Metagenomics-resolved genomics provide novel ecological insights into resistome community coalescence of wastewater in river environment.

The discharge of wastewater into rivers can lead to resistome coalescence, thereby enhancing the spread risk of antibiotic resistance genes (ARGs) through mixing of exogenous wastewater resistome communities with indigenous riverine communities. At present, the understanding on the role of resistome community coalescence in the dissemination of ARGs is still very limited, and little is known about the process and its ecological implications. To bridge the gap, this study has conducted field-based surveys and microcosm experiments to deeply dissect the coalescence of resistome community in wastewater within river environment, utilizing genome-centric metagenomic analysis approach.

Metagenomics-assembled analysis revealed the characteristics of antibiotic resistome and community coalescence in the soils irrigated with different irrigation materials.

Antibiotic resistance has received widespread attention in recent years. Soil irrigation and fertilization are routine agricultural practices, but also lead to the spread of antibiotic resistance genes (ARGs) in soil-crop system such as via resistome coalescence. Despite community coalescence being ubiquitous and important in natural ecosystems, little research has been done to investigate resistome coalescence during soil irrigation activities.

An integrated multimedia fate modeling framework for identifying mitigation strategy of antibiotic ecological risks: A case study in a peri-urban river.

Antibiotics have been heavily used over the past decades, resulting in their frequent detections in rivers and increasing ecological risks. Recognizing characteristics of antibiotic ecological risks (AERs) and making effective strategies to mitigate the AERs are essential to ensure the safety of aquatic ecosystem and public health. In this study, an integrated technological framework has been proposed toward identifying management options for reducing AERs by jointly utilizing multimedia fugacity modelling and ecotoxicological risk assessment, and applied to characterize the AERs in a peri-urban river in Beijing.

Microcosm experiments revealed resistome coalescence of sewage treatment plant effluents in river environment.

Sewage treatment plant (STP) effluents are important contributors of antibiotic resistance (AR) pollution in rivers. Effluent discharging into rivers causes resistome coalescence. However, their mechanisms and dynamic processes are poorly understood, especially for the effects of dilution, diffusion, and sunlight-induced attenuation on coalescence.

Meta-analysis addressing the characterization and risk identification of antibiotics and antibiotic resistance genes in global groundwater.

Antimicrobial resistance (AMR) is one of the significant global issues to public health. Compared to other aquatic environments, research on AMR in groundwater is scarce. In the study, a meta-analysis was conducted to explore the characteristics and risks of antibiotics and antibiotic resistance genes (ARGs) in global groundwater, using a data set of antibiotic concentrations collected from publications during 2000-2021 and a large-scale metagenomes of groundwater samples (n = 330).

Spectroscopic Characteristics and Speciation Distribution of Fe(III) Binding to Molecular Weight-Dependent Standard Pahokee Peat Fulvic Acid.

Peat-derived organic matter, as powerful chelators, is of great significance for the transport of Fe to the ocean and the enhancement of dissolved Fe. However, the iron binding capacity of molecular weight (MW)-fractionated dissolved organic matter is variable, due to its structure and composition heterogeneity. In this work, we used the standard Pahokee Peat fulvic acid (PPFA) as an example, and investigated the spectroscopy properties and Fe(III) binding ability of PPFA and different molecular weight fractions by UV−Vis absorbance and fluorescence spectroscopy and the Donnan Membrane Technique (DMT).

Effects on microbiomes and resistomes and the source-specific ecological risks of heavy metals in the sediments of an urban river.

This study aims to better understand the effects of heavy metal enrichment on microbiomes and resistomes and the source-specific ecological risks of metals in the sediments of an urban river. Geo-accumulation index and enrichment factor suggested the river sediments were contaminated by Cd, Cu, Pb, and Zn in varying degrees. High-throughput sequencing-based metagenomics analysis identified 430 types of antibiotic resistance genes (ARGs), dominated by the multidrug, MLS, bacitracin, quinolone, and aminoglycoside ARGs, and 52 metal resistance genes (MRGs) mainly conferring resistance to zinc, copper, cadmium, lead, mercury and multiple metals.

TDCPP mimics thyroid hormones associated with the activation of integrin αβ and ERK1/2.

Tri(1,3-dichloropropyl) phosphate (TDCPP) potentially damages the thyroid system in humans and animals. However, knowledge of its toxic effects and underlying mechanisms is limited. The present study was conducted to determine the thyroid hormone-disrupting effects of TDCPP and its major metabolite, bis(1,3-dichloro-2-propyl) phosphate (BDCPP) in rat pituitary cell lines (GH3).

Characterization and source identification of antibiotic resistance genes in the sediments of an interconnected river-lake system.

Antimicrobial resistance has been a global public health concern. The river-lake systems are one of the tightly connected terrestrial ecosystems and, appear to be reservoirs of antibiotic resistant genes (ARGs) and dispersal routes of resistant pathogens because they are easily impacted by human activities. Currently, systematic knowledge on the prevalence, transfer risk and source of ARGs in river-lake systems is largely lacking.

Characterization and source apportionment of heavy metals in the sediments of Lake Tai (China) and its surrounding soils.

Heavy metals (HMs) in lake sediments have aroused long-term attention due to their persistent threat to the lake ecosystems. Study into the pollution characteristics and potential sources of HMs in lakes, especially those heavily influenced by human activities, can give some insights to prevent and control the environmental risks of HMs. Lake Tai is the China's third largest freshwater lake but has been a drastic example of water pollution in recent decades.

Current status and associated human health risk of vanadium in soil in China.

A detailed assessment of vanadium contamination characteristics in China was conducted based on the first national soil pollution survey. The map overlay analysis was used to evaluate the contamination level of vanadium and the non-carcinogenic risk assessment model was calculated to quantify the vanadium exposure risks to human health. The results showed that, due to the drastically increased mining and smelting activities, 26.

Tracing Sources and Contamination Assessments of Heavy Metals in Road and Foliar Dusts in a Typical Mining City, China.

Road and foliar dust samples from four land-use districts of Panzhihua City, a famous V-Ti magnetite production area of China, were collected to investigate the sources and distribution characteristics of 9 heavy metals (V, Pb, Cd, Cu, Zn, Ni, Cr, Fe, and Mn). The results suggest that foliar samples had smaller particle size and higher heavy metal contents than road dusts. The contamination assessments of heavy metals were as follows: Pb and V (significant enrichment) > Zn, Ni, Cr, Fe, and Mn (moderate enrichment) > Cd and Ni (minimal enrichment).

Distribution, bioavailability, and potential ecological risk of Cu, Pb, and Zn in soil in a potential groundwater source area.

In this study, we examined three horizontal and vertical soil profiles along a sewage drainage ditch in order to determine the spatial distribution of Cu, Pb, and Zn in soils and to assess the bioavailability and potential ecological risks associated with these metals in a potential groundwater source area. Results showed that the concentrations of Cu, Pb, and Zn were approximately at background level, suggesting that human activities (industrial and agricultural pollution) had a negligible influence on these metals in soil, and that the concentrations reflected the natural background levels in the study area. Cu, Pb, and Zn concentrations were slightly higher in topsoil (0-20 cm) than deeper in the soil profile.

Total petroleum hydrocarbon distribution in soils and groundwater in Songyuan oilfield, Northeast China.

In order to investigate the distribution of the total petroleum hydrocarbons (TPH) in groundwater and soil, a total of 71 groundwater samples (26 unconfined groundwater samples, 37 confined groundwater samples, and 8 deeper confined groundwater samples) and 80 soil samples were collected in the Songyuan oilfield, Northeast China, and the vertical variation and spatial variability of TPH in groundwater and soil were assessed. For the groundwater from the unconfined aquifer, petroleum hydrocarbons were not detected in three samples, and for the other 23 samples, concentrations were in the range 0.01-1.

Characterization and source apportionment of water pollution in Jinjiang River, China.

Characterizing water quality and identifying potential pollution sources could greatly improve our knowledge about human impacts on the river ecosystem. In this study, fuzzy comprehensive assessment (FCA), pollution index (PI), principal component analysis (PCA), and absolute principal component score-multiple linear regression (APCS-MLR) were combined to obtain a deeper understanding of temporal-spatial characterization and sources of water pollution with a case study of the Jinjiang River, China. Measurement data were obtained with 17 water quality variables from 20 sampling sites in the December 2010 (withered water period) and June 2011 (high flow period).

Source apportionment of sediment PAHs in the Pearl River Delta region (China) using nonnegative matrix factorization analysis with effective weighted variance solution.

Considering the advantages and limitations of a single receptor model, in this study, a combined technique of nonnegative matrix factorization analysis with effective weighted variance solution (NMF-EWV) was proposed for source apportionment. Utilizing NMF, major linear independent factor loadings with nonnegative elements were extracted to identify potential pollution sources. Then, these physical reasonable factor loadings were regarded as source profiles to apportion contributions using effective weighted variance solutions.

Source apportionment of trace element pollution in surface sediments using positive matrix factorization combined support vector machines: application to the Jinjiang River, China.

In this study, a method of positive matrix factorization (PMF) combined support vector machines (SVMs) was adopted to identify possible sources and apportion contributions for trace element pollution in surface sediments from the Jinjiang River, Southeastern China. Utilizing diagnostics tools, four significant factors were extracted from sediment samplers, which were collected in December 2010 at 15 different sites. By treating source identification as a pattern recognition problem, the factor loadings derived from PMF were classified by SVM classifiers which have been trained and validated with fingerprints of eight potential source categories.

Bioavailability of vanadium extracted by EDTA, HCl, HOAC, and NaNO3 in topsoil in the Panzhihua urban park, located in southwest China.

Bioavailable vanadium was evaluated on the basis of soil vanadium single-extraction with ethylenediaminetetraacetic acid (EDTA), hydrochloric acid (HCl), acetic acid (HOAc), and sodium nitrate (NaNO(3)) in Panzhihua urban park. The soil vanadium concentration extracted by HOAc was 0.01-2.