IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i13p7766-d846962.html
   My bibliography  Save this article

Bio-Enhanced Degradation Strategies for Fluoroquinolones in the Sewage Sludge Composting Stage: Molecular Modification and Resistance Gene Regulation

Author

Listed:
  • Xingyan Jin

    (School of Environment, Harbin Institute of Technology, Harbin 150006, China)

  • Yuanyuan Zhao

    (MOE Key Laboratory of Resources and Environmental Systems Optimization, North China Electric Power University, Beijing 102206, China)

  • Zhixing Ren

    (College of Forestry, Northeast Forestry University, Harbin 150040, China)

  • Panpan Wang

    (School of Environment, Harbin Institute of Technology, Harbin 150006, China)

  • Yu Li

    (MOE Key Laboratory of Resources and Environmental Systems Optimization, North China Electric Power University, Beijing 102206, China)

Abstract

The molecular/protein–protein docking and the index normalization method assisted by the entropy weight method were used to quantitatively evaluate the biodegradability of fluoroquinolones (FQs) under different biodegradation systems. Four biodegradability three-dimensional quantitative structure–activity relationship (3D-QSAR) models of FQs were constructed to design FQ derivatives with improved biodegradability. Through the evaluation of the environmental friendliness and functional properties, the FQ derivatives with high biodegradability, improved functionality, and environmental friendliness were screened. Moreover, four bio-enhanced degradation scenarios of FQs were set up according to the different temperatures and carbon–nitrogen ratio (C/N) in the sewage sludge composting stage, and the molecular dynamic (MD) simulation assisted by protein–protein docking was used to screen the external environmental factors that promote the degradation of FQs by thermophilic bacteria or group under different scenarios. Finally, MD simulation assisted by sampling method was used to validate and screen the application scheme of field measures to enhance the expression of antibacterial resistance of FQ derivatives in an agricultural soil environment after activated sludge land use. This study aims to provide theoretical support for the development of highly biodegradable FQ derivatives and the mitigation of potential risks that FQs may pose to the environment and humans through the food chain.

Suggested Citation

  • Xingyan Jin & Yuanyuan Zhao & Zhixing Ren & Panpan Wang & Yu Li, 2022. "Bio-Enhanced Degradation Strategies for Fluoroquinolones in the Sewage Sludge Composting Stage: Molecular Modification and Resistance Gene Regulation," IJERPH, MDPI, vol. 19(13), pages 1-19, June.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7766-:d:846962
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/13/7766/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/13/7766/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhixing Ren & Yingwei Wang & Haihong Xu & Yufei Li & Song Han, 2019. "Fuzzy Comprehensive Evaluation Assistant 3D-QSAR of Environmentally Friendly FQs to Reduce ADRs," IJERPH, MDPI, vol. 16(17), pages 1-20, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Haigang Zhang & Chengji Zhao & Hui Na, 2020. "Enhanced Biodegradation of Phthalic Acid Esters’ Derivatives by Plasticizer-Degrading Bacteria ( Burkholderia cepacia , Archaeoglobus fulgidus , Pseudomonas aeruginosa ) Using a Correction 3D-QSAR Mod," IJERPH, MDPI, vol. 17(15), pages 1-17, July.
    2. Yilin Hou & Yuanyuan Zhao & Yu Li, 2020. "Environmentally Friendly Fluoroquinolone Derivatives with Lower Plasma Protein Binding Rate Designed Using 3D-QSAR, Molecular Docking and Molecular Dynamics Simulation," IJERPH, MDPI, vol. 17(18), pages 1-18, September.
    3. Yuting Chen & Yuying Dong & Le Li & Jian Jiao & Sitong Liu & Xuejun Zou, 2022. "Toxicity Rank Order (TRO) As a New Approach for Toxicity Prediction by QSAR Models," IJERPH, MDPI, vol. 20(1), pages 1-10, December.
    4. Peixuan Sun & Yuanyuan Zhao & Luze Yang & Zhixing Ren & Wenjin Zhao, 2020. "Environmentally Friendly Quinolones Design for a Two-Way Choice between Biotoxicity and Genotoxicity through Double-Activity 3D-QSAR Model Coupled with the Variation Weighting Method," IJERPH, MDPI, vol. 17(24), pages 1-22, December.
    5. Lu-ze Yang & Miao Liu, 2020. "A Double-Activity (Green Algae Toxicity and Bacterial Genotoxicity) 3D-QSAR Model Based on the Comprehensive Index Method and Its Application in Fluoroquinolones’ Modification," IJERPH, MDPI, vol. 17(3), pages 1-14, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7766-:d:846962. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.