ABSTRACT
Small interfering RNAs (siRNA) therapeutics have developed rapidly in recent years, despite the challenges associated with delivery of large, highly charged nucleic acids. Delivery of siRNA therapeutics to the liver has been established, with conjugation of siRNA to N-acetylgalactosamine (GalNAc) providing durable gene knockdown in hepatocytes following subcutaneous injection. GalNAc binds the asialoglycoprotein receptor (ASGPR) that is highly expressed on hepatocytes and exploits this scavenger receptor to deliver siRNA across the plasma membrane by endocytosis. However, siRNA needs to access the RNA-induced silencing complex (RISC) in the cytoplasm to provide effective gene knockdown and the entire siRNA delivery process is very inefficient, likely due to steps required for endosomal escape, intracellular trafficking, and stability of siRNA. To reveal the cellular factors limiting delivery of siRNA therapeutics, we performed a pooled, genome wide knockout screen based on delivery of GalNAc conjugated siRNA targeting the HPRT1 gene in the human hepatocellular carcinoma line Hep3B. Our primary pooled genome wide knockout screen identified candidate genes that when knocked out significantly enhanced siRNA efficacy in Hep3B cells. Follow-up studies indicate that knockout of one gene in particular, RAB18, improved siRNA efficacy.
INTRODUCTION
SiRNAs are short (20~25 base pairs), double-stranded RNA molecules that operate through the RNA interference (RNAi) pathway to specifically degrade target gene mRNA1. The therapeutic potential of siRNAs has been intensively investigated in recent years to treat a wide range of human diseases. Compared with traditional drug molecules, siRNAs are highly potent and capable to act on previously “non-druggable” targets2–4. More impressively, the duration of siRNA conjugate mediated potent mRNA knockdown has been shown to last for several months2–5.
Despite their substantial therapeutic potential, siRNA therapeutics are associated with challenges associated with the delivery of large, highly negatively charged nucleic acids into cells. Delivery of siRNA therapeutics to the liver has been established, with conjugation of siRNA to GalNAc providing durable gene knockdown in hepatocytes following subcutaneous injection6–8. On hepatocytes, GalNAc binds the highly expressed scavenger receptor, ASGPR, to deliver siRNA across the plasma membrane by clathrin-coated endosomes9–11. The human ASGPR exists as hetero-oligomers formed by two subunits: the major ASGR1 (asialoglycoprotein receptor 1) subunit and the minor ASGR2 (asialoglycoprotein receptor 2), with the ASGR1 subunit being critical for efficient GalNAc conjugated siRNA delivery12–14. Although GalNAc conjugation improves siRNA delivery, it is still an inefficient process15,16.
As endosomes mature, the internal pH drops and causes GalNAc conjugated siRNAs to be released from ASGPR. The ASGPR receptors then quickly recycle back to the cell surface, while GalNAc conjugated siRNAs remain inside the endosome15. The endosomal glycosidase then works to cleave GalNAc from siRNA conjugates15. Less than 1% of the remaining free siRNAs are capable of escape from endosomes through an unknown mechanism and have access to RISC in the cytoplasm to provide effective gene knockdown and induce RNAi responses in the cytoplasm16. After siRNA enters the cell, it remains inactive until becomes loaded into the core component of RISC. The passenger (sense) strand is cleaved and ejected at Argonaute 2 (Ago2), and the guide (antisense) strand is then bound to catalytic Ago217,18. The siRNA guide strand then guides and aligns the RISC complex on the target mRNA and induces cleavage of the target mRNA through the catalytic function of Ago2. The siRNA intracellular trafficking and escape steps are very inefficient, and the underlying mechanisms are not fully understood15,19.
In recent years, adaptation of the bacterial CRISPR-Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats-CRISPR-Associated Protein 9) system to mammalian cells have enabled genome wide loss-of-function screens to identify new biological mechanisms20–24. To reveal the cellular factors limiting delivery of siRNA therapeutics, we performed a pooled, genome wide CRISPR-Cas9 screen (referred as CRISPR screen in the rest of this article) based on delivery of GalNAc conjugated siRNA targeting the HPRT1 gene in the human hepatocellular carcinoma line Hep3B. Multiple candidate genes that when knocked out significantly enhance siRNA efficacy in Hep3B cells were identified from the CRISPR screen. A secondary, arrayed CRISPR screen using multiplexed synthetic gRNA in 96/384-well format was then used to validate these candidate genes. Additional follow-up studies of one top candidate gene, RAB18, indicate that knocking out RAB18 improves siRNA silencing potency at the mRNA level. The results of this study provide insights into mechanisms of siRNA delivery to both hepatic and extrahepatic tissues.
RESULTS
Hep3B cells demonstrated robust GalNAc conjugated siRNA induced silencing
An ideal system for identifying key regulators of GalNAc conjugated siRNA induced silencing would have the following attributes: 1) long-term maintenance; 2) stable Cas9 expression; 3) capability of gRNA lentivirus library transduction; and 4) sufficient siRNA induced silencing to allow ranking of candidate genes. Human primary hepatocytes have been proven to uptake GalNAc conjugated siRNA through cell surface ASGPR9–11. However, large scale CRISPR screens have been challenging in human primary hepatocytes due to their limited proliferative potential. We therefore explored the possibility of using human hepatocellular carcinoma cell lines such as HepG2 or Hep3B to perform our CRISPR screen. Although both HepG2 and Hep3B cells express high levels of ASGR1 and ASGR2 (Supplementary Table 1), only Hep3B cells displayed robust knockdown of target genes through GalNAc conjugated siRNA induced silencing in our hands (Figure 1a, Supplementary Table 2). GalNAc conjugated siRNA was able to induce target gene knockdown in Hep3B cell line in a dose dependent manner, and the level of silencing was sufficient to perform the CRISPR screen.
To further validate whether GalNAc conjugated siRNA induced silencing in Hep3B is mediated through ASGR1, an antibody blocking test was performed (Figure 1b). To perform this experiment, Hep3B cells were first pre-incubated with an in-house generated, anti-ASGR1 antibody (7E11), or no antibody treatment as control for half an hour, followed by treatment with GalNAc conjugated siRNA targeting HPRT1 (GalNAc-HPRT1 siRNA: 8172) (Supplementary Table 2) at multiple doses. The target gene (HPRT1) mRNA levels were measured on day 4 post-siRNA treatment through ddPCR (digital droplet polymerase chain reaction) analysis. As indicated in Figure 1b, application of the ASGR1 specific antibody was able to mitigate the siRNA silencing efficacy (13-fold higher IC50 for no antibody (5404nM) relative to anti-ASGR1 (407.7nM).
After establishing the suitability of Hep3B for GalNAc conjugated siRNA induced silencing, we then generated Hep3B cells stably expressing Cas9. The editing capability of the Cas9 stable Hep3B was assayed through validating their editing efficacy on two target genes, SLC3A2 and ASGR1 (Supplementary Table 3 and Supplementary Figure 1). The Cas9 stable Hep3B cells (referred as Hep3BCas9 in the rest of this article) were then used to perform the CRISPR screen to search for key regulators of GalNAc conjugated siRNA induced silencing.
HPRT1-6TG (6-ghioguanine) live/dead selection based CRISPR screen in Hep3BCas9 cells
A CRISPR knockout screen based on live/dead selection is the most efficient and convenient systematic experiment to identify potential regulators of siRNA efficacy. We therefore chose to take advantage of the established HPRT1-6TG based live/dead selection system for this CRISPR screen to look for key regulators of GalNAc conjugated siRNA induced silencing. 6-thioguanine (6TG), a purine analog, is incorporated into DNA and RNA resulting in cell death after being phosphorylated by hypoxanthine phosphoribosyl transferase (HPRT) encoded in humans by the HPRT1 gene25. Knocking down or knocking out HPRT1 provides resistance to 6TG and allows those cells to survive. One thing to keep in mind when utilizing HPRT1-6TG live/dead selection system is that mismatch repair defective cells and cells with HPRT1 mutations might also be resistant to 6TG26, necessitating independent validation of candidates identified using this method. Based on this theory, a GalNAc conjugated siRNA targeting human HPRT1 incorporating Fluoro (F) and Methoxy (OMe) modifications (Supplementary Table 2), GalNAc-HPRT1 siRNA (8172), was designed and validated. If GalNAc-HPRT1 siRNA can enter the cells and induce HPRT1 gene silencing, these cells would be able to survive in the presence of 6TG. Otherwise the cells would be killed by 6TG selection if GalNAc-HPRT1 siRNA does not silence HPRT1. Under the CRISPR knockout condition, if a gene is normally required for siRNA activity, knocking out this gene would diminish or abolish siRNA function and cause the cells to be eliminated by 6TG selection. Alternatively, if a gene normally functions to inhibit or block siRNA activity, knocking out this gene would improve siRNA potency and enable the cells to survive 6TG selection. Therefore, when sequencing gRNAs in surviving cells, the enriched gRNAs reflect genes that may normally inhibit siRNA activity, while gRNAs targeting genes essential for siRNA function would be depleted. However, other gRNAs targeting genes that impact cell viability through non-siRNA related mechanisms would also be depleted from live cell population, making it difficult to identify siRNA essential genes from the depleted gRNA population. We therefore chose to focus on analyzing the enriched gRNAs from surviving cells to enable us to identify genes that inhibit GalNAc conjugated siRNA induced silencing in Hep3B.
We first established the baseline 6TG kill curve in Hep3BCas9 cells without siRNA treatment (Figure 1c). To avoid both insufficient and excessive killing caused by 6TG, we performed a small-scale pilot run using 100 μM 6TG (~IC70) (Figure 1d) and 20 μM 6TG (~IC50) (Supplementary Figure 2). An 80k genome wide CRISPR gRNA lentivirus library (CRISPR KOHGW 80K (lot#17050301), Cellecta, Mountain View, CA) was transduced into Hep3BCas9 cells to generate a genome wide knockout pool. These gRNA transduced cells were then analyzed for their ability to be selected using GalNAc-HPRT1 siRNA and 6TG. As illustrated in Figure 1d, cells were divided into four groups (0.6E+06 cells/group): 1) siRNA only, 2) siRNA with 6TG treatment, 3) 6TG only, and 4) negative control. To obtain sufficient but not excessive siRNA effect, 750 nM (about IC60) GalNAc-HPRT1 siRNA (8172) was used. On day 3 post-6TG treatment, the 6TG only group had 35% viable cells while the HPRT1-si + 6TG group had 52% viable cells (Figure 1d). On day 6 post-6TG treatment, the 6TG only group had only 5% viable cells while the HPRT1-si + 6TG group had 17% viable cells (Figure 1d). These results indicate that GalNAc-HPRT1 siRNA treatment was partially protective. This provides a screening phenotype well-suited for detecting gene knockouts that enhance RNAi activity. Based on our findings from this initial screen, we chose to use 6-day 100 μM 6TG treatment as the condition for CRISPR screen. To test the impacts of siRNA dosage on CRISPR screen, the actual CRISPR screen was done with both 150 nM GalNAc-HPRT1 siRNA (low dose group), and 750 nM GalNAc-HPRT1 siRNA (high dose group). The CRISPR screen experimental scheme is diagramed in Figure 2a. The genomic DNA samples were extracted from all sample pellets collected during the screen and sent to Cellecta for NGS (next gen sequencing) barcode sequencing.
NGS sequencing results
The NGS sequencing results were analyzed by OGA algorithm27. False discovery rate (FDR) <0.2 was used as cutoff line. As shown in Supplementary Figure 3a-3b, all samples maintained good representation of gRNA library – roughly 77,000 gRNAs present with similar overall distribution. In addition, gRNAs that target HPRT1 were successfully enriched by about 2-fold in 6TG treated vs. no 6TG group (Supplementary Figure 4). We then looked for additional genes that may play key roles in regulating GalNAc conjugated siRNA activity.
In order to identify genes that when knocked out can improve GalNAc conjugated siRNA internalization, trafficking or RNAi activity, we focused on gRNAs that were enriched in samples treated with both siRNA and 6TG but were not enriched in the 6TG treated only control group. These hits include genes that when knocked out could: 1) enhance GalNAc-HPRT1 siRNA silencing potency, 2) increase sensitivity to 6TG in the absence of siRNA, or 3) enhance cell viability in the presence of 6TG. To select the genes with the most potent effects, we selected gene hits that were significantly (FDR<0.2) enriched in both high dose (750 nM) and low dose (150 nM) GalNAc-HPRT1 siRNA and 6TG treated groups. (Figure 2b). This analysis identified 17 genes (Figure 2b). To understand whether any of these 17 genes have impacts on cells’ sensitivity to 6TG treatment in the absence of siRNA, we plotted these genes with the genes depleted in no siRNA but only 6TG treated group vs. no siRNA and no 6TG treated samples (Figure 2c). In Figure 2c, the horizontal axis indicates the sensitivity to 6TG. The genes that when knocked out enhance the sensitivity to 6TG and lead to strong cell death upon 6TG treatment are enriched on the horizontal axis with smaller FDR. If FDR < 0.2 was set as the cutoff, 8 genes were identified as promoting sensitivity to 6TG treatment (Figure 2c). The genes that when knocked out have no impact on 6TG sensitivity have larger FDR on horizontal axis, and these genes (RAB18, YAP1, CCNE1, SLC30A9, C14orf80, HIF1AN, TRAF2, NAPG and SCFD2) are the most interesting to us because their enrichment is most likely to be directly related to siRNA delivery and activity.
Validation of primary CRISPR screen hits by secondary arrayed CRISPR screen
As discussed above, the HPRT1-6TG selection CRISPR screen may introduce false positive hits. To overcome this, we used a multiplexed synthetic gRNA system developed by Synthego (Redwood City, CA), which provides efficient knockout of target genes and can be scaled up to screen in 96-well or 384-well format without clonal isolation. In this multi-guide strategy, three gRNAs designed in close proximity to one another are delivered together to Cas9+ cells to induce a large deletion in the target gene and more efficient target gene knockout than individual gRNA. After inhouse validation of this strategy (Supplementary Figure 5), we ordered multiplexed synthetic gRNAs for some of the CRISPR screen hits along with control genes to run secondary arrayed CRISPR validation.
As illustrated in Figure 2d, the multiplexed synthetic gRNAs for genes identified in our initial CRISPR screen (RAB18, CCNE1, SLC30A9, NAPG, SCFD2, VPS37A, SAMD4B and CAB39) along with some control genes (AGO2, ASGR1, and ASGR2) were transfected into Hep3BCas9 cells. CRISPR-KO cells generated in this manner were then treated with GalNAc-HPRT1 siRNA or HPRT1 siRNA delivered through other conjugation formats (anti-ASGR1 antibody conjugated HPRT1 siRNA (6709) and cholesterol conjugated HPRT1 siRNA (17102), Supplementary Table 2). A heatmap of HPRT1 siRNA silencing efficacy as measured by ddPCR (normalized to no siRNA control) is shown in Figure 2e. As expected, when AGO2 is knocked out by multiplexed synthetic gRNA, the HPRT1 siRNA silencing activity is abolished in all tested siRNA conjugates. Because ASGR1 is a critical component of ASGPR receptor, ASGR1 CRISPR-KO leads to loss of response to GalNAc-HPRT1 siRNA as well as to anti-ASGR1 antibody conjugated HPRT1 siRNA. However, knocking out ASGR1 had no impacts on the function of Cholesterol conjugated HPRT1 siRNA. These results indicate that the multiplexed synthetic gRNA system was working as expected. Some CRISPR screen hits: RAB18, SCFD2, NAPG, and SAMD48 when knocked out by multiplexed synthetic gRNA enhanced siRNA effects to different degrees (Figure 2e). VPS37A specifically enhanced cholesterol conjugated siRNA efficacy. Other screen hits, CAB39, CCNE1 and SLC30A9, could not be validated by the multiplexed synthetic gRNA approach. Proteins encoded by ZW10 and STX18 had been shown to interact with RAB18 protein28,29. Knocking out ZW10 and STX18 by multiplexed synthetic gRNA also enhanced siRNA silencing efficacy (Figure 2e).
RAB18 knockdown/knockout enhances the silencing effects of multiple siRNA conjugates
Since RAB18 was the only RAB family member detected in our CRISPR screen, and because the RAB family is important in regulating intracellular vesicle trafficking, we decided to focus on understanding the mechanisms by which RAB18 regulates siRNA activity in Hep3B. To study the function of RAB18, three RAB18 specific siRNA molecules (siRAB18_1, siRAB18_2, and siRAB18_3) (Supplementary Table 4) purchased from Ambion were validated for their silencing potency of RAB18 in Hep3B cells through transfection study. Among three tested siRNA molecules, siRAB18_3 which showed the best knocking down potency of RAB18 (Figure 3a) was then used to study the function of RAB18. The Hep3B cells transfected with either siRAB18_3 or a non-targeting control siRNA molecule (siNTC) for 24hr were further treated with GalNAc-HPRT1 siRNA at various concentration. As illustrated in Figure 3b, the siRNA18_3 treated cells were able to maintain low level (23.2%) of RAB18 mRNA measured by ddPCR on day 4 post GalNAc-HPRT1 siRNA treatment compared with siNTC treated cells. The level of HPRT1 mRNA was also measured by ddPCR on day 4 post GalNAc-HPRT1 siRNA treatment. As shown in Figure 3c, the knockdown of HPRT1 was greater in siRAB18_3 treated Hep3B cells compared to siNTC treated Hep3B cells. The IC50 for siRAB18_3 treated cells or siNTC treated cells was 24.8nM versus 223.6nM (Figure 3c), respectively, a 10-fold change.
In order to completely abolish the function of RAB18, we created two RAB18 knockout pools (RAB18_KO_1 and RAB18_KO_2) by transducing two lentiviral gRNA vectors targeting RAB18 (SIGMA vector: U6-gRNA: PGK-puro-2A-tagBFP) into Hep3BCas9 cells (Supplementary Figure 6a). The RAB18 knockout efficiency was verified by Amplicon-EZ sequencing (GENEWIZ, Newbury Park, CA) (Supplementary Figure 6b and 6c). Knocking out RAB18 did not alter cell viability in Hep3BCas9 cells (supplementary Figure 6d). Since RAB18 was identified through HPRT1-6TG selection screen, we first repeated the same assay in RAB18 knockout cells. As shown in Figure 3d, compared with the parental Hep3BCas9 cells, when treated with GalNAc-HPRT1 siRNA approximately 15% more RAB18 knockout cells were able to survive under 6TG selection (58% in RAB18 knockout cells compared to 43% in Hep3BCas9 cells at the highest siRNA dose tested), indicating that HPRT1 siRNA induced greater gene silencing in RAB18 knockout cells than in Hep3BCas9 parental cells. Neither Hep3BCas9 cells nor RAB18 knockout cells treated with GalNAc conjugated siRNA targeting PPIB gene (8714) as a non-relevant siRNA control showed enhanced resistance to 6TG treatment (Figure 3d, Supplementary Table 2). We then used ddPCR to directly measure the siRNA silencing potency in RAB18 knockout cells. As illustrated in Figure 3e, 3c and 3d, Hep3BCas9 cells and RAB18 knockout cells were treated with three GalNAc conjugated siRNAs: HPRT1 siRNA, ASGR1 siRNA (16084) (Supplementary Table 2), and PPIB siRNA. For all three tested siRNAs, the target gene knockdown was greater in RAB18 knockout cells compared to Hep3BCas9 parental cells (Figure 3e-g). The IC50 for HPRT1 siRNA in Hep3BCas9 or two RAB18 knockout lines was 83.4nM versus 2.6nM or 4.1nM (Figure 3e), respectively, a 20~30-fold change. When tested using GalNAc-ASGR1 siRNA, the IC50 was 198.3nM in Hep3BCas9 cells and 7.9nM or 6.5nM in two RAB18 knockout cells (Figure 3f). Compared to HPRT1 and ASGR1, PPIB is a highly abundantly expressed gene in Hep3B cells (Figure 3g), that could not be silenced by GalNAc-PPIB siRNA in Hep3BCas9 cells (Figure 3g). However, the same PPIB siRNA was able to silence PPIB in two RAB18 knockout pools (IC50=205.2nM or 391.8nM) (Figure 3g). The siRNA silencing efficacy at a later time point (11 days) was also checked (Supplementary Figure 7a-c). Although the silencing effect declined as the cells proliferated over time, the silencing potency was greater in RAB18 knockout cells than in Hep3BCas9 cells. For example, when treated with GalNAc-ASGR1, the IC50 at day 11 was 363.6nM in Hep3BCas9 cells and 41.3nM or 58.3nM in two RAB18 knockout pools (Supplementary Figure 7a). These results lead us to conclude that RAB18 knockout enhances the silencing potency of GalNAc conjugated siRNA as well as cholesterol and antibody conjugated siRNA.
Gene silencing induced by GalNAc conjugated siRNA in RAB18 knockout cells requires ASGR1
As discussed and tested earlier, the GalNAc siRNA conjugate induced gene silencing is mediated through ASGR1. We therefore tested if ASGR1 was required for GalNAc siRNA conjugates to function in RAB18 knockout cells using an antibody blocking test (Figure 3h, Supplementary Figure 7d-e). As shown in Figure 3h, the application of 7E11 was able to reduce the siRNA silencing efficacy of HPRT1 gene in Hep3BCas9 and RAB18 knockout cells. Similar results were obtained when the same experiment performed by using ASGR1 siRNA and PPIB siRNA to silence ASGR1 and PPIB (Supplementary Figure 7d-e). Similarly to what we observed in Hep3B cells, the GalNAc siRNA conjugates rely on ASGR1 to enter RAB18 knockout cells. The two individually generated RAB18 knockout pools behaved identically in all tests. Therefore, only one RAB18 knockout pool was used for the rest of the related experiments (referred as RAB18_KO).
RAB18 knockout shows no effect on the activity of siRNA delivered through Lipofectamine transfection
Lipofectamine reagents have been widely used experimentally as a safe and efficient method to deliver exogenous DNA and RNA into cells. After confirming that knocking out RAB18 enhances siRNA potency delivered through GalNAc conjugates, we asked if knocking out RAB18 could enhance siRNA potency delivered through Lipofectamine mediated transfection. To address this question, we used an unconjugated HPRT1 siRNA (17629) (Supplementary Table 2) to treat the parental Hep3BCas9 and RAB18 knockout cells at various concentrations with or without Lipofectamine RNAiMAX reagent (Invitrogen, Waltham, MA). As summarized in Figure 3i, Lipofectamine reagents efficiently silenced the target gene HPRT1 at similar levels in both Hep3BCas9 (IC50=0.2nM) and RAB18 knockout cells (IC50=0.3nM). This finding indicates that RAB18 does not alter Lipofectamine mediated siRNA activity.
DISCUSSION
The HPRT1-6TG selection based CRISPR-Cas9 screen performed in Hep3B background has successfully identified several key regulators of GalNAc conjugated siRNA activity. Some of the hits from this screen, such as RAB18, SCFD2, NAPG, and VPS37A, have been validated through a secondary arrayed CRISPR screen system by using multiplexed synthetic gRNA. Here, we focused our efforts on studying the effects RAB18 on siRNA activity.
Having confirmed that knocking out RAB18 enhances siRNA silencing potency on multiple tested target genes (HPRT1, ASGR1, and PPIB) and through multiple siRNA conjugated formats (GalNAc, Cholesterol, and antibody conjugates), we attempted to elucidate the functional linkage between RAB18 and siRNA activity. RAB GTPases constitute the largest family of small GTPases that have important roles in regulating membrane trafficking through switching between GTP-bound ‘on’ form and GDP-bound ‘off’ forms. There are more than 60 RAB family members in humans that are localized to distinct intracellular membranes and play important roles in regulating intracellular vesicle budding, uncoating, motility, and fusion. Once internalized, siRNA has been shown to traffic through the endocytic pathway30,31. We therefore expected multiple members of the RAB family to be identified in our CRISPR screen as regulators of siRNA activity. To our surprise, RAB18 was the only RAB family member that came out of our screen (FDR<0.2).
As one of the 20 most highly conserved RAB GTPases present in the last eukaryotic common ancestor of both the plant and animal kingdoms32,33, RAB18 has attracted great research interest and attention. Studies conducted in the last couple decades have linked RAB18 to regulation of lipid droplet (LD) formation28,34, inhibition of COPI independent retrograde trafficking from Golgi to endoplasmic reticulum (ER)35, regulation of secretory granules36 and peroxisomes37, promotion of hepatitis C virus (HCV) assembly on the LD membrane38, and regulation of normal ER structure39. Despite the intensive efforts on studying RAB18, a defined molecular function of RAB18 and its site of action has remained elusive. It is very difficult to tease out what known functions of RAB18 gene might contribute to regulation of siRNA activity, or whether a novel function of RAB18 needs to be identified. However, several lines of evidence may provide a clue to a potential mechanism. First, the NRZ (NAG-RINT1-ZW10) tethering factors and their associated ER-localized SNAREs (Use1, Syntaxin18, and BNIP1) form a complex with GTP-bound form of RAB18 protein to mediate ER-LD contact formation28,29. Knocking out the genes ZW10 and STX18 (encoding Syntaxin18) by multiplexed synthetic gRNA enhanced siRNA silencing efficacy (Figure 2e). This indicates that genes interacting with RAB18 to regulate ER-LD tethering have the same function in inhibiting siRNA silencing activity. Although it is still not clear how the ER-LD tethering impacts siRNA efficacy, this finding guided our attention to ER. We then asked, what is the connection between ER and siRNA silencing? The siRNA mediated degradation of target mRNA has been shown to take place in the cytoplasm40. However, the subcellular sites of RNA silencing remain under debate. Intriguingly ER as a site for protein translation mediated by ribosomes has been shown to be a central nucleation site of siRNA mediated RNA silencing41. In addition, an ER membrane resident protein CLIMP-63 has been proven to interact with and stabilize Dicer42. As indicated in these studies, ER might serve as a subcellular silencing site for siRNA. After being internalized into endosomes, the siRNA inside endosomes could travel to ER through retrograde transport. There are two different pathways of retrograde transport: the COPI-dependent and the COPI-independent pathways. Interestingly, RAB18 loss of function mutants had been shown to specifically enhance COPI-independent retrograde Golgi-ER transport35. Although the exact molecular mechanism of RAB18 regulation of siRNA activity has not yet been elucidated, the fact that knocking out genes functioning together with RAB18 in regulating LD and ER tethering, such as ZW10 and STX18, has similar impacts on siRNA silencing potency (Figure 2e) suggests that ER and retrograde transport related regulation might be worth more attention.
Despite the success of our HPRT1-6TG selection screen in identifying candidate regulators of siRNA potency, there were some limitations to this approach. First, the live/dead selection represents a very harsh cutoff for improving siRNA silencing potency. The idea behind HPRT-6TG selection is to use siRNA to knockdown HPRT1 gene. Resistance to 6TG is associated with the extent of knockdown of HPRT143. Our follow up study of RAB18 has shown that by knocking out RAB18, the siRNA IC50 dose could be reduced by 20 to 30-fold (Figure 3e), indicating that RAB18 is a strong regulator of siRNA activity. Nevertheless, when both Hep3BCas9 and RAB18 knockout cells were challenged with HPRT1-6TG selection, the cell survival rate was only changed from 43% in Hep3BCas9 cells to 58% in RAB18 knockout cells at the highest siRNA dosage tested (Figure 3d). This suggests that gene knockouts that improve survival by less than this amount may not be detected, even if they improve siRNA efficacy. Second, genes that regulate the sensitivity to 6TG could also be identified from the screen without having any function related to siRNA activity. These could include genes such as HPRT1 itself as well as genes involved in the mismatch repair pathway26. Third, siRNA induced gene silencing is a complex process, in which multiple genes may be required to regulate individual steps. Therefore, one gRNA per cell strategy will miss the redundant genes. Finally, the screen described here is focused toward identifying genes that confer resistance but not genes that sensitize the siRNA activity. Knocking out genes that are normally required for siRNA activity would lead to resistance to siRNA activity and cause the cells to be depleted upon 6TG selection; consequently their corresponding gRNAs would be depleted from NGS sequencing along with other gRNAs that cause cell death and would not be detected by our approach.
The described CRISPR screen was performed in Hep3B cells. Despite the great success of delivering siRNA to liver through conjugating to GalNAc, delivering siRNA into other tissues is still challenging. While it is still unclear whether the same siRNA trafficking route is utilized in other tissue or cell types, RAB18 is a universally expressed gene across multiple tissue types and is highly conserved across species. It would therefore be interesting to see if RAB18 knockout in other cell or tissue types can also enhance siRNA activity.
We report here the identification, using a pooled genome-wide CRISPR-Cas9 screen, of a single gene (RAB18) that, when knocked out, can enhance siRNA mediated gene silencing by at least 20-fold (IC50) in Hep3B cells. Given the current interest in utilizing siRNA as a therapeutic modality, identification of this key regulator may allow for the development of future pharmacological strategies to enhance siRNA efficacy.
MATERIALS AND METHODS
Cell line and culture condition
The Hep3B cells were purchased from ATCC (Manassas, VA). The culture condition for Hep3B cells is: EMEM (Eagle’s Minimum Essential Medium from ATCC, Cat# 30-2003) + 10% FBS (Fetal Bovine Serum). The culture condition for Hep3Bcas9 cells is: EMEM + 10% FBS + 10 μg/mL Blasticidin. And the culture condition for RAB18 knockout cells is: EMEM + 10% FBS + 10 μg/mL Blasticidin + 0.5 μg/mL Puromycin.
Generate Hep3BCas9 cells and validate their editing function
A TransEDIT CRISPR Cas9 nuclease expression lentivirus (pCLIP-Cas9-Nuclease-EFS-Blast) ordered from TransOMIC technologies (Huntsville, AL, Cat# NC0956087) was transduced at multiple MOI (0.5, 1, and 2) into Hep3B cells to generate Cas9 stable pools: Hep3BCas9_0.5, Hep3BCas9_1, and Hep3BCas9_2, respectively. All cells were selected and maintained with 10 μg/mL Blasticidin after transduction. No toxicities were observed in all Cas9 stable expression Hep3B pools. Two gRNA lentivirus vectors targeting SLC3A2 and ASGR1 ordered from Milipore Sigma (Supplementary Table 3) were transduced individually into both parental Hep3B cell line and each of the Cas9 stable Hep3B pool. The SLC3A2 and ASGR1 expression levels before and after gRNA lentivirus transduction were measured through antibody staining followed by FLOW cytometry analysis. Compared to the parental Hep3B cell line, both target genes were successfully knocked out in all Cas9 stable Hep3B pools (Supplementary Figure 1), demonstrated the Cas9 stable Hep3BCas9 cells were fully equipped with editing function. Since the editing effects were similar in all three Cas9 stable Hep3B pools, the one with lowest MOI (0.5, referred as Hep3BCas9 in the rest of this article) was chosen to perform the CRISPR screen to search for key regulators of GalNAc conjugated siRNA induced silencing to minimized potential Cas9 toxicity.
HPRT1-6TG selection test
To avoid both insufficient and over killing caused by 6TG, the feasibility of using HPRT1-6TG live/dead selection for CRISPR screen was tested in a small-scale pilot run using 100 μM 6TG (a dose close to IC70, Figure 1d) and 20 μM 6TG (a dose close to IC50, Supplementary Figure 2). The cells were first equally divided into four groups (0.6E+06 cells/group): 1) siRNA only, 2) siRNA with 6TG treatment, 3) 6TG only, and 4) negative control. To obtain sufficient but not excessive siRNA effect, a 750nM (about IC60) GalNAc-HPRT1 siRNA (8172) was added to group 1 and 2 on day 0 of experiment. On day 3 of experiment, the tissue culture media was removed from each group and then 100 μM 6TG (or 20 μM 6TG) was added to group 2 and 3, while non-selection full growth media was added to group 1 and 4. The cells were incubated for 3 days after 6TG treatment. Then cells were then split and the 6TG media was replaced with full growth media without 6TG and cultured for additional 3 days. The cell count readings (measured by ViCell) were recorded on day 3 post-6TG treatment and day 6 post-6TG treatment and plotted in Figure 1d and Supplementary Figure 2.
Large scale pooled genome wide CRISPR screen
An 80k genome wide CRISPR gRNA lentivirus library (CRISPR KOHGW 80K (lot# 17050301)) was purchased from Cellecta (Mountain View, CA) to generate a gene knockout pool. The CRISPR KOHGW 80K library is constructed in Cellecta’s pRSG16-U6-sg-UbiC-TagRFP-2A-Puro lentiviral vector that expresses gRNA under a wild-type U6 promoter and TagRFP and Puro resistance genes under a human ubiquitin C promoter. This library covers approximately 19,000 genes with 4 gRNA for each gene. The procedure of large scale CRISPR screen is illustrated in Figure 2a. Briefly, the gRNA lentivirus library was transduced into 9.2E+07 Hep3BCas9 cells. The actual library transduction efficiency as reflected by RFP positive cell population (61%) was checked through flow cytometry analysis on day 4 post-transduction. Based on calculation, the actual gRNA lentivirus library transduction MOI was about 0.9, and the actual coverage was 1035. The transduced cells were then selected with puromycin and blasticidin for 14 days. On day 14 post-selection, 87% of the cells were RFP positive (indicating 87% of the cells had an integrated gRNA) by flow cytometry. On day 14 post-selection, 1E+08 cells were collected and frozen as baseline sample. The rest of cells were equally divided into three groups (2.4E+08 cells/group): group 1 was treated with 150 nM GalNAc-HPRT1 siRNA as low dose group, group 2 was treated with 750 nM GalNAc-HPRT1 siRNA as high dose group, and group 3 was set as no siRNA control. On day 3 post-siRNA treatment, 2E+08 cells were collected and frozen from each group as before 6TG treatment samples, then the rest of the cells in each group were further divided into two subgroups: a) no 6TG group and b) 6TG group. The cell culture medium with siRNA was removed from each flask and fresh medium containing 100 μM 6TG was added into each flask of 6TG groups and fresh medium without 6TG was added to each flask in no 6TG groups. All cells were incubated for another 3 days then all cells were split into fresh medium without 6TG. After a final 3-day incubation, all cells were harvested. The genomic DNA samples were extracted from all samples collected by using Gentra Puregene Cell Kit (QIAGEN INC, Cat# 158767) following the user manual and sent to Cellecta for NGS barcode sequencing.
Secondary arrayed CRISPR screen
The multiplexed synthesized gRNA of each target gene for secondary arrayed CRISPR screen was designed and synthesized by Synthego Corporation (Palo Alto, CA). All gRNAs were transfected into Hep3BCas9 stable cells at 96-well plate format using Lipofectamine CRISPRMAX Cas9 Transfection Reagent (Invitrogen, Cat# CMAX00008). 1.5 μL of 0.3 uM multiplexed synthesized gRNA was first mixed with 8.5 μL Opti-MEM medium in each well. 0.2 μL of CRISPRMAX reagent diluted in 5 μL of Opti-MEM medium was then added to each well and incubated at room temperature for 5 to 10 minutes. After incubation, 85 μL (15,000 cells per well) of Hep3BCas9 stable cells were added to each well. The plate was allowed to sit for 20 minutes prior to placing it in 37°C tissue culture incubator, and transfection medium was replaced with EMEM containing 10% FBS and 1% AA (Antibiotic Antimycotic Solution) at ~6 hours after transfection. The cells were split at 1:6 ratio on day 3 post-incubation. The cells were incubated for a total of 6 days after CRISPRMAX transfection to allow protein knockdown. On day 6 post-transfection, HPRT1 siRNA conjugated to different delivery vehicles (GalNAc, Cholesterol, Anti-ASGR1 antibody) was added to each well at the desired concentrations (500 nM, 100 nM and 20 nM) followed by 4-day incubation period in 37°C tissue culture incubator. The total RNA of each sample was extracted by using KingFisher Flex System (Thermo Fisher Scientific) and MagMAX mirVana Total RNA Isolation Kit (Applied Biosystems, Cat# A27828) as per manufacturer instructions. The cDNA was then synthesized from total RNA sample using the Applied Biosystems High Capacity Reverse Transcription Kit (Cat# 4368813), and used to quantify siRNA activity by ddPCR (Droplet Digital Polymerase Chain Reaction).
Droplet Digital Polymerase Chain Reaction (ddPCR)
The ddPCR reactions were assembled using BioRad’s ddPCR Supermix for Probes (Cat# 1863010) as per the user manual. Droplets were then generated by QX200 Automated Droplet Generator (BioRad, Cat# 1864101). Thermal cycling reactions were then performed on C1000 Touch Thermal Cycler with 96-Deep Well Reaction Module (BioRad, Cat# 1851197) (BioRad, Cat# 1851197). The reactions were then read by QX200 Droplet Reader (BioRad, Cat# 1864003) and analyzed by using BioRad’s QuantaSoft software package. The predesigned primer/probe for ddPCR assays were obtained from Integrated DNA Technologies (Coralville, IA) with 3.6:1 primer to probe ratio. The assay ID of primer/probe used for quantifying HPRT1 gene is: Hs.PT.39a.22214821. The assay ID of primer/probe used for quantifying ASGR1 gene is: Hs.PT.56a.24725395. The assay ID of primer/probe used for quantifying PPIB gene is: Hs.PT.58.40006718. The assay ID of primer/probe used for quantifying housekeeping gene TBP is: Hs.PT.58.19489510. The ddPCR copy number readings (copies/20 μL) of both target gene (HPRT1, ASGR1 or PPIB) and housekeeping gene TBP were recorded for each well. The normalized target gene mRNA level was calculated by dividing the ddPCR reading of the target gene by the ddPCR reading of TBP taken from the same well. The resulting number of siRNA treated sample was further divided by the number of no siRNA treatment sample to obtain the percentage reading of the target gene mRNA level, which was plotted in Figure 1b, Figure 3e~i, and Figure 4.
siRAB18 and siNTC transfection
The siRNA molecules targeting RAB18 gene, siRAB18_1 (Ambion Silencer Select cat# 4390824 ID# s22703), siRAB18_2 (ID# s22704), and siRAB18_3 (ID# s22705) were purchased from Ambion (Ambion, Austin, TX). The non-targeting negative control siRNA (siNTC, cat# 4390843) were purchased from Invitrogen. The sequence details of siRNA targeting RAB18 were described in Supplementary Table 4. To test siRAB18 efficacy, several concentrations of each siRAB18 molecule (0.24nM to 50nM) or sterile water (negative control) was individually reverse transfected in duplicate into Hep3B cells using lipofectamine RNAiMAX (Invitrogen, cat#13778075). 24 hours post-transfection, cells were lysed and harvested for RNA using MagMAX mirVana Total RNA Isolation kit (Applied Biosystems, Cat# A27828) and reverse transcribed for ddPCR analysis using the Applied Biosystems High Capacity Reverse Transcription Kit (Cat# 4368813), according to manufacturer instructions. For analysis of the effect of RAB18 knockdown on GalNAc-HPRT1 siRNA efficacy, siNTC (50nM) or siRAB18-3 (50nM) was reverse transfected into Hep3B cells. 24 hours post-transfection, cells were trypsinized and washed twice in EMEM to remove residual transfection reagent, then plated into 96-well plates containing either PBS or multiple concentrations of GalNAc-HPRT1 siRNA. On day 4 post GalNAc-HPRT1 siRNA treatment, the cells were lysed for RNA isolation and cDNA synthesis as described above.
Anti-ASGR1 antibody blocking test
The Hep3BCas9 cells and RAB18 knockout cells were first pre-incubated with in-house generated anti-ASGR1 antibody (7E11), isotype control antibody, or no antibody for half an hour, followed by adding GalNAc-HPRT1 siRNA treatment at different doses. The final antibody concentration was 50 μg/mL and 2,000 cells were seeded each well. After incubating in 37°C tissue culture incubator for 4 days, the target gene (HPRT1) mRNA levels were measured using ddPCR analysis.
AUTHOR CONTRIBUTIONS
Michael Ollmann, Jiamiao Lu, Patrick Collins, Chi-Ming Li, and Songli Wang conceived and designed the study. Jiamiao Lu carried out the pooled genome wide CRISPR screen, ddPCR analysis, RAB18 knockout study and drafted the manuscript. Elissa Swearingen carried out initial siRNA efficacy test and 6TG sensitivity test in Hep3B cells. Miki Hardy conducted the secondary arrayed CRISPR screen. Patrick Collins performed the statistical analysis of NGS results. Bin Wu conjugated siRNA molecules tested in this study. Eric Yuan performed RAB18 knockdown study. Daniel Lu carried out Amplicon_Seq analysis to assess the editing efficacy of arrayed CRISPR platform. All authors contributed to manuscript revisions. All authors approved the final version of the manuscript and agree to be held at countable for the content therein.
CONFLICTS OF INTEREST
All authors have the following conflicts of interest to declare: Jiamiao Lu, Elissa Swearingen, Bin Wu, Eric Yuan, Daniel Lu, Chi-Ming Li, and Songli Wang are employees at Amgen Inc. Michael Ollmann, Patrick Collins, and Miki Hardy were employed by Amgen Inc. while working on the study. All authors owned Amgen shares when the study was carried out. However, these do not alter the authors’ adherence to all journal policies on sharing data and materials. None of the authors serves as a current Editorial Team member for this journal.
ACKNOWLEDGEMENTS
We thank Stephen Wong and Oliver Homann for providing input for NGS data analysis. We also thank Karen Siegler for providing 7E11 antibody.