Occurrence and fate of antibiotic-resistance genes and their potential hosts in high-moisture alfalfa silage treated with or without formic acid bactericide

文献类型: 外文期刊

第一作者: Zhang, Xia

作者: Zhang, Xia;Usman, Samaila;Guo, Xusheng;Zhang, Xia;Usman, Samaila;Guo, Xusheng;Bature, Ibrahim

作者机构:

关键词: Antibiotic resistance genes; High -moisture alfalfa silage; Bactericide; Clinical ARGs; Mobile genetic elements

期刊名称:JOURNAL OF ENVIRONMENTAL MANAGEMENT ( 影响因子:8.7; 五年影响因子:8.4 )

ISSN: 0301-4797

年卷期: 2023 年 347 卷

页码:

收录情况: SCI

摘要: Silage as the main forage for ruminants could be a reservoir for antibiotic resistance genes (ARGs) through which these genes got access into the animals' system causing a latent health risk. This study employed metagenomics and investigated the ARGs' fate and transmission mechanism in high-moisture alfalfa silage treated with formic acid bactericide. The results showed that there were 22 ARGs types, in which multidrug, macrolide-lincosamidestreptogramine, bacitracin, beta-lactam, fosmidomycin, kasugamycin, and polymycin resistance genes were the most prevalent ARGs types in the ensiled alfalfa. The natural ensiling process increased ARGs enrichment. Intriguingly, after 5 days of ensiling, formic acid-treated silage reduced ARGs abundances by inhibiting host bacterial and plasmids. Although formic acid bactericide enhanced the fermentation characteristics of the highmoisture alfalfa by lowering silage pH, butyric acid concentration, dry matter losses and proteolysis, it increased ARGs abundances in alfalfa silage owing to increases in abundances of ARGs carriers and transposase after 90 days of ensiling. Notably, several pathogens like Staphylococcus, Clostridium, and Pseudomonas were inferred as potential ARGs hosts in high-moisture alfalfa silage, and high-moisture alfalfa silage may harbor a portion of the clinical ARGs. Fundamentally, microbes were distinguished as the foremost driving factor of ARGs propagation in ensiling microecosystem. In conclusion, although formic acid bactericide improved the fermentation characteristics of high-moisture alfalfa during ensiling and reduced ARGs enrichment at the initial ensiling stage, it increased ARGs enrichment at the end of ensiling.

分类号:

  • 相关文献
作者其他论文 更多>>
  • SPTS: Single Pixel in Time-Series Triangle Model for Estimating Surface Soil Moisture

    作者:Ma, Tian;Leng, Pei;Aliyu Kasim, Abba;Li, Zhao-Liang;Ma, Tian;Gao, Yu-Xin;Guo, Xiaonan;Zhang, Xia;Shang, Guo-Fei;Li, Zhao-Liang

    关键词:Land surface temperature (LST); Landsat; single pixel in time series (SPTS); soil moisture

  • Natural Variation of PH8 Allele Improves Architecture and Cold Tolerance in Rice

    作者:Chen, Cheng;Zhang, Xia;Xu, Mingjia;Zhao, Weiying;Wang, Yangkai;Xiong, Jiawei;Yuan, Hua;Chen, Weilan;Tu, Bin;Li, Ting;Kang, Liangzhu;Tang, Shiwen;Wang, Yuping;Ma, Bingtian;Li, Shigui;Qin, Peng;Chen, Cheng;Zhang, Xia;Chen, Jialin;Chen, Zhuo

    关键词:Rice; Plant height; Cold tolerance; GWAS; Selection

  • Alleviation of salt stress in strawberries by hydrogen-rich water: Physiological, transcriptomic and metabolomic responses

    作者:Wang, Renyuan;Chu, Shaohua;Zhang, Dan;Zhang, Xia;Chi, Yaowei;Ma, Xianzhong;Yang, Xijia;Zhou, Pei;Wang, Renyuan;Chu, Shaohua;Zhang, Dan;Zhang, Xia;Chi, Yaowei;Ma, Xianzhong;Yang, Xijia;Zhou, Pei;Wang, Renyuan;Chu, Shaohua;Zhang, Dan;Zhang, Xia;Chi, Yaowei;Ma, Xianzhong;Yang, Xijia;Zhou, Pei;Wang, Renyuan;Chu, Shaohua;Zhang, Dan;Yang, Haiyan;Ding, Wenjiang;Zhou, Pei;Wang, Renyuan;Chu, Shaohua;Zhang, Dan;Yang, Haiyan;Ding, Wenjiang;Zhou, Pei;Chu, Shaohua;Zhang, Dan;Zhao, Ting;Zhou, Pei;Chu, Shaohua;Zhang, Dan;Zhou, Pei;Ren, Yongfeng;Zhou, Pei;Hayat, Kashif;Chen, Xunfeng

    关键词:

  • Nitrogen cycle induced by plant growth-promoting rhizobacteria drives "microbial partners" to enhance cadmium phytoremediation

    作者:Chi, Yaowei;Ma, Xianzhong;Chu, Shaohua;Wang, Renyuan;Zhang, Xia;Zhang, Dongwei;Zhao, Ting;Zhang, Dan;Zhou, Pei;Chi, Yaowei;Ma, Xianzhong;Chu, Shaohua;Wang, Renyuan;Zhang, Xia;Zhang, Dongwei;Zhao, Ting;Zhang, Dan;Zhou, Pei;Chi, Yaowei;Ma, Xianzhong;Chu, Shaohua;Wang, Renyuan;Zhang, Xia;Zhang, Dongwei;Zhao, Ting;Zhang, Dan;Zhou, Pei;Chi, Yaowei;Ma, Xianzhong;Chu, Shaohua;Wang, Renyuan;Zhang, Xia;Zhang, Dongwei;Zhao, Ting;Zhang, Dan;Zhou, Pei;Chi, Yaowei;Ma, Xianzhong;Chu, Shaohua;Wang, Renyuan;Zhang, Xia;Zhang, Dongwei;Zhao, Ting;Zhang, Dan;Zhou, Pei;You, Yimin;Chen, Xunfeng;Wang, Juncai;Zhou, Pei

    关键词:Plant growth-promoting rhizobacteria; Phytoremediation; Heavy metal; Soil nitrate reductase; Microbiota; Synthetic community

  • Vertical stratification-enabled early monitoring of cotton Verticillium wilt using in-situ leaf spectroscopy via machine learning models

    作者:Gao, Yi;Huang, Changping;Zhang, Xia;Gao, Yi;Huang, Changping;Zhang, Ze;Chen, Bing

    关键词:cotton Verticillium wilt; vertical leaf layer; hyperspectral reflectance; machine learning; disease severity

  • Land Surface Temperature Retrieval From Channel Resolution Enhanced FY-3D/MWRI Observations

    作者:Wang, Binqian;Leng, Pei;Wang, Binqian;Zhang, Xia;Shang, Guo-Fei;Zhou, Fang-Cheng;Bai, Yihong

    关键词:Channel resolution enhanced (CRE) FengYun-3D (FY-3D)/microwave radiation imager (MWRI); land surface temperature (LST); passive microwave (PMW); precipitable water vapor (PWV)-cloud liquid water (CLW) method; thermal infrared (TIR); three-channel method; Channel resolution enhanced (CRE) FengYun-3D (FY-3D)/microwave radiation imager (MWRI); land surface temperature (LST); passive microwave (PMW); precipitable water vapor (PWV)-cloud liquid water (CLW) method; thermal infrared (TIR); three-channel method

  • Unveiling the Effects of Crop Rotation on Cropland Soil pH Mapping: A Remote Sensing-Based Soil Sample Grouping Strategy

    作者:Liu, Yuan;Zhu, Ji;Zhang, Xia;Shang, Guofei;Liu, Yuan;Zhu, Ji;Zhang, Xia;Shang, Guofei;Liu, Yuan;Cai, Zejiang;Yu, Qiangyi;Wu, Wenbin;Liu, Yuan;Chen, Cheng;Bellingrath-Kimura, Sonoko Dorothea;Chen, Songchao;Chen, Songchao;Shen, Ge;Zhou, Qingbo;Bellingrath-Kimura, Sonoko Dorothea

    关键词:soil pH; Sentinel-1/2 images; cropland soil; crop rotation; soil sample grouping; machine learning