Discovery of novel CRISPR enzymes for transcriptome engineering and human health

RNA plays important and diverse roles in biology, yet molecular tools to measure and manipulate RNA are limited. Recently, the bacterial adaptive immune system, CRISPR, has revolutionized our ability to manipulate DNA, but no known RNA-targeting versions exist. To discover parallel bacterial RNA-targeting systems that could be used for transcriptome engineering, we developed a computational pipeline to mine for novel Class 2 CRISPR systems across more than 25,000 bacterial genomes. Among the many novel CRISPR systems, we found a programmable RNA-targeting CRISPR system, CRISPR-Cas 13, that could provide immunity to E. coli against the ssRNA MS2 phage and biochemically characterized the enzyme. We adapted CRISPR-Casl3 for modulating the transcriptome in mammalian and plant cells by heterologously expressing Casl 3 and engineering the enzyme to precisely knockdown, bind, and edit RNA. Cas 13 knockdown was as efficient as RNA interference, but much more specific, across many transcripts tested. RNA editing with Cas 13 was also highly efficient, with up to 90% base editing rates, and as low as 20 off-targets with engineered specificity versions. Lastly, we combined Cas13 with isothermal amplification to develop a CRISPR-based diagnostic (CRISPR-Dx), providing rapid DNA or RNA detection with single-molecule sensitivity and singlebase mismatch specificity. We used this Casl3a-based molecular detection platform, termed SHERLOCK (Specific High Sensitivity Enzymatic Reporter UnLOCKing), to specifically detect pathogenic bacteria, genotype human DNA, and identify cell-free tumor DNA mutations. Our results establish CRISPR-Cas13 as a flexible platform for RNA targeting with wide applications in RNA biology, diagnostics, and therapeutics.

Department dc:contributor.department

Harvard--MIT Program in Health Sciences and Technology.

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2018

Author dc:creator

• Abudayyeh, Omar O

Advisor dc:contributor.advisor

• Feng Zhang.

• Harvard--MIT Program in Health Sciences and Technology.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/120887

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/120887