Model-directed generation of artificial CRISPR-Cas13a guide RNA sequences improves nucleic acid detection

Sreekar Mantena; Priya P Pillai; Brittany A Petros; Nicole L Welch; Cameron Myhrvold; Pardis C Sabeti; Hayden C Metsky

doi:10.1038/s41587-024-02422-w

Model-directed generation of artificial CRISPR-Cas13a guide RNA sequences improves nucleic acid detection

Nat Biotechnol. 2024 Oct 11. doi: 10.1038/s41587-024-02422-w. Online ahead of print.

Authors

Sreekar Mantena^{1

2

3}, Priya P Pillai¹, Brittany A Petros^{1

4

5

6}, Nicole L Welch¹, Cameron Myhrvold^{7

8

9

10}, Pardis C Sabeti^#^{11

12

13

14}, Hayden C Metsky^#¹⁵

Affiliations

¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
² Department of Statistics, Harvard University, Cambridge, MA, USA.
³ Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
⁴ Division of Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Cambridge, MA, USA.
⁵ MD-PhD Program, Harvard/Massachusetts Institute of Technology, Boston, MA, USA.
⁶ Department of Systems Biology, Harvard Medical School, Boston, MA, USA.
⁷ Department of Molecular Biology, Princeton University, Princeton, NJ, USA.
⁸ Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA.
⁹ Omenn-Darling Bioengineering Institute, Princeton University, Princeton, NJ, USA.
¹⁰ Department of Chemistry, Princeton University, Princeton, NJ, USA.
¹¹ Broad Institute of MIT and Harvard, Cambridge, MA, USA. pardis@broadinstitute.org.
¹² Howard Hughes Medical Institute, Chevy Chase, MD, USA. pardis@broadinstitute.org.
¹³ Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA. pardis@broadinstitute.org.
¹⁴ Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA. pardis@broadinstitute.org.
¹⁵ Broad Institute of MIT and Harvard, Cambridge, MA, USA. hayden@broadinstitute.org.

^# Contributed equally.

PMID: 39394482
DOI: 10.1038/s41587-024-02422-w

Abstract

CRISPR guide RNA sequences deriving exactly from natural sequences may not perform optimally in every application. Here we implement and evaluate algorithms for designing maximally fit, artificial CRISPR-Cas13a guides with multiple mismatches to natural sequences that are tailored for diagnostic applications. These guides offer more sensitive detection of diverse pathogens and discrimination of pathogen variants compared with guides derived directly from natural sequences and illuminate design principles that broaden Cas13a targeting.

Abstract

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