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Model-directed generation of CRISPR-Cas13a guide RNAs designs artificial sequences that improve nucleic acid detection.
Mantena, Sreekar; Pillai, Priya P; Petros, Brittany A; Welch, Nicole L; Myhrvold, Cameron; Sabeti, Pardis C; Metsky, Hayden C.
Afiliación
  • Mantena S; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Pillai PP; Department of Statistics, Harvard University, Cambridge, MA, USA.
  • Petros BA; Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
  • Welch NL; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Myhrvold C; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Sabeti PC; Division of Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Cambridge, MA, USA.
  • Metsky HC; Harvard/Massachusetts Institute of Technology, MD-PhD Program, Boston, MA, USA.
bioRxiv ; 2023 Sep 20.
Article en En | MEDLINE | ID: mdl-37786711
Generating maximally-fit biological sequences has the potential to transform CRISPR guide RNA design as it has other areas of biomedicine. Here, we introduce model-directed exploration algorithms (MEAs) for designing maximally-fit, artificial CRISPR-Cas13a guides-with multiple mismatches to any natural sequence-that are tailored for desired properties around nucleic acid diagnostics. We find that MEA-designed guides offer more sensitive detection of diverse pathogens and discrimination of pathogen variants compared to guides derived directly from natural sequences, and illuminate interpretable design principles that broaden Cas13a targeting.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: BioRxiv Año: 2023 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos