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Massively multiplexed nucleic acid detection with Cas13

Author

Listed:
  • Cheri M. Ackerman

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Department of Biological Engineering, MIT)

  • Cameron Myhrvold

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Harvard University)

  • Sri Gowtham Thakku

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Harvard Medical School and MIT)

  • Catherine A. Freije

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Harvard Medical School)

  • Hayden C. Metsky

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Department of Electrical Engineering and Computer Science, MIT)

  • David K. Yang

    (Broad Institute of Massachusetts Institute of Technology and Harvard)

  • Simon H. Ye

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Harvard Medical School and MIT)

  • Chloe K. Boehm

    (Broad Institute of Massachusetts Institute of Technology and Harvard)

  • Tinna-Sólveig F. Kosoko-Thoroddsen

    (Broad Institute of Massachusetts Institute of Technology and Harvard)

  • Jared Kehe

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Department of Biological Engineering, MIT)

  • Tien G. Nguyen

    (Broad Institute of Massachusetts Institute of Technology and Harvard)

  • Amber Carter

    (Broad Institute of Massachusetts Institute of Technology and Harvard)

  • Anthony Kulesa

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Department of Biological Engineering, MIT)

  • John R. Barnes

    (Centers for Disease Control and Prevention)

  • Vivien G. Dugan

    (Centers for Disease Control and Prevention)

  • Deborah T. Hung

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Massachusetts General Hospital)

  • Paul C. Blainey

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Department of Biological Engineering, MIT
    Koch Institute for Integrative Cancer Research at MIT)

  • Pardis C. Sabeti

    (Broad Institute of Massachusetts Institute of Technology and Harvard
    Harvard University
    Howard Hughes Medical Institute
    Harvard T.H. Chan School of Public Health)

Abstract

The great majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples1–3 while simultaneously testing for many pathogens4–6. Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanolitre droplets containing CRISPR-based nucleic acid detection reagents7 self-organize in a microwell array8 to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN–Cas13) enables robust testing of more than 4,500 crRNA–target pairs on a single array. Using CARMEN–Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with at least 10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN–Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. The intrinsic multiplexing and throughput capabilities of CARMEN make it practical to scale, as miniaturization decreases reagent cost per test by more than 300-fold. Scalable, highly multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health9–11.

Suggested Citation

  • 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.
  • Handle: RePEc:nat:nature:v:582:y:2020:i:7811:d:10.1038_s41586-020-2279-8
    DOI: 10.1038/s41586-020-2279-8
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    Citations

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    Cited by:

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. Huang, Fengfeng & Guo, Pengfei & Wang, Yulan, 2022. "Optimal group testing strategy for the mass screening of SARS-CoV-2," Omega, Elsevier, vol. 112(C).
    6. 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.

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