Nanoplastic contamination: Impact on zebrafish liver metabolism and implications for aquatic environmental health.

Nanoplastics (NPs) are increasingly pervasive in the environment, raising concerns about their potential health implications, particularly within aquatic ecosystems. This study investigated the impact of polystyrene nanoparticles (PSN) on zebrafish liver metabolism using liquid chromatography hybrid quadrupole time of flight mass spectrometry (LC-QTOF-MS) based non-targeted metabolomics. Zebrafish were exposed to 50 nm PSN for 28 days at low (L-PSN) and high (H-PSN) concentrations (0.1 and 10 mg/L, respectively) via water. The results revealed significant alterations in key metabolic pathways in low and high exposure groups. The liver metabolites showed different metabolic responses with L-PSN and H-PSN. A total of 2078 metabolite features were identified from the raw data obtained in both positive and negative ion modes, with 190 metabolites deemed statistically significant in both L-PSN and H-PSN groups. Disruptions in lipid metabolism, inflammation, oxidative stress, DNA damage, and amino acid synthesis were identified. Notably, L-PSN exposure induced changes in DNA building blocks, membrane-associated biomarkers, and immune-related metabolites, while H-PSN exposure was associated with oxidative stress, altered antioxidant metabolites, and liver injury. For the first time, L-PSN was found depolymerized in the liver by cytochrome P450 enzymes. Utilizing an analytical approach to the adverse outcome pathway (AOP), impaired lipid metabolism and oxidative stress have been identified as potentially conserved key events (KEs) associated with PSN exposure. These KEs further induced liver inflammation, steatosis, and fibrosis at the tissue and organ level. Ultimately, this could significantly impact biological health. The study highlights the PSN-induced effects on zebrafish liver metabolism, emphasizing the need for a better understanding of the risks associated with NPs contamination in aquatic ecosystems.

The size-dependence and reversibility of polystyrene nanoplastics-induced lipid accumulation in mice: Possible roles of lysosomes.

Nanoplastics (NPs) continue to accumulate in global aquatic and terrestrial systems, posing a potential threat to human health through the food chain and/or other pathways. Both in vivo and in vitro studies have confirmed that the liver is one of the main organs targeted for the accumulation of NPs in living organisms. However, whether exposure to NPs induces size-dependent disorders of liver lipid metabolism remains controversial, and the reversibility of NPs-induced hepatotoxicity is largely unknown. In this study, the effects of long-term exposure to environmentally relevant doses of polystyrene nanoplastics (PS-NPs) on lipid accumulation were investigated in terms of autophagy and lysosomal mechanisms. The findings indicated that hepatic lipid accumulation was more pronounced in mice exposed to 100 nm PS-NPs compared to 500 nm PS-NPs. This effect was effectively alleviated after 50 days of self-recovery for 100 nm and 500 nm PS-NPs exposure. Mechanistically, although PS-NPs exposure activated autophagosome formation through ERK (mitogen-activated protein kinase 1)/mTOR (mechanistic target of rapamycin kinase) signaling pathway, the inhibition of Rab7 (RAB7, member RAS oncogene family), CTSB (cathepsin B), and CTSD (cathepsin D) expression impaired lysosomal function, thereby blocking autophagic flux and contributing to hepatic lipid accumulation. After termination of PS-NPs exposure, lysosomal exocytosis was responsible for the clearance of PS-NPs accumulated in lysosomes. Furthermore, impaired lysosomal function and autophagic flux inhibition were effectively alleviated. This might be the main reason for the alleviation of PS-NPs-induced lipid accumulation after recovery. Collectively, we demonstrate for the first time that lysosomes play a dual role in the persistence and reversibility of hepatotoxicity induced by environmental relevant doses of NPs, which provide novel evidence for the prevention and intervention of liver injury associated with nanoplastics exposure.

[High-throughput qPCR and Amplicon Sequencing as Complementary Methods for Profiling Antibiotic Resistance Genes in Urban Wetland Parks].

Urban wetland parks are an important practice for urban wetland protection and utilization due to the vast ecosystem service value. As emerging contaminants, antibiotic resistance genes (ARGs) are great attractions for environmental research and public concerns. Based on high-throughput qPCR and high-throughput amplicon sequencing techniques, we investigated the occurrence, abundance, and distribution profiles of antibiotic resistance genes in the aquatic environment of Xiamen urban wetland parks (five sites). The influencing factors and driving mechanisms of antibiotic resistance genes were deciphered on the basis of microbial community structure and water quality. Diverse and abundant ARGs were observed and coexisted in urban wet parks. A total of 217 ARGs were detected in the water body of urban wetland parks, with an abundance up to 6.48×109 copies·L-1. Urban wetland parks were important hotspots and repositories of the antibiotic resistome. A total of nine bacterial genera, including Marivivens, NS5_marine_group, and Planktomarina, were identified as the potential carriers of diverse resistance genes (41 ARGs). The microbial communities could alone explain 51% of alterations in the antibiotic resistome in the aquatic environment of the urban wetland parks. Therefore, the microbial community was the key driving force for the occurrence and evolution of ARGs in urban wetland parks. Based on the results, with the presence of ARGs and antibiotic resistance bacteria, it is suggested that the water environments of urban wetland parks have potential risks of water ecological security and human health, and it is necessary to further enhance the research and control of microbial contaminants in the aquatic environment of urban wetland parks.

Mapping the profiles and underlying driving mechanisms of the antibiotic resistome and microbiome within a subtropical complex river watershed.

Antibiotic resistance is an escalating global concern, leading to millions of annual deaths worldwide. Human activities can impact antibiotic resistance gene (ARG) prevalence in aquatic ecosystems, but the intricate interplay between anthropogenic disturbances and river system resilience, and their respective contributions to the dynamics of different river segments, remains poorly understood. In this study, we investigate the antibiotic resistome and microbiome in water and sediment samples from two distinct sub-watersheds within a specific watershed. Results show a decrease in the number of core ARGs downstream in water, while sediments near densely populated areas exhibit an increase. PCoA ordination reveals clear geographic clustering of resistome and microbiome among samples from strong anthropogenic disturbed areas, reservoir areas, and estuary area. Co-occurrence networks highlight a higher connectivity of mobile genetic elements (MGEs) in disturbed areas compared to reservoir areas, presenting a threat to densely populated areas. Water quality parameters and antibiotics concentration were the key factors shaping the ARG profiles in sediment samples from urban regions. Overall, our study reveals distinct patterns of ARGs in sediment and water samples, emphasizing the importance of considering both anthropogenic and natural factors in comprehending and managing ARG distribution in river systems.

Long-term seawall barriers lead to the formation of an urban coastal lagoon with increased antibiotic resistome.

Urbanization has increased the spread of antibiotic resistance genes (ARGs) impacting urban aquatic ecosystems and threatening human health. However, an overview of the antibiotic resistome in artificial coastal lagoons formed by coastal seawall construction is unclear. This study investigated the resistome of sediment in a coastal lagoon, established for over 60 years and found that the composition of the resistome in the lagoon sediments associated with the seawall significantly differed from that of marine sediment external to the seawall. Moreover, the diversity, number, relative abundance, and absolute abundance of the antibiotic resistome in the lagoon sediments were significantly higher compared to marine sediment. Network analyses revealed that more co-occurrences were found in lagoon sediment between bacterial communities, ARGs and mobile genetic elements (MGEs) than in marine sediments, suggesting that bacteria in lagoon sediments may be associated with multiple antibiotic resistances. Random forest and structural equation models showed that an increase in the absolute abundance of MGEs had a concomitant effect on the absolute abundance and diversity of ARGs, whereas increasing salinity decreased the absolute abundance of ARGs. This study provides a basis to assess the risk of resistome diffusion and persistence in an artificial coastal lagoon.

Metabolic coupling of arsenic, carbon, nitrogen, and sulfur in high arsenic geothermal groundwater: Evidence from molecular mechanisms to community ecology.

Groundwater arsenic (As) poses a global environmental problem and is regulated by complex biogeochemical processes. However, the As biogeochemistry and its metabolic coupling with carbon (C), nitrogen (N), and sulfur (S) in high As geothermal groundwater remain unclear. Here, we reported significant shifts in the geothermal groundwater microbiome and its functional ecological clusters along the flow path with increased As levels and dynamic As-C-N-S biogeochemical cycle from the Guide Basin, China. Strong associations among As(III), NH4+, HCO3-, and corresponding functional microbial taxa suggest that microbe-mediated As transformation, ammonification, and organic carbon biodegradation potentially contributed to the As mobilization in the discharge area. And As oxidizers (coupling with denitrification or carbon fixation) and S oxidizers were closely linked to the transformation of As(III) to immobile As(V) in the recharge area. Our study provides a comprehensive insight into the complex microbial As-C-N-S coupling network and its potential role in groundwater As mobilization under hydrological disturbances.

Separation and flow cytometry analysis of microplastics and nanoplastics.

In recent years, the utilization of flow cytometry for quantitative microplastic analysis has gained prominence. However, the current methods have some drawbacks that need to be improved. The present study aims to enhance the flow cytometry detection protocols for Nile red (NR) stained microplastics, facilitating distinct microplastic and nanoplastic enumeration. By elevating dimethyl sulfoxide (DMSO) concentration to 20%-30% within the solution, NR solubility improved and agglomeration reduced. The analysis of 26 replicates of polystyrene (PS) liquid samples through four distinct dot plots highlighted the superior accuracy of dot plots integrating yellow fluorescence. Through systematic staining of varying NR concentrations across three microplastic liquid samples (polyethylene terephthalate, polyethylene, and polypropylene), the optimal staining concentration was determined to be 15-20 µg/mL. The distributions of agglomerated NR and NR stained PS under two scenarios-dissolved NR and partially agglomerated NR-were compared. Results showed their distinct distributions within the side scatter versus yellow fluorescence dot plot. Counting results from gradient-diluted PS liquid samples revealed a microplastic detection lower limit of 104 particles/mL, with an optimal concentration range of 105-106 particles/mL. Flow cytometric assessment of PS microspheres spanning 150 nm to 40 µm indicated a 150 nm particle size detection minimum. Our investigation validated the efficacy of NR staining and subsequent flow cytometry analysis across eleven types of microplastics. Separation and concentration of microplastics (1.0-50.0 µm) and nanoplastics (0.2-1.0 µm) were achieved via sequential sieving through 50, 1.0, and 0.2 µm filter membranes. We used a combination of multiple filtration steps and flow cytometry to analyze microplastics and nanoplastics in nine simulated water samples. Our results showed that the combined amount of microplastics (1.0-50.0 µm) and nanoplastics (0.2-1.0 µm) after filtration had a ratio of 0.80-1.19 compared to the total microplastic concentration before filtration. This result confirms the practicality of our approach. By enhancing flow cytometry-based microplastic and nanoplastic detection protocols, our study provides pivotal technical support for research concerning quantitative toxicity assessment of microplastic and nanoplastic pollution.

[Distribution and Driving Mechanisms of Antibiotic Resistance Genes in Desert-Oasis Continuum].

The oasis agro-ecosystem is a complex ecosystem with intensive human activities in arid areas. Microbial antibiotic resistance is posing threats to human health and ecological balance. It is of great importance to investigate the diversity, distribution profiles, and driving factors of soil antibiotic resistance genes under different land use patterns in a desert-oasis continuum, especially for assessing soil environmental and human health risks in arid regions. In this study, high throughput sequencing combined with high throughput quantitative PCR were used to investigate the microbial community structure and patterns of antibiotic resistance genes in a desert-oasis continuum, aiming to explore the distribution characteristics and driving mechanisms of soil resistance genes. The results showed that the diversity and abundance of antibiotic resistance increased significantly from the edge of desert to the central oasis, along with Dest, Cotn, Maiz, Reed, and Sedt, consecutively, implying that farmland soil was an important reservoir of resistance genes, which was closely related to land use and land cover change. Soil microbial communities were significantly correlated with antibiotic resistance genes. Thiobacillus, Pontibacter, Nocardioides, Salinimicrobium, Solirubrobacter, and Streptomyces were important potential hosts of various resistance genes. The patterns of antibiotic resistance genes were shaped by heavy metal elements, MGEs, and microbial communities in arid soil, which accumulatively accounted for 70% of the variations in resistance genes alone or together and therefore drove the occurrence, enrichment, and evolution of resistance genes in agricultural soil of the desert-oasis continuum.

Distinct patterns of the soil and phyllosphere antibiotic resistome in natural forest ecosystems under an altitudinal gradient.

Warming affects microbial functioning of soil and the phyllosphere across global ecosystems. However, little is known about the impact of increasing temperature on antibiotic resistome profiles in natural forests. To address this issue, we investigated antibiotic resistance genes (ARGs) in both soil and the plant phyllosphere using an experimental platform established in a forest ecosystem that delivers a temperature difference of 2.1 °C along an altitudinal gradient. Principal Coordinate Analysis (PCoA) showed that there were significant differences in the composition of soil and plant phyllosphere ARGs at different altitudes (P = 0.001). The relative abundance of phyllosphere ARGs and mobile genetic elements (MGEs) and soil MGEs increased with temperature. More resistance gene classes increased in abundance in the phyllosphere (10 classes) than soil (2 classes), and a Random Forest model analysis suggested that phyllosphere ARGs were more sensitive to temperature change than soil. Increasing temperature as a direct consequence of an altitudinal gradient, and the relative abundance of MGEs were the main drivers that shaped the profiles of ARGs in the phyllosphere and soil. Biotic and abiotic factors affected phyllosphere ARGs indirectly via MGEs. This study enhances our understanding of the influence of altitude gradients on resistance genes in natural environments.

Preparation of Cross-Sectional Membrane Samples for Scanning Electron Microscopy Characterizations Using a New Frozen Section Technique.

Characterization of the cross-sectional morphologies of polymeric membranes are critical in understanding the relationship of structure and membrane separation performances. However, preparation of cross-sectional samples with flat surfaces for scanning electron microscopy (SEM) characterizations is challenging due to the toughness of the non-woven fabric support. In this work, a new frozen section technique was developed to prepare the cross-sectional membrane samples. A special mold was self-designed to embed membranes orientationally. The frozen section parameters, including the embedding medium, cryostat working temperature, and sectioning thickness were optimized. The SEM characterizations demonstrated that the frozen section technique, using ultrapure water as the embedding medium at a working temperature of -30 °C and a sectioning thickness of 0.5 µm, was efficient for the preparation of the membrane samples. Three methods of preparation for the cross-sectional polymeric membranes, including the conventional liquid nitrogen cryogenic fracture, the broad ion beam (BIB) polishing, and the frozen section technique were compared, which showed that the modified frozen section method was efficient and low cost. This developed method could not only accelerate the development of membrane technology but also has great potential for applications in preparation of other solid samples.

Bayesian-Learning-Based Diffusion Least Mean Square Algorithms Over Networks.

To improve the learning performance of the conventional diffusion least mean square (DLMS) algorithms, this article proposes Bayesian-learning-based DLMS (BL-DLMS) algorithms. First, the proposed BL-DLMS algorithms are inferred from a Gaussian state-space model-based Bayesian learning perspective. By performing Bayesian inference in the given Gaussian state-space model, a variable step-size and an estimation of the uncertainty of information of interest at each node are obtained for the proposed BL-DLMS algorithms. Next, a control method at each node is designed to improve the tracking performance of the proposed BL-DLMS algorithms in the sudden change scenario. Then, a lower bound on the variable step-size of each node of the proposed BL-DLMS algorithms is derived to maintain the optimal steady-state performance in the nonstationary scenario (unknown parameter vector of interest is time-varying). Afterward, the mean stability and the transient and steady-state mean square performance of the proposed BL-DLMS algorithms are analyzed in the nonstationary scenario. In addition, two Bayesian-learning-based diffusion bias-compensated LMS algorithms are proposed to handle the noisy inputs. Finally, the superior learning performance of the proposed learning algorithms is verified by numerical simulations, and the simulated results are in good agreement with the theoretical results.

Response of microbial taxonomic and nitrogen functional attributes to elevated nitrate in suburban groundwater.

Anthropogenic nitrogen (N) input has led to elevated levels of nitrate nitrogen (NO3--N) in the groundwater. However, insights into the responses of the microbial community and its N metabolic functionality to elevated NO3--N in suburban groundwater are still limited. Here, we explored the microbial taxonomy, N metabolic attributes, and their responses to NO3--N pollution in groundwaters from Chaobai River catchment (CR) and Huai River catchment (HR) in Beijing, China. Results showed that average NO3--N and NH4+-N concentrations in CR groundwater were 1.7 and 3.0 folds of those in HR. NO3--N was the dominant nitrogen specie both in HR and CR groundwater (over 80 %). Significantly different structures and compositions of the microbial communities and N cycling gene profiles were found between CR groundwater and HR groundwater (p < 0.05), with CR groundwater harboring significantly lower microbial richness and abundance of N metabolic genes. However, denitrification was the dominant microbial N cycling process in both CR and HR groundwater. Strong associations among NO3--N, NH4+-N, microbial taxonomic, and N functional attributes were found (p < 0.05), suggesting denitrifiers and Candidatus_Brocadia might serve as potential featured biomarkers for the elevated NO3--N and NH4+-N concentration in groundwater. Path analysis further revealed the significant effect of NO3--N on the overall microbial N functionality and microbial denitrification (p < 0.05). Collectively, our results provide field evidence that elevated levels of NO3--N and NH4+-N under different hydrogeologic conditions had a significant effect on the microbial taxonomic and N functional attributes in groundwater, with potential implications for improving sustainable N management and risk assessment of groundwater.

Antibiotic resistome in groundwater and its association with mountain springs and river.

The distribution of antibiotic resistance genes (ARGs) in water sources potentially threatens drinking water safety. However, the sources of antibiotic resistome in groundwater are still under-investigated. Here, we evaluated the profiles of antibiotic resistome in peri-urban groundwater and its associated water sources (river and mountain spring) to characterize the antibiotic resistome from natural water sources on groundwater resistome. A total of 261 antibiotic resistome were detected in groundwater, mountain spring, and river samples. The relative abundances of ARGs and mobile genetic elements (MGEs) were significantly higher in the river samples than in spring water and groundwater samples. The resistome profiles were similar between groundwater and spring water but differed from the river samples. According to source tracking results, the groundwater resistome was likely to be derived from springs (28.0%-50.0%) and rivers (28.6%-48.6%), which share the same trend for the source tracking of bacterial communities. Bacterial α-diversity, bacterial ß-diversity, and MGEs directly or indirectly affected the ARGs in groundwater samples. Although the abundance of groundwater resistome was not elevated by river and spring water, groundwater resistomes were diverse and may be derived from both river and spring water. We highlight the importance of groundwater resistome and its association with potential water sources, providing a better understanding and basis for the effective control of the ARG proliferation and dissemination in groundwater from exogenous water bodies in the future.

Urbanization Reduces Phyllosphere Microbial Network Complexity and Species Richness of Camphor Trees.

Studies on microbial communities associated with foliage in natural ecosystems have grown in number in recent years yet have rarely focused on urban ecosystems. With urbanization, phyllosphere microorganisms in the urban environment have come under pressures from increasing human activities. To explore the effects of urbanization on the phyllosphere microbial communities of urban ecosystems, we investigated the phyllosphere microbial structure and the diversity of camphor trees in eight parks along a suburban-to-urban gradient. The results showed that the number of ASVs (amplicon sequence variants), unique on the phyllosphere microbial communities of three different urbanization gradients, was 4.54 to 17.99 times higher than that of the shared ASVs. Specific microbial biomarkers were also found for leaf samples from each urbanization gradient. Moreover, significant differences (R2 = 0.133, p = 0.005) were observed in the phyllosphere microbial structure among the three urbanization gradients. Alpha diversity and co-occurrence patterns of bacterial communities showed that urbanization can strongly reduce the complexity and species richness of the phyllosphere microbial network of camphor trees. Correlation analysis with environmental factors showed that leaf total carbon (C), nitrogen (N), and sulfur (S), as well as leaf C/N, soil pH, and artificial light intensity at night (ALIAN) were the important drivers in determining the divergence of phyllosphere microbial communities across the urbanization gradient. Together, we found that urbanization can affect the composition of the phyllosphere bacterial community of camphor trees, and that the interplay between human activities and plant microbial communities may contribute to shaping the urban microbiome.

VFG-Chip: A high-throughput qPCR microarray for profiling virulence factor genes from the environment.

As zoonotic pathogens are threatening public health globally, the virulence factor genes (VFGs) they carry underlie latent risk in the environment. However, profiling VFGs in the environment is still in its infancy due to lack of efficient and reliable quantification tools. Here, we developed a novel high-throughput qPCR (HT-qPCR) chip, termed as VFG-Chip, to comprehensively quantify the abundances of targeted VFGs in the environment. A total of 96 VFGs from four bacterial pathogens including Klebsiella pneumoniae, Acinetobacter baumannii, Escherichia coli, and Salmonella enterica were targeted by 120 primer pairs, which were involved in encoding five types of virulence factors (VFs) like toxin, adherence, secretion system, immune evasion/invasion, and iron uptake. The specificity of VFG-Chip was both verified computationally and experimentally, with high identity of amplicon sequencing and melting curves analysis proving its robust capability. The VFG-Chip also displayed high sensitivity (by plasmid serial dilution test) and amplification efficiency averaging 97.7%. We successfully applied the VFG-Chip to profile the distribution of VFGs along a wastewater treatment system with 69 VFGs detected in total. Overall, the VFG-Chip provides a robust tool for comprehensively quantifying VFGs in the environment, and thus provides novel information in assessing the health risks of zoonotic pathogens in the environment.

Plant identity shapes phyllosphere microbiome structure and abundance of genes involved in nutrient cycling.

The phyllosphere is a fluctuant micro-environment habitat that harbors diverse microbial communities that have the potential to influence plant growth through their effect on host fitness. However, we know little about the driving factors of phyllosphere microbial functional traits, e.g., genes related to nutrient cycling and microbial community structure under anthropic disturbance. Here, we characterized phyllosphere microbial communities and the abundance of genes related to nutrient cycling from diverse plant species between urban and natural habitats. We measured leaf functional traits to investigate the potential drivers of the phyllosphere microbial profile. Results indicated that phyllosphere microbial communities differed significantly between urban and natural habitats, and that this variation was dependent upon plant species. Host plant species had a greater influence on the abundance of genes involved in nutrient cycling in the phyllosphere than habitat. In addition, phyllosphere microbial diversity and functional gene abundance were significantly correlated. Furthermore, host leaf functional traits (e.g., specific leaf area and nutrient content) were potential driving factors of both phyllosphere microbial community structure and the abundance of genes involved in nutrient cycling. These findings contribute to a better understanding of the phyllosphere microbiome and its biotic and abiotic controlling factors, which improves our understanding of plant-microbe interactions and their ecosystem functions under anthropic disturbance.

Low complexity symmetric-coded based sphere decoding for low-rate polar codes.

The sphere decoding (SD) algorithm can provide (sub)optimal solutions with reduced computational complexity of maximum likelihood (ML) detection for multi-input multi-output (MIMO) communication systems. In this paper, we propose a novel low complexity symmetric-coded based SD algorithm for short polar codes with low rate. At the encoding stage, the first N/2 sub-channels transmit the frozen bits, while the information bits are selected from the latter N/2 sub-channels. Two symmetric codes are generated due to the mathematical structure of the generator matrix, which is well conditioned to the SD search. At the decoding stage, the presented SD algorithm computes the Euclidean distance value by the combined signals to estimate the latter N/2 input bits. Furthermore, the backtrack operation starts from the earlier [Formula: see text]-th bit, which can significantly reduce the average visited nodes (AVN). Simulation results show that, compared to the original SD algorithm, the presented variant of the SD algorithm can reduce the AVN to [Formula: see text] for the polar code P(64, 14) at SNR = 1  dB with a performance loss within 0.2 dB. The presented SD algorithm may find applications in MIMO systems where the complexity of the standar ML detection increases exponentially with the transmitting antennas.

Effect of phenol formaldehyde-associated microplastics on soil microbial community, assembly, and functioning.

Increasing investigations explore the effects of plastic pollutants on bacterial communities, diversity, and functioning in various ecosystems. However, the impact of microplastics (MPs) on the eukaryotic community, microbial assemblages, and interactions is still limited. Here, we investigated bacterial and micro-eukaryotic communities and functioning in soils with different concentrations of phenol formaldehyde-associated MPs (PF-MPs), and revealed the factors, such as soil properties, microbial community assembly, and interactions between microbes, influencing them. Our results showed that a high concentration (1%) of PF-MPs decreased the microbial interactions and the contribution of deterministic processes to the community assembly of microbes, and consequently changed the communities of bacteria, but not eukaryotes. A significant and negative relationship was determined between N2O emission rate and functional genes related to nitrification, indicating that the competitive interactions between functional microbes would affect the nitrogen cycling of soil ecosystem. We further found that vegetable biomass weakly decreased in treatments with a higher concentration of PF-MPs and positively related to the diversity of micro-eukaryotic communities and functional diversity of bacterial communities. These results suggest that a high concentration of the PF-MPs would influence crop growth by changing microbial communities, interactions, and eukaryotic and functional diversity. Our findings provide important evidence for agriculture management of phenol formaldehyde and suggest that we must consider their threats to microbial community compositions, diversity, and assemblage in soils due to the accumulation of PF-MPs widely used in the field.

Dissemination of antibiotic resistance genes from landfill leachate to groundwater.

Landfill leachate, a highly concentrated organic wastewater containing diverse microorganisms and various heavy metals, has become an important reservoir of antibiotic resistance genes (ARGs). In this study, a total of 203 unique ARGs and 10 mobile genetic elements (MGEs) were identified from collected landfill leachate and groundwater. The number and abundance (normalized and absolute) of antibiotic resistome in effluent of leachate treatment plants decreased significantly compared to influent. The abundance of ARGs in groundwater increased as the distance from the leachate basin decreased. Fast expectation-maximization microbial source tracking (FEAST) showed that up to 96 % of ARGs in groundwater (GW3) may originate from nearby leachate, suggesting that ARGs in leachate can penetrate and spread into the groundwater environment. A significant correlation between ARGs and bacterial communities was identified. Together with network analysis showing the 12 bacterial taxa co-occurring with seven classes of antibiotic-associated ARGs, our results revealed the diverse potential microbial hosts of ARGs in water samples around the landfill sites. Heavy metals, bacterial community and MGEs were the driving factors shaping the ARGs patterns in the water samples, with their interactions explaining 57 % of ARGs variations. Our results provide an understanding of the distribution and dissemination of ARGs from landfill leachate to the nearby groundwater and suggest a comprehensive impact assessment of ARGs in aquatic environments of landfills.

HiLi-chip: A high-throughput library construction chip for comprehensive profiling of environmental microbial communities.

Investigating the contribution and associations of environmental microbes to ecological health and human well-being is in great demand with the goal of One Health proposed. To achieve the goal, there is an urgent need for accurate approaches to obtaining a large amount of high-resolution molecular information from various microbes. In this study, we developed a high-throughput library construction chip (HiLi-Chip) for profiling environmental microbial communities and evaluated its performance. The HiLi-Chip showed high conformity with the conventional Pacbio method in terms of α-diversity, community composition of abundant bacteria (>83%), as well as rare taxa (>84%) and human pathogens detection (>67%), indicating its advantages of accuracy, high-throughput, cost-efficiency, and broad practicability. It is suggested that the optimal strategy of the HiLi-Chip was a 2.4 µL PCR mixture per sample (∼2.4 ng DNA) with a 216-sample × 24-replicate format. We have successfully applied the HiLi-Chip to the Jiulongjiang River and identified 51 potential human bacterial pathogens with a total relative abundance of 0.22%. Additionally, under limited nutrients and similar upstream environments, bacteria tended to impose competitive pressures, resulting in a more connected network at the downstream river confluence (RC). Whereas narrow niche breadth of bacteria and upstream environmental heterogeneity probably promoted niche complementary and environment selection leading to fewer links at RC in the midsection of the river. Core bacteria might represent the entire bacterial community and enhance network stability through synergistic interactions with other core bacteria. Collectively, our results demonstrate that the HiLi-Chip is a robust tool for rapid comprehensive profiling of microbial communities in environmental samples and has significant implications for a profound understanding of environmental microbial interactions.