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Membrane-Based In-Gel Loop-Mediated Isothermal Amplification (mgLAMP) System for SARS-CoV-2 Quantification in Environmental Waters

  • Yanzhe Zhu
    Yanzhe Zhu
    Linde Laboratories, California Institute of Technology, Pasadena, California 91125, United States
    More by Yanzhe Zhu
  • Xunyi Wu
    Xunyi Wu
    Linde Laboratories, California Institute of Technology, Pasadena, California 91125, United States
    More by Xunyi Wu
  • Alan Gu
    Alan Gu
    Linde Laboratories, California Institute of Technology, Pasadena, California 91125, United States
    More by Alan Gu
  • Leopold Dobelle
    Leopold Dobelle
    Linde Laboratories, California Institute of Technology, Pasadena, California 91125, United States
  • Clément A. Cid
    Clément A. Cid
    Linde Laboratories, California Institute of Technology, Pasadena, California 91125, United States
  • Jing Li*
    Jing Li
    Linde Laboratories, California Institute of Technology, Pasadena, California 91125, United States
    *Email: [email protected]
    More by Jing Li
  • , and 
  • Michael R. Hoffmann*
    Michael R. Hoffmann
    Linde Laboratories, California Institute of Technology, Pasadena, California 91125, United States
    *Email: [email protected]
Cite this: Environ. Sci. Technol. 2022, 56, 2, 862–873
Publication Date (Web):December 30, 2021
https://doi.org/10.1021/acs.est.1c04623
Copyright © 2021 American Chemical Society

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    Abstract

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    Since the COVID-19 pandemic is expected to become endemic, quantification of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in ambient waters is critical for environmental surveillance and for early detection of outbreaks. Herein, we report the development of a membrane-based in-gel loop-mediated isothermal amplification (mgLAMP) system that is designed for the rapid point-of-use quantification of SARS-CoV-2 particles in environmental waters. The mgLAMP system integrates the viral concentration, in-assay viral lysis, and on-membrane hydrogel-based RT-LAMP quantification using enhanced fluorescence detection with a target-specific probe. With a sample-to-result time of less than 1 h, mgLAMP successfully detected SARS-CoV-2 below 0.96 copies/mL in Milli-Q water. In surface water, the lowest detected SARS-CoV-2 concentration was 93 copies/mL for mgLAMP, while the reverse transcription quantitative polymerase chain reaction (RT-qPCR) with optimal pretreatment was inhibited at 930 copies/mL. A 3D-printed portable device is designed to integrate heated incubation and fluorescence illumination for the simultaneous analysis of nine mgLAMP assays. Smartphone-based imaging and machine learning-based image processing are used for the interpretation of results. In this report, we demonstrate that mgLAMP is a promising method for large-scale environmental surveillance of SARS-CoV-2 without the need for specialized equipment, highly trained personnel, and labor-intensive procedures.

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    The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.est.1c04623.

    • Principles for theoretical screening of QUASR quenching probe designs; comparison between QUASR and molecular beacon probing strategies; optimization of mgLAMP incubation time; performance of mgLAMP versus RT-qPCR in spiked Milli-Q water; environmental sample preparation; adaption of mgLAMP for bacterial detection; sequences and the corresponding target genes for 11 screened primer sets; summary of assay recipes and temperature protocols; primer set screening results based on sensitivity of detection; RT-LAMP results for assays with varying concentrations of Triton X-100 and X-405R; theoretical screening of QUASR probe design; fluorescence intensity of regular RT-LAMP reactions using qFIP12nt, qFIP17nt, qBIP10nt, and qBIP15nt quenching probes; detection sensitivity of RT-LAMP reaction using the four QUASR quenchers; primer sequences for E. coli and S. Typhi; environmental sampling location; pretreatment process; portable mgLAMP prototype design; real-time RT-LAMP fluorescence for the four most sensitive primer sets; picture of RT-LAMP tubes using QUASR and molecular beacon; smartphone images taken for mgLAMP samples corresponding to microscope images in Figure 3a–d; effect of mgLAMP incubation time; comparison of mgLAMP estimation and RT-qPCR count number (Ct) for spiked Milli-Q water; DLS analysis of environmental samples; and performance of mgLAMP for E. coli and S. Typhi cell-spiked Milli-Q water (PDF)

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    Cited By

    This article is cited by 10 publications.

    1. Mei Fang, Yiru Wang, Tao Yang, Jing Zhang, Hanry Yu, Zisheng Luo, Bin Su, Xingyu Lin. Nucleic Acid Plate Culture: Label-Free and Naked-Eye-Based Digital Loop-Mediated Isothermal Amplification in Hydrogel with Machine Learning. ACS Sensors 2024, Article ASAP.
    2. Payel Sen, Zijie Zhang, Phoebe Li, Bal Ram Adhikari, Tianyi Guo, Jimmy Gu, Adam R MacIntosh, Colin van der Kuur, Yingfu Li, Leyla Soleymani. Integrating Water Purification with Electrochemical Aptamer Sensing for Detecting SARS-CoV-2 in Wastewater. ACS Sensors 2023, 8 (4) , 1558-1567. https://doi.org/10.1021/acssensors.2c02655
    3. Haorui Cao, Kang Mao, Fang Ran, Pengqi Xu, Yirong Zhao, Xiangyan Zhang, Hourong Zhou, Zhugen Yang, Hua Zhang, Guibin Jiang. Paper Device Combining CRISPR/Cas12a and Reverse-Transcription Loop-Mediated Isothermal Amplification for SARS-CoV-2 Detection in Wastewater. Environmental Science & Technology 2022, 56 (18) , 13245-13253. https://doi.org/10.1021/acs.est.2c04727
    4. Yuhua Yan, Tao Yang, Zisheng Luo, Dong Li, Li Li, Xingyu Lin. Ultrasensitive quantification of pathogens in milliliters of beverage by filtration-based digital LAMP. Food Chemistry 2023, 408 , 135226. https://doi.org/10.1016/j.foodchem.2022.135226
    5. Abdellah Zakaria Sellam, Azeddine Benlamoudi, Clément Antoine Cid, Leopold Dobelle, Amina Slama, Yassin El Hillali, Abdelmalik Taleb-Ahmed. Deep Learning Solution for Quantification of Fluorescence Particles on a Membrane. Sensors 2023, 23 (4) , 1794. https://doi.org/10.3390/s23041794
    6. Tao Yang, Dong Li, Yuhua Yan, Fatima-ezzahra Ettoumi, Ricardo A. Wu, Zisheng Luo, Hanry Yu, Xingyu Lin. Ultrafast and absolute quantification of SARS-CoV-2 on food using hydrogel RT-LAMP without pre-lysis. Journal of Hazardous Materials 2023, 442 , 130050. https://doi.org/10.1016/j.jhazmat.2022.130050
    7. Mary Vermi Aizza Corpuz, Antonio Buonerba, Tiziano Zarra, Shadi W. Hasan, Gregory V. Korshin, Vincenzo Belgiorno, Vincenzo Naddeo. Advances in virus detection methods for wastewater-based epidemiological applications. Case Studies in Chemical and Environmental Engineering 2022, 6 , 100238. https://doi.org/10.1016/j.cscee.2022.100238
    8. Catherine Hoar, Jill McClary-Gutierrez, Marlene K. Wolfe, Aaron Bivins, Kyle Bibby, Andrea I. Silverman, Sandra L. McLellan. Looking Forward: The Role of Academic Researchers in Building Sustainable Wastewater Surveillance Programs. Environmental Health Perspectives 2022, 130 (12) https://doi.org/10.1289/EHP11519
    9. Aaron Bivins, Devrim Kaya, Warish Ahmed, Joe Brown, Caitlyn Butler, Justin Greaves, Raeann Leal, Kendra Maas, Gouthami Rao, Samendra Sherchan, Deborah Sills, Ryan Sinclair, Robert T. Wheeler, Cresten Mansfeldt. Passive sampling to scale wastewater surveillance of infectious disease: Lessons learned from COVID-19. Science of The Total Environment 2022, 835 , 155347. https://doi.org/10.1016/j.scitotenv.2022.155347
    10. Benjamin P. Sullivan, Yu-Shan Chou, Andrew T. Bender, Coleman D. Martin, Zoe G. Kaputa, Hugh March, Minyung Song, Jonathan D. Posner. Quantitative isothermal amplification on paper membranes using amplification nucleation site analysis. Lab on a Chip 2022, 22 (12) , 2352-2363. https://doi.org/10.1039/D2LC00007E

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