Multiplexed genome engineering with RNA-guided nucleases from CRISPR-Cas systems

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Fei Ann Ran, Le Cong, Shuailiang Lin, Ophir Shalem, Naomi Habib, Patrick David Hsu, Feng Zhang

The Broad Institute of MIT and Harvard, United States

The ability to engineer biological circuits and organisms for biomedical and technological applications is one of the key goals of synthetic biology. Constructing synthetic biological systems via genome engineering requires efficient and precise tools for manipulating genetic information and regulation. The currently available genome editing systems – designer zinc fingers, transcription activator-like effectors, and homing meganucleases – each have made enormous progress towards this end yet have unique limitations; there remains a need for tools that are easy to assemble, affordable, and amenable to multiplexed gene editing. The type II CRISPR (clustered regularly interspaced short palindromic repeats) loci found in bacteria function as an adaptive immune system that uses a pair of non-coding RNAs, crRNA and tracrRNA, to guide the Cas9 nuclease for site-specific DNA cleavage, presenting a simple, RNA-programmable system that can be harnessed to mediate genome editing in mammalian cells. We engineered two type II CRISPR systems from Streptococcus pyogenes SF370 and S. thermophilus LMD-9 through heterologous expression of the key protein and RNA components in mouse and human cells. We show that Cas9 nucleases can be guided by custom RNAs to introduce double stranded break (DSB) at multiple endogenous loci with high efficiency (up to 59%). Furthermore, we have engineered Cas9 into a nicking enzyme to minimize mutagenic DNA repair processes while maintaining the ability to facilitate template-directed homologous recombination for gene insertion or modification. Finally, we have encoded a pair of guide sequences into a single CRISPR array to direct simultaneous editing of multiple sites within the human genome. This technology will enable applications across basic science, biotechnology, and medicine, as well as allow scalable and iterative optimization of designer, multi-component biological systems.