Transformation and degradation of tebuconazole and its metabolites in constructed wetlands with arbuscular mycorrhizal fungi colonization.

Arbuscular mycorrhizal fungi (AMF) colonization has been used in constructed wetlands (CWs) to enhance treatment performance. However, its role in azole (fungicide) degradation and microbial community changes is not well understood. This study aims to explore the impact of AMF on the degradation of tebuconazole and its metabolites in CWs. Total organic carbon levels were consistently higher with the colonization of AMF (AMF+; 9.63- 16.37 mg/L) compared to without the colonization of AMF (AMF-; 8.79-14.48 mg/L) in CWs. Notably, tebuconazole removal was swift, occurring within one day in both treatments (p = 0.885), with removal efficiencies ranging from 94.10 % to 97.83 %. That's primarily due to rapid substrate absorption at the beginning, while degradation follows with a longer time. Four metabolites were reported in CWs first time: tebuconazole hydroxy, tebuconazole lactone, tebuconazole carboxy acid, and tebuconazole dechloro. AMF decreased the abundance of tebuconazole dechloro in the liquid phase, suggesting an inhibitory effect of AMF on dechlorination processes. Furthermore, tebuconazole carboxy acid and hydroxy were predominantly found in plant roots, with a higher abundance observed in AMF+ treatments. Metagenomic analysis highlighted an increasing abundance in bacterial community structure in favor of beneficial microorganisms (xanthomonadales, xanthomonadaceae, and lysobacter), along with a notable presence of functional genes like codA, NAD, and deaD in AMF+ treatments. These findings highlight the positive influence of AMF on tebuconazole stress resilience, microbial community modification, and the enhancement of bioremediation capabilities in CWs.

Accumulation of heavy metals from single and combined olive mill wastewater and pomace in soil and bioaccumulation in tissues of two earthworm species: Endogeic (Aporrectodea trapezoides) and Epigeic (Eisenia fetida).

Soil and earthworms are threatened by anthropogenic contamination resulting from olive mill waste dumping on the soil due to their pollutant properties. While several studies have explored the effects of olive mill waste on soil properties and the accumulation of heavy metals in soil, there is currently a gap in the literature regarding the potential bioaccumulation of heavy metals from olive mill waste in earthworms. In this study, soil with earthworms from two ecological categories (endogeic: Aporrectodea trapezoides and epigeic: Eisenia fetida) was treated with increasing doses of olive mill wastewater (OMWW) and olive mill pomace (OMP), applied individually or combined, in an indoor experiment in plastic containers, under laboratory conditions. The results revealed the presence of significant concentrations of heavy metals in the two types of wastes ranging as follows: Fe˃ Zn˃ Cu˃ Cd˃ Cr for OMWW, and Fe˃ Zn˃ Cu˃ Cr for OMP (with Cd below the detection limit). The study demonstrated distinct effects of OMWW and OMP, both individually and in combination, on soil heavy metal content, ranging as follows: soil OMWW > soil Combination > soil OMP for Cd; soil Combination > soil OMWW > soil OMP for Cr and Fe; and soil Combination > soil OMP > soil OMWW for Cu and Zn. Additionally, our investigation showed that both earthworm species exhibited significant uptake of these metals into their tissues, particularly the endogeic species. Interestingly, the most significant difference between species was in the accumulation of Cu, with the epigeic species accumulating significantly lower amounts.

Influence of different stalks on the metallization degree of FeCl3-derived magnetic biochar through pyrolysis behavior and compositional differences.

To investigate the effect of stalk type on the metallization degrees in FeCl3-derived magnetic biochar (MBC), MBC was synthesized via an impregnation-pyrolysis method using six different stalks. The Fe0 content in MBC significantly influenced its magnetic properties and ostensibly governed its catalytic capabilities. Analysis of the interaction between stalks and FeCl3 revealed that the variation in metallization degrees, resulting from FeCl2 decomposition (6.1%) and stalk-mediated reduction (20.7%), was directly responsible for the observed differences in MBC metallization. The presence of oxygen-containing functional groups and fixed carbon appeared to promote metallization in MBC induced by reduction. A series of statistical analyses indicated that the cellulose, lignin, and hemicellulose content of the stalks were key factors contributing to differences in MBC metallization degrees. Further exploration revealed that hemicellulose and cellulose were more effective than lignin in enhancing metallization through FeCl2 decomposition and reduction. Constructing stalk models demonstrated that the variance in the content of these three biomass components across the six stalk types could lead to differences in the metallization degree attributable to reduction and FeCl2 decomposition, thereby affecting the overall metallization degree of MBC. A prediction model for MBC metallization degree was developed based on these findings. Moreover, the elevated Si content in some stalks facilitated the formation of Fe2(SiO4), which subsequently impeded the reduction process. This study provides a theoretical foundation for the informed selection of stalk feedstocks in the production of FeCl3-derived MBC.

Community metagenomics reveals the processes of cadmium resistance regulated by microbial functions in soils with Oryza sativa root exudate input.

Plants exert a profound influence on their rhizosphere microbiome through the secretion of root exudates, thereby imparting critical effects on their growth and overall health. The results unveil that japonica rice showcases a remarkable augmentation in its antioxidative stress mechanisms under Cd stress. This augmentation is characterized by the sequestration of heavy metal ions within the root system and the prodigious secretion of a spectrum of flavonoids, including Quercetin, Luteolin, Apigenin, Kaempferide, and Sakuranetin. These flavonoids operate as formidable guardians, shielding the plant from oxidative damage instigated by Cd-induced stress. Furthermore, the metagenomic analyses divulge the transformative potential of flavonoids, as they induce profound alterations in the composition and structural dynamics of plant rhizosphere microbial communities. These alterations manifest through the recruitment of plant growth-promoting bacteria, effectively engineering a conducive milieu for japonica rice. In addition, our symbiotic network analysis discerns that flavonoid compounds significantly improved the positive correlations among dominant species within the rhizosphere of japonica rice. This, in turn, bolsters the stability and intricacy of the microenvironmental ecological network. KEGG functional analyses reveal a notable upregulation in the expression of flavonoid functional genes, specifically cadA, cznA, nccC, and czrB, alongside an array of transporters, encompassing RND, ABC, MIT, and P-ATPase. These molecular orchestrations distinctly demarcated the rhizosphere microbiome of japonica rice, markedly enhancing its tolerance to Cd-induced stress. These findings not only shed light on the establishment of Cd-resistant bacterial consortia in rice but also herald a promising avenue for the precise modulation of plant rhizosphere microbiomes, thereby fortifying the safety and efficiency of crop production.

Machine learning for cyanobacteria inversion via remote sensing and AlgaeTorch in the Trebon fishponds, Czech Republic.

Cyanobacteria blooms in fishponds, driven by climate change and anthropogenic activities, have become a critical concern for aquatic ecosystems worldwide. The diversity in fishpond sizes and fish densities further complicates their monitoring. This study addresses the challenge of accurately predicting cyanobacteria concentrations in turbid waters via remote sensing, hindered by optical complexities and diminished light signals. A comprehensive dataset of 740 sampling points was compiled, encompassing water quality metrics (cyanobacteria levels, total chlorophyll, turbidity, total cell count) and spectral data obtained through AlgaeTorch, alongside Sentinel-2 reflectance data from three Trebon fishponds (UNESCO Man and Biosphere Reserve) in the Czech Republic over 2022-2023. Partial Least Squares Regression (PLSR) and three machine learning algorithms, Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost), were developed based on seasonal and annual data volumes. The SVM algorithm demonstrated commendable performance on the one-year data validation dataset from the Svet fishpond for the prediction of cyanobacteria, reflected by the key performance indicators: R2 = 0.88, RMSE = 15.07 µg Chl-a/L, and RPD = 2.82. Meanwhile, SVM displayed steady results in the unified one-year validation dataset from Nadeje, Svet, and Vizír fishponds, with metrics showing R2 = 0.56, RMSE = 39.03 µg Chl-a/L, RPD = 1.50. Thus, Sentinel data proved viable for seasonal cyanobacteria monitoring across different fishponds. Overall, this study presents a novel approach for enhancing the precision of cyanobacteria predictions and long-term ecological monitoring in fishponds, contributing significantly to the water quality management strategies in the Trebon region.

Mixotrophic aerobic denitrification facilitated by denitrifying bacterial-fungal communities assisted with iron in micro-polluted water: Performance, metabolic activity, functional genes abundance, and community co-occurrence.

Low-dosage nitrate pollutants can contribute to eutrophication in surface water bodies, such as lakes and reservoirs. This study employed assembled denitrifying bacterial-fungal communities as bio-denitrifiers, in combination with zero-valent iron (ZVI), to treat micro-polluted water. Immobilized bacterial-fungal mixed communities (IBFMC) reactors demonstrated their ability to reduce nitrate and organic carbon by over 43.2 % and 53.7 %, respectively. Compared to IBFMC reactors, IBFMC combined with ZVI (IBFMC@ZVI) reactors exhibited enhanced removal efficiencies for nitrate and organic carbon, reaching the highest of 31.55 % and 17.66 %, respectively. The presence of ZVI in the IBFMC@ZVI reactors stimulated various aspects of microbial activity, including the metabolic processes, electron transfer system activities, abundance of functional genes and enzymes, and diversity and richness of microbial communities. The contents of adenosine triphosphate and electron transfer system activities enhanced more than 5.6 and 1.43 folds in the IBFMC@ZVI reactors compared with IBFMC reactors. Furthermore, significant improvement of crucial genes and enzyme denitrification chains was observed in the IBFMC@ZVI reactors. Iron played a central role in enhancing microbial diversity and activity, and promoting the supply, and transfer of inorganic electron donors. This study presents an innovative approach for applying denitrifying bacterial-fungal communities combined with iron enhancing efficient denitrification in micro-polluted water.

Integrated transcriptome and metabolomics analyses revealed key functional genes in Canna indica under Cr stress.

Chromium (Cr) can interfere with plant gene expression, change the content of metabolites and affect plant growth. However, the molecular response mechanism of wetland plants at different time sequences under Cr stress has yet to be fully understood. In this study, Canna indica was exposed to 100 mg/kg Cr-contaminated soil for 0, 7, 14, and 21 days and analyzed using untargeted metabolomics (LC-MS) and transcriptomics. The results showed that Cr stress increased the activities of superoxide dismutase (SOD), ascorbate peroxidase (APX) and peroxidase (POD), the contents of glutathione (GSH), malondialdehyde (MDA), and oxygen free radical (ROS), and inhibited the biosynthesis of photosynthetic pigments, thus leading to changes in plant growth and biomass. Metabonomics analysis showed that Cr stress mainly affected 12 metabolic pathways, involving 38 differentially expressed metabolites, including amino acids, phenylpropane, and flavonoids. By transcriptome analysis, a total of 16,247 differentially expressed genes (DEGs, 7710 up-regulated genes, and 8537 down-regulated genes) were identified, among which, at the early stage of stress (Cr contaminate seven days), C. indica responds to Cr toxicity mainly through galactose, starch and sucrose metabolism. With the extension of stress time, plant hormone signal transduction and MAPK signaling pathway in C. indica in the Cr14 (Cr contaminate 14 days) treatment group were significantly affected. Finally, in the late stage of stress (Cr21), C. indica co-defuses Cr toxicity by activating its Glutathione metabolism and Phenylpropanoid biosynthesis. In conclusion, this study revealed the molecular response mechanism of C. indica to Cr stress at different times through multi-omics methods.

Advancing toxicity studies of per- and poly-fluoroalkyl substances (pfass) through machine learning: Models, mechanisms, and future directions.

Perfluorinated and perfluoroalkyl substances (PFASs), encompassing a vast array of isomeric chemicals, are recognized as typical emerging contaminants with direct or potential impacts on human health and the ecological environment. With the complex and elusive toxicological profiles of PFASs, machine learning (ML) has been increasingly employed in their toxicity studies due to its proficiency in prediction and data analytics. This integration is poised to become a predominant trend in environmental toxicology, propelled by the swift advancements in computational technology. This review diligently examines the literature to encapsulate the varied objectives of employing ML in the toxicity studies of PFASs: (1) Utilizing ML to establish Quantitative Structure-Activity Relationship (QSAR) models for PFASs with diverse toxicity endpoints, facilitating the targeted toxicity prediction of unidentified PFASs; (2) Investigating and substantiating the Adverse Outcome Pathway (AOP) through the synergy of ML and traditional toxicological methods, with this refining the toxicity assessment framework for PFASs; (3) Dissecting and elucidating the features of established ML models to advance Open Research into the toxicity of PFASs, with a primary focus on determinants and mechanisms. The discourse extends to an in-depth examination of ML studies, segregating findings based on their distinct application trajectories. Given that ML represents a nascent paradigm within PFASs research, this review delineates the collective challenges encountered in the ML-mediated study of PFAS toxicity and proffers strategic guidance for ensuing investigations.

Utilizing transcriptomics and proteomics to unravel key genes and proteins of Oryza sativa seedlings mediated by selenium in response to cadmium stress.

BACKGROUND: Cadmium (Cd) pollution has declined crop yields and quality. Selenium (Se) is a beneficial mineral element that protects plants from oxidative damage, thereby improving crop tolerance to heavy metals. The molecular mechanism of Se-induced Cd tolerance in rice (Oryza sativa) is not yet understood. This study aimed to elucidate the beneficial mechanism of Se (1 mg/kg) in alleviating Cd toxicity in rice seedlings. RESULTS: Exogenous selenium addition significantly improved the toxic effect of cadmium stress on rice seedlings, increasing plant height and fresh weight by 20.53% and 34.48%, respectively, and increasing chlorophyll and carotenoid content by 16.68% and 15.26%, respectively. Moreover, the MDA, ·OH, and protein carbonyl levels induced by cadmium stress were reduced by 47.65%, 67.57%, and 56.43%, respectively. Cell wall metabolism, energy cycling, and enzymatic and non-enzymatic antioxidant systems in rice seedlings were significantly enhanced. Transcriptome analysis showed that the expressions of key functional genes psbQ, psbO, psaG, psaD, atpG, and PetH were significantly up-regulated under low-concentration Se treatment, which enhanced the energy metabolism process of photosystem I and photosystem II in rice seedlings. At the same time, the up-regulation of LHCA, LHCB family, and C4H1, PRX, and atp6 functional genes improved the ability of photon capture and heavy metal ion binding in plants. Combined with proteome analysis, the expression of functional proteins OsGSTF1, OsGSTU11, OsG6PDH4, OsDHAB1, CP29, and CabE was significantly up-regulated under Se, which enhanced photosynthesis and anti-oxidative stress mechanism in rice seedlings. At the same time, it regulates the plant hormone signal transduction pathway. It up-regulates the expression response process of IAA, ABA, and JAZ to activate the synergistic effect between each cell rapidly and jointly maintain the homeostasis balance. CONCLUSION: Our results revealed the regulation process of Se-mediated critical metabolic pathways, functional genes, and proteins in rice under cadmium stress. They provided insights into the expression rules and dynamic response process of the Se-mediated plant resistance mechanism. This study provided the theoretical basis and technical support for crop safety in cropland ecosystems and cadmium-contaminated areas.

Comprehensive physiology and proteomics analysis revealed the resistance mechanism of rice (Oryza sativa L) to cadmium stress.

Cadmium contamination can lead to a decrease in crop yield and quality. However, Cd-tolerant rice can improve rice resistance genes, improve crop tolerance to heavy metals, and protect plants from oxidative damage. In this study, Japonica rice: Chunyou 987 and Indica rice: Chuanzhong you 3607 were used to reveal the molecular response mechanism of Cd-tolerant rice under cadmium concentration of 3 mg/kg through comparative experiments combined with physiology and proteomics. The results showed that compared with indica rice, japonica rice showed more robust resistance to Cd stress and effectively retained many Cd ions in roots. Moreover, it enhanced its enzymatic and non-enzymatic anti-oxidative stress mechanism, which increased the activities of catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) by 47.37%, 21.75%, and 55.42%, respectively. The contents of non-enzymatic antioxidant substances ascorbic acid (AsA), glutathione (GSH), cysteine (Cys), proline (PRO), anthocyanins (OPC), and flavonoids were increased by 25.32%, 42.67%, 21.43%, 50.81%, 33.23%, and 72.16%, respectively. Through proteomics analysis, it was found that in response to the damage caused by cadmium stress, Japonica rice makes Photosynthesis functional proteins (psbO and PetH), Photosynthesis antenna proteins (LHCA and ASCAB9), Carbon fixation functional proteins (PEPC and OsAld), Porphyrin metabolism functional proteins (OsRCCR1 and SE5), Glyoxylate and dicarboxylate The expression of metabolism functional proteins (CATC and GLO4.) and Glutathione metabolism functional proteins (APX8 and OsGSTU13) were significantly up-regulated, which stimulated the antioxidant stress mechanism and photosynthetic system, and constructed a robust energy supply system to ensure the normal metabolic activities of life. Strengthening the mechanisms of plant homeostasis. In summary, this study revealed the molecular mechanism of tolerance to Cd stress in japonica rice, and the results of this study will provide a possible way to improve Cd-resistant rice seedlings.

Application of environmental DNA metabarcoding to identify fish community characteristics in subtropical river systems.

Fish are vital in river ecosystems; however, traditional investigations of fish usually cause ecological damage. Extracting DNA from aquatic environments and identifying DNA sequences offer an alternative, noninvasive approach for detecting fish species. In this study, the effects of environmental DNA (eDNA), coupled with PCR and next-generation sequencing, and electrofishing for identifying fish community composition and diversity were compared. In three subtropical rivers of southern China, fish specimens and eDNA in water were collected along the longitudinal (upstream-downstream) gradient of the rivers. Both fish population parameters, including species abundance and biomass, and eDNA OTU richness grouped 38 sampling sites into eight spatial zones with significant differences in local fish community composition. Compared with order-/family-level grouping, genus-/species-level grouping could more accurately reveal the differences between upstream zones I-III, midstream zones IV-V, and downstream zones VI-VIII. From the headwaters to the estuary, two environmental gradients significantly influenced the longitudinal distribution of the fish species, including the first gradient composed of habitat and physical water parameters and the second gradient composed of chemical water parameters. The high regression coefficient of alpha diversity between eDNA and electrofishing methods as well as the accurate identification of dominant, alien, and biomarker species in each spatial zone indicated that eDNA could characterize fish community attributes at a level similar to that of traditional approaches. Overall, our results demonstrated that eDNA metabarcoding can be used as an effective tool for revealing fish composition and diversity, which is important for using the eDNA technique in aquatic field monitoring.

Metabolomic reveals the responses of sludge properties and microbial communities to high nitrite stress in denitrifying phosphorus removal systems.

Nitrite, as an electron acceptor, plays a good role in denitrifying phosphorus removal (DPR); however, high nitrite concentration has adverse affects on sludge performance. We investigated the precise mechanisms of responses of sludge to high nitrite stress, including surface characteristics, intracellular and extracellular components, microbial and metabolic responses. When the nitrite stress reached 90 mg/L, the sludge settling performance was improved, but the activated sludge was aging. FTIR and XPS analysis revealed a significant increase in the hydrophobicity of the sludge, resulting in improve settling performance. However, the intracellular carbon sources synthesis was inhibited. In addition, the components in the tightly bound extracellular polymeric substances (TB-EPS) of sludge were significantly reduced and indicated the disturb of metabolism. Notably, Exiguobacterium emerged as a new genus when face high nitrite stress that could maintaining survival in hostile environments. Moreover, metabolomic analysis demonstrated strong biological response to nitrite stress further supported above results that include the inhibited of carbohydrate and amino acid metabolism. More importantly, some lipids (PS, PA, LysoPA, LysoPC and LysoPE) were significantly upregulated that related enhanced membrane lipid remodeling. The comprehensive analyses provide novel insights into the high nitrite stress responses mechanisms in activated sludge systems.

Molecular transformation of dissolved organic matter in manganese ore-mediated constructed wetlands for fresh leachate treatment.

The organic matter (OM) and nitrogen in Fresh leachate (FL) from waste compression sites pose environmental and health risks. Even though the constructed wetland (CW) can efficiently remove these pollutants, the molecular-level transformations of dissolved OM (DOM) in FL remain uncertain. This study reports the molecular dynamics of DOM and nitrogen removal during FL treatment in CWs. Two lab-scale vertical-flow CW systems were employed: one using only sand as substrates (act as a control, CW-C) and the other employing an equal mixture of manganese ore powder and sand (experimental, CW-M). Over 488 days of operation, CW-M exhibited significantly higher removal rates for chemical oxygen demand (COD), ammonia nitrogen (NH4+-N), and dissolved organic matter (represented by dissolved organic carbon, DOC) at 98.2 ± 2.5%, 99.2 ± 1.4%, and 97.9 ± 1.9%, respectively, in contrast to CW-C (92.8 ± 6.8%, 77.1 ± 28.1%, and 74.7 ± 9.5%). The three-dimensional fluorescence excitation-emission matrix (3D-EEM) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) analyses unveiled that the influent DOM was predominantly composed of readily biodegradable protein-like substances with high carbon content and low unsaturation. Throughout treatment, it led to the degradation of low O/C and high H/C compounds, resulting in the formation of DOM with higher unsaturation and aromaticity, resembling humic-like substances. CW-M showcased a distinct DOM composition, characterized by lower carbon content yet higher unsaturation and aromaticity than CW-C. The study also identified the presence of Gammaproteobacteria, reported as Mn-oxidizing bacteria with significantly higher abundance in the upper and middle layers of CW-M, facilitating manganese cycling and improving DOM removal. Key pathways contributing to DOM removal encompassed adsorption, catalytic oxidation by manganese oxides, and microbial degradation. This study offers novel insights into DOM transformation and removal from FL during CW treatment, which will facilitate better design and enhanced performance.

Algicidal activity synchronized with nitrogen removal by actinomycetes: Algicidal mechanism, stress response of algal cells, denitrification performance, and indigenous bacterial community co-occurrence.

The harmful algal blooms (HABs) can damage the ecological equilibrium of aquatic ecosystems and threaten human health. The bio-degradation of algal by algicidal bacteria is an environmentally friendly and economical approach to control HABs. This study applied an aerobic denitrification synchronization algicidal strain Streptomyces sp. LJH-12-1 (L1) to control HABs. The cell-free filtrate of the strain L1 showed a great algolytic effect on bloom-forming cyanobacterium, Microcystis aeruginosa (M. aeruginosa). The optimal algicidal property of strain L1 was indirect light-dependent algicidal with an algicidal rate of 85.0%. The functional metabolism, light-trapping, light-transfer efficiency, the content of pigments, and inhibition of photosynthesis of M. aeruginosa decreased after the addition of the supernatant of the strain L1 due to oxidative stress. Moreover, 96.05% nitrate removal rate synchronized with algicidal activity was achieved with the strain L1. The relative abundance of N cycling functional genes significantly increased during the strain L1 effect on M. aeruginosa. The algicidal efficiency of the strain L1 in the raw water was 76.70% with nitrate removal efficiency of 81.4%. Overall, this study provides a novel route to apply bacterial strain with the property of denitrification coupled with algicidal activity in treating micro-polluted water bodies.

Metagenomic analysis revealed N-metabolizing microbial response of Iris tectorum to Cr stress after colonization by arbuscular mycorrhizal fungi.

Arbuscular mycorrhizal fungi (AMF) and plant growth-promoting bacteria enhance plant tolerance to abiotic stress and promote plant growth in contaminated soil. However, the interaction mechanism between rhizosphere microbial communities under chromium (Cr) stress remains unclear. This study conducted a greenhouse pot experiment and metagenomics analysis to reveal the comprehensive effects of the interaction between AMF (Rhizophagus intraradices) and nitrogen-N metabolizing plant growth promoters on the growth of Iris tectorum. The results showed that AMF significantly increased the biomass and nutrient levels of I. tectorum in contaminated soil and decreased the content of Cr in the soil. Metagenomics analysis revealed that the structure and composition of the rhizosphere microbial community involved in nitrogen metabolism changed significantly after inoculation with AMF under Cr stress. Functional genes related to soil nitrogen mineralization (gltB, gltD, gdhA, ureC, and glnA), nitrate reduction to ammonium (nirB, nrfA, and nasA), and soil nitrogen assimilation (NRT, nrtA, and nrtC) were up-regulated in the N-metabolizing microbial community. In contrast, the abundance of functional genes involved in denitrification (nirK and narI) was down-regulated. In addition, the inoculation of AMF regulates the synergies between the N-metabolic rhizosphere microbial communities and enhances the complexity and stability of the rhizosphere ecological network. This study provides a basis for improving plant tolerance to heavy metal stress by regulating the functional abundance of N-metabolizing plant growth-promoting bacteria through AMF inoculation. It helps to understand the potential mechanism of wetland plant remediation of Cr-contaminated soil.

Neural network establishes co-occurrence links between transformation products of the contaminant and the soil microbiome.

It remains challenging to establish reliable links between transformation products (TPs) of contaminants and corresponding microbes. This challenge arises due to the sophisticated experimental regime required for TP discovery and the compositional nature of 16S rRNA gene amplicon sequencing and mass spectrometry datasets, which can potentially confound statistical inference. In this study, we present a new strategy by combining the use of 2H-labeled Stable Isotope-Assisted Metabolomics (2H-SIAM) with a neural network-based algorithm (i.e., MMvec) to explore links between TPs of pyrene and the soil microbiome. The links established by this novel strategy were further validated using different approaches. Briefly, a metagenomic study provided indirect evidence for the established links, while the identification of pyrene degraders from soils, and a DNA-based stable isotope probing (DNA-SIP) study offered direct evidence. The comparison among different approaches, including Pearson's and Spearman's correlations, further confirmed the superior performance of our strategy. In conclusion, we summarize the unique features of the combined use of 2H-SIAM and MMvec. This study not only addresses the challenges in linking TPs to microbes but also introduces an innovative and effective approach for such investigations. Environmental Implication: Taxonomically diverse bacteria performing successive metabolic steps of the contaminant were firstly depicted in the environmental matrix.

Occurrence, distribution, and risk assessment of antibiotics in a typical aquaculture area around the Dongzhai Harbor mangrove forest on Hainan Island.

The trees of the Dongzhai Harbor mangrove forest suffer from antibiotic contamination from surrounding aquaculture areas. Despite this being one of the largest mangrove forests in China, few studies have focused on the antibiotic pollution status in these aquaculture areas. In the present study, the occurrence, distribution, and risk assessment of 37 antibiotics in surface water and sediment samples from aquaculture areas around Dongzhai Harbor mangrove forests were analyzed. The concentration of total antibiotics (∑antibiotics) ranged from 78.4 ng/L to 225.6 ng/L in surface water (except S14-A2) and from 19.5 ng/g dry weight (dw) to 229 ng/g dw in sediment. In the sediment, the concentrations of ∑antibiotics were relatively low (19.5-52.3 ng/g dw) at 75 % of the sampling sites, while they were high (95.7-229.0 ng/g dw) at a few sampling sites (S13-A1, S13D, S8D). The correlation analysis results showed that the Kd values of the 9 antibiotics were significantly positively correlated with molecular weight (MW), Kow, and LogKow. Risk assessment revealed that sulfamethoxazole (SMX) in surface water and SMX, enoxacin (ENX), ciprofloxacin (CFX), enrofloxacin (EFX), ofloxacin (OFX), and norfloxacin (NFX) in sediment had medium/high risk quotients (RQs) at 62.5 % and 25-100 %, respectively, of the sampling sites. The antibiotic mixture in surface water (0.06-3.36) and sediment (0.43-309) posed a high risk at 37.5 % and 66.7 %, respectively, of the sampling sites. SMX was selected as an indicator of antibiotic pollution in surface water to assist regulatory authorities in monitoring and managing antibiotic pollution in the aquaculture zone of Dongzhai Harbor. Overall, the results of the present study provide a comprehensive and detailed analysis of the characteristics of antibiotics in the aquaculture environment around the Dongzhai Harbor mangrove system and provide a theoretical basis for the source control of antibiotics in mangrove systems.

Methane emission from water level fluctuation zone of the Three Gorges Reservoir: Seasonal variation and microbial mechanism.

Periodic and significant water level fluctuations within the Three Gorges Reservoir (TGR) create a complex water level fluctuation zone (WLFZ) that can significantly influence greenhouse gas emissions. However, the scarcity of comprehensive studies investigating long-term monitoring and analysis of CH4 flux patterns and underlying mechanisms concerning water level variations, environmental characteristics, and microbial communities has limited our understanding. This study conducted a four-year monitoring campaign to examine in situ CH4 emissions from three representative sampling sites. Results indicated that the CH4 flux remained relatively stable at lower water levels, specifically at the control site (S1). However, water level fluctuations significantly influenced CH4 emissions at the sampling sites situated within the WLFZ. Notably, the highest CH4 flux of 0.252 ± 0.089 mg/(m2·h) was observed during the drying period (June to August), while the lowest CH4 flux of 0.048 ± 0.026 mg/(m2·h) was recorded during the flooding period. Moreover, CH4 emissions through the water-air interface surpassed those through the soil-air interface. The CH4 flux positively correlated with organic carbon, temperature, and soil moisture. The relative abundance of methane metabolism microorganisms peaked during the drying period and decreased during the impounding and flooding periods. The primary methanogenesis pathway was hydrogenotrophic, whereas methanotrophic processes were mainly aerobic, with Ca. Methylomirabilis governing the anaerobic methanotrophic process. Overall, the current findings serve as crucial theoretical references for understanding CH4 emissions and carbon metabolism processes within WLFZ environments.

Arbuscular mycorrhizal fungi enhanced the drinking water treatment residue-based vertical flow constructed wetlands on the purification of arsenic-containing wastewater.

Arsenic (As) is a toxic metalloid that poses a potential risk to the environment and human health. In this study, drinking water treatment residue (DWTR) and ceramsite-based vertical flow constructed wetlands (VFCWs) were built to purify As-containing wastewater. As a method of bioaugmentation, arbuscular mycorrhizal fungi (AMF) was inoculated to Pteris vittata roots to enhance the As removal of the VFCWs. The results showed that the As removal rates reached 87.82-94.29% (DWTR) and 33.28-58.66% (ceramsite). DWTR and P. vittata contributed 64.33-72.07% and 7.57-29% to the removal of As, while AMF inoculation intensified the As accumulation effect of P. vittata. Proteobacteria, the main As3+ oxidizing bacteria in the aquatic systems, dominated the microbial community, occupying 72.41 ± 7.76%. AMF inoculation increased As-related functional genes abundance in DWTR-based wetlands and provided a reliable means of arsenic resistance in wetlands. These findings indicated that the DWTR-based VFCWs with AMF inoculated P. vittata had a great purification effect on As-containing wastewater, providing a theoretical basis for the application of DWTR and AMF for As removal in constructed wetlands.

Aerobic Denitrification Promoting by Actinomycetes Coculture: Investigating Performance, Carbon Source Metabolic Characteristic, and Raw Water Restoration.

The coculture theory that promotes denitrification relies on effectively utilizing the resources of low-efficiency denitrification microbes. Here, the strains Streptomyces sp. PYX97 and Streptomyces sp. TSJ96 were isolated and showed lower denitrification capacity when cultured individually. However, the coculture of strains PYX97 and TSJ96 enhanced nitrogen removal (removed 96.40% of total nitrogen) and organic carbon reduction (removed 92.13% of dissolved organic carbon) under aerobic conditions. Nitrogen balance analysis indicated that coculturing enhanced the efficiency of nitrate converted into gaseous nitrogen reaching 70.42%. Meanwhile, the coculturing promoted the cell metabolism capacity and carbon source metabolic activity. The coculture strains PYX97 and TSJ96 thrived in conditions of C/N = 10, alkalescence, and 150 rpm shaking speed. The coculturing reduced total nitrogen and CODMn in the raw water treatment by 83.32 and 84.21%, respectively. During this treatment, the cell metabolic activity and cell density increased in the coculture strains PYX97 and TSJ96 reactor. Moreover, the coculture strains could utilize aromatic protein and soluble microbial products during aerobic denitrification processes in raw water treatment. This study suggests that coculturing inefficient actinomycete strains could be a promising approach for treating polluted water bodies.