Inhomogeneous antibiotic distribution in sediment profiles in anthropogenically impacted lakes: Source apportionment, fate drivers, and risk assessment

Combining chemical analysis and toxicological methods to access the ecological risk of complex contamination in Daye Lake

As one of the nine primary non-ferrous metal smelting bases in China, Daye Lake basin was polluted due to diverse human activities. But so far the pollution status and related ecological risks of this region have not been detailly investigated. In current study, pollutants including heavy metals, polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides (OCPs) in eight sediment samples from Daye Lake were quantified. 18S rRNA gene sequencing was employed to profile the nematode community structure within these sediments. Model organism Caenorhabditis elegans (C. elegans) were further applied for a comprehensive ecological risk assessment of Daye Lake. Notably, Cadmium (Cd) was identified as a key driver of ecological risk, reaching an index of 1287.35. At sample point S4, OCPs particularly p,p'-DDT, displayed an extreme ecological risk with a value of 23.19. Cephalobidae and Mononchida showed strong sensitivity to pollutant levels, reinforcing their suitability as robust bioindicators. The composite pollutants in sampled sediments caused oxidative stress in C. elegans, with gene Vit-2 and Mtl-1 as sensitive biomarkers. By employing the multiple analysis methods, our data can offer valuable contributions to environmental monitoring and health risk assessment for composite polluted areas.

Distribution and ecological risk assessment of antibiotics in different freshwater aquaculture ponds in a typical agricultural plain, China

Freshwater aquaculture serves as a significant focal point for antibiotic contamination, yet understanding antibiotic distribution across different aquaculture models and stages remains limited. This study evaluated antibiotic pollution in three distinct freshwater aquaculture models: rice-crayfish coculture, fish aquaculture, and crab-crayfish aquaculture, during various aquaculture stages. Of the 33 target antibiotics, 16 antibiotics were detected, with the total concentrations ranging from 111.81 ng/L to 15,949.05 ng/L in water and 10.11 ng/g to 8986.30 ng/g in sediment. Among these antibiotics, erythromycin and lomefloxacin are prohibited for use in Chinese aquaculture. Dominant antibiotics in water included lincomycin, enrofloxacin, and enoxacin, whereas in sediment, oxytetracycline and erythromycin were predominant. Notably, lincomycin emerged as a dominant antibiotic in aquaculture for the first time. The concentrations of these dominant antibiotics were high compared to other aquaculture settings and exhibited elevated ecological risk. Critical periods for antibiotic contamination in water and sediment were found to be incongruent, occurring during the rainy season in July for water and the dry season in October for sediment. Notably, the rice-crayfish coculture model exerts a good effect in reducing antibiotic pollution. Overall, these findings offer valuable evidence for the healthful and sustainable advancement of aquaculture.

Insight into environmental adaptability of antibiotic resistome from surface water to deep sediments in anthropogenic lakes by metagenomics

The escalating antibiotic resistance threatens the long-term global health. Lake sediment is a vital hotpot in transmitting antibiotic resistance genes (ARGs); however, their vertical distribution pattern and driving mechanisms in sediment cores remain unclear. This study first utilized metagenomics to reveal how resistome is distributed from surface water to 45 cm sediments in four representative lakes, central China. Significant vertical variations in ARG profiles were observed (R2 = 0.421, p < 0.001), with significant reductions in numbers, abundance, and Shannon index from the surface water to deep sediment (all p-values < 0.05). ARGs also has interconnections within the vertical profile of the lakes: twelve ARGs persistently exist all sites and depths, and shared ARGs (e.g., vanS and mexF) were assembled by diverse hosts at varying depths. The 0-18 cm sediment had the highest mobility and health risk of ARGs, followed by the 18-45 cm sediment and water. The drivers of ARGs transformed along the profile of lakes: microbial communities and mobile genetic elements (MGEs) dominated in water, whereas environmental variables gradually become the primary through regulating microbial communities and MGEs with increasing sediment depth. Interestingly, the stochastic process governed ARG assembly, while the stochasticity diminished under the mediation of Chloroflexi, Candidatus Bathyarcaeota and oxidation-reduction potential with increasing depth. Overall, we formulated a conceptual framework to elucidate the vertical environmental adaptability of resistome in anthropogenic lakes. This study shed on the resistance risks and their environmental adaptability from sediment cores, which could reinforce the governance of public health issues.

Algae-Mediated Removal of Prevalent Genotoxic Antibiotics: Molecular Perspective on Algae-Bacteria Consortia and Bioreactor-Based Strategies

Antibiotic pollution poses a potential risk of genotoxicity, as antibiotics released into the environment can induce DNA damage and mutagenesis in various organisms. This pollution, stemming from pharmaceutical manufacturing, agriculture, and improper disposal, can disrupt aquatic ecosystems and potentially impact human health through the consumption of contaminated water and food. The removal of genotoxic antibiotics using algae-mediated approaches has gained considerable attention due to its potential for mitigating the environmental and health risks associated with these compounds. The paper provides an in-depth examination of the molecular aspects concerning algae and bioreactor-driven methodologies utilized for the elimination of deleterious antibiotics. The molecular analysis encompasses diverse facets, encompassing the discernment and profiling of algae species proficient in antibiotic degradation, the explication of enzymatic degradation pathways, and the refinement of bioreactor configurations to augment removal efficacy. Emphasizing the significance of investigating algal approaches for mitigating antibiotic pollution, this paper underscores their potential as a sustainable solution, safeguarding both the environment and human health.

Urban agglomerations as an environmental dimension of antibiotics transmission through the "One Health" lens

The spatiotemporal distributions of antibiotics in different media have been widely reported; however, their occurrence in the environmental dimension of the Chinese urban agglomerations has received less attention, especially in bioaccumulation and health risks of antibiotics through the "One Health" lens. The review presents the current knowledge on the environmental occurrence, bioaccumulation, as well as health exposure risks in urban agglomerations through the "One Health" lens, and identifies current information gaps. The reviewed studies suggested antibiotic concentrations in water and soil were more sensitive to social indicators of urban agglomerations than those in sediment. The ecological risk and resistance risk of antibiotics in water were much higher than those of sediments, and the high-risk phenomenon occurred at a higher frequency in urban agglomerations. Erythromycin-H2O (ETM-H2O), amoxicillin (AMOX) and norfloxacin (NFC) were priority-controlled antibiotics in urban waters. Tetracyclines (TCs) posed medium to high risks to soil organisms in the soil of urban agglomerations. Health risk evaluation based on dietary intake showed that children had the highest dietary intake of antibiotics in urban agglomerations. The health risk of antibiotics was higher in children than in other age groups. Our results also demonstrated that dietary structure might impact health risks associated with target antibiotics in urban agglomerations to some extent.

NCRD: A non-redundant comprehensive database for detecting antibiotic resistance genes

Antibiotic resistance genes (ARGs) are emerging pollutants present in various environments. Identifying ARGs has become a growing concern in recent years. Several databases, including the Antibiotic Resistance Genes Database (ARDB), Comprehensive Antibiotic Resistance Database (CARD), and Structured Antibiotic Resistance Genes (SARG), have been applied to detect ARGs. However, these databases have limitations, which hinder the comprehensive profiling of ARGs in environmental samples. To address these issues, we constructed a non-redundant antibiotic resistance genes database (NRD) by consolidating sequences from ARDB, CARD, and SARG. We identified the homologous proteins of NRD from Non-redundant Protein Database (NR) and the Protein DataBank Database (PDB) and clustered them to establish a non-redundant comprehensive antibiotic resistance genes database (NCRD) with similarities of 100% (NCRD100) and 95% (NCRD95). To demonstrate the advantages of NCRD, we compared it with other databases by using metagenome datasets. Results revealed its strong ability in detecting potential ARGs.