Microorganisms 2020, 8, 417. [Google Scholar] [CrossRef] [PubMed]
  351. Park, J.-W.; Park, K.; Kwak, I.-S. Surveillance Spilled Chironomidae (Diptera) Larvae from Drinking Water Treatment Plants in South Korea Using Morphogenetic Species Analysis and eDNA Metabarcoding. Sci. Total Environ. 2023, 896, 165241. [Google Scholar] [CrossRef] [PubMed]
  352. Pilliod, D.S.; Goldberg, C.S.; Arkle, R.S.; Waits, L.P. Factors Influencing Detection of eDNA from a Stream-Dwelling Amphibian. Mol. Ecol. Resour. 2014, 14, 109–116. [Google Scholar] [CrossRef] [PubMed]
  353. Uchida, N.; Kubota, K.; Aita, S.; Kazama, S. Aquatic Insect Community Structure Revealed by eDNA Metabarcoding Derives Indices for Environmental Assessment. PeerJ 2020, 2020, e9176. [Google Scholar] [CrossRef]
  354. Xie, R.; Zhao, G.; Yang, J.; Wang, Z.; Xu, Y.; Zhang, X.; Wang, Z. eDNA Metabarcoding Revealed Differential Structures of Aquatic Communities in a Dynamic Freshwater Ecosystem Shaped by Habitat Heterogeneity. Environ. Res. 2021, 201, 111602. [Google Scholar] [CrossRef]
  355. Pinna, M.; Zangaro, F.; Saccomanno, B.; Scalone, C.; Bozzeda, F.; Fanini, L.; Specchia, V. An Overview of Ecological Indicators of Fish to Evaluate the Anthropogenic Pressures in Aquatic Ecosystems: From Traditional to Innovative DNA-Based Approaches. Water 2023, 15, 949. [Google Scholar] [CrossRef]
  356. Yao, M.; Zhang, S.; Lu, Q.; Chen, X.; Zhang, S.Y.; Kong, Y.; Zhao, J. Fishing for Fish Environmental DNA: Ecological Applications, Methodological Considerations, Surveying Designs, and Ways Forward. Mol. Ecol. 2022, 31, 5132–5164. [Google Scholar] [CrossRef]
  357. Davison, H.; Macadam, C.R.; Smith, D. Pharmaceuticals in Freshwater Environments and Their Potential. Effects on Freshwater Invertebrates Saving the Small Things That Run the Planet; Buglife: Peterborough, UK, 2021. [Google Scholar]
  358. Biswas, C.; Maity, S.; Adhikari, M.; Chatterjee, A.; Guchhait, R.; Pramanick, K. Pharmaceuticals in the Aquatic Environment and Their Endocrine Disruptive Effects in Fish. Proc. Zool. Soc. 2021, 74, 507–522. [Google Scholar] [CrossRef]
  359. Khan, A.H.A.; Barros, R. Pharmaceuticals in Water: Risks to Aquatic Life and Remediation Strategies. Hydrobiology 2023, 2, 395–409. [Google Scholar] [CrossRef]
  360. Kitamura, R.S.A.; Vicentini, M.; Perussolo, M.C.; Lirola, J.R.; Cirilo dos Santos, C.F.; Moreira Brito, J.C.; Cestari, M.M.; Prodocimo, M.M.; Gomes, M.P.; Silva de Assis, H.C. Sublethal Biochemical, Histopathological and Genotoxicological Effects of Short-Term Exposure to Ciprofloxacin in Catfish Rhamdia Quelen. Environ. Pollut. 2022, 300, 118935. [Google Scholar] [CrossRef]
  361. Srivastava, B.; Reddy, P.B. Impacts of Human Pharmaceuticals on Fish Health. Int. J. Pharm. Sci. Res. 2021, 12, 5185. [Google Scholar] [CrossRef]
  362. Brodin, T.; Fick, J.; Jonsson, M.; Klaminder, J. Dilute Concentrations of a Psychiatric Drug Alter Behavior of Fish from Natural Populations. Science (1979) 2013, 339, 814–815. [Google Scholar] [CrossRef]
  363. Hubená, P.; Horký, P.; Grabic, R.; Grabicová, K.; Douda, K.; Slavík, O.; Randák, T. Prescribed Aggression of Fishes: Pharmaceuticals Modify Aggression in Environmentally Relevant Concentrations. Ecotoxicol. Environ. Saf. 2021, 227, 112944. [Google Scholar] [CrossRef]
  364. Mennigen, J.A.; Stroud, P.; Zamora, J.M.; Moon, T.W.; Trudeau, V.L. Pharmaceuticals as Neuroendocrine Disruptors: Lessons Learned from Fish on Prozac. J. Toxicol. Environ. Health B Crit. Rev. 2011, 14, 387–412. [Google Scholar] [CrossRef]
  365. Jenila, J.S.; Issac, P.K.; Lam, S.S.; Oviya, J.C.; Jones, S.; Munusamy-Ramanujam, G.; Chang, S.W.; Ravindran, B.; Mannacharaju, M.; Ghotekar, S.; et al. Deleterious Effect of Gestagens from Wastewater Effluent on Fish Reproduction in Aquatic Environment: A Review. Environ. Res. 2023, 236, 116810. [Google Scholar] [CrossRef]
  366. Du, B.; Haddad, S.P.; Luek, A.; Scott, W.C.; Saari, G.N.; Kristofco, L.A.; Connors, K.A.; Rash, C.; Rasmussen, J.B.; Chambliss, C.K.; et al. Bioaccumulation and Trophic Dilution of Human Pharmaceuticals across Trophic Positions of an Effluent-Dependent Wadeable Stream. Philos. Trans. R. Soc. B Biol. Sci. 2014, 369, 20140058. [Google Scholar] [CrossRef]
  367. Xie, Z.; Lu, G.; Yan, Z.; Liu, J.; Wang, P.; Wang, Y. Bioaccumulation and Trophic Transfer of Pharmaceuticals in Food Webs from a Large Freshwater Lake. Environ. Pollut. 2017, 222, 356–366. [Google Scholar] [CrossRef]
  368. Yang, H.; Lu, G.; Yan, Z.; Liu, J.; Dong, H.; Bao, X.; Zhang, X.; Sun, Y. Residues, Bioaccumulation, and Trophic Transfer of Pharmaceuticals and Personal Care Products in Highly Urbanized Rivers Affected by Water Diversion. J. Hazard. Mater. 2020, 391, 122245. [Google Scholar] [CrossRef]
  369. Seymour, M.; Edwards, F.K.; Cosby, B.J.; Kelly, M.G.; de Bruyn, M.; Carvalho, G.R.; Creer, S. Executing Multi-Taxa eDNA Ecological Assessment via Traditional Metrics and Interactive Networks. Sci. Total Environ. 2020, 729, 138801. [Google Scholar] [CrossRef]
  370. Zhang, X.; Xia, P.; Wang, P.; Yang, J.; Baird, D.J. Omics Advances in Ecotoxicology. Environ. Sci. Technol. 2018, 52, 3842–3851. [Google Scholar] [CrossRef]
  371. Anagnostopoulos, D.A.; Parlapani, F.F.; Natoudi, S.; Syropoulou, F.; Kyritsi, M.; Vergos, I.; Hadjichristodoulou, C.; Kagalou, I.; Boziaris, I.S. Bacterial Communities and Antibiotic Resistance of Potential Pathogens Involved in Food Safety and Public Health in Fish and Water of Lake Karla, Thessaly, Greece. Pathogens 2022, 11, 1473. [Google Scholar] [CrossRef]
  372. Li, Y.; Chen, X.; Wang, X.; Shang, J.; Niu, L.; Wang, L.; Zhang, H.; Zhang, W. The Effects of Paroxetine on Benthic Microbial Food Web and Nitrogen Transformation in River Sediments. Int. J. Environ. Res. Public Health 2022, 19, 14602. [Google Scholar] [CrossRef]
  373. Bessey, C.; Neil Jarman, S.; Simpson, T.; Miller, H.; Stewart, T.; Kenneth Keesing, J.; Berry, O. Passive eDNA Collection Enhances Aquatic Biodiversity Analysis. Commun. Biol. 2021, 4, 236. [Google Scholar] [CrossRef]
  374. Traugott, M.; Thalinger, B.; Wallinger, C.; Sint, D. Fish as Predators and Prey: DNA-Based Assessment of Their Role in Food Webs. J. Fish. Biol. 2021, 98, 367–382. [Google Scholar] [CrossRef]
  375. Berry, T.E.; Osterrieder, S.K.; Murray, D.C.; Coghlan, M.L.; Richardson, A.J.; Grealy, A.K.; Stat, M.; Bejder, L.; Bunce, M. DNA Metabarcoding for Diet Analysis and Biodiversity: A Case Study Using the Endangered Australian Sea Lion (Neophoca cinerea). Ecol. Evol. 2017, 7, 5435–5453. [Google Scholar] [CrossRef]
  376. D’Alessandro, S.; Mariani, S. Sifting Environmental DNA Metabarcoding Data Sets for Rapid Reconstruction of Marine Food Webs. Fish. Fish. 2021, 22, 822–833. [Google Scholar] [CrossRef]
  377. Naselli-Flores, L.; Padisák, J. Ecosystem Services Provided by Marine and Freshwater Phytoplankton. Hydrobiologia 2023, 850, 2691–2706. [Google Scholar] [CrossRef]
  378. Bergeron, S.; Boopathy, R.; Nathaniel, R.; Corbin, A.; LaFleur, G. Presence of Antibiotic Resistant Bacteria and Antibiotic Resistance Genes in Raw Source Water and Treated Drinking Water. Int. Biodeterior. Biodegrad. 2015, 102, 370–374. [Google Scholar] [CrossRef]
  379. Li, J.; Cheng, W.; Xu, L.; Strong, P.J.; Chen, H. Antibiotic-Resistant Genes and Antibiotic-Resistant Bacteria in the Effluent of Urban Residential Areas, Hospitals, and a Municipal Wastewater Treatment Plant System. Environ. Sci. Pollut. Res. 2015, 22, 4587–4596. [Google Scholar] [CrossRef] [PubMed]
  380. Pallares-Vega, R.; Blaak, H.; van der Plaats, R.; de Roda Husman, A.M.; Hernandez Leal, L.; van Loosdrecht, M.C.M.; Weissbrodt, D.G.; Schmitt, H. Determinants of Presence and Removal of Antibiotic Resistance Genes during WWTP Treatment: A Cross-Sectional Study. Water Res. 2019, 161, 319–328. [Google Scholar] [CrossRef] [PubMed]
  381. Xu, L.; Ouyang, W.; Qian, Y.; Su, C.; Su, J.; Chen, H. High-Throughput Profiling of Antibiotic Resistance Genes in Drinking Water Treatment Plants and Distribution Systems. Environ. Pollut. 2016, 213, 119–126. [Google Scholar] [CrossRef]
  382. Szekeres, E.; Chiriac, C.M.; Baricz, A.; Szőke-Nagy, T.; Lung, I.; Soran, M.L.; Rudi, K.; Dragos, N.; Coman, C. Investigating Antibiotics, Antibiotic Resistance Genes, and Microbial Contaminants in Groundwater in Relation to the Proximity of Urban Areas. Environ. Pollut. 2018, 236, 734–744. [Google Scholar] [CrossRef]
  383. Wang, Z.; Chen, Q.; Zhang, J.; Guan, T.; Chen, Y.; Shi, W. Critical Roles of Cyanobacteria as Reservoir and Source for Antibiotic Resistance Genes. Environ. Int. 2020, 144, 106034. [Google Scholar] [CrossRef]
  384. Jiang, L.; Hu, X.; Xu, T.; Zhang, H.; Sheng, D.; Yin, D. Prevalence of Antibiotic Resistance Genes and Their Relationship with Antibiotics in the Huangpu River and the Drinking Water Sources, Shanghai, China. Sci. Total Environ. 2013, 458–460, 267–272. [Google Scholar] [CrossRef]
  385. Zheng, J.; Gao, R.; Wei, Y.; Chen, T.; Fan, J.; Zhou, Z.; Makimilua, T.B.; Jiao, Y.; Chen, H. High-Throughput Profiling and Analysis of Antibiotic Resistance Genes in East Tiaoxi River, China. Environ. Pollut. 2017, 230, 648–654. [Google Scholar] [CrossRef] [PubMed]
  386. Zhou, M.; Li, Q.; Yu, S.; Han, H.; Osborne, N.J. Co-Proliferation of Antimicrobial Resistance Genes in Tilapia Farming Ponds Associated with Use of Antimicrobials. Sci. Total Environ. 2023, 887, 164046. [Google Scholar] [CrossRef] [PubMed]
  387. Saxena, G.; Marzinelli, E.M.; Naing, N.N.; He, Z.; Liang, Y.; Tom, L.; Mitra, S.; Ping, H.; Joshi, U.M.; Reuben, S.; et al. Ecogenomics Reveals Metals and Land-Use Pressures on Microbial Communities in the Waterways of a Megacity. Environ. Sci. Technol. 2015, 49, 1462–1471. [Google Scholar] [CrossRef]
  388. Cavicchioli, R.; Ripple, W.J.; Timmis, K.N.; Azam, F.; Bakken, L.R.; Baylis, M.; Behrenfeld, M.J.; Boetius, A.; Boyd, P.W.; Classen, A.T.; et al. Scientists’ Warning to Humanity: Microorganisms and Climate Change. Nat. Rev. Microbiol. 2019, 17, 569–586. [Google Scholar] [CrossRef]
  389. Wan, Y.; Ruan, X.; Zhang, Y.; Li, R. Illumina Sequencing-Based Analysis of Sediment Bacteria Community in Different Trophic Status Freshwater Lakes. Microbiologyopen 2017, 6, e00450. [Google Scholar] [CrossRef] [PubMed]
  390. Oetken, M.; Nentwig, G.; Löffler, D.; Ternes, T.; Oehlmann, J. Effects of Pharmaceuticals on Aquatic Invertebrates. Part I. The Antiepileptic Drug Carbamazepine. Arch. Environ. Contam. Toxicol. 2005, 49, 353–361. [Google Scholar] [CrossRef]
  391. Barznji, D.A.M. Role of Aquatic Plants in Improving Water Quality. Unique J. Pharm. Biol. Sci. 2014, 2, 12–16. [Google Scholar]
  392. Couto, E.; Assemany, P.P.; Assis Carneiro, G.C.; Ferreira Soares, D.C. The Potential of Algae and Aquatic Macrophytes in the Pharmaceutical and Personal Care Products (PPCPs) Environmental Removal: A Review. Chemosphere 2022, 302, 134808. [Google Scholar] [CrossRef]
  393. Kafle, A.; Timilsina, A.; Gautam, A.; Adhikari, K.; Bhattarai, A.; Aryal, N. Phytoremediation: Mechanisms, Plant Selection and Enhancement by Natural and Synthetic Agents. Environ. Adv. 2022, 8, 100203. [Google Scholar] [CrossRef]
  394. Bala, S.; Garg, D.; Thirumalesh, B.V.; Sharma, M.; Sridhar, K.; Inbaraj, B.S.; Tripathi, M. Recent Strategies for Bioremediation of Emerging Pollutants: A Review for a Green and Sustainable Environment. Toxics 2022, 10, 484. [Google Scholar] [CrossRef]
  395. Wei, H.; Tang, M.; Xu, X. Mechanism of Uptake, Accumulation, Transport, Metabolism and Phytotoxic Effects of Pharmaceuticals and Personal Care Products within Plants: A Review. Sci. Total Environ. 2023, 892, 164413. [Google Scholar] [CrossRef]
  396. Nieto, C.; Ovando, X.M.C.; Loyola, R.; Izquierdo, A.; Romero, F.; Molineri, C.; Rodríguez, J.; Rueda Martín, P.; Fernández, H.; Manzo, V.; et al. The Role of Macroinvertebrates for Conservation of Freshwater Systems. Ecol. Evol. 2017, 7, 5502–5513. [Google Scholar] [CrossRef]
  397. Saad El-Din, M.I. A Review of the Effects of Pharmaceuticals on Marine Invertebrates. Biomed. J. Sci. Tech. Res. 2023, 48, 40196–40198. [Google Scholar] [CrossRef]
  398. Grabicová, K.; Grabic, R.; Blaha, M.; Kumar, V.; Cerveny, D.; Fedorova, G.; Randak, T. Presence of Pharmaceuticals in Benthic Fauna Living in a Small Stream Affected by Effluent from a Municipal Sewage Treatment Plant. Water Res. 2015, 72, 145–153. [Google Scholar] [CrossRef]
  399. Grabicová, K.; Vojs Staňová, A.; Švecová, H.; Nováková, P.; Kodeš, V.; Leontovyčová, D.; Brooks, B.W.; Grabic, R. Invertebrates Differentially Bioaccumulate Pharmaceuticals: Implications for Routine Biomonitoring. Environ. Pollut. 2022, 309, 119715. [Google Scholar] [CrossRef]
  400. Rodrigues, S.; Antunes, S.C.; Nunes, B.; Correia, A.T. Histological Alterations in Gills and Liver of Rainbow Trout (Oncorhynchus mykiss) after Exposure to the Antibiotic Oxytetracycline. Environ. Toxicol. Pharmacol. 2017, 53, 164–176. [Google Scholar] [CrossRef]
  401. Rodrigues, S.; Antunes, S.C.; Nunes, B.; Correia, A.T. Histopathological Effects in Gills and Liver of Sparus Aurata Following Acute and Chronic Exposures to Erythromycin and Oxytetracycline. Environ. Sci. Pollut. Res. 2019, 26, 15481–15495. [Google Scholar] [CrossRef]
  402. Bereketoglu, C.; Pradhan, A.; Olsson, P.E. Nonsteroidal Anti-Inflammatory Drugs (NSAIDs) Cause Male-Biased Sex Differentiation in Zebrafish. Aquat. Toxicol. 2020, 223, 105476. [Google Scholar] [CrossRef]
  403. Kayode-Afolayan, S.D.; Ahuekwe, E.F.; Nwinyi, O.C. Impacts of Pharmaceutical Effluents on Aquatic Ecosystems. Sci. Afr. 2022, 17, e01288. [Google Scholar] [CrossRef]
  404. Hassan, S.; Sabreena; Poczai, P.; Ganai, B.A.; Almalki, W.H.; Gafur, A.; Sayyed, R.Z. Environmental DNA Metabarcoding: A Novel Contrivance for Documenting Terrestrial Biodiversity. Biology 2022, 11, 1297. [Google Scholar] [CrossRef]
  405. Su, G.; Logez, M.; Xu, J.; Tao, S.; Villéger, S.; Brosse, S. Human Impacts on Global Freshwater Fish Biodiversity. Science (1979) 2021, 371, 835–838. [Google Scholar] [CrossRef]
  406. Takahashi, M.; Saccò, M.; Kestel, J.H.; Nester, G.; Campbell, M.A.; van der Heyde, M.; Heydenrych, M.J.; Juszkiewicz, D.J.; Nevill, P.; Dawkins, K.L.; et al. Aquatic Environmental DNA: A Review of the Macro-Organismal Biomonitoring Revolution. Sci. Total Environ. 2023, 873, 162322. [Google Scholar] [CrossRef]
  407. Blackman, R.C.; Mächler, E.; Altermatt, F.; Arnold, A.; Beja, P.; Boets, P.; Egeter, B.; Elbrecht, V.; Filipe, A.F.; Iwan Jones, J.; et al. Advancing the Use of Molecular Methods for Routine Freshwater Macroinvertebrate Biomonitoring—The Need for Calibration Experiments. Metabarcoding Metagenomics 2019, 3, 49–57. [Google Scholar] [CrossRef]
  408. Espinosa Prieto, A.; Beisel, J.N.; Verschuren, P.; Hardion, L. Toward Freshwater Plant Diversity Surveys with eDNA Barcoding and Metabarcoding. Environ. DNA 2023, 5, 648–670. [Google Scholar] [CrossRef]
  409. Fernández, S.; Rodríguez, S.; Martínez, J.L.; Borrell, Y.J.; Ardura, A.; García-Vázquez, E. Evaluating Freshwater Macroinvertebrates from eDNA Metabarcoding: A River Nalón Case Study. PLoS ONE 2018, 13, e0201741. [Google Scholar] [CrossRef]
  410. Liu, J.; Zhang, H. Combining Multiple Markers in Environmental DNA Metabarcoding to Assess Deep-Sea Benthic Biodiversity. Front. Mar. Sci. 2021, 8, 684955. [Google Scholar] [CrossRef]
  411. Wu, F.; Zou, Y.; Qin, S.; Li, F.; Zhang, Y. eDNA Biomonitoring of Macroinvertebrate Communities for the Bioassessment of a River’s Ecological Status. Water 2023, 15, 308. [Google Scholar] [CrossRef]
  412. Pawlowski, J.; Esling, P.; Lejzerowicz, F.; Cedhagen, T.; Wilding, T.A. Environmental Monitoring through Protist Next-Generation Sequencing Metabarcoding: Assessing the Impact of Fish Farming on Benthic Foraminifera Communities. Mol. Ecol. Resour. 2014, 14, 1129–1140. [Google Scholar] [CrossRef] [PubMed]
  413. Pochon, X.; Wood, S.A.; Keeley, N.B.; Lejzerowicz, F.; Esling, P.; Drew, J.; Pawlowski, J. Accurate Assessment of the Impact of Salmon Farming on Benthic Sediment Enrichment Using Foraminiferal Metabarcoding. Mar. Pollut. Bull. 2015, 100, 370–382. [Google Scholar] [CrossRef] [PubMed]
  414. Grzesiuk, M.; Gryglewicz, E.; Bentkowski, P.; Pijanowska, J. Impact of Fluoxetine on Herbivorous Zooplankton and Planktivorous Fish. Environ. Toxicol. Chem. 2023, 42, 385–392. [Google Scholar] [CrossRef] [PubMed]
  415. Lagesson, A.; Fahlman, J.; Brodin, T.; Fick, J.; Jonsson, M.; Byström, P.; Klaminder, J. Bioaccumulation of Five Pharmaceuticals at Multiple Trophic Levels in an Aquatic Food Web—Insights from a Field Experiment. Sci. Total Environ. 2016, 568, 208–215. [Google Scholar] [CrossRef]
  416. Yan, Z.; Zhou, Y.; Zhang, Y.; Zhang, X. Distribution, Bioaccumulation, and Risks of Pharmaceutical Metabolites and Their Parents: A Case Study in an Yunliang River, Nanjing City. Int. J. Environ. Res. Public Health 2023, 20, 2967. [Google Scholar] [CrossRef]
  417. Nilsen, E.; Smalling, K.L.; Ahrens, L.; Gros, M.; Miglioranza, K.S.B.; Picó, Y.; Schoenfuss, H.L. Critical Review: Grand Challenges in Assessing the Adverse Effects of Contaminants of Emerging Concern on Aquatic Food Webs. Environ. Toxicol. Chem. 2019, 38, 46–60. [Google Scholar] [CrossRef]
  418. Sparrow, B.D.; Edwards, W.; Munroe, S.E.M.; Wardle, G.M.; Guerin, G.R.; Bastin, J.F.; Morris, B.; Christensen, R.; Phinn, S.; Lowe, A.J. Effective Ecosystem Monitoring Requires a Multi-Scaled Approach. Biol. Rev. 2020, 95, 1706–1719. [Google Scholar] [CrossRef]
  419. Cordier, T.; Esling, P.; Lejzerowicz, F.; Visco, J.; Ouadahi, A.; Martins, C.; Cedhagen, T.; Pawlowski, J. Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning. Environ. Sci. Technol. 2017, 51, 9118–9126. [Google Scholar] [CrossRef]
  420. Prakash, S.; Verma, A.K. Anthropogenic Activities and Biodiversity Threats. Int. J. Biol. Innov. 2022, 4, 94–103. [Google Scholar] [CrossRef]
  421. Rangel-Buitrago, N. Human Epoch—Human Responsibility: Rethinking Coastal Zone Management in the Anthropocene. Ocean. Coast. Manag. 2023, 244, 106801. [Google Scholar] [CrossRef]
  422. Miettinen, M.; Khan, S.A. Pharmaceutical Pollution: A Weakly Regulated Global Environmental Risk. Rev. Eur. Comp. Int. Environ. Law. 2022, 31, 75–88. [Google Scholar] [CrossRef]
  423. Küster, A.; Adler, N. Pharmaceuticals in the Environment: Scientific Evidence of Risks and Its Regulation. Philos. Trans. R. Soc. B Biol. Sci. 2014, 369, 20130587. [Google Scholar] [CrossRef]
  424. Paut Kusturica, M.; Jevtic, M.; Ristovski, J.T. Minimizing the Environmental Impact of Unused Pharmaceuticals: Review Focused on Prevention. Front. Environ. Sci. 2022, 10, 1077974. [Google Scholar] [CrossRef]
  425. Guo, M.; Chen, H.; Dong, S.; Zhang, Z.; Luo, H. CRISPR-Cas Gene Editing Technology and Its Application Prospect in Medicinal Plants. Chin. Med. 2022, 17, 33. [Google Scholar] [CrossRef]
  426. Rafeeq, H.; Afsheen, N.; Rafique, S.; Arshad, A.; Intisar, M.; Hussain, A.; Bilal, M.; Iqbal, H.M.N. Genetically Engineered Microorganisms for Environmental Remediation. Chemosphere 2023, 310, 136751. [Google Scholar] [CrossRef]
  427. Andújar, C.; Arribas, P.; Gray, C.; Bruce, C.; Woodward, G.; Yu, D.W.; Vogler, A.P. Metabarcoding of Freshwater Invertebrates to Detect the Effects of a Pesticide Spill. Mol. Ecol. 2018, 27, 146–166. [Google Scholar] [CrossRef]
  428. Zhang, X. Environmental DNA Shaping a New Era of Ecotoxicological Research. Environ. Sci. Technol. 2019, 53, 5605–5612. [Google Scholar] [CrossRef] [PubMed]
  429. Blaxter, M.; Mann, J.; Chapman, T.; Thomas, F.; Whitton, C.; Floyd, R.; Abebe, E. Defining Operational Taxonomic Units Using DNA Barcode Data. Philos. Trans. R. Soc. B Biol. Sci. 2005, 360, 1935–1943. [Google Scholar] [CrossRef]
  430. Wang, S.; Yan, Z.; Hänfling, B.; Zheng, X.; Wang, P.; Fan, J.; Li, J. Methodology of Fish eDNA and Its Applications in Ecology and Environment. Sci. Total Environ. 2021, 755, 142622. [Google Scholar] [CrossRef] [PubMed]
  431. Nagarajan, R.P.; Bedwell, M.; Holmes, A.E.; Sanches, T.; Acuña, S.; Baerwald, M.; Barnes, M.A.; Blankenship, S.; Connon, R.E.; Deiner, K.; et al. Environmental DNA Methods for Ecological Monitoring and Biodiversity Assessment in Estuaries. Estuaries Coasts 2022, 45, 2254–2273. [Google Scholar] [CrossRef]
  432. Harper, L.R.; Lawson Handley, L.; Carpenter, A.I.; Ghazali, M.; Di Muri, C.; Macgregor, C.J.; Logan, T.W.; Law, A.; Breithaupt, T.; Read, D.S.; et al. Environmental DNA (eDNA) Metabarcoding of Pond Water as a Tool to Survey Conservation and Management Priority Mammals. Biol. Conserv. 2019, 238, 108225. [Google Scholar] [CrossRef]
  433. Deiner, K.; Altermatt, F. Transport Distance of Invertebrate Environmental DNA in a Natural River. PLoS ONE 2014, 9, e88786. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Main pathways of pharmaceutical aquatic pollution (WWTPs: wastewater treatment plants).
Figure 1. Main pathways of pharmaceutical aquatic pollution (WWTPs: wastewater treatment plants).
Toxics 11 00903 g001
Table 1. Overview of the primary sources and associated environmental effects and health risks of PhACs.
Table 1. Overview of the primary sources and associated environmental effects and health risks of PhACs.
PharmaceuticalsSourcesEffectsReferences
AntibioticsContamination of water bodies from human and veterinary medicine wastes.
  • Induce an increase in ARBs and (ARGs);
  • Disrupt the equilibrium of natural microbial communities in water bodies;
  • Affect the cycling of nutrients and the overall functioning of the ecosystems;
  • Cause potential long-term effects on human health.
[81,82,83,84,85,86,87,88,89,90,91]
Hormones and endocrine-disrupting chemicals (EDCs)Enter the aquatic environment through agricultural and livestock manure, excretion (e.g., urine and feces), improper disposal.
  • Contribute to hormone pollution and ultimately disrupt the endocrine systems of aquatic organisms;
  • Induce developmental abnormalities in fish;
  • Alter sex ratios and reproductive success in fish populations;
  • Affect the growth and development of aquatic organisms;
  • Affect human endocrine systems by chronic exposure to low levels of hormone contaminants in potable water or consuming contaminated aquatic organisms.
[92,93,94,95,96,97,98,99,100]
Analgesics and nonsteroidal anti-inflammatory drugs (NSAIDs)Main pathways to the aquatic environment: human excretion, the inappropriate disposal of unused medications, wastewater discharges from pharmaceutical and healthcare facilities.
  • Induce long-lasting ecotoxic effects on the biotic components of ecosystems;
  • Induce detrimental effects on plants, including growth inhibition, cellular and root damage, and metabolic disorders;
  • Influence the behavior, reproduction, growth, and development of fish, amphibians, and invertebrates;
  • Cause bioaccumulation in aquatic predators through the food chain;
  • Affect the microbial communities of aquatic ecosystems and disrupt essential ecological processes.
[27,101,102,103,104,105]
Psychotropic and antiepileptic drugsEnter water bodies through human excretion, and wastewater systems via sewage or septic tanks
  • Inhibit the growth of aquatic organisms;
  • Alter fish, invertebrates, and other aquatic organisms’ behavior, reproduction, and physiological functions;
  • Disrupt natural ecological processes and aquatic ecosystem populations.
[43,44,106,107,108]
β-blockersInfiltrate the aquatic environment through human excretion, and wastewater systems via sewage or septic tanks
  • Alter fish pulse rate and other cardiovascular-related physiological processes;
  • Induce testosterone disruption, decrease fertility, reproduction rates, and aberrant behavior in aquatic organisms;
  • Affect microbial communities within wastewater treatment facilities.
[109,110,111,112]
Chemotherapy and anticancer drugsIntroduction to the aquatic environment via human excretion and the incorrect disposal of unused medicines
  • Affect organisms’ growth, development, and reproduction by interfering with normal cell division and DNA replication;
  • Induce toxic effects at environmental concentrations on fish, invertebrates, and other aquatic organisms;
  • Disrupt microbial communities in the environment, including soil and water microbial communities, through alterations in the growth and activity of beneficial microbes, leading to microbial population imbalances and disturbances in ecological processes.
[113,114,115]
Table 2. Removal efficiency of different treatment methods for pharmaceutical compounds (based on and modified by Stadlmair et al. [152]).
Table 2. Removal efficiency of different treatment methods for pharmaceutical compounds (based on and modified by Stadlmair et al. [152]).
Type of Treatment MethodTreatment MethodEfficiencyPharmaceutical CompoundsReferences
Physico-chemical TreatmentAerationLowAnalgesics and antibiotics[153]
Coagulation, flocculation, and sedimentationVery lowAntibiotics, antidepressants, AEDs, analgesics, NSAIDs[154,155,156]
AdsorptionHighAntibiotics and NSAIDs[157,158,159,160,161]
FiltrationContaminant dependentAEDs, NSAIDs, antibiotics, EDCs[162,163,164,165]
Nanofiltration Moderate to high EDCs, β-blockers, psychotropics and AEDs, antibiotics[166,167,168,169]
Reverse osmosis High Analgesics, NSAIDs, β-blockers, AEDs, psychotropic drugs[170,171,172]
Biological TreatmentConventional activated sludgeLow to moderateAnalgesics, EDCs, antibiotics, β-blockers, AEDs[173,174]
Membrane bioreactors Moderate to high EDCs, psychotropic drugs, NSAIDs, anti-diabetic drugs, β-blockers, [108,140,175]
Microalgal bioremediation processLow to moderateNSAIDs, β-blockers, AEDs, antibiotics, EDCs[176,177]
Enzyme-based treatment Moderate to high NSAIDs[152,178,179,180]
Oxidation TreatmentChlorinationContaminant-dependentAntibiotics, EDCs, β-blockers, analgesics, NSAIDs[181,182]
OzonationHighAntibiotics, EDCs, AEDs, NSAIDs, psychotropic drugs[172,183,184,185]
Advanced oxidation processes (AOPs)HighEDCs, antibiotics, NSAIDs, psychotropic drugs[89,186,187,188,189]
Electrochemical treatment Electrochemical technologies HighAntibiotics, EDCs, NSAIDs[190,191,192,193,194]
Table 3. Summary of bacterial indicators and coupled methods.
Table 3. Summary of bacterial indicators and coupled methods.
Methods Associated with the Use of Bacteria for Pharmaceutical PollutionIndicative Taxa (or Genus or Phylum)Pharmaceutical CompoundsMethod of DetectionRefs.
Indirect MethodsBioremediation Actinobacteria, Chryseobacterium, Flavobacterium, Pseudoxanthomonas, β-blockersPCR-DGGE and pyrosequencing[245]
Bacillus thuringiensis B1
Novosphingobium sp.
Sphingomonas sp.
Sphingopyxis sp.
Sphingobium sp.
Isoptericola sp.
Nubsella sp.
Rhodococcus sp.
Bacillus sp.
NSAIDs Gram staining, API CORYNE system analysis, FAMEs analysis, HPLC, cell cultures, PCR [246,247]
Pseudomonas sp. CE21
Pseudomonas sp. CE22
Paucibacter
Filomicrobium
AntibioticsCell cultures, PCR, LC-MS, degradation analysis with MS, BOD 5/COD Ratio, HPLC, TOC/TN analysis, ammonia and nitrate analysis, SEM[248,249]
Chryseobacterium taeanense
Rhizobium daejeonense
Diaphorobacter nitroreducens
Achromobacter mucicolens
Pseudomonas veronii
Pseudomonas lini
AEDsPCR and HPLC[250]
Microbacterium sp. C448Anti-cancerLiquid scintillation counting, HPLC-MS/MS, LC-MS, solvent extraction (ASE 200), NGS[251]
Flavobacterium
Novosphingobium sp.
Sphingomonas sp.
Sphingopyxis sp.
Sphingobium sp.
Isoptericola sp.
Nubsella sp.
Rhodococcus sp.
Bacillus sp.
Nitrosomonas europaea
Acinetobacter sp.
Phyllobacterium myrsinacearum
Ralstonia pickettii
Pseudomonas
EDCsHPLC, IC, TOC analysis, oxygen probe analysis, rep-PCR, NGS, fluorescence detection, colorimetric analysis, UV/fluorescence detection, GC-MS/MS and LC-MS/MS, ATP/OD measurement[247,252,253,254]
Communities’ function and structureActinobacteria, Bacteroidetes, Cyanobacteria, Flavobacteria, Firmicutes, Proteobacteria, FusobacteriaHormones, antibiotics, antipsychotic drugs, AEDs, NSAIDs, β-blockers, antihistamines, antidiabetics, analgesics, H2 blockers, ACE inhibitorsHPLC, UPLC-MS/MS, FTIR, LC-MS/MS, enzyme assays, MBR and batch cultures, qPCR, PCR-DGGE, NGS, metagenomics[255,256,257,258,259]
Detection of ARBs (and ARGs)Escherichia coli, Klebsiella pneumoniae, Aeromonas spp., Pseudomonas aeruginosa, Enterococcus faecalis, Enterococcus faecium, Acinetobacter baumannii, Flavobacterium, Poriferibacter, Bacteroides, Acinetobacter, Actinobaculum, StreptococcusAntibioticsMetagenomics-metatranscriptomics, qPCR, rep-PCR[260,261,262]
Direct MethodsWhole-cell BiosensorsEscherichia coli, Pseudomonas fluorescen, Bacillus subtilisAntibiotics, NSAIDs, EDCsBiosensor (optical, fluorescence, electrochemical, etc.)[263,264,265,266,267,268]
PCR: polymerase chain reaction, qPCR: quantitative polymerase chain reaction, rep-PCR: repetitive extragenic palindromic polymerase chain reaction, DGGE: denaturing gradient gel electrophoresis, FAMEs: fatty acid methyl ester, HPLC: high-performance liquid chromatography, LC-MS: liquid chromatography–mass spectrometry, MS: mass spectrometry, BOD: biochemical oxygen demand, COD: chemical oxygen demand, TOC: total organic carbon, TN: total water-born nitrogen, SEM: scanning electron microscopy, NGS: next generation sequencing, IC: ion chromatography, GC-MS/MS: gas chromatography tandem mass spectrometry, LC-MS/MS: liquid chromatography tandem mass spectrometry, ATP: adenosine triphosphate, OD: optical density, UPLC-MS/MS: ultra performance liquid chromatography tandem mass spectrometry, FTIR: Fourier transform infrared spectroscopy, MBR: membrane bioreactors.
Table 4. Overview of the role of eDNA metabarcoding in assessing aquatic organisms’ response to pharmaceutical pollution.
Table 4. Overview of the role of eDNA metabarcoding in assessing aquatic organisms’ response to pharmaceutical pollution.
Affected Aquatic OrganismsSummary of PhACs ImplicationsEvaluation of eDNA Metabarcoding in Pharmaceutical Pollution Assessment
Microbial
communities
  • Alterations in the structure, metabolic activity, composition, and formation of microbial biofilms [5,336];
  • Disruption of the balance of microbial populations, leading to an increase in ARBs and ARGs [90,336];
  • Perturbation in micro-photoautotrophic organisms which can impact higher trophic levels [14,35,337,338,339,340].
  • Provides comprehensive data regarding the influence of pharmaceutical pollutants on aquatic microbial diversity [341];
  • Facilitates the assessment of changes in the composition and diversity of microbial communities resulting from specific PhACs [342,343,344,345];
  • Provides valuable insights into predicting pollution levels and identifying the key factors influencing ecological networks [66,275].
Plants
  • Harmful effects during plants’ development [346];
  • Antichloroplastic activity in cyanobacteria, green algae, and other aquatic plants [347];
  • Perturbation in macro-photoautotrophic organisms which can significantly impact higher trophic levels [14,35,337,339].
  • Assesses the biotic composition, abundance, and distribution of aquatic species (i.e., macroinvertebrates, plants, fishes, and others in freshwater and marine ecosystems) [348,349,350,351,352,353,354];
  • Improves fish monitoring, fosters biodiversity conservation and fishery management that transcends both geographical and temporal boundaries [355,356].
Invertebrates
  • Notable effects on macroinvertebrates, mainly in terms of growth, behavior, and reproduction [357].
Vertebrates
  • Chronic adverse impacts on fish species that manifest mainly as locomotor and reproductive dysfunctions, hematological and hormonal imbalances, immunotoxicity, the disruption of endocrine function, genotoxicity, oxidative stress, physical deformities, teratogenic effects, and a deterioration in the overall physiological state of the organisms [39,358,359,360,361];
  • Influences on the behavior of fish, comprising alterations in activity, sociality, and feeding rate as well as aggression and reproductive behaviors [362,363,364,365].
Aquatic
food webs
  • Bioaccumulation: pharmaceutical compounds enter aquatic ecosystems and can be stored in the tissues of aquatic organisms [366,367];
  • Biomagnification: contaminants can be transferred across the food web, leading to higher concentrations in the aquatic organism tissues of higher trophic levels [368], potentially posing risks to human health [358].
  • Detects a broader spectrum of taxa and indicator groups that traditional taxonomic identification may miss, leading to more accurate assessments [369];
  • Provides valuable insights into the impacts of chemical stressors on freshwater ecosystems and allows for identifying keystone species and monitoring shifts in microbial functional groups, which can help predict potential changes in ecosystem functionality [317,370,371,372];
  • Identifies individual species and assesses community compositions in aquatic ecosystems [369], investigates biodiversity [313,373], characterizes prey in gut contents or fecal samples [374,375], and analyzes food web dynamics [376].
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Papaioannou, C.; Geladakis, G.; Kommata, V.; Batargias, C.; Lagoumintzis, G. Insights in Pharmaceutical Pollution: The Prospective Role of eDNA Metabarcoding. Toxics 2023, 11, 903. https://doi.org/10.3390/toxics11110903

AMA Style

Papaioannou C, Geladakis G, Kommata V, Batargias C, Lagoumintzis G. Insights in Pharmaceutical Pollution: The Prospective Role of eDNA Metabarcoding. Toxics. 2023; 11(11):903. https://doi.org/10.3390/toxics11110903

Chicago/Turabian Style

Papaioannou, Charikleia, George Geladakis, Vasiliki Kommata, Costas Batargias, and George Lagoumintzis. 2023. "Insights in Pharmaceutical Pollution: The Prospective Role of eDNA Metabarcoding" Toxics 11, no. 11: 903. https://doi.org/10.3390/toxics11110903

APA Style

Papaioannou, C., Geladakis, G., Kommata, V., Batargias, C., & Lagoumintzis, G. (2023). Insights in Pharmaceutical Pollution: The Prospective Role of eDNA Metabarcoding. Toxics, 11(11), 903. https://doi.org/10.3390/toxics11110903

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop