ABSTRACT
BACKGROUND: Peritoneal fibrosis is the prevailing complication induced by prolonged exposure to high glucose in patients undergoing peritoneal dialysis. METHODS: To elucidate the molecular mechanisms underlying this process, we conducted an integrated analysis of the transcriptome and chromatin accessibility profiles of human peritoneal mesothelial cells (HMrSV5) during high-glucose treatment. RESULTS: Our study identified 2775 differentially expressed genes (DEGs) related to high glucose-triggered pathological changes, including 1164 upregulated and 1611 downregulated genes. Genome-wide DEGs and network analysis revealed enrichment in the epithelial-mesenchymal transition (EMT), inflammatory response, hypoxia, and TGF-beta pathways. The enriched genes included VEGFA, HIF-1α, TGF-ß1, EGF, TWIST2, and SNAI2. Using ATAC-seq, we identified 942 hyper (higher ATAC-seq signal in high glucose-treated HMrSV5 cells than in control cells) and 714 hypo (lower ATAC-seq signal in high glucose-treated HMrSV5 cells versus control cells) peaks with differential accessibility in high glucose-treated HMrSV5 cells versus controls. These differentially accessible regions were positively correlated (R = 0.934) with the nearest DEGs. These genes were associated with 566 up- and 398 downregulated genes, including SNAI2, TGF-ß1, HIF-1α, FGF2, VEGFA, and VEGFC, which are involved in critical pathways identified by transcriptome analysis. Integrated ATAC-seq and RNA-seq analysis also revealed key transcription factors (TFs), such as HIF-1α, ARNTL, ELF1, SMAD3 and XBP1. Importantly, we demonstrated that HIF-1α is involved in the regulation of several key genes associated with EMT and the TGF-beta pathway. Notably, we predicted and experimentally validated that HIF-1α can exacerbate the expression of TGF-ß1 in a high glucose-dependent manner, revealing a novel role of HIF-1α in high glucose-induced pathological changes in human peritoneal mesothelial cells (HPMCs). CONCLUSIONS: In summary, our study provides a comprehensive view of the role of transcriptome deregulation and chromosome accessibility alterations in high glucose-induced pathological fibrotic changes in HPMCs. This analysis identified hub genes, signaling pathways, and key transcription factors involved in peritoneal fibrosis and highlighted the novel glucose-dependent regulation of TGF-ß1 by HIF-1α. This integrated approach has offered a deeper understanding of the pathogenesis of peritoneal fibrosis and has indicated potential therapeutic targets for intervention.
Subject(s)
Chromatin , Peritoneal Fibrosis , Humans , Chromatin/genetics , Transforming Growth Factor beta1/genetics , Transcriptome/genetics , Chromosome Aberrations , Transforming Growth Factor betaABSTRACT
Antibiotic resistance genes (ARGs), emerging environmental contaminants, have become challenges of public health security. However, the distribution and drivers of ARGs, especially high-risk ARGs, in large-scale aquaculture sediments remain unknown. Here, we collected sediment samples from 40 crayfish ponds in seven main crayfish culture provinces in China and then investigated the distribution and risk of ARGs based on high-throughput sequencing and quantitative PCR techniques. Our results suggested that aquaculture sediment was potential reservoir of ARGs and the abundance of aadA-02 was the highest. High-risk ARG (floR) was also prevalent in the sediment and was the most abundant in Jiangsu Province, where opportunistic pathogens were also enriched. The abundance of floR was positively correlated with different environmental factors, such as total phosphorus in water and total carbon in sediment. In addition, Mycobacterium sp., opportunistic pathogenic bacteria, might be potential host for floR. Furthermore, the potential propagation pathway of ARGs was from sediment to crayfish gut, and Bacteroidetes and Proteobacteria might be the main bacterial groups responsible for the proliferation of ARGs. Generally, our results illustrate that pond sediment may be an ARG reservoir of aquatic animals. Meanwhile, our study helps develop valuable strategies for accessing risks and managing ARGs.
Subject(s)
Anti-Bacterial Agents , Genes, Bacterial , Animals , Anti-Bacterial Agents/pharmacology , Drug Resistance, Microbial/genetics , Bacteria/genetics , Aquaculture , Astacoidea , ChinaABSTRACT
Drought stress (DS) is one of the most frequently occurring stresses in tomato plants. Detecting tomato plant DS is vital for optimizing irrigation and improving fruit quality. In this study, a DS identification method using the multi-features of hyperspectral imaging (HSI) and subsample fusion was proposed. First, the HSI images were measured under imaging condition with supplemental blue lights, and the reflectance spectra were extracted from the HSI images of young and mature leaves at different DS levels (well-watered, reduced-watered, and deficient-watered treatment). The effective wavelengths (EWs) were screened by the genetic algorithm. Second, the reference image was determined by ReliefF, and the first four reflectance images of EWs that are weakly correlated with the reference image and mutually irrelevant were obtained using Pearson's correlation analysis. The reflectance image set (RIS) was determined by evaluating the superposition effect of reflectance images on identification. The spectra of EWs and the image features extracted from the RIS by LeNet-5 were adopted to construct DS identification models based on support vector machine (SVM), random forest, and dense convolutional network. Third, the subsample fusion integrating the spectra and image features of young and mature leaves was used to improve the identification further. The results showed that supplemental blue lights can effectively remove the high-frequency noise and obtain high-quality HSI images. The positive effect of the combination of spectra of EWs and image features for DS identification proved that RIS contains feature information pointing to DS. Global optimal classification performance was achieved by SVM and subsample fusion, with a classification accuracy of 95.90% and 95.78% for calibration and prediction sets, respectively. Overall, the proposed method can provide an accurate and reliable analysis for tomato plant DS and is hoped to be applied to other crop stresses.
ABSTRACT
The propagation of antibiotic resistance genes (ARGs) has become a global public health concern. However, the distribution and influencing factors of ARGs, especially high-risk ARGs, in the gut of aquaculture animals remain unclear. Here, we employed 16S rRNA gene sequencing and high-throughput quantitative PCR techniques to determine crayfish gut microbiota and ARGs collected from 40 culture ponds in major crayfish farming provinces of China. We detected 74 ARGs in crayfish gut. Among them, the beta-lactamase and tetracycline resistance genes were dominant. The total ARG abundance was the highest in Hubei Province. High-risk ARGs were also found in crayfish gut, and ermB had the highest abundance and distributed in Anhui, Hubei, Henan and Jiangxi Province. In addition, opportunistic pathogens (Streptococcus, Aeromonas and Acinetobacter) might be potential hosts for ARGs, including high-risk ARGs. Finally, habitat, environmental factors (NO3-N, pH and temperature), microbial alpha diversity and mobile genetic elements (MGEs) showed significant influence on ARGs profiles. Generally, our results illustrate that ARGs are prevalent in crayfish gut and may pose potential risk to human health, which will help develop targeted strategies for the risk management and assessment of ARGs in the aquaculture.