TGC-ARG: Anticipating Antibiotic Resistance via Transformer-Based Modeling and Contrastive Learning.

In various domains, including everyday activities, agricultural practices, and medical treatments, the escalating challenge of antibiotic resistance poses a significant concern. Traditional approaches to studying antibiotic resistance genes (ARGs) often require substantial time and effort and are limited in accuracy. Moreover, the decentralized nature of existing data repositories complicates comprehensive analysis of antibiotic resistance gene sequences. In this study, we introduce a novel computational framework named TGC-ARG designed to predict potential ARGs. This framework takes protein sequences as input, utilizes SCRATCH-1D for protein secondary structure prediction, and employs feature extraction techniques to derive distinctive features from both sequence and structural data. Subsequently, a Siamese network is employed to foster a contrastive learning environment, enhancing the model's ability to effectively represent the data. Finally, a multi-layer perceptron (MLP) integrates and processes sequence embeddings alongside predicted secondary structure embeddings to forecast ARG presence. To evaluate our approach, we curated a pioneering open dataset termed ARSS (Antibiotic Resistance Sequence Statistics). Comprehensive comparative experiments demonstrate that our method surpasses current state-of-the-art methodologies. Additionally, through detailed case studies, we illustrate the efficacy of our approach in predicting potential ARGs.

Transmission of human-pet antibiotic resistance via aerosols in pet hospitals of Changchun.

In recent years, aerosols have been recognized as a prominent medium for the transmission of antibiotic-resistant bacteria and genes. Among these, particles with a particle size of 2 µm (PM2.5) can directly penetrate the alveoli. However, the presence of antibiotic-resistant genes in aerosols from pet hospitals and the potential risks posed by antibiotic-resistant bacteria in these aerosols to humans and animals need to be investigated. In this study, cefotaxime-resistant bacteria were collected from 5 representative pet hospitals in Changchun using a Six-Stage Andersen Cascade Impactor. The distribution of bacteria in each stage was analyzed, and bacteria from stage 5 and 6 were isolated and identified. Minimal inhibitory concentrations of isolates against 12 antimicrobials were determined using broth microdilution method. Quantitative Polymerase Chain Reaction was employed to detect resistance genes and mobile genetic elements that could facilitate resistance spread. The results indicated that ARBs were enriched in stage 5 (1.1-2.1 µm) and stage 3 (3.3-4.7 µm) of the sampler. A total of 159 isolates were collected from stage 5 and 6. Among these isolates, the genera Enterococcus spp. (51%), Staphylococcus spp. (19%), and Bacillus spp. (14%) were the most prevalent. The isolates exhibited the highest resistance to tetracycline and the lowest resistance to cefquinome. Furthermore, 56 (73%) isolates were multidrug-resistant. Quantitative PCR revealed the expression of 165 genes in these isolates, with mobile genetic elements showing the highest expression levels. In conclusion, PM2.5 from pet hospitals harbor a significant number of antibiotic-resistant bacteria and carry mobile genetic elements, posing a potential risk for alveolar infections and the dissemination of antibiotic resistance genes.

Microbial communities, antibiotic resistance genes, and virulence factors in urinary infectious stone-associated urinary tract infections.

Urinary infectious stones are challenging due to bacterial involvement, necessitating a comprehensive understanding of these conditions. Antibiotic-resistant urease-producing bacteria further complicate clinical management. In this study, analysis of urine and stone samples from urinary tract infection (UTI) patients revealed microbial shifts, gene enrichment in stones, and metabolic pathway disparities; antibiotic resistance gene trends were phylum-specific, urease-producing bacteria are at risk of acquiring AMR carried by Enterobacteriaceae under antibiotic, emphasizing potential AMR dissemination between them; Correlations of key pathogenic species in kidney stone and urine microbial communities highlight the need for targeted therapeutic strategies to manage complexities in UTIs; Stones and urine contain a variety of deleterious genes even before antibiotic use, and piperacillin/tazobactam better reduced the abundance of antibiotic resistance genes in stones and urine. The presence of diverse antibiotic resistance and virulence genes underscores challenges in clinical management and emphasizes the need for effective treatment strategies to mitigate risks associated with UTIs and urinary infectious stone formation. Ongoing research is vital for advancing knowledge and developing innovative approaches to address these urological conditions.

Mechanism of self-supporting montmorillonite composite material for bio-enhanced degradation of chlorotetracycline: Electron transfer and microbial response.

The efficient degradation of antibiotics holds significant implications for mitigating environmental pollution. This study synthesized a montmorillonite chitosan composite material (MMT-CS) using the gel template method. Subsequently, a bio-enhanced reactor was constructed to facilitate the degradation of chlorotetracycline (CTC). The addition of MMT-CS composite material enables the degradation of different concentrations of CTC. MMT-CS, a conductive carrier, effectively promotes microbial adhesion and boosts the metabolic activity of functional microorganisms. Additionally, it facilitates the maintenance of microbial activity under CTC pressure by promoting the secretion of extracellular polymeric substances, increasing critical enzyme activity, and enhancing the electron transfer capacity within the system. In this MMT-CS bio-enhanced process, Paracoccus (11.4%) and Bacillus (3.9%) are utilized as essential bacteria genes. The results of metabolic pathways prediction indicated significant enhancements in membrane-transport, nucleotide-metabolism, replication-repair, and lipid-metabolism. Thus, the developed self-supporting MMT-CS bio-enhanced process ensured the stability of the system during the removal of antibiotics.

A panoramic view of the virosphere in three wastewater treatment plants by integrating viral-like particle-concentrated and traditional non-concentrated metagenomic approaches.

Wastewater biotreatment systems harbor a rich diversity of microorganisms, and the effectiveness of biotreatment systems largely depends on the activity of these microorganisms. Specifically, viruses play a crucial role in altering microbial behavior and metabolic processes throughout their infection phases, an aspect that has recently attracted considerable interest. Two metagenomic approaches, viral-like particle-concentrated (VPC, representing free viral-like particles) and non-concentrated (NC, representing the cellular fraction), were employed to assess their efficacy in revealing virome characteristics, including taxonomy, diversity, host interactions, lifestyle, dynamics, and functional genes across processing units of three wastewater treatment plants (WWTPs). Our findings indicate that each approach offers unique insights into the viral community and functional composition. Their combined use proved effective in elucidating WWTP viromes. We identified nearly 50,000 viral contigs, with Cressdnaviricota and Uroviricota being the predominant phyla in the VPC and NC fractions, respectively. Notably, two pathogenic viral families, Asfarviridae and Adenoviridae, were commonly found in these WWTPs. We also observed significant differences in the viromes of WWTPs processing different types of wastewater. Additionally, various phage-derived auxiliary metabolic genes (AMGs) were active at the RNA level, contributing to the metabolism of the microbial community, particularly in carbon, sulfur, and phosphorus cycling. Moreover, we identified 29 virus-carried antibiotic resistance genes (ARGs) with potential for host transfer, highlighting the role of viruses in spreading ARGs in the environment. Overall, this study provides a detailed and integrated view of the virosphere in three WWTPs through the application of VPC and NC metagenomic approaches. Our findings enhance the understanding of viral communities, offering valuable insights for optimizing the operation and regulation of wastewater treatment systems.

Unraveling the determinants of antibiotic resistance evolution in farmland under fertilizations.

Organic fertilization is a major driver potentiating soil antibiotic resistance in farmland. However, it remains unclear how bacterial antibiotic resistance evolves in fertilized soils and even spreads to crops. Compared with no fertilizer and commercial fertilizer treatments, organic fertilizers markedly increased the abundance of soil antibiotic resistance genes (ARGs) but the relatively weaker transfer of resistance genes from soil to crops. The introduction of organic fertilizers enriches the soil with nutrients, driving indigenous microorganisms towards a K-strategy. The pH, EC, and nutrients as key drivers influenced the ARGs abundance. The neutral (pH 7.2), low salt (TDS 1.4 %) and mesotrophic (carbon content 3.54 g/L) habitats similar to the soil environment conditioned by organic fertilizers. These environmental conditions clearly prolonged the persistence of resistant plasmids, and facilitated their dissemination to massive conjugators soil microbiome but not to plant endophytes. This suggested that organic fertilizers inhibited the spread of ARGs to crops. Moreover, the composition of conjugators showed differential selection of resistant plasmids by endophytes under these conditions. This study sheds light on the evolution and dissemination of antibiotic resistance in farmlands and can aid in the development of antimicrobial resistance control strategies in agriculture.

Streambed immobilization controls the transport of antibiotic resistance genes in flowing water.

Antibiotic resistance is a serious global health issue, resulting in at least 1.2 million deaths in 2019. The environment is a potentially important reservoir of antibiotic resistance; however, the fate of Antibiotic Resistance Genes (ARGs) in the environment remains poorly characterized. One important environmental source of ARGs is manure used as a soil amendment. ARGs from manure may then enter nearby flowing waterbodies, where the factors governing their downstream transport remain unknown. To address this, we conducted experiments by spiking cattle manure in an artificial stream to estimate removal rates (k; m-1) for three ARGs (mefA, tetQ, and tetW) and a ruminant fecal marker (bacR). We then used a Stochastic Mobile-Immobile Model (SMIM) to separate the overall removal into two components, rs, and rh, corresponding to immobilizations in the surface (i.e., water column) and subsurface (i.e., streambed), respectively. Finally, we applied the SMIM across four model streams to predict the downstream travel distance of ARGs and bacR. Our results showed measurable removal for all targets in all experimental replicates (n = 3) and no differences were found in the removal rates among replicates for any target (ANCOVA; p > 0.05). We found that the removal of bacR was significantly lower than tetW (p < 0.05) and slightly lower than mefA (p = 0.088), while tetQ removal was slightly different from tetW's (p = 0.072). We also found that rh values were orders of magnitude larger than rs for ARGs and bacR (t-test; p < 0.05). These findings suggest that ARGs and bacR are being removed from the water column through immobilization reactions occurring in the streambed. Additionally, we predicted that the 90 % removal (or D90) of targets occurs within the first 500 m in all model streams except in a slow-flow pastoral stream, which required 1400 m of downstream transport for 90 % removal. Our findings and model stand out as promising tools to predict the fate of ARGs in streams and will contribute to improving and managing agricultural practices that employ animal manure.

Rapid inference of antibiotic resistance and susceptibility for Klebsiella pneumoniae by clinical shotgun metagenomic sequencing.

OBJECTIVES: The study aimed to develop a genotypic antimicrobial resistance testing method for Klebsiella pneumoniae using metagenomic sequencing data. METHODS: We utilized Lasso regression on assembled genomes to identify genetic resistance determinants for six antibiotics (Gentamicin, Tobramycin, Imipenem, Meropenem, Ceftazidime, Trimethoprim/Sulfamethoxazole). The genetic features were weighted, grouped into clusters to establish classifier models. Origin species of detected antibiotic resistant gene (ARG) was determined by novel strategy integrating "possible species," "gene copy number calculation" and "species-specific kmers." The performance of the method was evaluated on retrospective case studies. RESULTS: Our study employed machine learning on 3928 K. pneumoniae isolates, yielding stable models with AUCs > 0.9 for various antibiotics. GenseqAMR, a read-based software, exhibited high accuracy (AUC 0.926-0.956) for short-read datasets. The integration of a species-specific kmer strategy significantly improved ARG-species attribution to an average accuracy of 96.67%. In a retrospective study of 191 K. pneumoniae-positive clinical specimens (0.68-93.39% genome coverage), GenseqAMR predicted 84.23% of AST results on average. It demonstrated 88.76-96.26% accuracy for resistance prediction, offering genotypic AST results with a shorter turnaround time (mean ± SD: 18.34 ± 0.87 hours) than traditional culture-based AST (60.15 ± 21.58 hours). Furthermore, a retrospective clinical case study involving 63 cases showed that GenseqAMR could lead to changes in clinical treatment for 24 (38.10%) cases, with 95.83% (23/24) of these changes deemed beneficial. CONCLUSIONS: In conclusion, GenseqAMR is a promising tool for quick and accurate AMR prediction in Klebsiella pneumoniae, with the potential to improve patient outcomes through timely adjustments in antibiotic treatment.

Tracking the impact of perfluoroalkyl acid emissions on antibiotic resistance gene profiles in receiving water by metagenomic analysis.

The ecological risks posed by perfluoroalkyl acids (PFAAs) to the aquatic environment have recently been of great concern. However, little information was available on the impact of PFAAs on antibiotic resistance genes (ARGs) profiles. In this study, the receiving river of the largest fluoropolymer production facility in China was selected to investigate the effects of PFAAs on ARGs profiles. The highest PFAAs concentration for water samples near the industrial effluent discharge point was 310.9 µg/L, which was thousands times of higher than the average concentration collected at upstream sites. Perfluorooctanoic acid accounted for more than 67.2 % of ∑PFAAs concentration in water samples collected at the downstream sites, followed by perfluorohexanoic acid (3.6 %-15.9 %). 145 ARG subtypes including high-risk ARGs were detected by metagenomic technology. The results indicated that the discharge of PFAA-containing effluents had a significant impact on the abundance and diversity of ARGs in receiving waters, and PFAAs and water quality parameters (e.g., pH, NH3N, CODMn, TP) could largely affect ARG profiles. Specifically, short-chain PFAAs had similar impacts on ARG profiles compared to the restricted long-chain PFAAs. This study confirmed the potential effects of PFAAs on ARGs in aquatic environment and provided more insights into the ecological risk raised by PFAAs.

Assessing Antibiotic-Resistant Genes in University Dormitory Washing Machines.

University dormitories represent densely populated environments, and washing machines are potential sites for the spread of bacteria and microbes. However, the extent of antibiotic resistance gene (ARG) variation in washing machines within university dormitories and their potential health risks are largely unknown. To disclose the occurrence of ARGs and antibiotic-resistant bacteria from university dormitories, we collected samples from washing machines in 10 dormitories and used metagenomic sequencing technology to determine microbial and ARG abundance. Our results showed abundant microbial diversity, with Proteobacteria being the dominant microorganism that harbors many ARGs. The majority of the existing ARGs were associated with antibiotic target alteration and efflux, conferring multidrug resistance. We identified tnpA and IS91 as the most abundant mobile genetic elements (MGEs) in washing machines and found that Micavibrio aeruginosavorus, Aquincola tertiaricarbonis, and Mycolicibacterium iranicum had high levels of ARGs. Our study highlights the potential transmission of pathogens from washing machines to humans and the surrounding environment. Pollution in washing machines poses a severe threat to public health and demands attention. Therefore, it is crucial to explore effective methods for reducing the reproduction of multidrug resistance.

Comprehensive Assessment of Multidrug-Resistant and Extraintestinal Pathogenic Escherichia coli in Wastewater Treatment Plant Effluents.

Multidrug-resistant (MDR) Escherichia coli poses a significant threat to public health, contributing to elevated rates of morbidity, mortality, and economic burden. This study focused on investigating the antibiotic resistance profiles, resistance and virulence gene distributions, biofilm formation capabilities, and sequence types of E. coli strains resistant to six or more antibiotic classes. Among 918 strains isolated from 33 wastewater treatment plants (WWTPs), 53.6% (492/918) demonstrated resistance, 32.5% (298/918) were MDR, and over 8% (74/918) were resistant to six or more antibiotic classes, exhibiting complete resistance to ampicillin and over 90% to sulfisoxazole, nalidixic acid, and tetracycline. Key resistance genes identified included sul2, blaTEM, tetA, strA, strB, and fimH as the predominant virulence genes linked to cell adhesion but limited biofilm formation; 69% showed no biofilm formation, and approximately 3% were strong producers. Antibiotic residue analysis detected ciprofloxacin, sulfamethoxazole, and trimethoprim in all 33 WWTPs. Multilocus sequence typing analysis identified 29 genotypes, predominantly ST131, ST1193, ST38, and ST69, as high-risk clones of extraintestinal pathogenic E. coli. This study provided a comprehensive analysis of antibiotic resistance in MDR E. coli isolated from WWTPs, emphasizing the need for ongoing surveillance and research to effectively manage antibiotic resistance.

Non-negligible roles of upstream rivers in determining the antibiotic resistance genes community in an interconnected river-lake system (Dongting lake, China).

Emergence and spread of antibiotic resistance genes (ARGs) in lakes have been considered as a global health threat. However, a thorough understanding of the distribution patterns and ecological processes that shape the ARGs profile in interconnected river-lake systems remains largely unexplored. In this study, we collected paired water and sediment samples from a typical interconnected river-lake system, Dongting Lake in China, during both wet and dry seasons. Using high-throughput quantitative PCR, we investigated the spatial and temporal distribution of ARGs and the factors that influence them. A total of 8 major antibiotic classes and 10 mobile genetic elements were detected across the Dongting Lake basin. The unique hydrological characteristics of this interconnected river-lake system result in a relatively stable abundance of ARGs across different seasons and interfaces. During the wet season, deterministic processes dominated the assembly of ARGs, allowing environmental factors, such as heavy metals, to serve as main driving forces of ARGs distribution. When the dry season arrived, variations in hydrological conditions and changes in ARGs sources caused stochastic processes to dominate the assembly of ARGs. Our findings provide valuable insights for understanding the ecological processes of ARGs in interconnected river-lake systems, emphasizing the necessity of upstream restoration and clarifying river-lake relationships to mitigate ARGs dissemination.

Microbiome and antibiotic resistome in bioelectrochemical toilets for onsite treatment of fecal sludge.

Effective management of fecal sludge (FS) is essential for preventing environmental and public health risks. Developing safe and efficient FS treatment technology is crucial for reducing the health risks of onsite sanitation systems. In this study, bioelectrochemical toilets (BETs) were developed to treat FS onsite. Compared with the open-circuit BETs (OC-BETs), BETs exhibited higher removal efficiencies for total organic carbon, total nitrogen, and total phosphorus. Specifically, the enhancements in removal efficiencies were 18.82 ± 1.73 %, 7.28 ± 0.32 %, and 11.41 ± 0.05 % for urine, and 19.28 ± 4.08 %, 21.65 ± 1.23 %, and 24.68 ± 0.95 % for feces, respectively. Microbiome analysis indicated that the dominant populations were affiliated with electroactive bacteria (Desulfuromonas and Pseudomonas) in the electrode biofilm of BETs. The species co-occurrence network showed that the electrode biofilm microbiome in BETs had more complex correlations than that in OC-BETs, suggesting that a weak electrical current enhanced the microbiome stability. The relative abundance of antibiotic resistance genes in BETs and OC-BETs reduced by 59.85 ± 1.32 % and 53.01 ± 2.81 % compared with the initial FS, respectively. These findings indicate that BETs are an alternative system for enhancing onsite treatment of fecal sludge and provide a theoretical foundation for the implementation of BETs.

The resistance change and stress response mechanisms of chlorine-resistant bacteria under microplastic stress in drinking water distribution system.

The presence of both chlorine-resistant bacteria (CRB) and microplastics (MPs) in drinking water distribution systems (DWDS) poses a threat to water quality and human health. However, the risk of CRB bio evolution under the stress of MPs remains unclear. In this study, polypropylene (PP) and polyethylene (PE) were selected to study the adsorption and desorption behavior of sulfamethoxazole (SMX), and it was clear that MPs had the risk of carrying pollutants into DWDS and releasing them. The results of the antibiotic susceptibility test and disinfection experiment confirmed that MPs could enhance the resistance of CRB to antibiotics and disinfectants. Bacteria epigenetic resistance mechanisms were approached from multiple perspectives, including physiological and biochemical characteristics, as well as molecular regulatory networks. When MPs enter DWDS, CRB could attach to the surface of MPs and directly interact with both MPs and the antibiotics they release. This attachment process promoted changes in the composition and content of extracellular polymers (EPS) within cells, enhanced surface hydrophobicity, stimulated oxidative stress function, and notably elevated the relative abundance of certain antibiotic resistance genes (ARGs). This study elucidates the mechanism by which MPs alter the intrinsic properties of CRB, providing valuable insights into the effective avoidance of biological risks to water quality during CRB evolution.

[Spatial and Temporal Distribution of Antibiotic Resistance Genes in Different River Sediments in Typical Cities: A Case Study of Shijiazhuang].

Rivers are important reservoirs of antibiotic resistance genes (ARGs). However, most current studies have focused on the temporal and spatial distribution, and data on the differences in the species and abundance of ARGs between urban and rural rivers is still lacking for certain areas. In view of this, two rural rivers and three urban rivers were selected in Shijiazhuang City. In both December 2020 and April 2021, sediments were collected at 15 sampling sites. Metagenomic sequencing technology was used to compare the differences in temporal-spatial variation for ARGs in sediments. The results showed that:① 162 and 79 ARGs were detected in urban (4 776 ±4 452) and rural rivers (1 043 ±632), respectively. The abundance and species of ARGs in urban rivers were higher than those in rural rivers. ② The relative abundances of sulfonamide (SAs,27 %), aminoglycoside (AGs,26 %), and multidrug (MDs,15 %) ARGs had the highest abundance in urban rivers, whereas the relative abundance of MDs ARGs was highest in rural rivers (65 %). On the whole, the complexity of ARGs in urban rivers was higher than that in rural rivers. ③ There was a significant positive correlation between SAs, AGs, MDs, tetracycline, phenicol, macrolides-lincosamids-streptogramins (MLS), ß-lactams, and diaminopyrimidine ARGs in urban rivers (P < 0.01); however, there was a significant negative correlation between glycopeptide ARGs and all types of ARGs (P < 0.05 and P < 0.01). There was a significant positive correlation between MDs and SAs ARGs in rural rivers (P < 0.05), but there was a significant negative correlation between amino aminocoumarin, peptide, rifamycin, and fosfomycin ARGs (P < 0.05 and P < 0.01). ④ For the temporal variation in urban rivers, 162 ARGs (4 776 ±4 452) and 148 ARGs (5 673 ±5 626) were detected in December and April, respectively. For the temporal variation in rural rivers, 79 species (1 043 ±632) and 46 species (467 ±183) were detected in December and April, respectively. ⑤ RDA analysis results showed that the spatial-temporal distributions of ARGs in urban and rural rivers were different. Correlation analysis showed that the ARGs in urban rivers were significantly correlated with the number of industrial enterprises, whereas the ARGs in rural rivers were significantly correlated with the output value of animal husbandry. In general, this study identified the main influencing factors for ARGs in different rivers and provided data support for ARGs risk management in different rivers.

A review of spatial distribution of typical antibiotic resistance genes in marine environment surrounding China.

Antibiotic resistance genes (ARGs) have been steadily increasing due to the extensive overuse of antibiotics in the marine environment. Currently, the research considering ARGs distribution in marine ecosystems gains more interest. As the coastal sea has been regarded as one of the most polluted areas by antibiotic contaminants in China. However, no comprehensive review of the spatial distribution of ARGs in marine environment surrounding China. The main objective of this review is to investigate the level, characteristic, and spatial distribution of ARGs in the marine environment (seawater and sediments) surrounding China. Key sea areas, such as Bohai Sea, Yellow Sea, East China Sea, and South China Sea were selected in this review. The marine environment was the reservoir of ARGs, and ARGs in seawater were generally 1 to 2 orders of magnitude higher than that in sediments. Total ARGs were more abundant in the Yellow Sea, followed by the Bohai Sea, the East China Sea, and the South China Sea. This study raises questions regarding the spread and distribution for antibiotic resistance in marine environments.

High-throughput microfluidic quantitative PCR system for the simultaneous detection of antibiotic resistance genes and bacterial and viral pathogens in wastewater.

Comprehensive data on bacterial and viral pathogens of diarrhea and studies applying culture-independent methods for examining antibiotic resistance in wastewater are lacking. This study aimed to simultaneously quantify antibiotic resistance genes (ARGs), class 1 integron-integrase (int1), bacterial and viral pathogens of diarrhea, 16S rRNA, and other indicators using a high-throughput quantitative PCR (HT-qPCR) system. Thirty-six grab wastewater samples from a wastewater treatment plant in Japan, collected three times a month between August 2022 and July 2023, were centrifuged, followed by nucleic acid extraction, reverse transcription, and HT-qPCR. Fourteen targets were included, and HT-qPCR was performed on the Biomark X9™ System (Standard BioTools). For all qPCR assays, R2 was ≥0.978 and the efficiencies ranged from 90.5% to 117.7%, exhibiting high performance. Of the 36 samples, 20 (56%) were positive for Norovirus genogroup II (NoV-GII), whereas Salmonella spp. and Campylobacter jejuni were detected in 24 (67%) and Campylobacter coli in 13 (36%) samples, with mean concentrations ranging from 3.2 ± 0.8 to 4.7 ± 0.3 log10 copies/L. NoV-GII detection ratios and concentrations were higher in winter and spring. None of the pathogens of diarrhea correlated with acute gastroenteritis cases, except for NoV-GII, suggesting the need for data on specific bacterial infections to validate bacterial wastewater-based epidemiology (WBE). All samples tested positive for sul1, int1, and blaCTX-M, irrespective of season. The less explored blaNDM-1 showed a wide prevalence (>83%) and consistent abundance ranging from 4.3 ± 1.0 to 4.9 ± 0.2 log10 copies/L in all seasons. sul1 was the predominant ARG, whereas absolute abundances of 16S rRNA, int1, and blaCTX-M varied seasonally. int1 was significantly correlated with blaCTX-M in autumn and spring, whereas it showed no correlation with blaNDM-1, questioning the applicability of int1 as a sole indicator of overall resistance determinants. This study exhibited that the HT-qPCR system is pivotal for WBE.

Metagenomic Insights into Potential Impacts of Antibacterial Biosynthesis and Anthropogenic Activity on Nationwide Soil Resistome.

The presence of antibiotic resistance genes (ARGs) in soils has received extensive attention regarding its impacts on environmental, animal, and human systems under One Health. However, the health risks of soil ARGs and microbial determinants of soil resistomes remain poorly understood. Here, a nationwide metagenomic investigation of ARGs in cropland and forest soils in China was conducted. The findings indicated that the abundance and richness of high-risk (i.e., mobilizable, pathogen-carriable and clinically relevant) ARGs in cropland soils were 25.7 times and 8.4 times higher, respectively, compared to those identified in forest soils, suggesting the contribution of agricultural practices to the elevated risk level of soil resistomes. The biosynthetic potential of antibacterials best explained the total ARG abundance (Mantel's r = 0.52, p < 0.001) when compared with environmental variables and anthropogenic disturbance. Both microbial producers' self-resistance and antagonistic interactions contributed to the ARG abundance, of which self-resistance ARGs account for 14.1 %- 35.1 % in abundance. With the increased biosynthetic potential of antibacterials, the antagonistic interactions within the microbial community were greatly enhanced, leading to a significant increase in ARG abundance. Overall, these findings advance our understanding of the emergence and dissemination of soil ARGs and provide critical implications for the risk control of soil resistomes.

The mystery of rich human gut antibiotic resistome in the Yellow River with hyper-concentrated sediment-laden flow.

Human gut antibiotic resistome widely occur in anoxic environments characterized by high density of bacterial cells and frequent transmission of antibiotic resistance genes (ARGs). Such resistome is greatly diluted, degraded, and restrained in the aerobic habitats within most natural rivers (regarded as "terrestrial guts") connecting continents and the oceans. Here we implemented a large-scale monitoring campaign extending 5,200 km along the Yellow River, and provide the first integral biogeographic pattern for both ARGs and their hosts. We identified plentiful ARGs (24 types and 809 subtypes) and their hosts (24 phyla and 757 MAGs) in three media (water, suspended particulate matter (SPM), and sediment). Unexpectedly, we found diverse human gut bacteria (HGB) acting as supercarriers of ARGs in this oxygen-rich river. We further discovered that numerous microhabitats were created within stratified biofilms that surround SPMs, particularly regarding the aggregation of anaerobic HGB. These microhabitats provide numerous ideal sinks for anaerobic bacteria and facilitate horizontal transfer of ARGs within the stratified biofilms, Furthermore, the stratification of biofilms surrounding SPMs has facilitated synergy between human gut flora and denitrifiers for propagation of ARGs in the anoxic atmospheres, leading to high occurrence of human gut antibiotic resistome. SPMs play active roles in the dynamic interactions of river water and sediment, thus accelerating the evolution of riverine resistome and transmission of human gut antibiotic resistome. This study revealed the special contribution of SPMs to the propagation of ARGs, and highlighted the necessity of making alternative strategies for sustainable management of large rivers with hyper-concentrated sediment-laden flows.

Quantitative proteomics investigating the intrinsic adaptation mechanism of Aeromonas hydrophila to streptomycin.

Aeromonas hydrophila, a prevalent pathogen in the aquaculture industry, poses significant challenges due to its drug-resistant strains. Moreover, residues of antibiotics like streptomycin, extensively employed in aquaculture settings, drive selective bacterial evolution, leading to the progressive development of resistance to this agent. However, the underlying mechanism of its intrinsic adaptation to antibiotics remains elusive. Here, we employed a quantitative proteomics approach to investigate the differences in protein expression between A. hydrophila under streptomycin (SM) stress and nonstress conditions. Notably, bioinformatics analysis unveiled the potential involvement of metal pathways, including metal cluster binding, iron-sulfur cluster binding, and transition metal ion binding, in influencing A. hydrophila's resistance to SM. Furthermore, we evaluated the sensitivity of eight gene deletion strains related to streptomycin and observed the potential roles of petA and AHA_4705 in SM resistance. Collectively, our findings enhance the understanding of A. hydrophila's response behavior to streptomycin stress and shed light on its intrinsic adaptation mechanism.