FnCas9 based CRISPR diagnostic for rapid and accurate detection of major SARS-CoV2 variants on a paper strip

  1. Manoj Kumar
  2. Sneha Gulati
  3. Asgar H Ansari
  4. Rhythm Phutela
  5. Sundaram Acharya
  6. Mohd Azhar
  7. Jayaram Murthy
  8. Poorti Kathpalia
  9. Akshay Kanakan
  10. Ranjeet Maurya
  11. Janani Srinivasa Vasudevan
  12. Aparna Murali
  13. Rajesh Pandey
  14. Souvik Maiti  Is a corresponding author
  15. Debojyoti Chakraborty  Is a corresponding author
  1. CSIR Institute of Genomics and Integrative Biology, India
  2. CSIR-Institute of Genomics and Integrative Biology, India

Abstract

The COVID-19 pandemic originating in the Wuhan province of China in late 2019 has impacted global health, causing increased mortality among elderly patients and individuals with comorbid conditions. During the passage of the virus through affected populations, it has undergone mutations, some of which have recently been linked with increased viral load and prognostic complexities. Several of these variants are point mutations that are difficult to diagnose using the gold standard quantitative real-time PCR (qRT-PCR) method and necessitates widespread sequencing which is expensive, has long turn-around times, and requires high viral load for calling mutations accurately. Here, we repurpose the high specificity of Francisella novicida Cas9 (FnCas9) to identify mismatches in the target for developing a lateral flow assay that can be successfully adapted for the simultaneous detection of SARS-CoV2 infection as well as for detecting point mutations in the sequence of the virus obtained from patient samples. We report the detection of the S gene mutation N501Y (present across multiple variant lineages of SARS-CoV2) within an hour using lateral flow paper strip chemistry. The results were corroborated using deep sequencing on multiple wild type (n=37) and mutant (n=22) viral RNA samples with a sensitivity of 87% and specificity of 97%. The design principle can be rapidly adapted for other mutations (as shown also for E484K and T716I) highlighting the advantages of quick optimization and roll-out of CRISPR diagnostics (CRISPRDx) for disease surveillance even beyond COVID-19. This study was funded by Council for Scientific and Industrial Research, India.

Data availability

Sequencing data associated with the manuscript have been deposited to GISAID with the following numbers:EPI_ISL_911542, EPI_ISL_911532, EPI_ISL_911543, EPI_ISL_911533, EPI_ISL_911544, EPI_ISL_911534, EPI_ISL_911545, EPI_ISL_911535, EPI_ISL_911546, EPI_ISL_911536, EPI_ISL_911547, EPI_ISL_911537, EPI_ISL_911538, EPI_ISL_911540, EPI_ISL_911541, EPI_ISL_911539 were just released and are now available to all participants in GISAID.

Article and author information

Author details

  1. Manoj Kumar

    in, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0772-1399
  2. Sneha Gulati

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  3. Asgar H Ansari

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  4. Rhythm Phutela

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  5. Sundaram Acharya

    IGIB, CSIR Institute of Genomics and Integrative Biology, New Delhi, India
    Competing interests
    No competing interests declared.
  6. Mohd Azhar

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    Mohd Azhar, Mohd. Azhar is currently an employee of TATA Medical and Diagnostics.
  7. Jayaram Murthy

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  8. Poorti Kathpalia

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  9. Akshay Kanakan

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  10. Ranjeet Maurya

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  11. Janani Srinivasa Vasudevan

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3381-5228
  12. Aparna Murali

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, Delhi, India
    Competing interests
    No competing interests declared.
  13. Rajesh Pandey

    CSIR Ayurgenomics Unit (TRISUTRA), CSIR Institute of Genomics and Integrative Biology, New Delhi, India
    Competing interests
    No competing interests declared.
  14. Souvik Maiti

    Chemical and Systems Biology, CSIR-Institute of Genomics and Integrative Biology, New Delhi, India
    For correspondence
    souvik@igib.res.in
    Competing interests
    No competing interests declared.
  15. Debojyoti Chakraborty

    Genomics and Molecular Medicine, CSIR Institute of Genomics and Integrative Biology, New Delhi, India
    For correspondence
    debojyoti.chakraborty@igib.in
    Competing interests
    Debojyoti Chakraborty, A patent application has been filed in relation to this work. (0127NF2019)..
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1460-7594

Funding

University Grants Commission (Graduate student fellowship)

  • Manoj Kumar

IUSSTF (CLP-0033)

  • Rajesh Pandey

CSIR Sickle Cell Anemia Mission (HCP0008)

  • Debojyoti Chakraborty

Tata Steel (SSP 2001)

  • Debojyoti Chakraborty

Lady Tata Young Investigator (GAP0198)

  • Debojyoti Chakraborty

CSIR Sickle Cell Anemia Mission (HCP0008)

  • Souvik Maiti

CSIR (Graduate Student fellowship)

  • Mohd Azhar

CSIR (Graduate Student fellowship)

  • Jayaram Murthy

CSIR (Research Associateship)

  • Sneha Gulati

Indian Council of Medical Research (Graduate Student fellowship)

  • Asgar H Ansari

CSIR (Graduate Student fellowship)

  • Rhythm Phutela

CSIR (Graduate Student fellowship)

  • Sundaram Acharya

CSIR (Research Associateship)

  • Poorti Kathpalia

CSIR (MLP 2005)

  • Rajesh Pandey

Fondation Botnar (CLP-0031)

  • Rajesh Pandey

Intel Corporation (CLP-0034)

  • Rajesh Pandey

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: The present study was approved by the Ethics Committee, Institute of Genomics and Integrative Biology, New Delhi (CSIR-IGIB/IHEC/2020-21/01.)

Reviewing Editor

  1. Yamuna Krishnan, University of Chicago, United States

Publication history

  1. Received: February 1, 2021
  2. Accepted: June 7, 2021
  3. Accepted Manuscript published: June 9, 2021 (version 1)
  4. Version of Record published: July 19, 2021 (version 2)

Copyright

© 2021, Kumar et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Manoj Kumar
  2. Sneha Gulati
  3. Asgar H Ansari
  4. Rhythm Phutela
  5. Sundaram Acharya
  6. Mohd Azhar
  7. Jayaram Murthy
  8. Poorti Kathpalia
  9. Akshay Kanakan
  10. Ranjeet Maurya
  11. Janani Srinivasa Vasudevan
  12. Aparna Murali
  13. Rajesh Pandey
  14. Souvik Maiti
  15. Debojyoti Chakraborty
(2021)
FnCas9 based CRISPR diagnostic for rapid and accurate detection of major SARS-CoV2 variants on a paper strip
eLife 10:e67130.
https://doi.org/10.7554/eLife.67130
  1. Further reading

Further reading

    1. Epidemiology and Global Health
    Nikkil Sudharsanan et al.
    Research Article

    Background:

    Fear over side-effects is one of the main drivers of COVID-19 vaccine hesitancy. A large literature in the behavioral and communication sciences finds that how risks are framed and presented to individuals affects their judgments of its severity. However, it remains unknown whether such framing changes can affect COVID-19 vaccine behavior and be deployed as policy solutions to reduce hesitancy.

    Methods:

    We conducted a pre-registered randomized controlled trial among 8998 participants in the United States and the United Kingdom to examine the effects of different ways of framing and presenting vaccine side-effects on individuals’ willingness to get vaccinated and their perceptions of vaccine safety.

    Results:

    Adding a descriptive risk label (‘very low risk’) next to the numerical side-effect and providing a comparison to motor-vehicle mortality increased participants’ willingness to take the COVID-19 vaccine by 3.0 percentage points (p=0.003) and 2.4 percentage points (p=0.049), respectively. These effects were independent and additive and combining both framing strategies increased willingness to receive the vaccine by 6.1 percentage points (p<0.001). Mechanistically, we find evidence that these framing effects operate by increasing individuals’ perceptions of how safe the vaccine is.

    Conclusions:

    Low-cost side-effect framing strategies can meaningfully affect vaccine intentions at a population level.

    Funding:

    Heidelberg Institute of Global Health.

    Clinical trial number:

    German Clinical Trials Registry (#DRKS00025551).

    1. Epidemiology and Global Health
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    Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) have been key drivers of new coronavirus disease 2019 (COVID-19) pandemic waves. To better understand variant epidemiologic characteristics, here we apply a model-inference system to reconstruct SARS-CoV-2 transmission dynamics in South Africa, a country that has experienced three VOC pandemic waves (i.e. Beta, Delta, and Omicron BA.1) by February 2022. We estimate key epidemiologic quantities in each of the nine South African provinces during March 2020 to February 2022, while accounting for changing detection rates, infection seasonality, nonpharmaceutical interventions, and vaccination. Model validation shows that estimated underlying infection rates and key parameters (e.g. infection-detection rate and infection-fatality risk) are in line with independent epidemiological data and investigations. In addition, retrospective predictions capture pandemic trajectories beyond the model training period. These detailed, validated model-inference estimates thus enable quantification of both the immune erosion potential and transmissibility of three major SARS-CoV-2 VOCs, that is, Beta, Delta, and Omicron BA.1. These findings help elucidate changing COVID-19 dynamics and inform future public health planning.