RNA-dependent RNA targeting by CRISPR-Cas9

Abstract
eLife digest
Introduction
Results
Discussion
Materials and methods
Data availability
References
Article and author information
Metrics

Abstract

Double-stranded DNA (dsDNA) binding and cleavage by Cas9 is a hallmark of type II CRISPR-Cas bacterial adaptive immunity. All known Cas9 enzymes are thought to recognize DNA exclusively as a natural substrate, providing protection against DNA phage and plasmids. Here, we show that Cas9 enzymes from both subtypes II-A and II-C can recognize and cleave single-stranded RNA (ssRNA) by an RNA-guided mechanism that is independent of a protospacer-adjacent motif (PAM) sequence in the target RNA. RNA-guided RNA cleavage is programmable and site-specific, and we find that this activity can be exploited to reduce infection by single-stranded RNA phage in vivo. We also demonstrate that Cas9 can direct PAM-independent repression of gene expression in bacteria. These results indicate that a subset of Cas9 enzymes have the ability to act on both DNA and RNA target sequences, and suggest the potential for use in programmable RNA targeting applications.

https://doi.org/10.7554/eLife.32724.001

eLife digest

Similar to humans, bacteria use an immune system known as the CRISPR-Cas system to protect themselves against invading pathogens such as viruses. CRISPRs are specialized stretches of DNA that guide Cas9 to the right location, while Cas9 proteins act like scissors that can cut foreign DNA.

When a virus infects a bacterium, the bacterium steals a piece of DNA from the virus and stores it in its CRISPR region. The bacterium then produces a small RNA template that matches the stolen DNA of the virus and adds a specialized protein to it. When the virus infects the cell again, the protein-RNA complex can recognize the virus and stop the infection.

Researchers have successfully adapted this system as a gene-editing tool to target and modify specific DNA sequences in different organisms. Cas9 can target and cut DNA, but until now, it was not clear whether this protein could also efficiently target RNA – the ‘genetic middleman’ between DNA and proteins. RNA is essential to make proteins, and being able to target RNA would allow researchers to answer many important questions about RNA biology.

To investigate this further, Strutt et al. used three different subtypes of Cas9 proteins and small RNA sequences in a test tube. The results showed that two of the protein subtypes could target RNA efficiently, and one of which was able to target any RNA sequence. Strutt et al. then used one Cas9 to target specific RNA sequences in bacteria and were able to reduce the amount of protein made from that gene. Moreover, the Cas9 protein helped to protect the bacteria against an RNA virus.

This work lays the foundation for using this Cas9 protein as a tool for researchers to study RNA in cells. A next step will be to test if Cas9 can cut RNA in human cells. If this works, it could allow direct targeting of RNA viruses, such as West Nile and Dengue, to stop them from infecting human cells.

https://doi.org/10.7554/eLife.32724.002

Introduction

Prokaryotic clustered regularly interspaced short palindromic repeat (CRISPR)-CRISPR-associated (Cas) systems provide immunity against plasmids and bacteriophage by using foreign DNA stored as CRISPR spacer sequences together with Cas nucleases to stop infection (Wright et al., 2016; Mohanraju et al., 2016). One such nuclease, Cas9 of the type II systems, employs a CRISPR RNA (crRNA) and a trans-activating crRNA (tracrRNA) to target spacer-complementary regions (protospacers) on the foreign genetic element to guide double-stranded DNA cleavage (Jinek et al., 2012). A protospacer adjacent motif (PAM) must also be present for the Cas9-RNA complex to bind and cleave DNA (Jinek et al., 2012; Gasiunas et al., 2012; Anders et al., 2014; Szczelkun et al., 2014). Combining the crRNA and tracrRNA into a chimeric, single-guide RNA (sgRNA) simplified the system for widespread adoption as a versatile genome editing technology (Jinek et al., 2012).

To date, both genetic and biochemical data support the conclusion that in vivo, Cas9 is exclusively a DNA-targeting enzyme. Nonetheless, multiple studies have harnessed Cas9 for RNA targeting under specific circumstances. For example, the S. pyogenes Cas9 (SpyCas9) can be supplied with a short DNA oligo containing the PAM sequence (a PAMmer) to induce single-stranded RNA (ssRNA) binding and cutting (O'Connell et al., 2014; Nelles et al., 2016). More recently, it was demonstrated that SpyCas9 could be used to target repetitive RNAs and repress translation in certain mRNAs in the absence of a PAMmer (Liu et al., 2016; Batra et al., 2017). A different Cas9 homolog from Francisella novicida (FnoCas9) has been implicated in degradation of a specific mRNA but through a mechanism independent of RNA-based cleavage (Sampson et al., 2013). Together with evidence that some Cas9 homologs can target single-stranded DNA substrates under some conditions (Ma et al., 2015; Zhang et al., 2015), these studies raised the possibility that certain Cas9 enzymes might have intrinsic RNA-guided RNA cleavage activity.

To determine whether evolutionarily divergent Cas9 homologs have a native capacity for programmable RNA targeting, we compared biochemical behavior of enzymes from the three major Cas9 subtypes. This analysis revealed that certain type II-A and II-C Cas9s can bind and cleave single-stranded RNA sequences with no requirement for a PAM or PAMmer. Furthermore, we found that this activity can inhibit gene expression and confer moderate protection against infection by ssRNA phage through a mechanism reminiscent of RNA-guided DNA targeting. These results establish the utility of Cas9 for facile RNA-guided RNA targeting and suggest that this activity may have biological relevance in bacteria.

Results

Cas9 catalyzes PAM-independent RNA-guided RNA cleavage

To assess whether divergent Cas9 enzymes can catalyze binding to and cleavage of RNA substrates by a mechanism distinct from that of double-stranded DNA cleavage, we tested homologs from the three major subtypes of Cas9 proteins for their ability to cleave single-stranded RNA in vitro (Figure 1A,B; Figure 1—figure supplement 1A–C). When programmed with a cognate sgRNA, S. aureus Cas9 (SauCas9) and C. jejuni Cas9 (CjeCas9) direct cleavage of RNA in the absence of a PAMmer (Figure 1; Figure 1—figure supplement 1). No RNA cleavage was detected using SpyCas9, which requires a PAMmer for efficient RNA cleavage in vitro (O'Connell et al., 2014), or using F. novicida Cas9 (FnoCas9). While the cleavage efficiencies for both SauCas9 and CjeCas9 are indistinguishable (Figure 1—figure supplement 1D), we focused on the activity of SauCas9 due to the abundance of mechanistic and structural data for this enzyme (Nishimasu et al., 2015; Friedland et al., 2015; Ran et al., 2015; Kleinstiver et al., 2015).

Figure 1 with 4 supplements see all

Download asset Open asset

SauCas9 cleaves single-stranded RNA without a PAMmer.

(A) Schematic of Cas9 proteins tested for sgRNA-mediated RNA cleavage. RuvC, RuvC nuclease domain; BH, bridge-helix; REC, recognition domain; HNH, HNH nuclease domain; PLL, phosphate-lock loop; WED, wedge domain; PI, PAM-interacting domain. Adapted from (Nishimasu et al., 2014; 2015; Hirano et al., 2016; Yamada et al., 2017). (B) Representative in vitro cleavage of ssRNA by Cas9-sgRNA RNP complexes of homologs in (A). Radiolabeled pUC target RNA was incubated with Cas9 RNP at 37˚C and time points were taken at 0, 10, 30, and 60 min. Full time course is presented in Figure 1—figure supplement 1B. T1 indicates size markers generated by RNase T1 digestion of ssRNA target. Size in nucleotides is indicated on the left. (C) (Right) In vitro cleavage assay of various RNA substrates (Left). Full time course is presented in Figure 1—figure supplement 3A.

https://doi.org/10.7554/eLife.32724.003

RNA cleavage activity and products were similar to those of canonical Cas9-mediated DNA cleavage activity in vitro. RNA targeting by SauCas9 requires the presence of a guide RNA and a catalytically-active protein, as both apo protein lacking the guide RNA and a catalytically inactive mutant (D10A and N580A) do not cleave RNA (Figure 1—figure supplement 2A). Furthermore, addition of EDTA to chelate divalent metal ions abolished RNA cleavage, verifying that divalent metal ions are necessary for catalysis. As with DNA substrates (Sternberg et al., 2014), incubation of SauCas9 with an excess of RNA target demonstrated that cleavage is single-turnover (Figure 1—figure supplement 2B,C). Hydrolysis mapping of the cleavage product revealed that the predominant RNA cleavage site is shifted by one nucleotide compared to the site of DNA cleavage (Garneau et al., 2010; Jinek et al., 2012; Gasiunas et al., 2012) (Figure 1—figure supplement 2D,E). The shift is consistent with that observed for PAM-dependent SpyCas9 RNA-cleavage (O'Connell et al., 2014) and is likely due to the more compact geometry of an RNA-RNA helix relative to an RNA-DNA hybrid helix (Wang et al., 1982).

SauCas9 targets ssRNA in the absence of a PAMmer, a contrast to SpyCas9 targeting of ssRNA (O'Connell et al., 2014). Testing SauCas9 in vitro ssRNA cleavage in the presence of a PAMmer (30x molar excess over ssRNA target) revealed that turn-over was two-fold slower than the reaction with only target ssRNA (Figure 1C, Figure 1—figure supplement 3C). SauCas9 ssRNA cleavage conducted in the presence of a non-complementary, control DNA oligo did not yield a similar reduction in cleavage rate (Figure 1—figure supplement 3C), indicating that the complementary PAMmer impairs RNA cleavage activity. Consistent with cleavage being guide-dependent, single-stranded RNA that is not complementary to the sgRNA is not cleaved (Figure 1 and Figure 1—figure supplement 3). Double-stranded RNA (dsRNA) is also not a substrate for SauCas9.

Given that Cas9 proteins are active with different length guide RNA segments (~20–24 nt) (Chylinski et al., 2013; Ran et al., 2015; Friedland et al., 2015; Kim et al., 2017), we tested whether longer guide segments might enhance ssRNA targeting activity. Increasing the length of the targeting region of the guide up to 23 nt results in tighter binding and more efficient cleavage (Figure 1—figure supplement 4), mirroring the preference for longer guides for DNA cleavage (Ran et al., 2015; Friedland et al., 2015). Extending the guide strand complementarity to the target beyond 23 nt did not increase RNA target binding or cleavage efficiency, indicating that 23 nt is the optimal length for in vitro binding and targeting applications. The apparent dissociation constant (K_d,app) of the SauCas9-sgRNA complex (23 nt targeting region) for the ssRNA target is 1.8 ± 0.09 nM (Figure 1—figure supplement 4D), which is ~5 x weaker than the 0.34 ± 0.03 nM binding affinity measured for a dsDNA substrate of the same sequence.

Cleavage efficiency is impaired by duplex regions in target RNA

We noted that SauCas9-catalyzed ssRNA cleavage is limited to ~30% fraction cleaved (Figure 1—figure supplement 3), compared to >80% fraction cleaved for ssDNA and dsDNA targets. Greater thermodynamic stability of RNA secondary structures, relative to those in ssDNA (Bercy and Bockelmann, 2015), might occlude SauCas9-sgRNA binding to an ssRNA target sequence, a possibility that we tested using a panel of partially duplexed RNA substrates (Figure 2). Previously, introduction of a short segment of mismatched base pairs to mimic partially unwound dsDNA substrates was shown to enhance the ability of type II-C Cas9s (including CjeCas9) to unwind and cleave dsDNA (Ma et al., 2015). Here, we found that duplex-RNA substrates containing a 2- or 6-base pair mismatched segment located near the 5’ or 3’ end of the 23 nt guide RNA region of the sgRNA could not be cleaved (Figure 2A–C, substrates 5, 6, 10, and 11). However, when the unpaired region was increased to 12-base pairs, SauCas9 was able to cleave the target strand. There was a slight cleavage preference for RNA substrates in which the 12-base pair mismatched segment is located near the 5´ end of the guide sequence of the sgRNA (Figure 2A–C, substrates 7 and 12).

Figure 2 with 1 supplement see all

Download asset Open asset

In vitro RNA cleavage is impaired by strong secondary structure.

(A) Schematic representation of structured RNA targets for in vitro cleavage assays. Symbols on right indicate relative level of cleavage activity for each substrate: ‘-”, no cleavage; ‘+”, low cleavage; ‘++”, medium cleavage; ‘+++” high cleavage. (B) Representative cleavage assay of partially-duplexed RNA targets diagrammed in (A). T1 indicates size markers generated by RNase T1 digestion of ssRNA target. Size in nucleotides is indicated on the left. (**C and D**) Fraction of target cleaved (C) and K_d,app (D) for substrates diagrammed in (A). Fits were determined in Prism using a single-exponential decay and a one-site binding model, respectively. Bars represent mean ± S.D. (n = 3). N.s. denotes no significant cleavage or binding.

https://doi.org/10.7554/eLife.32724.012

Figure 2—source data 1 Quantification of cleavage and binding of structured RNA substrates by SauCas9.: https://doi.org/10.7554/eLife.32724.015
Download elife-32724-fig2-data1-v2.xlsx

Interestingly, the 23-base pair mismatched segment RNA substrates (‘Bubble’ substrates 8 and 9) are targeted more efficiently than their ssRNA counterparts (substrates 1 and 2) (Figure 2C). We measured the binding affinity of all substrates and found that both the 23-base pair mismatched segment RNA and ssRNA substrates are bound with similar affinity (Figure 2D). Furthermore, the apparent difference in cleavage efficiency was not due to the presence of a double-stranded PAM sequence, as mutating the PAM region does not impair cleavage (Figure 2C, compare substrates 8 and 9). We hypothesize that RNA containing a mismatched segment presents a more accessible substrate to the Cas9-sgRNA complex due to stable annealing between the ends of the non-target and target strands, whereas the ssRNA substrate alone has ends that are predicted to stabilize a conformation that is partially structured and therefore inaccessible (Figure 2—figure supplement 1A).

An alternative hypothesis to explain the limited cleavage of ssRNA substrates is that SauCas9 enzyme inactivation occurs over the course of the reaction, even with SauCas9 protein-sgRNA (ribonucleoprotein, RNP) present in 10-fold excess relative to the ssRNA substrate. To test this, we spiked reactions with fresh SauCas9 protein alone or SauCas9 RNP after reactions reached equilibrium; however, we did not observe an increase in the amount of ssRNA cleavage (Figure 2—figure supplement 1B,C). We also tested whether the SauCas9 RNP was able to cleave a second ssRNA substrate that was added to the reaction after it reached completion (Figure 2—figure supplement 1D,E). After 1 hr of incubation, the addition of a second target ssRNA complementary to the guide RNA resulted in a burst of cleavage activity, whereas a non-complementary ssRNA substrate did not stimulate cleavage. The second target ssRNA is cleaved to a comparable extent to that observed when this second target was the only substrate in the reaction (Figure 2—figure supplement 1D,E, compare reactions 1 and 3). These observations suggest that SauCas9 RNP is still competent and available for cleavage at the end of the reaction and that a property intrinsic to the ssRNA substrate is the limiting factor. We propose that the observed difference in cleavage extents for various RNA substrates reflects the fraction of molecules that are structurally accessible for cleavage by the SauCas9 RNP.

SauCas9 confers in vivo protection against RNA phage

Based on the biochemical ability of SauCas9 RNP to bind and cleave ssRNA substrates, we wondered whether this activity might provide protection against RNA phage infection in bacteria. To test this, we generated a plasmid library encoding sgRNAs containing guide sequences complementary to the genome of MS2, a single-stranded RNA phage that can infect E. coli. A subset of these sgRNAs contained scrambled guide sequences that should not target MS2, providing negative controls. Another sgRNA subset included single-nucleotide mismatches introduced at each position of a target sequence to test for mismatch sensitivity in ssRNA recognition. This plasmid library, comprising 18,114 sgRNAs, was co-transformed into E. coli along with a vector encoding a catalytically active version of SauCas9 and the population of transformants was subjected to infection by bacteriophage MS2 (Figure 3A). The experiment was performed in biological triplicate and included an untreated control population and two experimental conditions (multiplicities of infection (MOIs) of 10 and 100). After selection, plasmids were recovered from surviving colonies and sequenced (Figure 3A).

Figure 3 with 4 supplements see all

Download asset Open asset

SauCas9 confers in vivo protection against an RNA phage.

(A) Overview of MS2 targeting screen. Guides tiled against the library were cloned into sgRNA expression plasmids and co-transformed into *E. coli* with a plasmid containing wild-type SauCas9 under inducible control. Plasmids from surviving colonies after MS2 selection were recovered and sequenced. For more detail, see Materials and methods. (B) Number of guides with significant positive enrichment from three biological experiments. SNP, guides with single-nucleotide mismatch. (C) Box and whiskers plot of average log₂ fold-change of perfect MS2 guides by length. Whiskers represent 5% and 95% values with outliers graphed as points. *p<0.05, **p<0.01, ****p<0.0001, by one-way ANOVA. (D) (Upper) Log₂ fold-change of guides with an FDR-corrected p-value<0.05 mapped to the MS2 genome for MOI-100 treatment. Schematic of MS2 genome is provided above. (Lower) Individual guides mapped to highlighted regions of MS2 genome. Other graphs for MOI-10 and −100 treatments are presented in Figure 3—figure supplement 1. (E) Representative plaque assay of SauCas9 in vivo protection. *E. coli* containing constructs on the right are spotted with various phage dilutions as indicated. Scr signifies that the targeting portion of the guide has been scrambled to serve as a non-targeting control. (F) Relative plaque forming units (PFU) (mean ± S.D., n = 3) from results in (E). More guides and controls are presented in Figure 3—figure supplement 3.

https://doi.org/10.7554/eLife.32724.016

Figure 3—source data 1 List of guides, normalized read counts, enriched guides, fold change distribution and plaque enumeration.: https://doi.org/10.7554/eLife.32724.025
Download elife-32724-fig3-data1-v2.xlsx

We identified between 131 and 166 sgRNAs that were significantly enriched (false discovery rate (FDR)-adjusted p-value<0.05) in the two different MS2 infection conditions (Figure 3B). The majority of these sgRNAs were perfectly complementary to the MS2 genome, and only three and five control sgRNAs (out of 708 total control sgRNAs) for the MOI-10 and −100 conditions, respectively, were enriched (Figure 3B). The lengths of enriched guide sequences were skewed toward shorter targeting lengths (Figure 3—figure supplement 1A, left); however, this likely reflects bias in the cloned input library since the ratio between the enriched guide sequences and those of the library without phage selection are similar (Figure 3—figure supplement 1A, right). When comparing the degree of enrichment between the different guide lengths, the 23-nt guide segment sgRNAs were preferentially enriched over those of shorter length (Figure 3C), consistent with the in vitro observation that longer guides are more efficient for directing ssRNA cleavage (Figure 1—figure supplement 4C). To assess whether there was any sequence bias within the enriched guides, we aligned guide sequences of all lengths at their 3’ end. These alignments showed no specific sequence bias in the enriched guides relative to those in the unselected library (Figure 3—figure supplement 1B). This is consistent with the crystal structure of an SauCas9-sgRNA-DNA-bound complex which revealed the absence of base-specific contacts of Cas9 to the target strand (Nishimasu et al., 2015).

Strikingly, mapping enriched guide sequences onto the MS2 genome showed that enriched sgRNAs were clustered at specific regions, which were consistent across both experimental conditions (Figure 3D; Figure 3—figure supplement 1C,D). Together with our biochemical data suggesting that SauCas9 cannot bind or cleave structured RNAs (Figure 3), we interpret these targeting ‘hotspots’ to be regions of low structural complexity. It is important to note that sgRNAs containing different guide segment lengths overlap at these regions, possibly indicating that increases in targeting efficiency due to guide length are secondary to target accessibility to the Cas9 RNP. We mapped the enriched guide sequences onto the published secondary structure of the MS2 genome determined through cryoelectron microscopy (Dai et al., 2017) (Figure 3—figure supplement 2). Guides targeted not only single-stranded, accessible regions but also those that form apparently stable secondary structures. The structure of the MS2 genome was determined on the intact phage particle, however, and may not represent the RNA structure(s) relevant to the infection stage during which SauCas9-mediated protection is crucial.

Highly enriched sgRNAs from the screen were confirmed for their ability to confer protection against MS2 phage infection through a soft-agar plaque assay. Reconstitution of SauCas9 with a targeting guide confers approximately a ten-fold protection against the RNA phage (Figure 3E,F). No protection was observed in the absence of an sgRNA or SauCas9 protein. Scrambling the sequence of the guide also abrogates protection, confirming that sequence complementary is necessary for phage elimination. Guide segments of all lengths tested (20–23 nts) conferred protection to a similar level (Figure 3—figure supplement 3A,B), consistent with the result from the MS2 screen that guide segments of all lengths were enriched in ‘hotspot’ regions (Figure 3D; Figure 3—figure supplement 1C). Two ‘control’ guides were enriched in both the MOI-10 and −100 treatments. Interestingly, both guides conferred protection but their scrambled counterparts did not (Figure 3—figure supplement 3C,D). Whereas a possible off-target binding site was found for one guide (#14238) within the MS2 genome (Figure 3—figure supplement 3E), it remains unclear how guide #14210 confers protection. Possibly this sgRNA acts by targeting an E. coli host factor that is necessary for infection.

Screening against the MS2 genome was also used to test the effect of single-nucleotide mismatches on SauCas9’s targeting ability. We computed an average fold change (between phage treated and untreated samples) for all sgRNAs that contained a mismatch at the same position, and obtained average values for mismatches at each position across the guide. We observed a pronounced gradient of increasing guide stringency with length. On average, short guides were less sensitive to mismatches, while mismatches in longer sgRNAs led to decreased recovery compared to control samples (Figure 3—figure supplement 4A,B). Previous work and models suggest that shorter guide segments should be more sensitive to mismatches and lead to higher fidelity Cas9 targeting (Fu et al., 2014; Bisaria et al., 2017). Further study is needed to thoroughly examine this unexpected pattern of RNA-targeting stringency, as one shortcoming of this experiment is that mismatched guides were not designed, a priori, to recognize accessible parts of the MS2 genome. Nevertheless, despite potential noise introduced in this analysis due to guide segments that target inaccessible MS2 regions, we observe an interesting correlation between mismatches in the MS2 screen and in vitro biochemical cleavage assays for the sgRNA with a 23 nt guide segment sequence (Figure 3—figure supplement 4C,D). The first few nucleotides in the ‘seed’ region (guide 3´ end proximal) are sensitive to mismatches, while a central region of sensitivity is also observed, similar to previously demonstrated regions of sensitivity for SpyCas9 DNA cleavage (Cong et al., 2013; Jiang et al., 2013; Fu et al., 2016; Gorski et al., 2017).

SauCas9 represses gene expression in E. coli

An efficient RNA-targeting Cas9 could serve as an important tool in regulating gene expression in vivo. To test the ability of SauCas9 to mediate repression of host gene expression, we targeted dSauCas9 and dSpyCas9 RNPs to a GFP reporter sequence encoded in the E. coli chromosome (Qi et al., 2013). Catalytically inactive versions of Cas9 were used to prevent cleavage of the bacterial chromosome when targeting a site adjacent to a PAM. As expression of Cas9 and sgRNA exerts metabolic stress on E. coli, GFP fluorescence values were normalized by the OD₆₀₀ value to account for differences in cell growth between cultures (Oakes et al., 2016). When using sgRNAs designed to recognize a sequence in the GFP gene adjacent to the appropriate PAM for SauCas9 (NNGRRT) or SpyCas9 (NGG), GFP expression is significantly reduced (Figure 4A) consistent with CRISPR-interference (CRISPRi) (Qi et al., 2013; Gilbert et al., 2014). When sgRNAs were designed to recognize GFP sequences not flanked by a PAM, dSauCas9 but not dSpyCas9 was able to repress GFP expression. The SauCas9-mediated GFP repression was dependent on sgRNAs that target the coding strand; sgRNAs that recognize the non-coding strand did not result in reduced GFP expression (Figure 4—figure supplement 1A). The length of the targeting sequence in vivo corroborates in vitro data, with longer guides working more efficiently (Figure 4B).

Figure 4 with 1 supplement see all

Download asset Open asset

SauCas9 repression of a GFP reporter in vivo.

(A) Comparison of dSpy and dSauCas9 to repress GFP expression on the DNA and RNA level. GFP signal is normalized to OD₆₀₀ to control for difference in cell density between samples. GFP/OD₆₀₀ ratios for guide alone and RNP are normalized to values for a non-targeting guide vector and an Apo protein control, respectively. Target sites were chosen to be adjacent to PAM sites for Spy, Sau, both, or neither as indicated. Note: the slight GFP repression observed with dSpyCas9 using the target sequence adjacent to the Sau PAM (CAGAGT) likely results from the ability of SpyCas9 to use an NAG PAM, albeit with reduced efficiency (Hsu et al., 2013). ****p<0.0001 by one-way ANOVA. (B) Relative expression of GFP using guides with different length targeting sequences. Target site here is the GFP2 sequence chosen for its robust targeting activity. (C) (Upper) Diagram of targeting sequences across the GFP mRNA and ribosome-binding site (RBS). (Lower) Relative expression of GFP of SauCas9 RNP normalized to sgRNA alone for targeting sequences across the GFP reporter. Dashed red line indicates that the sgRNA alone is as efficient as the RNP for GFP repression. (**A–C**) Bars represent mean ± S.D. (n = 3). (D) Model for observed SauCas9 ssRNA targeting activity. We propose that accessible RNA is cleaved or repressed efficiently while structured and protein-bound RNA is not targeted by SauCas9.

https://doi.org/10.7554/eLife.32724.026

Figure 4—source data 1 Raw data for PAM dependency, length efficiency, and GFP mRNA tiling for GFP repression assays.: https://doi.org/10.7554/eLife.32724.029
Download elife-32724-fig4-data1-v2.xlsx

Different guide sequences display variable efficiencies of targeting. We tiled sgRNAs across the GFP mRNA sequence to test the robustness of dSauCas9 to repress GFP expression (Figure 4C). As no sites are adjacent to PAM sequences, all repression presumably occurs on the mRNA level. The efficiency of dSauCas9-mediated GFP repression varied according to the target sequence, with some dSauCas9 RNPs reducing GFP signal to 15–30% of that observed in the presence of the sgRNA alone (Figure 4C, GFP2 and 6) and others showing no ability to repress GFP expression (GFP7 and 9). Electrophoretic mobility shift assays support the conclusion that repression is not occurring at the dsDNA level by promiscuous PAM binding (Figure 4—figure supplement 1B). Repression is largely equivalent between catalytically active and inactive forms of SauCas9 (Figure 4—figure supplement 1C), suggesting that binding of the Cas9-sgRNA complex to the mRNA is sufficient for repression and consistent with in vitro data showing that the enzyme does not catalyze multiple-turnover RNA cleavage. While we speculate that the Cas9-RNP blocks the ribosome directly (either at initiation or during elongation), our data do not rule out the possibility that Cas9 is otherwise destabilizing the mRNA transcript through an unknown mechanism.

Together our biochemical and in vivo data support a model in which SauCas9 can readily bind and cleave bacteriophage RNA and mRNA sequences that are exposed and unstructured (Figure 4D). Regions that form strong structures are inaccessible to SauCas9 RNP binding, thereby preventing cleavage or repression activity. As Cas9 cleavage activity is limited by target accessibility, we expect that RNA occluded by RNA-binding proteins would also be recalcitrant to cleavage.

Discussion

Investigation of CRISPR-Cas9 has focused on its function as a double-stranded DNA endonuclease, while the ability of diverse homologs to cleave natural RNA substrates has remained unexplored. Here, we present evidence that type II-A and type II-C Cas9 enzymes can catalyze programmable and PAM-independent single-stranded RNA cleavage. Focusing on SauCas9, we show that this enzyme can be employed both biochemically and in cells to cleave RNA and regulate genes on both the transcriptional and translational level in parallel by accounting for target site PAM proximity. Importantly, SauCas9 ssRNA scission requires only an sgRNA and does not need a PAMmer, thereby simplifying applications (Nelles et al., 2015) and facilitating delivery to cells as a pre-assembled RNP (Zuris et al., 2015; Mout et al., 2017)

The RNA-targeting capability of SauCas9 and related Cas9 enzymes offers the advantage of repressing viruses whose lifecycles do not involve a DNA genome or intermediate, thereby rendering them inaccessible to Cas9-mediated DNA cleavage. We demonstrated that SauCas9 could be programmed to confer protection to E. coli against MS2, an RNA bacteriophage with no DNA intermediate. Whether RNA-based viral repression by Cas9 occurs in natural systems is not known, but seems possible based on our results. DNA cleavage by SauCas9 remains more rapid than RNA cleavage, indicating that DNA-targeting is probably the biologically preferred method for phage and plasmid interference. However, Cas9 activity on RNA is PAM-independent and may mitigate the effects of PAM-escape mutants that would evade DNA-level interference (Deveau et al., 2008), thus acting as an additional line of defense.

Intriguingly, ‘hotspots’ of preferential targeting emerged when tiling guides across the genome, but these sites were devoid of sequence bias. In conjunction with in vitro cleavage data of partially structured RNAs, we suggest that SauCas9 cleavage efficiency is inversely related to structural complexity of the RNA target. As an alternative to the current approach of screening multiple sgRNAs for activity, experimental knowledge about RNA structure, such as SHAPE-seq data (Loughrey et al., 2014), would simplify target identification for viral targeting and repression experiments. Nevertheless, future work will concentrate on understanding the structural constraints on RNA targeting and methods to improve Cas9 access to duplex RNA regions.

SauCas9 holds promise for a range of RNA targeting applications. We showed that SauCas9 could repress gene expression in E. coli. Repression of the reporter occurs in the absence of the PAM and is specific for targeting of the coding strand. Recently, the Type VI CRISPR-Cas system effector, Cas13, has been proposed and demonstrated to target RNA (Shmakov et al., 2015; Abudayyeh et al., 2016; East-Seletsky et al., 2016). ‘Activated’ Cas13 exhibits robust trans cleavage of RNAs(Abudayyeh et al., 2016; East-Seletsky et al., 2016; Smargon et al., 2017). While RNA-cleavage by SauCas9 is single-turnover and kinetically less robust than that of Cas13, Cas9 does not cleave RNAs indiscriminately and lends itself to targeting of specific transcripts. A programmable Cas9 capable of repressing genes on the RNA level has potential advantages over CRISPRi DNA-based techniques (Qi et al., 2013; Gilbert et al., 2014). For example, isoform-specific targeting of different transcripts originating from the same transcription start site or resulting from alternative splicing events might be possible. More broadly, due to its intrinsic ssRNA-binding activity, SauCas9 may have utility as a platform for directing other effector proteins to specific RNA molecules, such as proteins or domains that up-regulate translation or RNA base-modifying enzymes for site-specific epigenetic modification of RNAs.

Materials and methods

Key resources table

Reagent type (species) or resource	Designation	Source or reference	Identifiers	Additional information
Strain, strain background (E. coli)	BL21(DE3)	Thermo Fisher
Strain, strain background (E. coli)	XL1-Blue	QB3-MacroLab
Strain, strain background (E. coli)	strain with GFP reporter	PMID: 27136077
Recombinant DNA reagent	SauCas9 expression vector	this paper		SauCas9 sequence in vector backbone from PMID: 27136077
Recombinant DNA reagent	His-MBP vector (plasmid - #29706)	addgene
Recombinant DNA reagent	SauCas9 guide expression vector	this paper		SauCas9 guide scaffold in vector backbone from PMID: 27136077
Software, algorithm	ImageQuantTL	GE Healthcare	RRID:SCR_014246
Software, algorithm	Prism7	GE Healthcare	RRID:SCR_015807

Phylogenetic tree construction and RNA folding

Request a detailed protocol

Cas9 homolog sequences were obtained from Chylinski and colleagues (Chylinski et al., 2014). A structure-guided alignment was produced using PROMALS3D (Pei et al., 2008) and a maximum-likelihood tree was inferred using PHYML3.0 (Guindon et al., 2010). The structure of the pUC ssRNA target was predicted using Mfold (Zuker, 2003).

Protein purification

Request a detailed protocol

All proteins were expressed as His-MBP fusions (Addgene vector #29706) in E. coli strain BL21(DE3). Cells were grown to an OD₆₀₀ of 0.6–0.8, induced with 0.4M IPTG, and then incubated overnight at 16˚C with shaking. Proteins were purified using Superflow Ni-NTA affinity resin (Qiagen, Valencia, CA), followed by a HiTrap HP Heparin column (GE Healthcare, Pittsburgh, PA) and gel filtration on a Superdex S200 (GE Healthcare, Pittsburgh, PA), as previously described (Jinek et al., 2012). Cas9 protein sequences can be found in Supplementary file 1.

Oligonucleotide purification and radiolabeling

Request a detailed protocol

DNA oligonucleotides were synthesized by IDT (Coralville, IA). Target RNAs and sgRNAs were transcribed in vitro as previously described (Sternberg et al., 2012). DNA targets and in vitro transcribed RNAs were gel purified by 7M urea denaturing PAGE. Target RNAs and DNAs were 5´ end-labeled with [γ-P32-ATP] by treatment with PNK (NEB, Ipswich, MA). T1 sequencing and hydrolysis ladders were prepared according to manufacturer’s directions (Ambion, Grand Island, NY). A list of all sgRNAs and targets can be found in Supplementary file 1.

In vitro cleavage assays

Request a detailed protocol

Cas9 was reconstituted with equimolar sgRNA in 1x cleavage buffer (20 mM Tris-HCl – pH 7.5, 200 mM KCl, 1 mM TCEP, 5% glycerol, 5 mM MgCl2) for 10 min at 37˚C, then immediately placed on ice. Cleavage reactions were conducted with 1 nM target and 10 nM reconstituted Cas9-sgRNA in 1x cleavage buffer unless otherwise noted. Structured RNA substrates were prepared by annealing two separate in vitro transcribed RNAs. The target strand was annealed with 10-fold excess of the non-target strand to ensure that all target is complexed prior to the cleavage reaction. Reactions were incubated at 37˚C for the indicated time and quenched in Heparin-EDTA buffer (10 µg/ml heparin, 25 mM EDTA) at 25˚C for 5 min. Reactions were diluted with 2x Formamide loading buffer and incubated at 95˚C for 5 min prior to separation on a 15% denaturing 7M urea PAGE gel. Gels were dried overnight and exposed to a phosphor imaging screen (Amersham/GE Healthcare, Pittsburgh, PA). Results were visualized on a Typhoon (GE Healthcare, Pittsburgh, PA) and quantified in ImageQuantTL (v8.1, GE Healthcare, Pittsburgh, PA). The cleaved fraction of total signal was calculated independently for three separate experiments and were fit with a one-phase exponential decay model in Prism7 (GraphPad Software, La Jolla, CA).

Filter binding and electrophoretic mobility shift assays

Request a detailed protocol

Binding reactions consisted of 750 nM catalytically inactive SauCas9 reconstituted with sgRNA to the final concentrations indicated. Radiolabeled target RNA was added to a final concentration of 1 nM and the reactions were incubated at 37˚C for one hour. Bound probe was separated from unbound using a three-filter system on a vacuum manifold (Rio, 2012). Membranes were allowed to dry prior to phosphor imaging and quantification. EMSAs were performed in the presence of 300 nM dSauCas9 and 1 nM radiolabeled target strand DNA pre-annealed in the presence of 10x non-target strand. Complexes were incubated at 37˚C for 1 hr prior to separation on 6% non-denaturing PAGE. Gels were dried prior to phosphor imaging. Three independent experiments were performed and the fraction of bound out of total signal was calculated in ImageQuantTL. Binding isotherms were determined in Prism7 using a one-site binding model.

MS2 screen and plaque assay

Request a detailed protocol

All guides of length 20–23 nt antisense to the MS2 bacteriophage genome were synthesized (CustomArray Inc., Bothell, WA) and cloned into a guide expression vector (Oakes et al., 2016) modified with the SauCas9 sgRNA scaffold. XL1-Blue E. coli cells with a vector containing a tetracycline-inducible wtSauCas9 construct were made electrocompetent and transformed with the MS2-guide plasmid library in triplicate. Approximately 1 × 10⁶ transformants were grown for 30 min at 37˚C with shaking prior to addition of antibiotics and 10 nM anhydrotetracycline (aTc) (Sigma, St. Louis, MO) for protein induction. After an additional 30 min of growth, cultures were split into three equal pools and treated with none, 3.3 × 10⁶, or 3.3 × 10⁷ MS2 bacteriophage. After 3 hr of infection, cells were plated on LB-agar supplemented with antibiotics and incubated at 37˚C for 16 hr. Plates were scraped with LB and plasmids were isolated using a MidiPrep kit (Qiagen, Valencia, CA), according to the manufacturer’s protocol. High-throughput sequencing libraries were prepared by PCR amplification of the variable region of the guide plasmid. Dual unique-molecular identifiers (UMIs), included to separate true single-nucleotide mismatches, as well as duplicates, from PCR artifacts (Kou et al., 2016), were incorporated during a single round of PCR. Excess UMIs were removed by ExoI digestion (Thermo Scientific, Waltham, MA) prior to library amplification and barcoding. Individual guides (Supplementary file 1) were cloned using oligonucleotides synthesized by IDT and co-transformed into XL1-Blue E. coli cells with the SauCas9 vector. Resistance to MS2 bacteriophage was conducted using a soft-agar overlay method (Abudayyeh et al., 2016) and plaque forming units (PFUs) were calculated. To minimize variability in plaquing efficiency, the same phage dilutions were used for all experiments.

MS2 survival and mismatch analysis

Request a detailed protocol

After applying a low-pass filter, reads were trimmed using cutadapt v. 1.14 (Martin, 2011) and paired-end overlapping reads were merged using pandaseq (Masella et al., 2012) for error correction. Reads were mapped to the MS2 genome with bowtie2 v2.3.0 (Langmead and Salzberg, 2012) using the ‘very-sensitive’ option and de-duplicated based on the dual-UMI (Smith et al., 2017). Feature counts were obtained using HTSeq-count (Anders et al., 2015). Differential expression was calculated using standard pipelines implemented in ‘edgeR’ (Robinson et al., 2010; McCarthy et al., 2012). Significantly enriched guides were defined as those with an FDR-corrected p-value<0.05. Guides with a positive fold-change compared to the control were mapped to the MS2 genome and visualized using the ‘Sushi’ package (Phanstiel et al., 2014). To examine for nucleotide composition bias, sequences of guides with a significant positive enrichment were aligned at the 3´ end (PAM-proximal) and motifs were analyzed using the WebLogo server (Crooks et al., 2004). The distribution of log₂ fold-change values of significantly enriched guides plotted as box and whisker plots in Prism. The secondary structure of the MS2 genome was obtained from (Dai et al., 2017) and reads were mapped and visualized in Forna (Kerpedjiev et al., 2015). Log₂ fold-change values of single-nucleotide mismatch (SNP) guides for each treatment were partitioned by length and averaged at each position. High-throughput sequencing data accompanying this paper are available through the Sequencing Read Archive under the BioProject accession number PRJNA413805.

E. coli in vivo GFP repression

Request a detailed protocol

Based on the system outlined previously, SauCas9 was cloned into a tetracycline-inducible vector, while individual guides are under control of a constitutive promoter (Oakes et al., 2016). Plasmids were transformed into an E. coli strain with a GFP reporter gene integrated into the chromosome (Qi et al., 2013). Cultures were grown in M9 medium supplemented with 0.4% w/v glucose to mid-log phase and diluted to an OD₆₀₀ of 0.05 prior to transfer to a Tecan Microplate reader (Tecan Systems, San Jose, CA). Protein expression was induced with 10 nM aTc. GFP and OD₆₀₀ were measured every ten minutes for at least 18 hr. Curves of GFP expression over time were fit with a logistic growth model in Prism. At 80% of the maximum value, or at least after 16 hr of growth, the GFP signal was normalized by cell density at OD₆₀₀. To account for effects of guide and protein expression, GFP/OD₆₀₀ was normalized to a null guide or null protein culture, respectively. As expression of different guides change GFP expression levels, the ratio between normalized RNP and guide values was taken to allow comparison of RNP-based repression across different guides. All experiments were conducted in triplicate and all graphing and quantitative analyses were conducted in Prism. Guide and target sequences can be found in Supplementary file 1.

Data availability

The following data sets were generated

1. Strutt S
2. Doudna J
(2017) MS2 CRISPR screen in E. coli
Publicly available at NCBI BioProject (Accession no: PRJNA413805).

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA413805

References

1. Abudayyeh OO
2. Gootenberg JS
3. Konermann S
4. Joung J
5. Slaymaker IM
6. Cox DB
7. Shmakov S
8. Makarova KS
9. Semenova E
10. Minakhin L
11. Severinov K
12. Regev A
13. Lander ES
14. Koonin EV
15. Zhang F
(2016) C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector
Science 353:aaf5573.

https://doi.org/10.1126/science.aaf5573
- PubMed
- Google Scholar
(2014) Structural basis of PAM-dependent target DNA recognition by the Cas9 endonuclease
Nature 513:569–573.

https://doi.org/10.1038/nature13579
- PubMed
- Google Scholar
1. Anders S
2. Pyl PT
3. Huber W
(2015) HTSeq--a Python framework to work with high-throughput sequencing data
Bioinformatics 31:166–169.

https://doi.org/10.1093/bioinformatics/btu638
- PubMed
- Google Scholar
1. Batra R
2. Nelles DA
3. Pirie E
4. Blue SM
5. Marina RJ
6. Wang H
7. Chaim IA
8. Thomas JD
9. Zhang N
10. Nguyen V
11. Aigner S
12. Markmiller S
13. Xia G
14. Corbett KD
15. Swanson MS
16. Yeo GW
(2017) Elimination of toxic microsatellite repeat expansion RNA by RNA-Targeting Cas9
Cell 170:899–912.

https://doi.org/10.1016/j.cell.2017.07.010
- PubMed
- Google Scholar
1. Bercy M
2. Bockelmann U
(2015) Hairpins under tension: RNA versus DNA
Nucleic Acids Research 43:gkv860.

https://doi.org/10.1093/nar/gkv860
- Google Scholar
(2017) Lessons from enzyme kinetics reveal specificity principles for rna-guided nucleases in RNA interference and CRISPR-based genome editing
Cell Systems 4:21–29.

https://doi.org/10.1016/j.cels.2016.12.010
- PubMed
- Google Scholar
(2013) The tracrRNA and Cas9 families of type II CRISPR-Cas immunity systems
RNA Biology 10:726–737.

https://doi.org/10.4161/rna.24321
- PubMed
- Google Scholar
(2014) Classification and evolution of type II CRISPR-Cas systems
Nucleic Acids Research 42:6091–6105.

https://doi.org/10.1093/nar/gku241
- PubMed
- Google Scholar
1. Cong L
2. Ran FA
3. Cox D
4. Lin S
5. Barretto R
6. Habib N
7. Hsu PD
8. Wu X
9. Jiang W
10. Marraffini LA
11. Zhang F
(2013) Multiplex genome engineering using CRISPR/Cas systems
Science 339:819–823.

https://doi.org/10.1126/science.1231143
- PubMed
- Google Scholar
(2004) WebLogo: a sequence logo generator
Genome Research 14:1188–1190.

https://doi.org/10.1101/gr.849004
- PubMed
- Google Scholar
1. Dai X
2. Li Z
3. Lai M
4. Shu S
5. Du Y
6. Zhou ZH
7. Sun R
(2017) In situ structures of the genome and genome-delivery apparatus in a single-stranded RNA virus
Nature 541:112–116.

https://doi.org/10.1038/nature20589
- PubMed
- Google Scholar
1. Deveau H
2. Barrangou R
3. Garneau JE
4. Labonté J
5. Fremaux C
6. Boyaval P
7. Romero DA
8. Horvath P
9. Moineau S
(2008) Phage response to CRISPR-encoded resistance in Streptococcus thermophilus
Journal of Bacteriology 190:1390–1400.

https://doi.org/10.1128/JB.01412-07
- PubMed
- Google Scholar
(2016) Two distinct RNase activities of CRISPR-C2c2 enable guide-RNA processing and RNA detection
Nature 538:270–273.

https://doi.org/10.1038/nature19802
- PubMed
- Google Scholar
1. Friedland AE
2. Baral R
3. Singhal P
4. Loveluck K
5. Shen S
6. Sanchez M
7. Marco E
8. Gotta GM
9. Maeder ML
10. Kennedy EM
11. Kornepati AV
12. Sousa A
13. Collins MA
14. Jayaram H
15. Cullen BR
16. Bumcrot D
(2015) Characterization of Staphylococcus aureus Cas9: a smaller Cas9 for all-in-one adeno-associated virus delivery and paired nickase applications
Genome Biology 16:257.

https://doi.org/10.1186/s13059-015-0817-8
- PubMed
- Google Scholar
1. Fu BX
2. St Onge RP
3. Fire AZ
4. Smith JD
(2016) Distinct patterns of Cas9 mismatch tolerance in vitro and in vivo
Nucleic Acids Research 44:5365–5377.

https://doi.org/10.1093/nar/gkw417
- PubMed
- Google Scholar
1. Fu Y
2. Sander JD
3. Reyon D
4. Cascio VM
5. Joung JK
(2014) Improving CRISPR-Cas nuclease specificity using truncated guide RNAs
Nature Biotechnology 32:279–284.

https://doi.org/10.1038/nbt.2808
- PubMed
- Google Scholar
1. Garneau JE
2. Dupuis MÈ
3. Villion M
4. Romero DA
5. Barrangou R
6. Boyaval P
7. Fremaux C
8. Horvath P
9. Magadán AH
10. Moineau S
(2010) The CRISPR/Cas bacterial immune system cleaves bacteriophage and plasmid DNA
Nature 468:67–71.

https://doi.org/10.1038/nature09523
- PubMed
- Google Scholar
(2012) Cas9-crRNA ribonucleoprotein complex mediates specific DNA cleavage for adaptive immunity in bacteria
PNAS 109:E2579–E2586.

https://doi.org/10.1073/pnas.1208507109
- PubMed
- Google Scholar
1. Gilbert LA
2. Horlbeck MA
3. Adamson B
4. Villalta JE
5. Chen Y
6. Whitehead EH
7. Guimaraes C
8. Panning B
9. Ploegh HL
10. Bassik MC
11. Qi LS
12. Kampmann M
13. Weissman JS
(2014) Genome-Scale CRISPR-Mediated control of gene repression and activation
Cell 159:647–661.

https://doi.org/10.1016/j.cell.2014.09.029
- PubMed
- Google Scholar
(2017) RNA-based recognition and targeting: sowing the seeds of specificity
Nature Reviews Molecular Cell Biology 18:215–228.

https://doi.org/10.1038/nrm.2016.174
- PubMed
- Google Scholar
(2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0
Systematic Biology 59:307–321.

https://doi.org/10.1093/sysbio/syq010
- PubMed
- Google Scholar
1. Hirano H
2. Gootenberg JS
3. Horii T
4. Abudayyeh OO
5. Kimura M
6. Hsu PD
7. Nakane T
8. Ishitani R
9. Hatada I
10. Zhang F
11. Nishimasu H
12. Nureki O
(2016) Structure and engineering of francisella novicida Cas9
Cell 164:950–961.

https://doi.org/10.1016/j.cell.2016.01.039
- PubMed
- Google Scholar
1. Hsu PD
2. Scott DA
3. Weinstein JA
4. Ran FA
5. Konermann S
6. Agarwala V
7. Li Y
8. Fine EJ
9. Wu X
10. Shalem O
11. Cradick TJ
12. Marraffini LA
13. Bao G
14. Zhang F
(2013) DNA targeting specificity of RNA-guided Cas9 nucleases
Nature Biotechnology 31:827–832.

https://doi.org/10.1038/nbt.2647
- PubMed
- Google Scholar
1. Jiang F
2. Zhou K
3. Ma L
4. Gressel S
5. Doudna JA
(2015) STRUCTURAL BIOLOGY. A Cas9-guide RNA complex preorganized for target DNA recognition
Science 348:1477–1481.

https://doi.org/10.1126/science.aab1452
- PubMed
- Google Scholar
1. Jiang W
2. Bikard D
3. Cox D
4. Zhang F
5. Marraffini LA
(2013) RNA-guided editing of bacterial genomes using CRISPR-Cas systems
Nature Biotechnology 31:233–239.

https://doi.org/10.1038/nbt.2508
- PubMed
- Google Scholar
1. Jinek M
2. Chylinski K
3. Fonfara I
4. Hauer M
5. Doudna JA
6. Charpentier E
(2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity
Science 337:816–821.

https://doi.org/10.1126/science.1225829
- PubMed
- Google Scholar
(2015) Forna (force-directed RNA): Simple and effective online RNA secondary structure diagrams
Bioinformatics 31:3377–3379.

https://doi.org/10.1093/bioinformatics/btv372
- PubMed
- Google Scholar
1. Kim E
2. Koo T
3. Park SW
4. Kim D
5. Kim K
6. Cho HY
7. Song DW
8. Lee KJ
9. Jung MH
10. Kim S
11. Kim JH
12. Kim JH
13. Kim JS
(2017) In vivo genome editing with a small Cas9 orthologue derived from Campylobacter jejuni
Nature Communications 8:14500.

https://doi.org/10.1038/ncomms14500
- PubMed
- Google Scholar
1. Kleinstiver BP
2. Prew MS
3. Tsai SQ
4. Nguyen NT
5. Topkar VV
6. Zheng Z
7. Joung JK
(2015) Broadening the targeting range of Staphylococcus aureus CRISPR-Cas9 by modifying PAM recognition
Nature Biotechnology 33:1293–1298.

https://doi.org/10.1038/nbt.3404
- PubMed
- Google Scholar
1. Kou R
2. Lam H
3. Duan H
4. Ye L
5. Jongkam N
6. Chen W
7. Zhang S
8. Li S
(2016) Benefits and Challenges with Applying Unique Molecular Identifiers in Next Generation Sequencing to Detect Low Frequency Mutations
PLoS One 11:e0146638.

https://doi.org/10.1371/journal.pone.0146638
- PubMed
- Google Scholar
1. Langmead B
2. Salzberg SL
(2012) Fast gapped-read alignment with Bowtie 2
Nature Methods 9:357–359.

https://doi.org/10.1038/nmeth.1923
- PubMed
- Google Scholar
1. Liu Y
2. Chen Z
3. He A
4. Zhan Y
5. Li J
6. Liu L
7. Wu H
8. Zhuang C
9. Lin J
10. Zhang Q
11. Huang W
(2016) Targeting cellular mRNAs translation by CRISPR-Cas9
Scientific Reports 6:srep29652.

https://doi.org/10.1038/srep29652
- PubMed
- Google Scholar
(2014) SHAPE-Seq 2.0: systematic optimization and extension of high-throughput chemical probing of RNA secondary structure with next generation sequencing
Nucleic Acids Research 42:e165.

https://doi.org/10.1093/nar/gku909
- Google Scholar
1. Ma E
2. Harrington LB
3. O'Connell MR
4. Zhou K
5. Doudna JA
(2015) Single-Stranded DNA cleavage by divergent CRISPR-Cas9 Enzymes
Molecular Cell 60:398–407.

https://doi.org/10.1016/j.molcel.2015.10.030
- PubMed
- Google Scholar
1. Martin M
(2011) Cutadapt removes adapter sequences from high-throughput sequencing reads
EMBnet.journal 17:10.

https://doi.org/10.14806/ej.17.1.200
- Google Scholar
(2012) PANDAseq: paired-end assembler for illumina sequences
BMC Bioinformatics 13:31.

https://doi.org/10.1186/1471-2105-13-31
- PubMed
- Google Scholar
(2012) Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation
Nucleic Acids Research 40:4288–4297.

https://doi.org/10.1093/nar/gks042
- PubMed
- Google Scholar
(2016) Diverse evolutionary roots and mechanistic variations of the CRISPR-Cas systems
Science 353:aad5147.

https://doi.org/10.1126/science.aad5147
- PubMed
- Google Scholar
1. Mout R
2. Ray M
3. Yesilbag Tonga G
4. Lee YW
5. Tay T
6. Sasaki K
7. Rotello VM
(2017) Direct cytosolic delivery of CRISPR/Cas9-ribonucleoprotein for efficient gene editing
ACS Nano 11:2452–2458.

https://doi.org/10.1021/acsnano.6b07600
- PubMed
- Google Scholar
1. Nelles DA
2. Fang MY
3. Aigner S
4. Yeo GW
(2015) Applications of Cas9 as an RNA-programmed RNA-binding protein
BioEssays 37:732–739.

https://doi.org/10.1002/bies.201500001
- PubMed
- Google Scholar
1. Nelles DA
2. Fang MY
3. O'Connell MR
4. Xu JL
5. Markmiller SJ
6. Doudna JA
7. Yeo GW
(2016) Programmable RNA tracking in live cells with CRISPR/Cas9
Cell 165:488–496.

https://doi.org/10.1016/j.cell.2016.02.054
- PubMed
- Google Scholar
1. Nishimasu H
2. Cong L
3. Yan WX
4. Ran FA
5. Zetsche B
6. Li Y
7. Kurabayashi A
8. Ishitani R
9. Zhang F
10. Nureki O
(2015) Crystal structure of Staphylococcus aureus Cas9
Cell 162:1113–1126.

https://doi.org/10.1016/j.cell.2015.08.007
- PubMed
- Google Scholar
1. Nishimasu H
2. Ran FA
3. Hsu PD
4. Konermann S
5. Shehata SI
6. Dohmae N
7. Ishitani R
8. Zhang F
9. Nureki O
(2014) Crystal structure of Cas9 in complex with guide RNA and target DNA
Cell 156:935–949.

https://doi.org/10.1016/j.cell.2014.02.001
- PubMed
- Google Scholar
(2014) Programmable RNA recognition and cleavage by CRISPR/Cas9
Nature 516:263–266.

https://doi.org/10.1038/nature13769
- PubMed
- Google Scholar
1. Oakes BL
2. Nadler DC
3. Flamholz A
4. Fellmann C
5. Staahl BT
6. Doudna JA
7. Savage DF
(2016) Profiling of engineering hotspots identifies an allosteric CRISPR-Cas9 switch
Nature Biotechnology 34:646–651.

https://doi.org/10.1038/nbt.3528
- PubMed
- Google Scholar
1. Pei J
2. Kim BH
3. Grishin NV
(2008) PROMALS3D: a tool for multiple protein sequence and structure alignments
Nucleic Acids Research 36:2295–2300.

https://doi.org/10.1093/nar/gkn072
- PubMed
- Google Scholar
(2014) Sushi.R: flexible, quantitative and integrative genomic visualizations for publication-quality multi-panel figures
Bioinformatics 30:2808–2810.

https://doi.org/10.1093/bioinformatics/btu379
- PubMed
- Google Scholar
1. Qi LS
2. Larson MH
3. Gilbert LA
4. Doudna JA
5. Weissman JS
6. Arkin AP
7. Lim WA
(2013) Repurposing CRISPR as an RNA-guided platform for sequence-specific control of gene expression
Cell 152:1173–1183.

https://doi.org/10.1016/j.cell.2013.02.022
- PubMed
- Google Scholar
1. Ran FA
2. Cong L
3. Yan WX
4. Scott DA
5. Gootenberg JS
6. Kriz AJ
7. Zetsche B
8. Shalem O
9. Wu X
10. Makarova KS
11. Koonin EV
12. Sharp PA
13. Zhang F
(2015) In vivo genome editing using Staphylococcus aureus Cas9
Nature 520:186–191.

https://doi.org/10.1038/nature14299
- PubMed
- Google Scholar
(2004) Fast and effective prediction of microRNA/target duplexes
RNA 10:1507–1517.

https://doi.org/10.1261/rna.5248604
- PubMed
- Google Scholar
1. Rio DC
(2012) Filter-binding assay for analysis of RNA-protein interactions
Cold Spring Harbor Protocols 2012:pdb.prot071449.

https://doi.org/10.1101/pdb.prot071449
- PubMed
- Google Scholar
(2010) edgeR: a bioconductor package for differential expression analysis of digital gene expression data
Bioinformatics 26:139–140.

https://doi.org/10.1093/bioinformatics/btp616
- PubMed
- Google Scholar
(2013) A CRISPR/Cas system mediates bacterial innate immune evasion and virulence
Nature 497:254–257.

https://doi.org/10.1038/nature12048
- PubMed
- Google Scholar
1. Shmakov S
2. Abudayyeh OO
3. Makarova KS
4. Wolf YI
5. Gootenberg JS
6. Semenova E
7. Minakhin L
8. Joung J
9. Konermann S
10. Severinov K
11. Zhang F
12. Koonin EV
(2015) Discovery and functional characterization of diverse class 2 CRISPR-Cas systems
Molecular Cell 60:385–397.

https://doi.org/10.1016/j.molcel.2015.10.008
- PubMed
- Google Scholar
1. Smargon AA
2. Cox DBT
3. Pyzocha NK
4. Zheng K
5. Slaymaker IM
6. Gootenberg JS
7. Abudayyeh OA
8. Essletzbichler P
9. Shmakov S
10. Makarova KS
11. Koonin EV
12. Zhang F
(2017) Cas13b Is a Type VI-B CRISPR-Associated RNA-Guided RNase differentially regulated by accessory proteins Csx27 and Csx28
Molecular Cell 65:618–630.

https://doi.org/10.1016/j.molcel.2016.12.023
- PubMed
- Google Scholar
(2017) UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy
Genome Research 27:491–499.

https://doi.org/10.1101/gr.209601.116
- PubMed
- Google Scholar
(2012) Mechanism of substrate selection by a highly specific CRISPR endoribonuclease
RNA 18:661–672.

https://doi.org/10.1261/rna.030882.111
- PubMed
- Google Scholar
(2014) DNA interrogation by the CRISPR RNA-guided endonuclease Cas9
Nature 507:62–67.

https://doi.org/10.1038/nature13011
- PubMed
- Google Scholar
(2014) Direct observation of R-loop formation by single RNA-guided Cas9 and Cascade effector complexes
PNAS 111:9798–9803.

https://doi.org/10.1073/pnas.1402597111
- PubMed
- Google Scholar
(1982) Molecular structure of r(GCG)d(TATACGC): a DNA--RNA hybrid helix joined to double helical DNA
Nature 299:601–604.

https://doi.org/10.1038/299601a0
- PubMed
- Google Scholar
(2016) Biology and applications of CRISPR systems: harnessing nature's toolbox for genome engineering
Cell 164:29–44.

https://doi.org/10.1016/j.cell.2015.12.035
- PubMed
- Google Scholar
1. Yamada M
2. Watanabe Y
3. Gootenberg JS
4. Hirano H
5. Ran FA
6. Nakane T
7. Ishitani R
8. Zhang F
9. Nishimasu H
10. Nureki O
(2017) Crystal structure of the minimal cas9 from campylobacter jejuni reveals the molecular diversity in the CRISPR-Cas9 systems
Molecular Cell 65:1109–1121.

https://doi.org/10.1016/j.molcel.2017.02.007
- PubMed
- Google Scholar
(2015) DNase H activity of neisseria meningitidis Cas9
Molecular Cell 60:242–255.

https://doi.org/10.1016/j.molcel.2015.09.020
- PubMed
- Google Scholar
1. Zuker M
(2003) Mfold web server for nucleic acid folding and hybridization prediction
Nucleic Acids Research 31:3406–3415.

https://doi.org/10.1093/nar/gkg595
- PubMed
- Google Scholar
1. Zuris JA
2. Thompson DB
3. Shu Y
4. Guilinger JP
5. Bessen JL
6. Hu JH
7. Maeder ML
8. Joung JK
9. Chen ZY
10. Liu DR
(2015) Cationic lipid-mediated delivery of proteins enables efficient protein-based genome editing in vitro and in vivo
Nature Biotechnology 33:73–80.

https://doi.org/10.1038/nbt.3081
- PubMed
- Google Scholar

Article and author information

Author details

Steven C Strutt

Department of Molecular and Cell Biology, University of California, Berkeley, United States

Contribution
Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing—original draft, Writing—review and editing

Competing interests
is listed on a patent application (No. 62598888) related to this work

"This ORCID iD identifies the author of this article:" 0000-0002-4653-5559
Rachel M Torrez

Department of Molecular and Cell Biology, University of California, Berkeley, United States

Present address
Department of Medicinal Chemistry, University of Michigan, Michigan, United States

Contribution
Investigation, Writing—review and editing

Competing interests
No competing interests declared
Emine Kaya

Department of Molecular and Cell Biology, University of California, Berkeley, United States

Present address
Global Blood Therapeutics, South San Francisco, United States

Contribution
Resources, Investigation, Writing—review and editing

Competing interests
No competing interests declared
Oscar A Negrete

Sandia National Laboratories, Biotechnology and Bioengineering Department, Livermore, United States

Contribution
Conceptualization, Supervision, Funding acquisition, Writing—review and editing

Competing interests
Oscar A Negrete: is listed on a patent application (No. 62598888) related to this work
Jennifer A Doudna
1. Department of Molecular and Cell Biology, University of California, Berkeley, United States
2. Howard Hughes Medical Institute, Maryland, United States
3. Department of Chemistry, University of California, Berkeley, United States
4. Innovative Genomics Institute, University of California, Berkeley, United States
5. MBIB Division, Lawrence Berkeley National Laboratory, Berkeley, United States
Contribution
Conceptualization, Supervision, Funding acquisition, Writing—original draft, Writing—review and editing

For correspondence
doudna@berkeley.edu

Competing interests
is a co-founder of to Caribou Biosciences, Intellia Therapeutics, and Editas Medicine and a scientific advisor to Caribou, Intellia, eFFECTOR Therapeutics and Driver. JAD is listed on a patent application (No. 62598888) related to this work

"This ORCID iD identifies the author of this article:" 0000-0001-9161-999X

Funding

National Science Foundation (MCB-1244557)

Steven C Strutt
Jennifer A Doudna

Howard Hughes Medical Institute

Rachel M Torrez
Jennifer A Doudna

German Academic Exchange Program

Emine Kaya

Laboratory Directed Research and Development (U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525)

Oscar A Negrete

Paul Allen Frontiers Science Program

Jennifer A Doudna

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

Acknowledgements

We thank G Knott and A Tambe for critical reading of the manuscript, members of the Doudna lab for helpful advice, L Gilbert and A Tambe for technical expertise, and N Ma, J Ye, and K Zhou for technical assistance. The Vincent J Coates Genomics Sequencing Laboratory is supported by NIH S10 Instrumentation Grants S10RR029668 and S10RR027303.

Copyright

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