IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-60917-9.html
   My bibliography  Save this article

Cas12a Cis-cleavage mediated lateral flow assay enables multiplex and ultra-specific nucleic acid detection

Author

Listed:
  • Mei Lin

    (South China Normal University)

  • Zhiqiang Qiu

    (South China Normal University)

  • Mengen Hao

    (South China Normal University)

  • Weiwei Qi

    (South China Normal University)

  • Ting Zhang

    (South China Normal University)

  • Yuting Shen

    (South China Normal University)

  • Hongrui Xiao

    (South China Normal University)

  • Chaoyue Liang

    (South China Normal University)

  • Longxu Xie

    (Guangzhou Hybribio Medicine Technology Ltd)

  • Yongzhong Jiang

    (Hubei Provincial Center for Disease Control and Prevention)

  • Meng Cheng

    (The First Affiliated Hospital of Guangzhou Medical University)

  • Tian Tian

    (South China Normal University)

  • Xiaoming Zhou

    (South China Normal University
    South China Normal University)

Abstract

CRISPR technology holds significant promise for advancing nucleic acid assays. However, current CRISPR diagnostic techniques, reliant on indiscriminate trans-cleavage mechanisms, face challenges in developing multiplex detection formats. Moreover, chaotic trans-cleavage activity often results from mismatched targets, leading to specificity issues. To address these limitations, here we exploit a double-key recognition mechanism based on CRISPR-Cas12a cis-cleavage and invasive hybridization identification of released sticky-end DNA products. By integrating multiplexed nucleic acid amplification, the double-key Cas12a detection mechanism, and a lateral flow detection platform, we develop a method termed Cas12a cis-cleavage mediated lateral flow assay (cc-LFA). We demonstrate that the cc-LFA exhibited superior specificity compared to three mainstream trans-cleavage-based CRISPR diagnostic techniques, achieving single-base resolution detection free from high-concentration wild-type DNA background interference. cc-LFA is also applied for highly specific detection of multiple respiratory pathogen samples and precise multiplexed detection of nine high-risk human papillomavirus (HPV) subtypes, achieving over 90% sensitivity and 100% specificity, respectively. Additionally, we present a portable device to automate nucleic acid amplification and strip detection procedures, showcasing the potential of cc-LFA for future applications in decentralized laboratory scenarios.

Suggested Citation

  • Mei Lin & Zhiqiang Qiu & Mengen Hao & Weiwei Qi & Ting Zhang & Yuting Shen & Hongrui Xiao & Chaoyue Liang & Longxu Xie & Yongzhong Jiang & Meng Cheng & Tian Tian & Xiaoming Zhou, 2025. "Cas12a Cis-cleavage mediated lateral flow assay enables multiplex and ultra-specific nucleic acid detection," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-60917-9
    DOI: 10.1038/s41467-025-60917-9
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-60917-9
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-025-60917-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Cheri M. Ackerman & Cameron Myhrvold & Sri Gowtham Thakku & Catherine A. Freije & Hayden C. Metsky & David K. Yang & Simon H. Ye & Chloe K. Boehm & Tinna-Sólveig F. Kosoko-Thoroddsen & Jared Kehe & Ti, 2020. "Massively multiplexed nucleic acid detection with Cas13," Nature, Nature, vol. 582(7811), pages 277-282, June.
    2. Santosh R. Rananaware & Emma K. Vesco & Grace M. Shoemaker & Swapnil S. Anekar & Luke Samuel W. Sandoval & Katelyn S. Meister & Nicolas C. Macaluso & Long T. Nguyen & Piyush K. Jain, 2023. "Programmable RNA detection with CRISPR-Cas12a," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. Yanan Tang & Turun Song & Lu Gao & Saifu Yin & Ming Ma & Yun Tan & Lijuan Wu & Yang Yang & Yanqun Wang & Tao Lin & Feng Li, 2022. "A CRISPR-based ultrasensitive assay detects attomolar concentrations of SARS-CoV-2 antibodies in clinical samples," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    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. Huiyou Chen & Fengge Song & Buhua Wang & Hui Huang & Yanchi Luo & Xiaosheng Han & Hewen He & Shaolu Lin & Liudang Wan & Zhengliang Huang & Zhaoyong Fu & Rodrigo Ledesma-Amaro & Dapeng Yin & Haimei Mao, 2025. "Ultrasensitive detection of clinical pathogens through a target-amplification-free collateral-cleavage-enhancing CRISPR-CasΦ tool," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    2. Sri Gowtham Thakku & Jackson Lirette & Kanagavel Murugesan & Julie Chen & Grant Theron & Niaz Banaei & Paul C. Blainey & James Gomez & Sharon Y. Wong & Deborah T. Hung, 2023. "Genome-wide tiled detection of circulating Mycobacterium tuberculosis cell-free DNA using Cas13," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Andrew Bo Liu & Daniel Lee & Amogh Prabhav Jalihal & William P. Hanage & Michael Springer, 2023. "Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    4. Zhichen Xu & Dongjuan Chen & Tao Li & Jiayu Yan & Jiang Zhu & Ting He & Rui Hu & Ying Li & Yunhuang Yang & Maili Liu, 2022. "Microfluidic space coding for multiplexed nucleic acid detection via CRISPR-Cas12a and recombinase polymerase amplification," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    5. Xiaolong Cheng & Zexu Li & Ruocheng Shan & Zihan Li & Shengnan Wang & Wenchang Zhao & Han Zhang & Lumen Chao & Jian Peng & Teng Fei & Wei Li, 2023. "Modeling CRISPR-Cas13d on-target and off-target effects using machine learning approaches," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    6. Yichuan Chen & Xinping Wang & Junqi Zhang & Qingyuan Jiang & Bin Qiao & Baoxia He & Wenhao Yin & Jie Qiao & Yi Liu, 2024. "Split crRNA with CRISPR-Cas12a enabling highly sensitive and multiplexed detection of RNA and DNA," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    7. Huang, Fengfeng & Guo, Pengfei & Wang, Yulan, 2022. "Optimal group testing strategy for the mass screening of SARS-CoV-2," Omega, Elsevier, vol. 112(C).
    8. Jiaqi Wang & Xiaofang Ye & Yuanfang Liu & Wentao Li & Xue Zhang & Wei Zhang & Changqing Yi & Chaoxing Liu, 2025. "Regulating cleavage activity and enabling microRNA detection with split sgRNA in Cas12b," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    9. Yinqiu Ji & Christopher C. M. Baker & Viorel D. Popescu & Jiaxin Wang & Chunying Wu & Zhengyang Wang & Yuanheng Li & Lin Wang & Chaolang Hua & Zhongxing Yang & Chunyan Yang & Charles C. Y. Xu & Alex D, 2022. "Measuring protected-area effectiveness using vertebrate distributions from leech iDNA," Nature Communications, Nature, vol. 13(1), pages 1-17, December.
    10. Yuqian Guo & Yaofeng Zhou & Hong Duan & Derong Xu & Min Wei & Yuhao Wu & Ying Xiong & Xirui Chen & Siyuan Wang & Daofeng Liu & Xiaolin Huang & Hongbo Xin & Yonghua Xiong & Ben Zhong Tang, 2024. "CRISPR/Cas-mediated “one to more” lighting-up nucleic acid detection using aggregation-induced emission luminogens," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    11. Aidan T. Riley & James M. Robson & Aiganysh Ulanova & Alexander A. Green, 2025. "Generative and predictive neural networks for the design of functional RNA molecules," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    12. Yiran He & Min Jiang & Zhenlong Liang & Zhaoxu Luo & Jingyi Qin & Ye Shen & Yayun Gu & Xiaodong Ma & Hong Wang & Xin Li & Ying Shi & Yanhua Chen & Kefeng Pu & Jiong Li, 2025. "Lab-in-a-Tip: a multiplex immunoassay platform based on a self-assembled barcoded protein array," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    13. Chunlei Jiao & Natalia L. Peeck & Jiaqi Yu & Mohammad Ghaem Maghami & Sarah Kono & Daphne Collias & Sandra L. Martinez Diaz & Rachael Larose & Chase L. Beisel, 2024. "TracrRNA reprogramming enables direct PAM-independent detection of RNA with diverse DNA-targeting Cas12 nucleases," Nature Communications, Nature, vol. 15(1), pages 1-15, December.

    More about this item

    Statistics

    Access and download statistics

    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:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-60917-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.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.