Pharmaceutical and Antibiotic Environmental Impacts

This study evaluates how micropollutants, especially antibiotics, affect bacterial communities in different environmental compartments of a river basin, showing reduced diversity and altered functional capabilities in polluted sites.

MetaCompare 2.0 differentiates human health and ecological resistome risks using metagenomic data, showing higher risk scores for human-contaminated environments.

The paper identifies a novel sulfatase in Shinella strains for acesulfame degradation in wastewater and traces its recent emergence in global wastewater treatment systems.

This study investigates the effects of treated wastewater on stream biofilm resistomes, identifying a new planctomycete beta-lactamase that is functionally active despite low sequence similarity to known ARGs.

This study uses sewage metagenomics to distinguish seasonal, human-derived, and environmental microbial communities, offering potential for improved AMR surveillance.

This study compares culture-based and ddPCR methods for detecting carbapenem-resistant bacteria in wastewater, finding weak correlations between quantitative results due to method sensitivity and specificity differences.

The paper detects pharmaceutical contaminants in amphipods of Lake Baikal using HPLC-MS, identifying multiple active ingredients and their annual loads.

This study investigates how zooplankton grazing affects the persistence of the intI1 gene in lake water, showing its association with aggregated microbial communities and vulnerability to grazing.

The paper presents a dataset of emerging contaminants in various water and sediment samples from Chile's central and southern coast, highlighting urban and aquaculture impacts.

This study uses stable isotopes and nanoSIMS to show soil bacteria on plastics can assimilate sulfamethoxazole, revealing their role in soil ecosystems.

This study examines how ginger and soil microbes respond to combined chromium and ofloxacin pollution, revealing hormesis effects, microbial shifts, and risks in the food chain.

This study evaluates how composting and storage affect the microbiome and resistome of cattle manure, finding both methods reduce antibiotic resistance genes but with varying impacts on different gene types.

This study identifies substrate promiscuity in DEET hydrolases from stream biofilms exposed to treated wastewater, showing broad enzymatic activity across multiple contaminants.

The paper shows that pollutome complexity drives biodegradation of recalcitrant pharmaceuticals through microbial community shifts and high-order interactions.

The paper validates a workflow for detecting antibiotic residues and measuring water chemistry in hospital sink samples, and confirms boric acid preserves microbial and resistome composition for metagenomic sequencing.

The paper validates and applies intI1 primer sets for quantifying gene abundance in septic tanks, finding no significant difference between primer sets but highlighting the importance of primer choice for accurate environmental monitoring.

The paper uses machine learning to predict plasmid permissiveness in wastewater microbiomes from 16S rDNA sequences, showing moderate-to-strong correlations with experimental data.

This paper presents a CRISPR-Cas-based system called VADER for degrading antibiotic resistance genes (ARGs) in environmental biotechnology, achieving 100% ARG elimination in a prototype reactor.

This study surveys the resistome in 350 Canadian lakes to assess how human and veterinary antibiotic use affects antibiotic resistance gene diversity.

MagnaExtract is a magnetic bead-based DNA extraction method for detecting antimicrobial resistance genes in river water, showing comparable or better performance than commercial kits and crude methods.

The paper identifies antimicrobial resistance genes in silage samples and finds that many are mobile, suggesting silage as a potential source of resistance in the food chain.

The paper analyzes gut metagenomes from pigs to investigate co-occurrence patterns of antibiotic resistance genes (ARGs) with metal and biocide resistance genes, finding non-random phylogenetic associations.

This study uses machine learning to analyze metagenomic data from the TARA Oceans project to identify and characterize antibiotic resistance genes (ARGs) in marine environments, revealing their abundance, distribution, and potential for horizontal gene transfer.

The paper uses metagenomics to analyze urban beach and sewage waters in Montevideo, finding distinct bacterial communities and antibiotic resistance genes in sewage.

The paper characterizes the genomic diversity of multi-drug resistant Escherichia coli in wastewater, finding high genetic variation and resistance/virulence genes.