Programmable C‐to‐U RNA editing using the human APOBEC 3A deaminase
2020; Springer Nature; Volume: 39; Issue: 22 Linguagem: Inglês
10.15252/embj.2020104741
ISSN1460-2075
AutoresXinxin Huang, Junjun Lv, Yongqin Li, Shaoshuai Mao, Zhifang Li, Zhengyu Jing, Yidi Sun, Xiaoming Zhang, Shengxi Shen, Xin Wang, Minghui Di, Jianyang Ge, Xingxu Huang, Erwei Zuo, Tian Chi,
Tópico(s)RNA Interference and Gene Delivery
ResumoResource15 October 2020free access Programmable C-to-U RNA editing using the human APOBEC3A deaminase Xinxin Huang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Junjun Lv School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Yongqin Li School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Shaoshuai Mao School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Zhifang Li Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China Search for more papers by this author Zhengyu Jing School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Yidi Sun Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China Search for more papers by this author Xiaoming Zhang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Shengxi Shen School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Xinxin Wang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China Search for more papers by this author Minghui Di School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Jianyang Ge School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Xingxu Huang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China Search for more papers by this author Erwei Zuo Corresponding Author [email protected] orcid.org/0000-0001-8259-0275 Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China Search for more papers by this author Tian Chi Corresponding Author [email protected] orcid.org/0000-0002-9675-6990 School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA Search for more papers by this author Xinxin Huang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Junjun Lv School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Yongqin Li School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Shaoshuai Mao School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Zhifang Li Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China Search for more papers by this author Zhengyu Jing School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Yidi Sun Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China Search for more papers by this author Xiaoming Zhang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Shengxi Shen School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Xinxin Wang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China Search for more papers by this author Minghui Di School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Jianyang Ge School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China University of Chinese Academy of Sciences, Beijing, China Search for more papers by this author Xingxu Huang School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China Search for more papers by this author Erwei Zuo Corresponding Author [email protected] orcid.org/0000-0001-8259-0275 Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China Search for more papers by this author Tian Chi Corresponding Author [email protected] orcid.org/0000-0002-9675-6990 School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA Search for more papers by this author Author Information Xinxin Huang1,2,‡, Junjun Lv1,2,‡, Yongqin Li1,2,‡, Shaoshuai Mao1,2, Zhifang Li3, Zhengyu Jing1,2, Yidi Sun4, Xiaoming Zhang1,2, Shengxi Shen1,2, Xinxin Wang1, Minghui Di1,2, Jianyang Ge1,2, Xingxu Huang1, Erwei Zuo *,3 and Tian Chi *,1,5 1School of Life Sciences and Technology, ShanghaiTech University, Shanghai, China 2University of Chinese Academy of Sciences, Beijing, China 3Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China 4Institute of Neuroscience, State Key Laboratory of Neuroscience, Key Laboratory of Primate Neurobiology, CAS Center for Excellence in Brain Science and Intelligence Technology, Shanghai Research Center for Brain Science and Brain-Inspired Intelligence, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China 5Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA ‡These authors contributed equally to this work *Corresponding author. Tel: +86 2068 4549; E-mail: [email protected] *Corresponding author. Tel: +86 0755 23250159; E-mail: [email protected] EMBO J (2020)39:e104741https://doi.org/10.15252/embj.2020104741 Correction(s) for this article Programmable C-to-U RNA editing using the human APOBEC3A deaminase03 May 2021 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract Programmable RNA cytidine deamination has recently been achieved using a bifunctional editor (RESCUE-S) capable of deaminating both adenine and cysteine. Here, we report the development of “CURE”, the first cytidine-specific C-to-U RNA Editor. CURE comprises the cytidine deaminase enzyme APOBEC3A fused to dCas13 and acts in conjunction with unconventional guide RNAs (gRNAs) designed to induce loops at the target sites. Importantly, CURE does not deaminate adenosine, enabling the high-specificity versions of CURE to create fewer missense mutations than RESCUE-S at the off-targets transcriptome-wide. The two editing approaches exhibit overlapping editing motif preferences, with CURE and RESCUE-S being uniquely able to edit UCC and AC motifs, respectively, while they outperform each other at different subsets of the UC targets. Finally, a nuclear-localized version of CURE, but not that of RESCUE-S, can efficiently edit nuclear RNAs. Thus, CURE and RESCUE are distinct in design and complementary in utility. Synopsis The current approach for programmable C-to-U RNA editing (RESCUE-S) is limited by low editing efficiency at certain targets, the inability to edit nuclear RNAs, and non-specific deamination of adenosines. Here, an alternative C-to-U RNA editing system—”CURE”—is introduced that complements RESCUE-S in application. Fusion of the human cytidine-specific deaminase APOBEC3A to dCas13 yields a distinct C>U RNA editor (CURE) The CURE system uses unconventional guide RNAs, which induce loops at target sites to imitate the natural substrate of APOBEC3A CURE and RESCUE-S can complement each other in terms of editing motif preference, on-target editing efficiency and off-target effects. Introduction Site-Directed RNA editing (SDRE), including A>I and C>U editing, is an essential complement to DNA base editing for both basic research and patient treatment (Rees & Liu, 2018; Mao et al, 2019; Montiel-Gonzalez et al, 2019; Vogel & Stafforst, 2019; Reardon, 2020). In particular, whereas DNA editing is irreversible and so its use restricted to repairing the mutations in genetic diseases, RNA editing is reversible and thus theoretically fit not only for correcting mutations at the RNA level to treat genetic diseases, but also for altering wild-type protein sequences in non-genetic conditions such as inflammation and pain; indeed, a major advantage of SDRE over DNA editing is its applicability to non-genetic conditions (Montiel-Gonzalez et al, 2019). Intensive effort has led to the development of many versions of A>I RNA base editors, all exploiting the human RNA adenine deaminase ADAR proteins (Montiel-Gonzalez et al, 2013; Montiel-González et al, 2016; Cox et al, 2017; Sinnamon et al, 2017; Vallecillo-Viejo et al, 2018; Vogel et al, 2018; Katrekar et al, 2019; Rauch et al, 2019). In contrast, C>U editors have remained elusive till recently. Specifically, via a combination of rationale mutagenesis and protein evolution, the human ADAR2 deaminase domain was successfully converted into a bifunctional enzyme capable of deaminating not only adenosines but also cytidines; the modified enzyme was fused to the catalytically dead RNA-targeting CRISPR-Cas13b (dCas13b) to create the bifunctional editor named RESCUE for programmable C> U and A>I editing (Abudayyeh et al, 2019). Although RESCUE can selectively deaminate cytidine (but not adenosine) on the bulged target nucleotides in the presence of proper gRNAs, it has massive global off-target effects on adenosines. Introducing a point mutation (S375A) into the ADAR2 deaminase domain in RESCUE markedly suppresses the off-target editing, producing a high-specificity version of RESCUE dubbed RESCUE-S (Abudayyeh et al, 2019). However, low levels of off-target edits (both A>I and C>U) persist in RESCUE-S. Furthermore, our reanalysis of the published data indicates that editing at endogenous transcripts by RESCUE is strongly biased against the GC and CC motifs, a situation exacerbated in RESCUE-S which is generally weaker than RESCUE (Appendix Fig S1). Indeed, the editing efficiencies of RESCUE-S at GC and CC on endogenous transcripts are typically below 2%, making it practically inapplicable. Finally, although RESCUE(-S) can edit both AC and UC, UC editing is less efficient, with the rates below 4% at some targets (Appendix Fig S1A and B). We have developed a distinct editing system named C>U RNA Editor (CURE), the first programmable C>U editor that does not deaminate adenine, with unique benefits in terms of both on-target and off-target editing. Results Development of the CURE system In humans, C>U RNA editing is catalyzed by the cytidine deaminases of the APOBEC family, which comprises 11 members including Apobec1A (A1A), A2, A3A, and A3G (Salter et al, 2016). Among the various members, the best-defined is A3A, which preferentially edits the target C (in the UC dinucleotide) located in particular forms of hairpins, as exemplified by the hairpin in the SDHB mRNA comprising a 5-bp stem linked to a tetra-loop that ends at the target C (Fig 1A; Sharma & Baysal, 2017). Stem stability, loop length, and target C position in the loop all dramatically impact editing. For example, moving the UC dinucleotide in the SDHB hairpin loop one nucleotide upstream reduces editing efficiency 10-fold (Sharma & Baysal, 2017). Thus, there are strict structural requirements at the target sites for A3A-mediated RNA editing. Figure 1. Development of CURE A. Secondary RNA structure of a well-defined A3A substrate harbored in the human SDHB mRNA. The target C is situated at the end of the tetra-loop (UAUC). B. Various versions of CURE. CURE-C1 consists of A3A (Y132D) or A3A* fused to dCas13b via a nuclear export sequence (NES), with a nuclear localization signal (NLS) added at the N-terminus of dCas13b. CURE-C2 and CURE-N were derived from CURE-C1 by replacing the NLS with a mutant version (NLS*) and appending an extra copy of WT NLS, respectively. CURE-X comprises A3A (Y132D) inserted into a flexible loop on dCasRx, with part of the loop (aa 559–585) deleted during plasmid construction (Zhang et al, 2018). C. The GFP reporter system. We split GFP into two parts (β1–10 and β11), flanked each with a pair of interacting leucine zippers (ZIP) to prevent their spontaneous association (To et al, 2016), and inserted a 90-bp linker (blue) between GFP (β1–10) and the downstream Zip. The linker bears CGA (preceded by UAU to mimic the SDHB tetra-loop), where C>U editing would convert CGA (R12) to a stop codon (UGA), thus eliminating the downstream ZIP. The loss of this ZIP triggers GFP reconstitution (To et al, 2016), an event detectable by FACS. To reduce editing-independent reconstitution (leakiness), the ZIP was flanked by a NLS and a degron (Chung et al, 2015). D–G. GFP reporter editing by CURE-C1. gRNA#1, predicted to induce a 14-nt loop encompassing UAUC, was tested together with various controls (gRNA#2–5; Fig 1D). Plasmids expressing CURE-C1-P2A-mCherry, a gRNA, or the GFP reporter were co-transfected into HEK293 cells, and editing measured 2 days later by FACS or sequencing. Representatives of FACS plot and Sanger chromatograph are shown (E and F), together with NGS analysis of editing efficiencies (G, displaying mean ± SEM, n = 3). The values in F are % editing. The blue boxes in the FACS plots indicate the gates for the cell populations analyzed, with the blue numbers being the abundance (%) of the gated cells, and the green and red numbers their mean fluorescence intensities of GFP and mCherry, respectively. Non-targeting (NT) gRNA is identical to gRNA #1 except that the spacer sequence is irrelevant to the target transcript. H. Editing of endogenous mRNAs. The target sites and gRNAs are depicted at the left, with the edited codon (auC) underlined. CURE-C1-P2A-mCherry and gRNAs were co-expressed in HEK293T cells and the mCherry+ cells analyzed 2 days later by Sanger sequencing and NGS in parallel. The bar graph displays mean ± SEM (n = 3). The gRNAs carried 32-nt spacers capable of inducing 14-nt loops (designated 32-14 hereafter). NT, non-targeting RNA. Download figure Download PowerPoint To harness A3A to create C>U RNA Editor (CURE), we fused it to the catalytically dead mutants of Cas13. Several key versions of CURE were created, the first being CURE-C1 (CURE-Cytoplasmic1), comprising A3A (Y132D) fused via a nuclear export sequence (NES) to the C-terminus of dPspCas13b (Cox et al, 2017; Fig 1B). Y132D was found to increase the editing efficiency (see further). CURE-C1 also carries a Nuclear Localization Signal (NLS) at the N-terminus, intended to drive a significant portion of CURE-C1 molecules into the nucleus, thus potentially enhancing mRNA editing. The mRNA editing rate was indeed increased (see further), but unexpectedly, CURE-C1 proved predominantly (albeit not exclusively) cytoplasmic (Appendix Fig S2A, top), but this subcellular distribution pattern should not hamper our characterization of the basic properties of the CURE system. We also constructed a reporter system based on split GFP, where deamination at the target C (in the context of UAUC, as in the SDHB tetra-loop) would produce GFP fluorescence detectable by FACS (Fig 1C). GFP signal offers a convenient and fast albeit indirect and preliminary readout of editing. In contrast, sequencing of the reporter transcript enables direct and reliable quantifications of editing, with Sanger sequencing producing results generally consistent with that obtained using next-generation sequencing (NGS; Sharma et al, 2016, 2017), especially when the chromatograms are analyzed with the EditR method (Kluesner et al, 2019). As the UAUC in the SDHB RNA is embedded in the tetra-loop on top of the 5-bp stem, we reasoned that creating a similar structure (e.g., a 14-nt loop with centrally positioned UAUC) at our reporter transcript might facilitate editing. Therefore, we designed a gRNA capable of inducing such a loop (gRNA#1, Fig 1D). Indeed, gRNA#1 markedly increased GFP fluorescence as compared with a non-targeting gRNA carrying a random spacer sequence (Fig 1E). Sanger sequencing and NGS revealed that gRNA#1 induced efficient (~40%) C>U editing at the target C (Fig 1F and G, lane 1–2). In contrast, gRNA#2, capable of loop induction but not editor recruitment, was inactive, as were gRNA#3–5 capable of editor recruitment but not loop induction (Fig 1G, lane 3–6), indicating loop formation and CURE-C1 recruitment were both necessary for editing. In agreement with this, A3A, alone or in combination with the free dCas13b, failed to edit the target even in the presence of gRNA#1 (Fig 1G, lane 7–8). These data demonstrate that CURE-C1 was recruited to the target site at the reporter transcript via gRNA-dCas13b interaction, where it could deaminate the target C if and only if embedded in an induced loop. We then tested the ability of CURE-C1 to edit UC at endogenous mRNA transcripts. We opted to focus on the codon AUC where the C>U edit would produce synonymous substitutions (I>I), in order to avoid potential confounding effects resulting from protein alterations. We found that CURE-C1 edited multiple endogenous targets (ACTB, GAPDH, and TYMS) as efficiently as it did the GFP reporter (40–50%; Fig 1H). As mentioned before, despite the presence of NLS, CURE-C1 was predominantly cytoplasmic. Consistent with this, CURE-C2 (Fig 1B), a CURE-C1 variant carrying a mutant NLS and therefore exclusively cytoplasmic (Appendix Fig S2A, bottom), was as active as CURE-C1 in editing the endogenous transcripts (Appendix Fig S2B). In contrast, deleting the NLS from CURE-C1, removing the Y132D mutation, or replacing it with other mutations, each negatively affected CURE-C1 activity (Appendix Fig S2C and D; it is unclear how a mutant NLS could enhance editing efficiency). Finally, fusing A3A to the N-terminus of dCas13b as opposed to the C-terminus also impaired editing (Appendix Figs S3 and S4A, compare A3A-dCas13b vs. dCas13b-A3A). Collectively, these data indicate that A3A is tractable for SDRE. We have also tested multiple other Apobec proteins including A1, A2, and A3G, but without success (Appendix Figs S3–S4). Creation of CURE-N and CURE-X, the potential high-specificity versions of CURE A3A overexpression in HEK293 cells is known to induce C>U editing at ~ 4,200 sites at the transcriptome (Sharma et al, 2017), suggesting that CURE-C may also has such off-target effects. We took two approaches to address this potential problem. First, inspired by the finding that nuclear localization of an A>I RNA editor can reduce its off-target effects (Vallecillo-Viejo et al, 2018), we sought to create a nuclear-localized version of CURE. To this end, we added a copy of NLS to CURE-C1 at the C-terminus, finding the resulting editor (CURE-N; Fig 1B) indeed nuclear and remained highly active at the GFP reporter (Appendix Fig S5A). The second approach of off-target reduction involves CasRx, another member of the Cas13 family(Konermann et al, 2018). In contrast to Cas13b, CasRx is known to possess multiple flexible loops(Zhang et al, 2018). We have found, during the optimization of an A>I RNA editor comprising dCasRx fused to the ADAR2 deaminase domain, that inserting the deaminase domain into Loop 3 of dCasRx helps minimize the global off-target effects of the editor without compromising on-target editing (accompanying manuscript). Accordingly, we inserted A3A(Y132D) into Loop 3 of dCasRx (CURE-X; Fig 1B). Remarkably, CURE-X was more active than all other fusion proteins tested, including a conventional N-terminal fusion configuration (Appendix Fig S5B). Further characterization of the CURE system We next systematically defined the determinants in gRNA and GFP reporter sequences that may impact editing. We tested both CURE-C1 and CURE-X because the two editors may behave differently, given the marked differences in both the dCas moiety and the fusion configuration. On the other hand, CURE-C2 and CURE-N were both highly similar in structure to CURE-C1, and therefore not tested. For CURE-C1 editing, we first fixed the loop length at 14 nt at the GFP reporter but varied the spacer length (24–60 nt), finding diverse lengths (24–52 nt) capable of inducing editing, the efficiencies exceeding 20% and peaking at 38%, the latter achieved with the 32-nt spacer (Fig 2A; see Appendix Fig S6A for a parallel FACS analysis). The same trend was observed at a few shorter (10-nt and 6-nt) loops tested (Appendix Fig S6B). We then fixed the spacer length at 32 nt, but systematically varied the loop length (4–20 nt) by flanking UAUC with increasing numbers of bases, adding equal numbers of bases to each side so as to maintain the central position for UAUC. Loops of all these lengths supported efficient editing (40–58%) except the tetra-loop (16%; Fig 2B). A caveat is that when the loop length was increased, so was the distance of the target C relative to the ends of the loop, which complicated data interpretations. To isolate the potential effects of target C positions, we fixed the loop length to 14 nt and placed the C at various (5th to 11th) positions. Since repositioning the target C can alter its sequence context and confound the analysis, we moved it together with seven flanking bases (AUAUCGAG) as a single unit. Efficient (34–55%) editing was detected at all these positions, with a broad peak spanning the 6th–9th positions (Fig 2C). These data demonstrate that at the induced loops, CURE-C1-catalyzed deamination of UC was quite robust to the context (loop/spacer length and target C position), which was unexpected given the stringent structural requirements imposed on the natural A3A targets. Presumably, dCas13b-enforced recruitment of A3A was able to make CURE-C1 tolerant of suboptimal target structures, which greatly simplified gRNA design for SDRE. Figure 2. Parameters affecting editing by CURE-C1 and CURE-X A–D. Basic features impacting editing: gRNA spacer length (A), loop length (B), target C position at the induced loop (C), and the bases flanking the target C (D). In (B-D), the spacer for CURE-C1 is 32 nt as depicted, whereas that for CURE-X is 28 nt (not shown). Values are mean ± SEM (n = 3). NT, non-targeting. E. Sparing a bystander in a target site. The target region is a synthetic 200-nt fragment from the human PGAP2 transcript bearing a U>C mutation (red) to be corrected. The bystander (green) was included in or excluded from the induced loops depending on the gRNAs. This transcript was co-expressed with gRNA and CURE-C1 in HEK293T cells, and editing analyzed 2 days later by Sanger sequencing (Fig 2E, bottom left, bar graph along with a representative chromatogram, where the values are % editing). To compare CURE-C1 and CURE-X, select gRNAs (32-6, 32-10, 32-14, and 28-14) were expressed and the transcript analyzed by NGS (Fig 2E, right). The bar graphs display mean ± SEM (n = 3). Data information: For each parameter tested, the target sites and the gRNA spacers are depicted at the left, while the top and bottom bar graphs at the right display the editing rates for CURE-C1 and CURE-X, respectively; CURE-C1 editing was analyzed by Sanger sequencing and while CURE-X by NGS. Download figure Download PowerPoint We next explored editing motif preference of CURE-C1. CURE-C1 proved highly active when C was preceded by U (53% editing rates) but inactive if preceded by other bases (2–5%), as predicted from the known property of A3A (Fig 2D, middle panel in the top bar graph). In contrast to the strict requirement of U preceding C, editing was relatively robust to the variations in the bases flanking UC, achieving about 20–63% of editing rates in different contexts (Fig 2D, top, position +1 and −2). Interestingly, in the auCC motif, the second C became editable once the first C was converted to U (Appendix Fig S6C). Thus, C does not have to be preceded by U for editing by CURE-C1; CC is also editable if the dinucleotide is preceded by U. The ability to edit CC is a unique and useful feature of CURE, as it enlarges its editing scope (Appendix Fig S6D), which is particularly attractive considering the inability of RESCUE-S to edit CC (Appendix Fig S6C). Of note, in contrast to CURE-C1, free A3A is known to be inactive if UC is followed by U or C, or preceded by G (Sharma et al, 2017), again suggesting relaxed target site requirement for CURE-C1 due to its forced tethering by dCas13b. Finally, we considered a situation where two UC are located within the same loop. We found both editable by CURE-C1, which would be undesirable if one of the Cs is a bystander (Fig 2E, gRNAs with a 14-nt loop). However, this scenario could be readily avoided by excluding the bystander from the loop via gRNA adjustment (Fig 2E, gRNAs with 6-nt and 10-nt loops). On the other hand, the potential of CURE-C1 to edit multiple UCs can be valuable for certain applications, such as stop codon induction within the editing window via C>U editing at CAA, CAG, and CGA(Billon et al, 2017); indeed, a C>U DNA base editor (BE-Plus) has been developed to achieve analogous multiplex editing to ensure stop codon induction at the DNA level (Jiang et al, 2018). We conclude that CURE-C1 could be flexibly programmed to edit user-defined UCC in a variety of contexts, and the editing was rather robust to variation in the gRNA configuration, with reasonable efficiencies achievable using gRNAs carrying 24- to 56-nt spacers capable of inducing 6- to 20-nt loops. Remarkably, a similar trend was seen for CURE-X, although, in general, CURE-X was less active than CURE-C1 and more sensitive to gRNA designs (Fig 2A–E, right, bottom bar graph in each panel; Appendix Fig S6C, which also shows that CURE-N could edit UCC as did CURE-C1). The CURE system has complementary strengths and weaknesses to RESCUE-S at endogenous transcripts We next compared CUREs with RESCUE-S in terms of on-target editing efficiency and global off-target effects on the transcriptome. RESCUE, the precursor to RESCUE-S, was excluded in the comparison given the massive off-target effects that prohibit its practical uses. For CURE, we tested CURE-C2, CURE-N, and CURE-X; CURE-C2 instead of its precursor CURE-C1 was used here (even though the two performed indistinguishably; Appendix Fig S2A), as CURE-C2, but not CURE-C1, was exclusively localized to the cytoplasm just like RESCUE-S, thus making the comparison more rigorous. To avoid biases, we compared the editors not only at our standard four transcripts (GFP reporter, GAPDH, ACTB, TYMS) but also at the representative target sites of RESCUE(S), located at the PPIB, CTNNB1, SMARCA4, and KRAS (Appendix Fig S1B; Abudayyeh et al, 2019). For RESCUE-S, the information on the optimized gRNAs is available for all the four targets except KRAS, and so we only optimized the gRNAs for editing KRAS and for our standard targets (Appendix Fig S7A). We also optimized the gRNAs for CURE-X (Appendix Fig S7B). In contrast, for CURE-C2 and CURE-N, we simply used a generic gRNA format (32-14) for convenience. Compared with RESCUE-S, all three CUREs proved substantially more active at GFP reporter and PPIB (editing rates ~30–50% vs. ~10%; Fig 3A, first two target sites). At the remaining six sites, CURE-C2 editing was moderately more active (TYMS, ACTB, and CTNNB1) or as active (KRAS, SMARCA4, and GAPDH), CURE-N was as active except at KRAS and SMARCA4 where its edit
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