Hidden diversity and potential ecological function of phosphorus acquisition genes in widespread terrestrial bacteriophages.

Phosphorus (P) limitation of ecosystem processes is widespread in terrestrial habitats. While a few auxiliary metabolic genes (AMGs) in bacteriophages from aquatic habitats are reported to have the potential to enhance P-acquisition ability of their hosts, little is known about the diversity and potential ecological function of P-acquisition genes encoded by terrestrial bacteriophages. Here, we analyze 333 soil metagenomes from five terrestrial habitat types across China and identify 75 viral operational taxonomic units (vOTUs) that encode 105 P-acquisition AMGs. These AMGs span 17 distinct functional genes involved in four primary processes of microbial P-acquisition. Among them, over 60% (11/17) have not been reported previously. We experimentally verify in-vitro enzymatic activities of two pyrophosphatases and one alkaline phosphatase encoded by P-acquisition vOTUs. Thirty-six percent of the 75 P-acquisition vOTUs are detectable in a published global topsoil metagenome dataset. Further analyses reveal that, under certain circumstances, the identified P-acquisition AMGs have a greater influence on soil P availability and are more dominant in soil metatranscriptomes than their corresponding bacterial genes. Overall, our results reinforce the necessity of incorporating viral contributions into biogeochemical P cycling.

Phenotype and function of MAIT cells in patients with alveolar echinococcosis.

Mucosal-associated invariant T (MAIT) cells are a subpopulation of unconventional T cells widely involved in chronic liver diseases. However, the potential role and regulating factors of MAIT cells in alveolar echinococcosis (AE), a zoonotic parasitic disease by Echinococcus multilocularis (E. multilocularis) larvae chronically parasitizing liver organs, has not yet been studied. Blood samples (n=29) and liver specimens (n=10) from AE patients were enrolled. The frequency, phenotype, and function of MAIT cells in peripheral blood and liver tissues of AE patients were detected by flow cytometry. The morphology and fibrosis of liver tissue were examined by histopathology and immunohistochemistry. The correlation between peripheral MAIT cell frequency and serologic markers was assessed by collecting clinicopathologic characteristics of AE patients. And the effect of in vitro stimulation with E. multilocularis antigen (Emp) on MAIT cells. In this study, MAIT cells are decreased in peripheral blood and increased in the close-to-lesion liver tissues, especially in areas of fibrosis. Circulating MAIT exhibited activation and exhaustion phenotypes, and intrahepatic MAIT cells showed increased activation phenotypes with increased IFN-γ and IL-17A, and high expression of CXCR5 chemokine receptor. Furthermore, the frequency of circulating MAIT cells was correlated with the size of the lesions and liver function in patients with AE. After excision of the lesion site, circulating MAIT cells returned to normal levels, and the serum cytokines IL-8, IL-12, and IL-18, associated with MAIT cell activation and apoptosis, were altered. Our results demonstrate the status of MAIT cell distribution, functional phenotype, and migration in peripheral blood and tissues of AE patients, highlighting their potential as biomarkers and therapeutic targets.

Treatment of Coking Wastewater Using Hydrodynamic Cavitation Coupled with Fenton Oxidation Process.

Effective and economical processes for the advanced treatment of coking wastewater were urgently needed to reduce the persistent organic pollutants of external drainage. In the present work, we investigated the degradation of organic pollutants in coking wastewater through IHC/FO (imping stream hydrodynamic cavitation (IHC) coupled with the Fenton oxidation (FO) process) and IHC alone for their feasibility in the advanced treatment of coking wastewater. To select the optimum parameters, attention was paid to the effects of main operation conditions including inlet fluid pressure, medium temperature, initial pH, reaction time, and initial Fe(II) and initial H2O2 concentrations. The results showed that the effects of conditions that need energy to be maintained (such as initial pH and inlet pressure) on the organic pollutant removal efficiency through IHC/FO were less pronounced than those through IHC alone. Moreover, the application of IHC/FO could remove more organic pollutants from coking wastewater than IHC even at an energy-efficient condition. For example, the highest COD removal efficiency of 12.5% was achieved in the IHC treatment at 0.4 MPa, pH 3, and 60 min for the reaction time. In the case of IHC/FO, the maximum COD removal of 33.2% was obtained at pH 7, 0.1 MPa, 12 mmol/L H2O2, and 3 mmol/L Fe2+ after reacting for 15 min. The ultraviolet and visible spectrophotometry (UV-Vis) absorption spectra and gas chromatography and mass spectrometry (GC-MS) analysis further revealed that the kinds and amounts of pollutants (especially those that had benzenes) remaining in water treated through IHC/FO were much fewer and smaller than in water treated through IHC alone. The better performances of IHC/FO than IHC alone were likely related to the more hydroxyl radicals produced through IHC/FO. Taken together, our findings indicate that IHC/FO has great application potential in the advanced treatment of coking wastewater.

Unexpected effect of halogenation on the water solubility of small organic compounds.

Halogenation is an indispensable method in the structural modification of lead compounds. It is known to increase lipophilicity and is hence used to improve membrane permeability and thus bioavailability. In this study, we compare the water solubility (logS) of organohalogen compounds and their non-halogenated parent compounds using the molecular matched pair (MMP) analysis method. Unexpectedly, 19.9% of the compounds increased their water solubility upon halogenation. Iodination was observed to have the greatest effect on solubility, followed by chlorination, bromination, and fluorination. Introducing amino, hydroxyl and carboxyl groups into organohalogens improves their aqueous solubilities, whereas introducing a trifluoromethyl group has the opposite effect. According to our quantum chemical calculations, the increased water solubility upon halogenation is, at least partially, attributed to an increased polarity and polarizability. These results improve our understanding of the influence of halogenation on bioactivity.

Impact of Halogen Bonds on Protein-Peptide Binding and Protein Structural Stability Revealed by Computational Approaches.

Halogen bonds (XBs) are essential noncovalent interactions in molecular recognition and drug design. Current studies on XBs in drug design mainly focus on the interactions between halogenated ligands and target proteins, lacking a systematic study of naturally existing and artificially prepared halogenated residue XBs (hr_XBs) and their characteristics. Here, we conducted a computational study on the potential hr_XBs in proteins/peptides using database searching, quantum mechanics calculations, and molecular dynamics simulations. XBs at the protein-peptide interaction interfaces are found to enhance their binding affinity. Additionally, the formation of intramolecular XBs (intra_XBs) within proteins may significantly contribute to the structural stability of structurally flexible proteins while having a minor impact on proteins with inherently high structural rigidity. Impressively, introducing halogens without the formation of intra_XBs may lead to a decrease in the protein structural stability. This study enriches our understanding of the roles and effects of halogenated residue XBs in biological systems.

D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds.

Continuous exploration of the chemical space of molecules to find ligands with high affinity and specificity for specific targets is an important topic in drug discovery. A focus on cyclic compounds, particularly natural compounds with diverse scaffolds, provides important insights into novel molecular structures for drug design. However, the complexity of their ring structures has hindered the applicability of widely accepted methods and software for the systematic identification and classification of cyclic compounds. Herein, we successfully developed a new method, D3Rings, to identify acyclic, monocyclic, spiro ring, fused and bridged ring, and cage ring compounds, as well as macrocyclic compounds. By using D3Rings, we completed the statistics of cyclic compounds in three different databases, e.g., ChEMBL, DrugBank, and COCONUT. The results demonstrated the richness of ring structures in natural products, especially spiro, macrocycles, and fused and bridged rings. Based on this, three deep generative models, namely, VAE, AAE, and CharRNN, were trained and used to construct two data sets similar to DrugBank and COCONUT but 10 times larger than them. The enlarged data sets were then used to explore the molecular chemical space, focusing on complex ring structures, for novel drug discovery and development. Docking experiments with the newly generated COCONUT-like data set against three SARS-CoV-2 target proteins revealed that an expanded compound database improves molecular docking results. Cyclic structures exhibited the best docking scores among the top-ranked docking molecules. These results suggest the importance of exploring the chemical space of structurally novel cyclic compounds and continuous expansion of the library of drug-like compounds to facilitate the discovery of potent ligands with high binding affinity to specific targets. D3Rings is now freely available at http://www.d3pharma.com/D3Rings/.

Machine learning-assisted serum SERS strategy for rapid and non-invasive screening of early cystic echinococcosis.

Early and accurate diagnosis of cystic echinococcosis (CE) with existing technologies is still challenging. Herein, we proposed a novel strategy based on the combination of label-free serum surface-enhanced Raman scattering (SERS) spectroscopy and machine learning for rapid and non-invasive diagnosis of early-stage CE. Specifically, by establishing early- and middle-stage mouse models, the corresponding CE-infected and normal control serum samples were collected, and silver nanoparticles (AgNPs) were utilized as the substrate to obtain SERS spectra. The early- and middle-stage discriminant models were developed using a support vector machine, with diagnostic accuracies of 91.7% and 95.7%, respectively. Furthermore, by analyzing the serum SERS spectra, some biomarkers that may be related to early CE were found, including purine metabolites and protein-related amide bands, which was consistent with other biochemical studies. Thus, our findings indicate that label-free serum SERS analysis is a potential early-stage CE detection method that is promising for clinical translation.

Strong succession in prokaryotic association networks and community assembly mechanisms in an acid mine drainage-impacted riverine ecosystem.

Acid mine drainage (AMD) serves as an ideal model system for investigating microbial ecology, interaction, and assembly mechanism in natural environments. While previous studies have explored the structure and function of microbial communities in AMD, the succession patterns of microbial association networks and underlying assembly mechanisms during natural attenuation processes remain elusive. Here, we investigated prokaryotic microbial diversity and community assembly along an AMD-impacted river, from the extremely acidic, heavily polluted headwaters to the nearly neutral downstream sites. Microbial diversity was increased along the river, and microbial community composition shifted from acidophile-dominated to freshwater taxa-dominated communities. The complexity and relative modularity of the microbial networks were also increased, indicating greater network stability during succession. Deterministic processes, including abiotic selection of pH and high contents of sulfur and iron, governed community assembly in the headwaters. Although the stochasticity ratio was increased downstream, manganese content, microbial negative cohesion, and relative modularity played important roles in shaping microbial community structure. Overall, this study provides valuable insights into the ecological processes that govern microbial community succession in AMD-impacted riverine ecosystems. These findings have important implications for in-situ remediation of AMD contamination.

In situ enrichment of sulphate-reducing microbial communities with different carbon sources stimulating the acid mine drainage sediments.

The applications of sulphate-reducing microorganisms (SRMs) in acid mine drainage (AMD) treatment systems have received extensive attention due to their ability to reduce sulphate and stabilize metal(loid)s. Despite great phylogenetic diversity of SRMs, only a few have been used in AMD treatment bioreactors. In situ enrichment could be an efficient approach to select new effective SRMs for AMD treatment. Here, we performed in situ enrichment of SRMs in highly stratified AMD sediment cores using different kinds of carbon source mixture. The dsrAB (dissimilatory sulfite reductase) genes affiliated with nine phyla (two archaeal and seven bacterial phyla) and 26 genera were enriched. Remarkably, those genes affiliated with Aciduliprofundum and Vulcanisaeta were enriched in situ in AMD-related environments for the first time, and their relative abundances were negatively correlated with pH. Furthermore, 107 dsrAB-containing metagenome-assembled genomes (MAGs) were recovered from metagenomic datasets, with 14 phyla (two archaeal and 12 bacterial phyla) and 15 genera. The relative abundances of MAGs were positively correlated with total carbon and sulphate contents. Our findings expanded the diversity of SRMs that can be enriched in AMD sediment, and revealed the physiochemical properties that might affect the growth of SRMs, which provided guidance for AMD treatment bioreators.

Protective effect of quercetin on lung epithelial cell bystander-effect in the conditioned medium model of lung cancer metastasis induced by radiation.

To investigate the protective effect of Quercetin (Que) on lung epithelial cells (BEAS-2B) induced bystander effect (RIBE) after heavy ion irradiation of A549 cells. A549 cells were irradiated with 2 Gy X heavy ion rays to obtain a conditioned medium. BEAS-2B was incubated with a conditioned medium or Que. CCK-8 assay was used to screen the optimal effective concentration of Que and detect cell proliferation. Cell number was measured by cell counter and apoptosis rate was measured by flow cytometry. HMGB1 and ROS levels were measured by ELISA. Western blot was used to detect the protein expression of HMGB1, TLR4, p65, Bcl-2, Bax, Caspase3 and Cleaved Caspase3. The growth and proliferation rate of BEAS-2B decreased while the apoptosis rate increased after conditioned medium stimulation, and Que intervention inhibited this effect. The expression of HMGB1 and ROS increased after conditioned medium stimulation, and this effect was inhibited by Que intervention. In addition, the conditioned medium increased the levels of proteins of HMGB1, TLR4, p65, Bax, Caspase3 and Cleaved Caspase 3, and decreased levels of Bcl-2 protein, but Que intervention decreased the levels of HMGB1, TLR4, p65, Bax, Caspase3 and Cleaved Caspase 3proteins, and increased levels of Bcl-2 protein. The RIBE of BEAS-2B induced by irradiation of A549 is associated with HMGB1TLR4/NF-κB signaling pathway in conditioned medium inducing apoptosis by activating ROS, and Que may block RIBE-induced apoptosis by regulating HMGB1/TLR4/NF-κB pathway.

Preferred microenvironments of halogen bonds and hydrogen bonds revealed using statistics and QM/MM calculation studies.

Hydrogen bonds (HBs) and halogen bonds (XBs) are two essential non-covalent interactions for molecular recognition and drug design. As proteins are heterogeneous in structure, the microenvironments of protein structures should have effects on the formation of HBs and XBs with ligands. However, there are no systematic studies reported on this effect to date. For quantitatively describing protein microenvironments, we defined the local hydrophobicities (LHs) and local dielectric constants (LDCs) in this study. With the defined parameters, we conducted an elaborate database survey on the basis of 22 011 ligand-protein structures to explore the microenvironmental preference of HBs (91 966 in total) and XBs (1436 in total). The statistics show that XBs prefer hydrophobic microenvironments compared to HBs. The polar residues like ASP are more likely to form HBs with ligands, while nonpolar residues such as PHE and MET prefer XBs. Both the LHs and LDCs (10.69 ± 4.36 for HBs; 8.86 ± 4.00 for XBs) demonstrate that XBs are prone to hydrophobic microenvironments compared with HBs with significant differences (p < 0.001), indicating that evaluating their strengths in the corresponding environments should be necessary. Quantum Mechanics-Molecular Mechanics (QM/MM) calculations reveal that in comparison with vacuum environments, the interaction energies of HBs and XBs are decreased to varying degrees given different microenvironments. In addition, the strengths of HBs are impaired more than those of XBs when the local dielectric constant's difference between the XB microenvironments and the HB microenvironments is large.

Exogenous Electroactive Microbes Regulate Soil Geochemical Properties and Microbial Communities by Enhancing the Reduction and Transformation of Fe(III) Minerals.

Electroactive microbes can conduct extracellular electron transfer and have the potential to be applied as a bioresource to regulate soil geochemical properties and microbial communities. In this study, we incubated Fe-limited and Fe-enriched farmland soil together with electroactive microbes for 30 days; both soils were incubated with electroactive microbes and a common iron mineral, ferrihydrite. Our results indicated that the exogenous electroactive microbes decreased soil pH, total organic carbon (TOC), and total nitrogen (TN) but increased soil conductivity and promoted Fe(III) reduction. The addition of electroactive microbes also changed the soil microbial community from Firmicutes-dominated to Proteobacteria-dominated. Moreover, the total number of detected microbial species in the soil decreased from over 700 to less than 500. Importantly, the coexistence of N-transforming bacteria, Fe(III)-reducing bacteria and methanogens was also observed with the addition of electroactive microbes in Fe-rich soil, indicating the accelerated interspecies electron transfer of functional microflora.

Rapid detection of cholecystitis by serum fluorescence spectroscopy combined with machine learning.

While cholecystitis is a critical public health problem, the conventional diagnostic methods for its detection are time consuming, expensive and insufficiently sensitive. This study examined the possibility of using serum fluorescence spectroscopy and machine learning for the rapid and accurate identification of patients with cholecystitis. Significant differences were observed between the fluorescence spectral intensities of the serum of cholecystitis patients (n = 74) serum and those of healthy subjects (n = 71) at 455, 480, 485, 515, 625 and 690 nm. The ratios of characteristic fluorescence spectral peak intensities were first calculated, and principal component analysis (PCA)-linear discriminant analysis (LDA) and PCA-support vector machine (SVM) classification models were then constructed using the ratios as variables. Compared with the PCA-LDA model, the PCA-SVM model displayed better diagnostic performance in differentiating cholecystitis patients from healthy subjects, with an overall accuracy of 96.55%. This exploratory study showed that serum fluorescence spectroscopy combined with the PCA-SVM algorithm has significant potential for the development of a rapid cholecystitis screening method.

Label-free surface-enhanced Raman spectroscopy of serum with machine-learning algorithms for gallbladder cancer diagnosis.

Gallbladder cancer (GBC) is a rare but frequently fatal biliary tract malignancy that is typically discovered when it is already advanced. In this study, we investigated a novel technique for the quick and non-invasive diagnosis of GBC based on serum surface-enhanced Raman spectroscopy (SERS). SERS spectra of serum from 41 patients with GBC and 72 normal subjects were recorded. Principal component analysis-linear discriminant analysis (PCA-LDA), and PCA-support vector machine (PCA-SVM), Linear SVM and Gaussian radial basis function-SVM (RBF-SVM) algorithms were used to establish the classification models, respectively. When the Linear SVM was used, the overall diagnostic accuracy for classifying the two groups could achieve 97.1%, and when RBF-SVM was used, the diagnostic sensitivity of GBC was 100%. The results demonstrated that SERS combination with a machine learning algorithm is a promising candidate to be one of the diagnostic tools for GBC in the future.

Rapid detection of serological biomarkers in gallbladder carcinoma using fourier transform infrared spectroscopy combined with machine learning.

Gallbladder cancer (GBC) is the most common malignant tumour of the biliary tract. GBC is difficult to diagnose and treat at an early stage because of the lack of effective serum markers and typical symptoms, resulting in low survival rates. This study aimed to investigate the applicability of dried serum Fourier-transform infrared (FTIR) spectroscopy combined with machine learning algorithms to correctly differentiate patients with GBC from patients with gallbladder disease (GBD), cholangiocarcinoma (CCA), hepatocellular carcinoma (HCC) and healthy individuals. The differentiation between healthy individuals and GBC serum was better using principal component analysis (PCA) and linear discriminant analysis (LDA) for six spectral regions, especially in the protein (1710-1475 cm-1) and combined (1710-1475 + 1354-980 cm-1) region. However, the PCA-LDA model poorly differentiated GBC from GBD, CCA, and HCC in serum spectra. We evaluated the PCA- LDA, PCA-support vector machine (SVM), and radial basis kernel function support vector machine (RBF-SVM) models for GBC diagnosis and found that the RBF-SVM model performed the best, with 88.24-95% accuracy, 95.83% sensitivity, and 78.38-94.44% specificity in the 1710-1475 + 1354-980 cm-1 region. This study demonstrated that serum FTIR spectroscopy combined with the RBF-SVM algorithm has great clinical potential for GBC screening.

Rapid Identification of Benign Gallbladder Diseases Using Serum Surface-Enhanced Raman Spectroscopy Combined with Multivariate Statistical Analysis.

In this study, we looked at the viability of utilizing serum to differentiate between gallbladder (GB) stones and GB polyps using Surface-enhanced Raman spectroscopy (SERS), which has the potential to be a quick and accurate means of diagnosing benign GB diseases. Rapid and label-free SERS was used to conduct the tests on 148 serum samples, which included those from 51 patients with GB stones, 25 patients with GB polyps and 72 healthy persons. We used an Ag colloid as a Raman spectrum enhancement substrate. In addition, we employed orthogonal partial least squares discriminant analysis (OPLS-DA) and principal component linear discriminant analysis (PCA-LDA) to compare and diagnose the serum SERS spectra of GB stones and GB polyps. The diagnostic results showed that the sensitivity, specificity, and area under curve (AUC) values of the GB stones and GB polyps based on OPLS-DA algorithm reached 90.2%, 97.2%, 0.995 and 92.0%, 100%, 0.995, respectively. This study demonstrated an accurate and rapid means of combining serum SERS spectra with OPLS-DA to identify GB stones and GB polyps.

Pharmacological characterization of the small molecule 03A10 as an inhibitor of α-synuclein aggregation for Parkinson's disease treatment.

Aggregation of α-synuclein, a component of Lewy bodies (LBs) or Lewy neurites in Parkinson's disease (PD), is strongly linked with disease development, making it an attractive therapeutic target. Inhibiting aggregation can slow or prevent the neurodegenerative process. However, the bottleneck towards achieving this goal is the lack of such inhibitors. In the current study, we established a high-throughput screening platform to identify candidate compounds for preventing the aggregation of α-synuclein among the natural products in our in-house compound library. We found that a small molecule, 03A10, i.e., (+)-desdimethylpinoresinol, which is present in the fruits of Vernicia fordii (Euphorbiaceae), modulated aggregated α-synuclein, but not monomeric α-synuclein, to prevent further elongation of α-synuclein fibrils. In α-synuclein-overexpressing cell lines, 03A10 (10 µM) efficiently prevented α-synuclein aggregation and markedly ameliorated the cellular toxicity of α-synuclein fibril seeds. In the MPTP/probenecid (MPTP/p) mouse model, oral administration of 03A10 (0.3 mg· kg-1 ·d-1, 1 mg ·kg-1 ·d-1, for 35 days) significantly alleviated behavioral deficits, tyrosine hydroxylase (TH) neuron degeneration and p-α-synuclein aggregation in the substantia nigra (SN). As the Braak hypothesis postulates that the prevailing site of early PD pathology is the gastrointestinal tract, we inoculated α-synuclein preformed fibrils (PFFs) into the mouse colon. We demonstrated that α-synuclein PFF inoculation promoted α-synuclein pathology and neuroinflammation in the gut and brain; oral administration of 03A10 (5 mg· kg-1 ·d-1, for 4 months) significantly attenuated olfactory deficits, α-synuclein accumulation and neuroinflammation in the olfactory bulb and SN. We conclude that 03A10 might be a promising drug candidate for the treatment of PD. 03A10 might be a novel drug candidate for PD treatment, as it inhibits α-synuclein aggregation by modulating aggregated α-synuclein rather than monomeric α-synuclein to prevent further elongation of α-synuclein fibrils and prevent α-synuclein toxicity in vitro, in an MPTP/p mouse model, and PFF-inoculated mice.

Diverse Methylmercury (MeHg) Producers and Degraders Inhabit Acid Mine Drainage Sediments, but Few Taxa Correlate with MeHg Accumulation.

Methylmercury (MeHg) is a notorious neurotoxin, and its production and degradation in the environment are mainly driven by microorganisms. A variety of microbial MeHg producers carrying the gene pair hgcAB and degraders carrying the merB gene have been separately reported in recent studies. However, surprisingly little attention has been paid to the simultaneous investigation of the diversities of microbial MeHg producers and degraders in a given habitat, and no studies have been performed to explore to what extent these two contrasting microbial groups correlate with MeHg accumulation in the habitat of interest. Here, we collected 86 acid mine drainage (AMD) sediments from an area spanning approximately 500,000 km2 in southern China and profiled the sediment-borne putative MeHg producers and degraders using genome-resolved metagenomics. 46 metagenome-assembled genomes (MAGs) containing hgcAB and 93 MAGs containing merB were obtained, including those from various taxa without previously known MeHg-metabolizing microorganisms. These diverse MeHg-metabolizing MAGs were formed largely via multiple independent horizontal gene transfer (HGT) events. The putative MeHg producers from Deltaproteobacteria and Firmicutes as well as MeHg degraders from Acidithiobacillia were closely correlated with MeHg accumulation in the sediments. Furthermore, these three taxa, in combination with two abiotic factors, explained over 60% of the variance in MeHg accumulation. Most of the members of these taxa were characterized by their metabolic potential for nitrogen fixation and copper tolerance. Overall, these findings improve our understanding of the ecology of MeHg-metabolizing microorganisms and likely have implications for the development of management strategies for the reduction of MeHg accumulation in the AMD sediments. IMPORTANCE Microorganisms are the main drivers of MeHg production and degradation in the environment. However, little attention has been paid to the simultaneous investigation of the diversities of microbial MeHg producers and degraders in a given habitat. We used genome-resolved metagenomics to reveal the vast phylogenetic and metabolic diversities of putative MeHg producers and degraders in AMD sediments. Our results show that the diversity of MeHg-metabolizing microorganisms (particularly MeHg degraders) in AMD sediments is much higher than was previously recognized. Via multiple linear regression analysis, we identified both microbial and abiotic factors affecting MeHg accumulation in AMD sediments. Despite their great diversity, only a few taxa of MeHg-metabolizing microorganisms were closely correlated with MeHg accumulation. This work underscores the importance of using genome-resolved metagenomics to survey MeHg-metabolizing microorganisms and provides a framework for the illumination of the microbial basis of MeHg accumulation via the characterization of physicochemical properties, MeHg-metabolizing microorganisms, and the correlations between them.

Subcutaneous infection mouse model could be applied into real time monitoring the efficacy of anti-cystic echinococcosis drug in vivo.

Cystic echinococcosis (CE) is a zoonotic parasitic disease with a cosmopolitan distribution, and it is urgent to develop novel anti-helminthic agents. The intraperitoneal (ip) infection mice model was widely used to evaluate the efficacy of potential anti-CE compounds. Still, it's time-consuming, and the inability to achieve real-time monitoring hinders the development of potential anti-CE compounds. In this study, a CE mouse model was established by subcutaneous (sc) injection of protoscoleces of Echinococcus granulosus sensu stricto (E.granulosus s.s.) and used to assess the efficiency and efficacy of prospective anti-CE drugs. Compared to the ip infection CE mice model, the lesion volume of sc infection protoscoleces of E.granulosus s.s. (EgPSCs) could be measured by vernier caliper at week 6 post-infection. In contrast, the lesion volume of ip infection CE mice model was detected by ultrasound-assisted diagnosis at week 16 post-infection. Oral administration of albendazole (ABZ) could reduce cystic weight by 32.17% and 17.61%, the cystic number by 12.24% and 25.19%, and damage the ultrastructure of the cysts of E. granulosus s.s. in the sc and ip infection group, respectively. Furthermore, we found that the sc infection mice model could real-time monitor the lesion volume of E. granulosus s.s. during the ABZ and everolimus treatment. Therefore, we consider that the sc infection CE mice model is an assistant tool for screening and developing potential anti-CE compounds.

Phytostabilization mitigates antibiotic resistance gene enrichment in a copper mine tailings pond.

Mining-impacted environments are distributed globally and have become increasingly recognized as hotspots of antibiotic resistance genes (ARGs). However, there are currently no reports on treatment technologies to deal with such an important environmental problem. To narrow this knowledge gap, we implemented a phytostabilization project in an acidic copper mine tailings pond and employed metagenomics to explore ARG characteristics in the soil samples. Our results showed that phytostabilization decreased the total ARG abundance in 0-10 cm soil layer by 75 %, which was companied by a significant decrease in ARG mobility, and a significant increase in ARG diversity and microbial diversity. Phytostabilization was also found to drastically alter the ARG host composition and to significantly reduce the total abundance of virulence factor genes of ARG hosts. Soil nutrient status, heavy metal toxicity and SO42- concentration were important physicochemical factors to affect the total ARG abundance, while causal mediation analysis showed that their effects were largely mediated by the changes in ARG mobility and microbial diversity. The increase in ARG diversity associated with phytostabilization was mainly mediated by a small subgroup of ARG hosts, most of which could not be classified at the genus level and deserve further research in the future.