Visible Light-Accelerated Palladium-Catalyzed Thiocarbonylation Using Oxalic Acid Monothioester with Aryl/Alkenyl Sulfonium Salts.

Herein, we present a decarboxylative thiocarbonylation of aryl and alkenyl sulfonium salts with oxalic acid monothioethers (OAMs), which can be achieved by visible light-accelerated palladium catalysis. Sulfonium salts are widely available, and OAM is an easily accessible and stored reagent; this mild reaction method can also be used for the synthesis of different types of thioester compounds. The reaction represents a new application of visible light-accelerated palladium catalysis in catalytic decarboxylative cross-couplings.

Nitrifiers Cooperate to Produce Nitrous Oxide in Plateau Wetland Sediments.

The thawing of dormant plateau permafrost emits nitrous oxide (N2O) through wetlands; however, the N2O production mechanism in plateau wetlands is still unclear. Here, we used the 15N-18O double tracer technique and metagenomic sequencing to analyze the N2O production mechanism in the Yunnan-Kweichow and Qinghai-Tibet plateau wetlands during the summer of 2020. N2O production activity was detected in all 16 sediment samples (elevation 1020-4601 m: 2.55 ± 0.42-26.38 ± 3.25 ng N g-1 d-1) and was promoted by nitrifier denitrification (ND). The key functional genes of ND (amoA, hao, and nirK) belonged to complete ammonia oxidizing (comammox) bacteria, and the key ND species was the comammox bacterium Nitrospira nitrificans. We found that the comammox bacterial species N. nitrificans and the ammonia oxidizing bacterial (AOB) species Nitrosomonas europaea cooperate to produce N2O in the plateau wetland sediments. Furthermore, we inferred that environmental factors (elevation and total organic matter (TOM)) influence the cooperation pattern via N. nitrificans, thus affecting the N2O production activity in the plateau wetland sediments. Our findings advance the mechanistic understanding of nitrifiers in biogeochemical cycles and global climate change.

Amelioration of AsV toxicity by concurrent application of ZnO-NPs and Se-NPs is associated with differential regulation of photosynthetic indexes, antioxidant pool and osmolytes content in soybean seedling.

Arsenic is a significant food safety and environmental concern due to its mutagenic and carcinogenic effect on living organism. Soybean (Glycine max [L.] Merrill) is a global staple crop grown intensively in arsenic-contaminated regions of the world (e.g., Southern Province of China). Therefore, the objective of this study was to investigate whether Se-NPs and/or ZnO-NPs could be used as an eco-friendly and efficient amendment to reduce arsenic uptake and toxicity in soybean. Ten-days-old seedling, grown in vermiculite, were transferred to hydroponic media and further grown till V2 growth stage appeared. AsV (25 µM Na2HAsO4) stressed plants were treated with ZnONP (25 µM ZnO) and SeNP (25 µM Se) separately and in combination, which were grown for another 10 d. The result demonstrated that arsenic-treated soybean plants displayed a reduction in photosynthetic efficiency, increased proline and glycine betaine accumulation in tissues, and altered antioxidant activity compared to an untreated control. The application of zinc oxide and selenium nanoparticles, both independently and in tandem, reduced arsenic stress in root and shoot tissues and rescued plant health. This was reflected through increased levels of reduced glutathione content, ascorbic acid, and various photosynthesis- and antioxidant-relevant enzymes. In addition, nanoparticle-treated soybean plants displayed higher expression of defense- and detoxification-related genes compared to controls. Cellular toxicants (i.e., oxidized glutathione, reactive oxygen species, and malondialdehyde) were reduced upon nanoparticle treatment. These data collectively suggest that selenium and zinc oxide nanoparticles may be a solution to ameliorate arsenic toxicity in agricultural soils and crop plants.

Active ammonia-oxidizing bacteria and archaea in wastewater treatment systems.

Ammonia-oxidizing bacteria (AOB) and archaea (AOA) are two microbial groups mediating nitrification, yet little is presently known about their abundances and community structures at the transcriptional level in wastewater treatment systems (WWTSs). This is a significant issue, as the numerical abundance of AOA or AOB at the gene level may not necessarily represent their functional role in ammonia oxidation. Using amoA genes as molecular markers, this study investigated the transcriptional abundance and community structure of active AOA and AOB in 14 WWTSs. Quantitative PCR results indicated that the transcriptional abundances of AOB amoA (averaged: 1.6 × 108 copies g-1 dry sludge) were higher than those of AOA (averaged: 3.4 × 107 copies g-1 dry sludge) in all WWTSs despite several higher abundances of AOA amoA at the gene level. Moreover, phylogenetic analysis demonstrated that Nitrosomonas europaea and unknown clusters accounted for 37.66% and 49.96% of the total AOB amoA transcripts, respectively, suggesting their dominant role in driving ammonia oxidation. Meanwhile, AOA amoA transcripts were only successfully retrieved from 3 samples, and the Nitrosospaera sister cluster dominated, accounting for 83.46%. Finally, the substrate utilization kinetics of different AOA and AOB species might play a fundamental role in shaping their niche differentiation, community composition, and functional activity. This study provides a basis for evaluating the relative contributions of ammonia-oxidizing microorganisms (AOMs) to nitrogen conversions in WWTSs.

Gut microbiota in children with juvenile idiopathic arthritis: characteristics, biomarker identification, and usefulness in clinical prediction.

BACKGROUND: Recent studies have suggested that the gut microbiota is altered in children with juvenile idiopathic arthritis (JIA). However, age, sex, and body mass index (BMI) were not matched in the previous studies, and the results are inconsistent. We conducted an age-, sex-, and BMI-matched cross-sectional study to characterize the gut microbiota in children with JIA, and evaluate its potential in clinical prediction. METHODS: A total of 40 patients with JIA and 42 healthy controls, ranging from 1 to 16 years, were enrolled in this study. Fecal samples were collected for 16S rDNA sequencing. The data were analyzed using QIIME software and R packages. Specifically, the random forest model was used to identify biomarkers, and the receiver operating characteristic curve and the decision curve analysis were used to evaluate model performance. RESULTS: A total of 39 fecal samples from patients with JIA, and 42 fecal samples from healthy controls were sequenced successfully. The Chao 1 and Shannon-Wiener index in the JIA group were significantly lower than those in the control group, and the Bray-Curtis dissimilarity also differed significantly between the two groups. The relative abundance of 4 genera, Anaerostipes, Dialister, Lachnospira, and Roseburia, decreased significantly in the JIA group compared to those in the control group. The 4 genera included microbes that produce short-chain fatty acids (SCFAs) and were negatively correlated with some rheumatic indices. Moreover, 12 genera were identified as potential biomarkers by using the nested cross-validation function of the random forest. A random forest model constructed using these genera was able to differentiate the patients with JIA from the healthy controls, and the area under the receiver operating characteristic curve was 0.7975. The decision curve analysis indicated that the model had usefulness in clinical practice. CONCLUSIONS: The gut microbiota in patients with JIA is altered and characterized by a decreased abundance of 4 SCFA-producing genera. The decreases in the 4 genera correlated with more serious clinical indices. Twelve genera could be used as biomarkers and predictors in clinical practice. TRIAL REGISTRATION: The study is registered online at the Chinese Clinical Trial Registry on 11 May 2018 (registration number: ChiCTR1800016110).

Analysis of rice root bacterial microbiota of Nipponbare and IR24.

The root-associated bacterial microbiota is closely related to life activities of land plants, and its composition is affected by geographic locations and plant genotypes. However, the influence of plant genotypes on root microbiota in rice grown in northern China remains to be explained. In this study, we performed 16S rRNA gene amplicon sequencing to generate bacterial community profiles of two representative rice cultivars, Nipponbare and IR24. They are planted in Changping and Shangzhuang farms in Beijing and have reached the reproductive stage. We compared their root microbiota in details by Random Forest machine learning algorithm and network analysis. We found that the diversity of rice root microbiota was significantly affected by geographic locations and rice genotypes. Nipponbare and IR24 showed distinct taxonomic composition of the root microbiota and the interactions between different bacteria. Moreover, the root bacteria could be used as biomarkers to distinguish Nipponbare from IR24 across regions. Our study provides a theoretical basis for the in-depth understanding of rice root microbiota in Northern China and the improvement of rice breeding from the perspective of the interaction between root microorganisms and plants.

Observation of Nonlinear Standing Waves Excited by Plasma-Series-Resonance-Enhanced Harmonics in Capacitive Discharges.

We report the first experimental observation of nonlinear standing waves excited by plasma-series-resonance-enhanced harmonics in low pressure, very high frequency, parallel plate, capacitively coupled plasmas. Spatial structures of the harmonics of the magnetic field, measured by a magnetic probe, are in very good agreement with simulations based on a nonlinear electromagnetics model. At relatively low pressure, the nonlinear sheath motion generates high-order harmonics that can be strongly enhanced near the series resonance frequencies. Satisfying certain conditions, such nonlinear harmonics induce radial standing waves, with voltage and current maxima on axis, resulting in center-high plasma density. Excitation of higher harmonics is suppressed at higher pressures.

Dynamic chromatin changes associated with de novo centromere formation in maize euchromatin.

The inheritance and function of centromeres are not strictly dependent on any specific DNA sequence, but involve an epigenetic component in most species. CENH3, a centromere histone H3 variant, is one of the best-described epigenetic factors in centromere identity, but the chromatin features required during centromere formation have not yet been revealed. We previously identified two de novo centromeres on Zea mays (maize) minichromosomes derived from euchromatic sites with high-density gene distributions but low-density transposon distributions. The distribution of gene location and gene expression in these sites indicates that transcriptionally active regions can initiate de novo centromere formation, and CENH3 seeding shows a preference for gene-free regions or regions with no gene expression. The locations of the expressed genes detected were at relatively hypomethylated loci, and the altered gene expression resulted from de novo centromere formation, but not from the additional copy of the minichromosome. The initial overall DNA methylation level of the two de novo regions was at a low level, but increased substantially to that of native centromeres after centromere formation. These results illustrate the dynamic chromatin changes during euchromatin-originated de novo centromere formation, which provides insight into the mechanism of de novo centromere formation and regulation of subsequent consequences.

[Antioxidant effects of celastrol against hydrogen peroxide-induced oxidative stress in the cell model of amyotrophic lateral sclerosis].

To investigate the anti-oxidative effect of celastrol on H2O2-induced oxidative stress in the cell model of amyotrophic lateral sclerosis (ALS) and its molecular mechanism, NSC34 motor neuron-like cells were transfected with EGFP-G93A-SOD1 plasmid and used as in vitro ALS cell model. SOD1G93A transfected NSC34 cells were treated with different doses of H2O2 and celastrol. The survival rate of the cells was detected by CCK-8 assay, and malondialdehyde (MDA) content was detected by corresponding kit. The mRNA expression of glutamate-cysteine ligase catalytic subunit (GCLC) and glutathione S-transferases (GST) were detected by real-time PCR. The activation of intracellular MEK/ERK and PI3K/Akt signal pathways was detected by Western blot. The results showed that pre-incubation of celastrol (50 nmol/L) for 4 h prior to H2O2 (10 µmol/L) co-treatment for another 24 h significantly attenuated H2O2-induced cell death and MDA level in SOD1G93A transfected NSC34 cells. Real-time PCR showed that the mRNA expressions of GCLC and GST were enhanced with pre-incubation of celastrol. Celastrol quickly induced phosphorylation of ERK1/2 and Akt within 30 min and 1 h respectively in SOD1G93A transfected NSC34 cells. Pharmacological inhibitors of MEK (PD98059, 10 µmol/L) or Akt (MK2206, 10 µmol/L) could reverse the phosphorylation of ERK1/2 and Akt, and abolish up-regulation of GCLC and GST induced by celastrol at mRNA levels. Taken together, we conclude that celastrol exerts a beneficial antioxidant effect in SOD1G93ANSC34 cells, which might be dependent on MEK/ERK and PI3K/Akt signaling pathway activation.

Experimental Observation and Computational Analysis of Striations in Electronegative Capacitively Coupled Radio-Frequency Plasmas.

Self-organized spatial structures in the light emission from the ion-ion capacitive rf plasma of a strongly electronegative gas (CF_{4}) are observed experimentally for the first time. Their formation is analyzed and understood based on particle-based kinetic simulations. These "striations" are found to be generated by the resonance between the driving radio frequency and the eigenfrequency of the ion-ion plasma (derived from an analytical model) that establishes a modulation of the electric field, the ion densities, as well as the energy gain and loss processes of electrons in the plasma. The growth of the instability is followed by the numerical simulations.

[Discrimination of Crude Oil Samples Using Laser-Induced Time-Resolved Fluorescence Spectroscopy].

The Laser-induced fluorescence spectra combined with pattern recognition method has been widely applied in discrimination of different spilled oil, such as diesel, gasoline, and crude oil. However, traditional three-dimension fluorescence analysis method, which is not adapted to requirement of field detection, is limited to laboratory investigatio ns. The development of oil identification method for field detection is significant to quick response and operation of oil spill. In this paper, a new method based on laser-induced time-resolved fluorescence combined with support vector machine (SVM) model was introduced to discriminate crude oil samples. In this method, time-resolved spectra data was descended into two dimensions with selecting appropriate range in time and wavelength domains respectively to form a SVM data base. It is found that the classification accurate rate increased with an appropriate selection. With a selected range from 54 to 74 ns in time domain, the classification accurate rate has been increased from 83.3% (without selection) to 88.1%. With a selected wavelength range of 387.00~608.87 nm, the classification accurate rate of suspect oil was improved from 84% (without selection) to 100%. Since the detection delay of fluorescence lidar fluctuates due to wave and platform swing, the identification method with optimizing in both time and wavelength domains could offer a better flexibility for field applications. It is hoped that the developed method could provide some useful reference with data reduction for classification of suspect crude oil in the future development.

Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses.

The increasing application of meta-omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud-a specialized platform for -omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user-friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration-independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.

Visualizing set relationships: EVenn's comprehensive approach to Venn diagrams.

Venn diagrams serve as invaluable tools for visualizing set relationships due to their ease of interpretation. Widely applied across diverse disciplines such as metabolomics, genomics, transcriptomics, and proteomics, their utility is undeniable. However, the operational complexity has been compounded by the absence of standardized data formats and the need to switch between various platforms for generating different Venn diagrams. To address these challenges, we introduce the EVenn platform, a versatile tool offering a unified interface for efficient data exploration and visualization of diverse Venn diagrams. EVenn (http://www.ehbio.com/test/venn) streamlines the data upload process with a standardized format, enhancing the capabilities for multimodule analysis. This comprehensive protocol outlines various applications of EVenn, featuring representative results of multiple Venn diagrams, data uploads in the centralized data center, and step-by-step case demonstrations. Through these functionalities, EVenn emerges as a valuable and user-friendly tool for the in-depth exploration of multiomics data.

Large-scale bacterial genomic and metagenomic analysis reveals Pseudomonas aeruginosa as potential ancestral source of tigecycline resistance gene cluster tmexCD-toprJ.

BACKGROUND: The global dissemination of the multidrug resistance efflux pump gene cluster tmexCD-toprJ has greatly weakened the effects of multiple antibiotics, including tigecycline. However, the potential origin and transmission mechanisms of the gene cluster remain unclear. METHODS: Here, we concluded a comprehensive bioinformatics analysis on integrated 73,498 bacterial genomes, including Pseudomonas spp., Klebsiella spp., Aeromonas spp., Proteus spp., and Citrobacter spp., along with 1,152 long-read metagenomic datasets to trace the origin and propagation of tmexCD-toprJ. RESULTS: Our results demonstrated that tmexCD-toprJ was predominantly found in Pseudomonas aeruginosa sourced from human hosts in Asian countries and North American countries. Phylogenetic and genomic feature analyses showed that tmexCD-toprJ was likely evolved from mexCD-oprJ of some special clones of P. aeruginosa. Furthermore, metagenomic analysis confirmed that P. aeruginosa is the only potential ancestral bacterium for tmexCD-toprJ. A putative mobile genetic structure harboring tmexCD-toprJ, int-int-hp-hp-tnfxB-tmexCD-toprJ, was the predominant genetic context of tmexCD-toprJ across various bacterial genera, suggesting that the two integrase genes play a pivotal role in the horizontal transmission of tmexCD-toprJ. CONCLUSIONS: Based on these findings, it is almost certain that the tmexCD-toprJ gene cluster was derived from P. aeruginosa and further spread to other bacteria.

ChatGPT and generative AI are revolutionizing the scientific community: A Janus-faced conundrum.

The advent of generative artificial intelligence (AI) technologies marks a transformative moment for the scientific sphere, unlocking novel avenues to elevate scientific writing's efficiency and quality, expedite insight discovery, and enhance code development processes. Essential to leveraging these advancements is prompt engineering, a method that enhances AI interaction efficiency and quality. Despite its benefits, effective application requires blending researchers' expertise with AI, avoiding overreliance. A balanced strategy of integrating AI with independent critical thinking ensures the advancement and quality of scientific research, leveraging innovation while maintaining research integrity.

The gut microbiota-aromatic hydrocarbon receptor (AhR) axis mediates the anticolitic effect of polyphenol-rich extracts from Sanghuangporus.

Inflammatory bowel disease (IBD) is a significant global health concern. The gut microbiota plays an essential role in the onset and development of IBD. Sanghuangporus (SH), a traditional Chinese medicinal mushroom, has excellent anti-inflammatory effects and is effective at modulating the gut microbiota. Despite these attributes, the specific anticolitic effects of SH and the mechanisms through which the gut microbiota mediates its benefits remain unclear. Herein, we demonstrated that polyphenol-rich extract from SH effectively alleviated the pathological symptoms of dextran sodium sulfate (DSS)-induced colitis in mice by modulating the gut microbiota. Treatment with SH distinctly enriched Alistipes, especially Alistipes onderdonkii, and its metabolite 5-hydroxyindole-3-acetic acid (5HIAA). Oral gavage of live A. onderdonkii or 5HIAA potently mitigated DSS-induced colitis in mice. Moreover, both 5HIAA and SH significantly activated the aromatic hydrocarbon receptor (AhR), and the administration of an AhR antagonist abrogated their protective effects against colitis. These results underscore the potent efficacy of SH in diminishing DSS-induced colitis through the promotion of A. onderdonkii and 5HIAA, ultimately activating AhR signaling. This study unveils potential avenues for developing therapeutic strategies for colitis based on the interplay between SH and the gut microbiota.

Vaginal microbiota are associated with in vitro fertilization during female infertility.

The vaginal microbiome plays an essential role in the reproductive health of human females. As infertility increases worldwide, understanding the roles that the vaginal microbiome may have in infertility and in vitro fertilization (IVF) treatment outcomes is critical. To determine the vaginal microbiome composition of 1411 individuals (1255 undergoing embryo transplantation) and their associations with reproductive outcomes, clinical and biochemical features are measured, and vaginal samples are 16S rRNA sequenced. Our results suggest that both too high and too low abundance of Lactobacillus is not beneficial for pregnancy; a moderate abundance is more beneficial. A moderate abundance of Lactobacillus crispatus and Lactobacillus iners (~80%) (with a pregnancy rate of I-B: 54.35% and III-B: 57.73%) is found beneficial for pregnancy outcomes compared with a higher abundance (>90%) of Lactobacillus (I-A: 44.81% and III-A: 51.06%, respectively). The community state type (CST) IV-B (contains a high to moderate relative abundance of Gardnerella vaginalis) shows a similar pregnant ratio (48.09%) with I-A and III-A, and the pregnant women in this CST have a higher abundance of Lactobacillus species. Metagenome analysis of 71 samples shows that nonpregnant women are detected with more antibiotic-resistance genes, and Proteobacteria and Firmicutes are the main hosts. The inherent differences within and between women in different infertility groups suggest that vaginal microbes might be used to detect infertility and potentially improve IVF outcomes.

The best practice for microbiome analysis using R.

With the gradual maturity of sequencing technology, many microbiome studies have published, driving the emergence and advance of related analysis tools. R language is the widely used platform for microbiome data analysis for powerful functions. However, tens of thousands of R packages and numerous similar analysis tools have brought major challenges for many researchers to explore microbiome data. How to choose suitable, efficient, convenient, and easy-to-learn tools from the numerous R packages has become a problem for many microbiome researchers. We have organized 324 common R packages for microbiome analysis and classified them according to application categories (diversity, difference, biomarker, correlation and network, functional prediction, and others), which could help researchers quickly find relevant R packages for microbiome analysis. Furthermore, we systematically sorted the integrated R packages (phyloseq, microbiome, MicrobiomeAnalystR, Animalcules, microeco, and amplicon) for microbiome analysis, and summarized the advantages and limitations, which will help researchers choose the appropriate tools. Finally, we thoroughly reviewed the R packages for microbiome analysis, summarized most of the common analysis content in the microbiome, and formed the most suitable pipeline for microbiome analysis. This paper is accompanied by hundreds of examples with 10,000 lines codes in GitHub, which can help beginners to learn, also help analysts compare and test different tools. This paper systematically sorts the application of R in microbiome, providing an important theoretical basis and practical reference for the development of better microbiome tools in the future. All the code is available at GitHub github.com/taowenmicro/EasyMicrobiomeR.

High-fat diet-disturbed gut microbiota-colonocyte interactions contribute to dysregulating peripheral tryptophan-kynurenine metabolism.

BACKGROUND: Aberrant tryptophan (Trp)-kynurenine (Kyn) metabolism has been implicated in the pathogenesis of human disease. In particular, populations with long-term western-style diets are characterized by an excess of Kyn in the plasma. Host-gut microbiota interactions are dominated by diet and are essential for maintaining host metabolic homeostasis. However, the role of western diet-disturbed gut microbiota-colonocyte interactions in Trp metabolism remains to be elucidated. RESULTS: Here, 4-week-old mice were fed with a high-fat diet (HFD), representing a typical western diet, for 4 weeks, and multi-omics approaches were adopted to determine the mechanism by which HFD disrupted gut microbiota-colonocyte interplay causing serum Trp-Kyn metabolism dysfunction. Our results showed that colonocyte-microbiota interactions dominated the peripheral Kyn pathway in HFD mice. Mechanistically, persistent HFD-impaired mitochondrial bioenergetics increased colonic epithelial oxygenation and caused metabolic reprogramming in colonites to support the expansion of Proteobacteria in the colon lumen. Phylum Proteobacteria-derived lipopolysaccharide (LPS) stimulated colonic immune responses to upregulate the indoleamine 2,3-dioxygenase 1 (IDO1)-mediated Kyn pathway, leading to Trp depletion and Kyn accumulation in the circulation, which was further confirmed by transplantation of Escherichia coli (E.coli) indicator strains and colonic IDO1 depletion. Butyrate supplementation promoted mitochondrial functions in colonocytes to remodel the gut microbiota in HFD mice, consequently ameliorating serum Kyn accumulation. CONCLUSIONS: Our results highlighted that HFD disrupted the peripheral Kyn pathway in a gut microbiota-dependent manner and that the continuous homeostasis of gut bacteria-colonocytes interplay played a central role in the regulation of host peripheral Trp metabolism. Meanwhile, this study provided new insights into therapies against western diet-related metabolic disorders. Video Abstract.

Long-read metagenomic sequencing reveals that high-copy small plasmids shape the highly prevalent antibiotic resistance genes in animal fecal microbiome.

The emergence and prevalence of animal-derived antibiotic resistance genes (ARGs) pose a great threat to public health globally. Long-read metagenomic sequencing is increasingly being used to decipher the fate of environmental ARGs. However, the investigations of the distribution, co-occurrence patterns, and host information of animal-derived environmental ARGs with long-read metagenomic sequencing have received little attention. To cover the gap, we employed a novel QitanTech nanopore long-read metagenomic sequencing method to perform a comprehensive and systematic investigation of the microbial communities and antibiotic resistance profiles, as well as to analyze the host information and genetic structures of ARGs in the feces of laying hens. Our results showed that highly abundant and diverse ARGs were detected in the feces of different ages of laying hens, indicating that feeding animal feces was an important reservoir for the enrichment and maintenance of ARGs. The distribution pattern of chromosomal ARGs was more strongly associated with fecal microbial communities than plasmid-mediated ARGs. Further long-read host tracking analysis revealed that ARGs from Proteobacteria are commonly located on plasmids, whereas in Firmicutes, they are usually carried by chromosomes. Co-occurrence analysis displayed that co-selection phenomena of different ARGs were common occurrences and highly active insertion sequences (ISs) could result in the serious prevalence of many ARGs. Notably, small high-copy plasmids played a significant role in the dissemination of several ARGs, such as floR and tet(L), which could disturb the compositions of fecal ARGs. Overall, our findings significantly expand our knowledge of the comprehensive landscape of feeding animal feces resistome, which is important for the prevention and management of multi-drug resistant bacteria in laying hens.