The currently available RESCUE RNA base editing system demonstrates considerable potential for the treatment of genetic diseases at the transcriptional level. However, the relatively high incidence of off-target events hampers the precise RNA editing, thereby limiting its use in the clinical setting. This study describes a new RNA base editing method, named ecRESCUE, which utilizes inducible stabilization of the protein ecDHFR DD fused at the C-terminal of the original RESCUE system. In vitro experiments in 293T cells showed that the ecRESCUE editor markedly reduced the incidence of off-target single nucleotide polymorphisms without affecting the RNA A-to-I and C-to-U base editing efficiency. Altogether, these results demonstrate that the inducible ecRESCUE system represents an attractive approach to regulate and improve the outcome of the available RNA base editor with reduced off-targeting activity.Video AbstractThe online version contains supplementary material available at 10.1186/s12964-021-00759-2. Riemerella anatipestifer (dRanCas13b) and adenosine deaminase acting on RNA (ADAR) enzymes to catalyze the hydrolysis of adenosine (A) to inosine (I) in mammalian cells using RNA as template. The first RNA base editor, named RNA Editing for Programmable A to I Replacement (REPAIR), does not require strict sequence constraints and can be used to mediate all the A-to-I base editing of the full-length transcripts [Researchers have recently developed RNA editors that use deactivated Cas13 from nscripts . Hence, Escherichia coli dihydrofolate reductase destabilization domain) has been used to regulate interest protein expression in mammalian cells [The ecDHFR DD (an cells –5. The dhttps://www.addgene.org/). To construct ecDHFR-mCherry and mCherry-ecDHFR, we initially amplified the ecDHFR DD and mCherry expression plasmids, including the colinear homologous segments. Subsequently, the ecDHFR DD was fused to the N- or C-terminal of mCherry using the ClonExpressII One Step Cloning Kit . Similarly, the mCherry expression RESCUE system (mCherry-RESCUE) was obtained by performing fusion of mCherry with the C-terminal of ADAR2 obtained from the pC0078 RESCUE backbone. Thereafter, the ecRESCUE plasmid was constructed by performing fusion of ecDHFR DD with the C-terminal of mCherry obtained from the mCherry-RESCUE expression backbone. The sgRNA expression plasmids, which expressed the GFP fluorescence protein, were cloned into two BbsI restriction enzyme digestion sites   was obta30661  wa2 under humid conditions and supplemented with 10% fetal bovine serum .293T cells were cultured in the Dulbecco’s Modified Eagle Medium , maintained at 37 °C with 5% COd-lysine-coated 48-well plates and maintained at approximately 60–70% confluence. The cells were transfected with 500 ng of mCherry-ecDHFR or mCherry expression plasmids, which mCherry was used as a fluorescent tracer, using 1.5 µL EZ Trans Reagent diluted in 25 µL DMEM. The diluted EZ Trans Reagent was added into the diluted DNA solution; the mixture was mixed gently and incubated for 15 min at 20–25 °C to allow the formation of DNA-EZ Trans Reagent complexes. Thereafter, the DNA-EZ Trans Reagent complexes were directly added to each well containing cells and mixed gently by rocking the plate several times.293T cells were seeded in poly-The culture medium was carefully removed 6 h post-transfection and 0.3 mL of the complete growth medium was added to the wells. At 24 h post-transfection, different doses of TMP  were added to the medium. Fluorescence imaging was conducted among different time points.All fluorescence images were acquired using the Nikon Ti-E microscope , and the Image J software  was used to analyze the mCherry integrated density as follows:dRanCas13b, ADAR2, and mCherry expression. Primers used for conducting RT-PCR are listed in supplemental information . cDNA was synthesized using oligo d(T) primers and used as the RT-PCR template for the detection of 4 GFP-positive cells were collected by fluorescence activating cell sorting and total RNA was extracted using the TRIzol reagent (Thermo Fisher Scientific). cDNA was acquired by HiScript III 1st Strand cDNA Synthesis Kit (+gDNA wiper) . Thereafter, the editing segments of the endogenous mRNA targets were amplified by PCR and separated by performing agarose gel electrophoresis. The gel products with the correct size were purified and sequenced using the amplification primers. The RNA editing efficiency was assessed using the Edit R tool (https://moriaritylab.shinyapps.io/editr_v10/). [Before transfection, 293T cells were cultured in 24-well plates and maintained at approximately 60–70% confluence. The DNA transfection mixes included 330 ng sgRNA expression plasmids in each well, along with 660 ng of ecRESCUE or RESCUE expression plasmids. Overall, 0.99 μg DNA and 4.5 µL EZ Trans Reagent diluted in 40 µL DMEM were added to each well. The diluted EZ Trans Reagent was added into the diluted DNA solution; the mixture was mixed gently and incubated for 15 min at 20–25 °C. The mixture was directly added to each well containing cells and mixed gently by rocking the plate several times. The complexes were then removed 6 h post-transfection and 0.5 mL of the complete growth medium was added to the cells. At 48 h post-transfection, 2 × 10KRAS, NFKB1, and NRAS) were selected to detect the RNA off-target events across the transcriptome. sgRNA expression plasmids targeting KRAS, NFKB1, and NRAS were co-transfected with each of two RNA editors, RESCUE or ecRESCUE, into 293T cells seeded in 6-well plates. Two biological repeats were set up for each sample. More than 5 × 105 GFP-positive cells for each sample were sorted by fluorescence-activated cell sorting and approximately 5 μg total RNA of each sample was extracted and subjected to RNA sequencing.The RNA off-targets released by RESCUE system may affect the endogenous RNA expression, because the point mutation locates in different site, such as inducing the STOP codon formation, and the off-targets may affect the miRNA expression and circRNA-miRNA-mRNA network. The over-expression of ADAR2 in the RESCUE system is responsible for the numerous RNA off-targets. In this study, we reduced the effective time of ADAR2 by the use of the ecDHFR/TMP regulation system to reduce the RNA off-targets. Three sites  by Novogene . NEBNext® UltraTM RNA Library Prep Kit for Illumina®  was used to generate the sequencing libraries. TruSeq PE Cluster Kit v3-cBot-HS (Illumia) was used to perform the index-coded samples’ clusters. Then the library preparations were sequenced on an Illumina Novaseq platform.Two main software were used to analyze the off-target SNPs, including GATK2 (v3.7) for performing SNP calling and SnpEff for annotation the variable sites. The RNA off-target SNPs analysis method for the RESCUE system was performed in accordance with methods reported by Abudayyeh et al. [mCherry.ecDHFR DD can regulate the expression of the fused proteins with the effect of TMP . To assedRanCas13b, ADAR2, and fused mCherry in both the RESCUE and ecRESCUE RNA base editors was evaluated by performing reverse transcriptase-polymerase chain reaction (RT-PCR). As expected, the expression of dRanCas13b, ADAR2, and fused mCherry in the presence or absence of TMP was similar in the two RNA base editor systems , which reduced the RESCUE effective time and off-target events, was evaluated . [Furthermore, the endogenous RNA editing efficiency of ecRESCUE was evaluated in 293T cells. To detect A-to-I and C-to-U editing efficiency, 13 endogenous sites were selected. Specifically, we considered KRAS, NFKB1, and NRAS) were examined for mRNA A-to-I base editing by using the RESCUE and ecRESCUE RNA editors (Fig. KRAS targeting cells obtained by using RESCUE, and 136 and 148 off-targets were obtained by using ecRESCUE with 50 × coverage; 2726 and 2700 A-to-I off-targets in NFKB1 targeting cells were obtained by using RESCUE, and 139 and 127 off-targets were obtained by using ecRESCUE with 50 × coverage; and 1507 and 1568 A-to-I off-targets in NRAS targeting cells were obtained by using RESCUE, and 150 and 124 off-targets were obtained by using ecRESCUE with 50 × coverage (Fig. KRAS targeting cells obtained by using RESCUE, and 54 and 52 off-targets were obtained by using ecRESCUE with 50 × coverage; 1,974 and 1,965 C-to-U off-targets in NFKB1 targeting cells were obtained by using RESCUE, and 60 and 50 off-targets were obtained by using ecRESCUE with 50 × coverage; and 1,098 and 1,142 C-to-U off-targets in NFKB1 targeting cells were obtained by using RESCUE, and 84 and 80 off-targets were obtained by using ecRESCUE with 50 × coverage (Fig. We evaluated whether the new RNA base editor could decrease the off-target effects. To this end, three endogenous sites (ors Fig. a. In a fRNA base editing technologies result in temporary changes in the cell state or modify the function of proteins by mRNA single base inversions without inflicting damage to the genome, which holds considerable advantage in the treatment of certain genetic disorders. Currently, there are two main efficient RNA base editors, namely REPAIR  and RESCADAR2 gene and remarkably reduced the number of off-target SNPs without influencing the endogenous RNA editing efficiency. Hence, ecRESCUE represents a novel approach to reduce RNA off-target editing events with similar efficiency but higher specificity than that observed with the application of the RESCUE editing system. To a certain extent, it may represent a better approach to achieve RNA editing, or even DNA editing, by regulating heterologous protein expression.When considering applicability in the treatment of genetic diseases, it is important to assess whether the RNA editing tools are indeed safe. Despite the numerous RNA off-target effects produced by RNA base editors, the off-target events have been significantly decreased using the RESCUE system compared with the REPAIR RNA editor. Nonetheless, the results presented herein demonstrated that it was feasible to reduce the incidence of off-target SNPs with the utilization of the RESCUE editor by applying a TMP conditionally induced ecDHFR DD system. This study showed that ecDHFR DD-TMP combination could effectively regulate the expression of mCherry when fused with the C-terminal mCherry sequence. Moreover, this system also demonstrated the regulation of the dRanCas13b and ADAR2 levels with reduction in the off-target incidence compared with the RESCUE system. As expected, ecDHFR DD markedly inhibited the expression of mCherry fused with the C-terminal of the Despite the enhanced outcome, the ecRESCUE system is associated with the induction of off-target events. Previous study showed that without the effect of the TMP, ecDHFR DD exhibit a functional background, which may not regulate the fused protein degradation completely. Particularly, they investigated a double architecture for the DD-gene-DD-fused sequence and found that such a construction completely suppressed the protein function in an uninduced state . Hence, In summary, this study describes the new ecRESCUE RNA editor that can be utilized for efficient and specific on-target RNA base editing, thereby representing a safe tool for conducting RNA base editing and genetic function research.Additional file 1. Figure S1. TMP induced ecDHFR DD-regulated mCherry protein expression. Figure S2. Detection of expression of TMP-induced ecDHFR DD fused RESCUE-mCherry protein. Table S1. Guide sequences used for endogenous gene editing. Table S2. Primer sequences used for PCR fragments amplification. Table S3. Primer sequences used for dCas13b, ADAR2 and mCherry mRNA expression detection by RT-PCR. Table S4. mCherry reporter expression vectors. Table S5. RNA base editor expression vectors.


Supplemental Digital Content is available in the text. Lymph node metastasis is the single most important prognostic risk factor for recurrence in patients with colon cancer who have undergone curative surgery. The routine method for detecting disseminated tumor cells in lymph nodes is microscopic examination of one or a few hematoxylin and eosin-stained tissue sections by a trained pathologist. This method, however, is insensitive mainly because less than 1% of the lymph node volume is examined, leading to misclassification.This study aimed to investigate whether analysis of a selected group of biomarker mRNAs improves detection and characterization of lymph node metastases/micrometastases compared with the routine method.This study is a side-by-side comparison of biomarker mRNA analysis and histopathology of 185 lymph nodes from patients with colon cancer representing stages I to IV, and an investigation of the importance of lymph node tissue volume for tumor cell detection.This is a collaborative study between a high-volume central hospital and a preclinical university institution.Fifty-seven patients who had undergone tumor resection for colon cancer were included.The primary outcomes measured were mRNA copies per 18S rRNA copy of CEACAM5, KLK6, SLC35D3, POSTN, and MUC2 by multiplex assay and metastases/micrometastases detected by histopathology.p < 0.0001). Similarly, the number of positive nodes for the aggressiveness marker KLK6 increased from 9 of 107 to 24 of 107.The number of tumor cell-positive lymph nodes was 1.33-fold higher based on CEACAM5 mRNA levels compared with histopathological examination. Increasing the tissue volume analyzed for CEACAM5 levels from an 80-µm section to half a lymph node increased the number of positive nodes from 34 of 107 to 80 of 107 . De manera similar, el número de nodos positivos para el marcador de agresividad KLK6 aumentó de 9/107 a 24/107.El número de ganglios linfáticos con células tumorales positivas fue 1,33 veces mayor según los niveles de ARNm de CEACAM5 en comparación con el examen histopatológico. El aumento del volumen de tejido analizado para los niveles de CEACAM5 de una sección de 80 µm a la mitad de un ganglio linfático aumentó el número de ganglios positivos de 34/107 a 80/107 (LIMITACIONES:Solo un número limitado de ganglios linfáticos individuales / paciente estuvo disponible para el análisis.CONCLUSIONES:Video Resumen en http://links.lww.com/DCR/B650.El análisis de ARNm de CEACAM5, KLK6 y SLC35D3 mejora la detección de células tumorales en los ganglios linfáticos de pacientes con cáncer de colon tratados quirúrgicamente y, junto con POSTN y MUC2, permite además la caracterización de las células tumorales con respecto a la agresividad y el entorno celular tumoral. Consulte  This method has poor sensitivity, most likely because less than 1% of the LN volume is examined.7 In addition, the obvious risk of missing LN metastases (>2 mm in diameter), of importance for the decision on adjuvant chemotherapy, is accompanied by the even greater risk of missing micrometastases (clusters of 20 or more cells or 0.2–2.0 mm in diameter), pN1(mi), and isolated tumor cells (clusters with up to 20 tumor cells or <0.2 mm in diameter), pN0(i+).9 One way to increase the analyzed volume without excessively increasing the workload is to quantify biomarker mRNAs as proxies for tumor cells. We previously showed that CEACAM5 mRNA is expressed at high levels in tumor cells and not detected in immune cells, and that CEACAM5 mRNA levels are proportional to the number of disseminated tumor cells.11 Furthermore, high levels of CEACAM5 mRNA in LNs is an indicator of poor prognosis,12 and, when analyzed in combination with the 4 biomarker mRNAs KLK6, SLC35D3, POSTN, and MUC2, can identify patients at risk of recurrence with higher sensitivity than H&E.14 Except for MUC2, the latter biomarkers were identified by genome-wide hybridization bead array analysis by individually comparing the gene expression of 4 H&E(+) LNs and 3 primary tumors from 3 patients with stage III colon cancer (CC) against the gene expression of a panel of control tissues including LNs of 4 control patients and normal colon epithelial cells.14 Mucinous adenocarcinoma in CRC has better prognosis than adenocarcinoma, in general, and a high MUC2:CEACAM5 ratio in LNs is a sign of good prognosis.15 Combined in a formula, these biomarkers allow the allocation of patients with CRC to different risk categories with respect to recurrence, and biomarker risk category was shown to be an independent prognostic factor to TNM stage and tumor grade.14 Thus, in both metastasis-negative and metastasis-positive scenarios, this tumor biomarker combination may provide improved information about the risk of recurrence.The curative treatment for colorectal cancer (CRC) is surgery. However, recurrence is common and regional lymph node (LN) metastasis is the single most important prognostic risk factor.Here, we investigate whether analysis of CEACAM5 mRNA in combination with KLK6, SLC35D3, POSTN, and MUC2 mRNAs improves detection and characterization of LN metastases/micrometastases compared with the routine method by performing a side-by-side comparison between histopathology and the quantification of mRNA levels in adjacent LN sections. Furthermore, we addressed the question whether analyzing a larger part of the LN volume improves detection of aggressive tumor cells by comparing detection of CEACAM5, KLK6, and SLC35D3 mRNAs in the entire volume of half a LN with the small volume of 8 consecutive 10-µm sections from the other half of the LN.Figure The other half of the LNs were snap-frozen in liquid nitrogen and stored at –70°C until RNA extraction. For the comparison between half-LN and 80-µm section RNA extracts, 107 paired extracts were analyzed. These LNs were from 30 patients , with a median of 3 (IQR: 1–6) LNs per patient.Lymph nodes were given individual codes that were different for RNA extracted from sections, RNA extracted from fresh-frozen LN halves, and H&E-stained sections. Analyses were performed in a double-blinded manner.http://links.lww.com/DCR/B649). Total RNA was extracted from the fresh-frozen half-LNs by using the acid guanidine phenol chloroform method, as described.14 RNA was stored at –70°C in RNase-free water containing RNasin ribonuclease inhibitor .Total RNA was extracted from the formalin-fixed, paraffin-embedded 80-µm sections by using the RNeasy FFPE Kit  with minor modifications (Supplement http://links.lww.com/DCR/B649). Purity, estimated as OD260/OD280 ratio, was 1.95 (IQR: 1.92–1.99) for the 80-µm section extracts and 2.06 (IQR: 2.03–2.10) for the half-LN extracts.Concentrations of RNA in the extracts were determined by measuring optical density at 260 nm (OD260), OD280, and OD230 using a NanoDrop ND-2000 spectrophotometer V1.4.1 . Undiluted samples were used for RNA extracted from 80-µm sections and 1:10 dilutions for half-LN RNA extracts. The average yield of total RNA was 2.9 µg from the 80-µm section RNA extracts (n = 200) and 3574 µg from the half-LN extracts  values were 0.860 and 0.802 between total RNA and 18S rRNA determined by single-marker and multiplex qRT-PCR . Similarly, there was strong correlation between the concentrations of total RNA and 18S rRNA in the half-LN RNA extracts .Concentrations of 18S rRNA in RNA extracts were determined using a ColoNode Multiplex qRT-PCR kit  and an in-house constructed single-marker, real-time qRT-PCR assay with RNA copy standard described in Table S2 10 and 3.13 × 1010 copies as determined by single-marker and multiplex qRT-PCR (Table S1 http://links.lww.com/DCR/B649). The yield of 18S rRNA in half-LN extracts was approximately 3 orders of magnitude higher (average 1.09 × 1013 copies), which is compatible with the average 1230 -fold higher yield of total RNA. 18S rRNA qRT-PCR also gave significant signals in samples with very low levels of total RNA measured as OD260 . There was excellent correlation between 18S rRNA concentrations obtained by the multiplex and single-marker qRT-PCR  and the 2 assays gave very similar estimates of total yield of 18S rRNA in the samples (Table S1 http://links.lww.com/DCR/B649).The average yield of 18S rRNA in 80-µm section RNA extracts was 1.43 × 10http://links.lww.com/DCR/B649 describes the single-marker qRT-PCR assays for CEACAM5, KLK6, and MUC2 mRNAs. The assays for SLC35D3 and POSTN mRNAs were described previously.14 Results are expressed as concentration of mRNA copies/µL after correction for dilution or expressed as mRNA level normalized to the amount of 18S rRNA in the sample (mRNA copies per 18S rRNA copy). All qRT-PCR analyses were performed with samples containing >2.9 × 106 18S rRNA copies, with medians of 4.2 × 109 (IQR: 1.8 × 109 to 7.9 × 109) and 5.6 × 1010 (IQR: 3.2 × 1010 to 8.3 × 1010) 18S rRNA copies per reaction for 80-µm section and half-LN RNA extracts.Quantification of mRNAs for CEACAM5, KLK6, SLC35D3, POSTN, and MUC2 was done in total RNA using the ColoNode Multiplex qRT-PCR kit and in-house constructed single-marker qRT-PCR assays with RNA copy standards. ColoNode is composed of 2 triplex assays that are run simultaneously, 1 reaction measuring CEACAM5, KLK6, and SLC35D3 and 1 reaction measuring POSTN, MUC2, and 18S rRNA. Analyses by multiplex qRT-PCR were performed in duplicate, and analyses by single-marker qRT-PCR were performed in triplicate. RNA extracts of the 80-µm sections were analyzed undiluted and half-LN extracts at 1:10 dilution. Table S2 p < 0.0001) was seen between concentrations determined by multiplex and single-marker qRT-PCR for all 5 biomarker mRNAs. In 80-µm section extracts, the r values were 0.825, 0.942, 0.759, 0.934, and 0.734 for CEACAM5, KLK6, SLC35D3, POSTN, and MUC2 . POSTN was detected in all LNs by the single-marker assay and in all except 3 by the multiplex assay . There was good congruence between results obtained by multiplex and single-marker assays also in half-LN extracts . The multiplex assay was slightly less sensitive than the corresponding single-marker assays for CEACAM5, SLC35D3, and MUC2 mRNAs with detection limits in the multiplex assay of 100, 1000, and 10 mRNA copies/µL. All 5 biomarker mRNAs showed a strong correlation between the multiplex and single-marker assays in samples with concentrations above the detection limit of the multiplex assay . No sample was positive in the multiplex assay only.A highly significant correlation  for the presence of metastases >2.0 mm in diameter and micrometastases ≤2.0 mm in diameter grouped together with aggregated and isolated tumor cells. Fourteen LNs were excluded because the microscopy slides were empty, which excluded side-by-side comparison with RNA extracts, and 1 LN was excluded because the slide had primary tumor deposit.U test. Significance of differences in numbers of LNs with detected CEACAM5 mRNA by analysis of half-LN compared to 80-µm section RNA extracts was analyzed by using the Fisher exact test. A p value <0.05 was considered statistically significant. Descriptive values are given as median and IQR. GraphPad Prism 6  was used for statistical calculations.Correlation analyses were performed using 2-sided Spearman rank correlation test. Differences in biomarker mRNA concentrations and levels between 2 groups were analyzed by 2-tailed Mann-Whitney All procedures involving human participants were performed in accordance with the ethical standards of the institutional research committee and with the Helsinki Declaration. Lymph nodes were collected after patients’ written, informed consent. The study was approved by the Local Ethics Research Committee of the Medical Faculty, Umeå University, Umeå, Sweden (Registration number: 03-503). Access to archived samples was granted by Regional Biobank Center, Southern Healthcare Region, Lund, Sweden (Dnr 2015-A-68).Expression levels of CEACAM5, KLK6, SLC35D3, POSTN, and MUC2 mRNAs were determined in 80-µm section RNA extracts of 200 LNs from 57 patients with CC by multiplex qRT-PCR. CEACAM5 mRNA was detected in 28.5% of the LNs, as a single biomarker in 13% of the LNs and in combination with other biomarkers in the residual 15.5%. POSTN was the only biomarker detected in CEACAM5-negative LNs, and 7.5% of the LNs were single positive for POSTN with levels above the cutoff for prognostic value (Table http://links.lww.com/DCR/B649). Among the patients with only H&E(–) LNs, there were 2 patients in whom the LNs had CEACAM5 levels within the range of the H&E(+) LNs, 14 patients with significant but lower CEACAM5 levels, and 27 patients with no detectable CEACAM5 mRNA in their LNs .Detection of tumor cells in LNs by histopathological examination was compared to estimation of the number of tumor cells by CEACAM5 mRNA levels in 185 LNs from 56 patients with CC. To examine the same region of the LN, 9 consecutive sections were cut. The first was stained by H&E, and RNA was extracted from the remaining 8 sections (80-µm section). Twenty-one of the LNs had detectable metastases (H&E(+)). Eighteen of these had metastases >2 mm and 3 had micrometastases (<2 mm). All H&E(+) LNs had high CEACAM5 mRNA levels . SLC35D3 mRNA was detected in 11 of the H&E(+) LNs and not in any of the H&E(–) LNs. POSTN mRNA was detected in all but 2 LNs and with significantly higher levels in H&E(+) LNs (median 48.0 × 10-6 and 1.5 × 10–6 for H&E(+) and H&E(–) LNs; p < 0.0001). However, the H&E(–) LNs that had POSTN levels above the 75th quartile all overlapped with the H&E(+) LN POSTN levels, suggesting that as many as 25% of the LNs have signs of influence from disseminated tumor cells. MUC2 mRNA, a marker for good prognosis, was detected in 9 of the H&E(+) and 6 of the H&E(–) LNs.The other 4 biomarker mRNAs in the combination, ie, KLK6, SLC35D3, POSTN, and MUC2, were all detected, although with different expression patterns . The total mRNA copy yield in the half-LN extracts was on average 100-fold higher than the mRNA copy yield in the corresponding 80-µm section extract with a median half-LN extract/80-µm section extract ratio of 96.3 (IQR: 18.9–586).The number of LNs identified as tumor cell positive by detection of CEACAM5 mRNA was significantly increased when the extract was from half-LNs compared with from 80-µm sections  18S rRNA, measured by qRT-PCR in multiplex and in single-marker format, strongly correlates with the amount of total RNA as determined by OD260 in extracts from both formalin-fixed and fresh-frozen LN tissue, and 18S rRNA is a good “house-keeping gene” for normalization of mRNA expression levels in LNs; 2) determination of CEACAM5 mRNA levels in LN RNA extracts provides an excellent, sensitive assessment of disseminated tumor cells and is more sensitive than histopathological examination of H&E-stained LN tissue for the detection of disseminated tumor cells; 3) increasing the volume of LN tissue from which RNA is extracted strongly increases the sensitivity for detection of tumor cells, measured as CEACAM5 mRNA level, and for the detection of “aggressive” tumor cells expressing KLK6 and/or SLC35D3 mRNAs; and 4) micrometastases are commonly unevenly distributed in LNs.14 which in turn suggests that the LNs with low CEACAM5 levels indeed harbor tumor cells. It is possible that patients with CEACAM5 levels in this lower range, without expressing aggressiveness markers, will, if left untreated, develop distant metastases after a longer time span.The utility of determining CEACAM5 mRNA levels to detect disseminated tumor cells is underscored by the fact that all H&E(+) LNs (21/185) in the side-by-side analysis of LN sections by histopathology and qRT-PCR had high CEACAM5 mRNA levels, and several H&E(–) LNs (7/164) had CEACAM5 levels within the same range. Additional H&E(–) LNs (26/164) had lower, but still readily detected CEACAM5 levels. The clinical significance of LNs with CEACAM5 levels below those of H&E(+) LNs is yet to be determined. Approximately one-fourth of the H&E(–) LNs had POSTN mRNA levels in the range of those in H&E(+) LNs, suggesting that these LNs were affected by tumor cells,16 This, together with the previous finding that very low levels of CEACAM5 mRNA are detected in LNs of control patients,11 suggests that CEACAM5 mRNA concentrations <100 copies/µL are not relevant for LN classification.The detection limit for CEACAM5 in the multiplex assay was ≈100 CEACAM5 mRNA copies/µL, which is approximately the signal of 1 tumor cell (range: 30–400 CEACAM5 mRNA copies per cell).14 it is important to analyze RNA extracts from as large a volume as possible to identify patients at high risk of recurrence.Increasing the tissue volume from which RNA is extracted significantly increased the number of LNs with detectable CEACAM5 mRNA. Thus, more than 40% of the LNs had detectable CEACAM5 mRNA only in the larger volume of a half-LN extract. As expected for unevenly distributed micrometastases, there were occasional LNs (6.5%) in which CEACAM5 mRNA was only detected in the 80-µm section extract. H&E(+) LNs with metastases >2 mm all had significant CEACAM5 levels in extracts from both 80-µm sections and half-LNs. This suggests that metastases >2 mm occupy a large proportion of the LN, thereby making it less important where the sample for analysis is taken from, either for histopathology or CEACAM5 level determination. In contrast, micrometastases ≤2 mm and clusters of tumor cells are unevenly distributed in the LN and the small chance of detection in one or a few sections by histopathology leads to uncertain pN classification. The aggressiveness markers KLK6 and SLC35D3 mRNAs were only detected in CEACAM5-positive LNs. As for CEACAM5, the chance of detecting KLK6 and SLC35D3 increased with increasing LN volume from which RNA was extracted. Over 60% of the KLK6-positive LNs had signals only in the half-LN extract. The corresponding figure for SLC35D3 was over 40%. Because both mRNAs have high prognostic value,each LN examined by routine histopathology is also analyzed for biomarker mRNA expression levels. Because the LN volume analyzed is found to increase the detection rate, RNA is extracted from half-LNs in all LNs larger than 2 mm.This study shows that the multiplex assay provides accurate determinations of CEACAM5, KLK6, SLC35D3, POSTN, and MUC2 mRNA levels in RNA extracts from tissue volumes as small as a few sections of formalin-fixed tissue, and that analysis of CEACAM5 mRNA in such extracts is a more sensitive technique than histopathology for the detection of disseminated tumor cells. In the present clinical material, the number of tumor cell-positive LNs was 1.33-fold higher based on CEACAM5 mRNA levels than on histopathological examination. Furthermore, we showed that accuracy in detection of tumor cells is strongly improved when the analyzed tissue volume is increased, which is easily achieved with biomarker mRNA analysis but not feasible with histopathology. A possible explanation for why the CEACAM5, KLK6, SLC35D3, POSTN, and MUC2 combination is useful for discriminating between tumors with different propensity to form distant metastasis is shown in Figure The skillful technical assistance of technologist Assar Bäckman is gratefully acknowledged.


Circular RNA (circRNA), a class of RNA molecule with a loop structure, has recently attracted researchers due to its diverse biological functions and potential biomarkers of human diseases. Most of the current circRNA detection methods from RNA-sequencing (RNA-Seq) data utilize the mapping information of paired-end (PE) reads to eliminate false positives. However, much of the practical RNA-Seq data such as cross-linking immunoprecipitation sequencing (CLIP-Seq) data usually contain single-end (SE) reads. It is not clear how well these tools perform on SE RNA-Seq data.In this study, we present a systematic evaluation of six advanced RNA-based methods and two CLIP-Seq based methods for detecting circRNAs from SE RNA-Seq data. The performances of the methods are rigorously assessed based on precision, sensitivity, F1 score, and true discovery rate. We investigate the impacts of read length, false positive ratio, sequencing depth and PE mapping information on the performances of the methods using simulated SE RNA-Seq simulated datasets. The real datasets used in this study consist of four experimental RNA-Seq datasets with ≥100bp read length and 124 CLIP-Seq samples from 45 studies that contain mostly short-read (≤50bp) RNA-Seq data. The simulation study shows that the sensitivities of most of the methods can be improved by increasing either read length or sequencing depth, and that the levels of false positive rates significantly affect the precision of all methods. Furthermore, the PE mapping information can improve the method’s precision but can not always guarantee the increase of F1 score. Overall, no method is dominant for all SE RNA-Seq data. The RNA-based methods perform better for the long-read datasets but are worse for the short-read datasets. In contrast, the CLIP-Seq based methods outperform the RNA-Seq based methods for all the short-read samples. Combining the results of these methods can significantly improve precision in the CLIP-Seq data.The results provide a systematic evaluation of circRNA detection methods on SE RNA-Seq data that would facilitate researchers’ strategies in circRNA analysis.The online version contains supplementary material available at (10.1186/s12864-022-08329-7). Circular RNA (circRNA) is a type of single-stranded RNA molecule with a closed structure. Unlike the conventional linear RNA, which is a straight nucleotide chain in 5’-3’ direction commonly obtained in transcription, 5’ cap and 3’ poly-A tails do not exist in a circRNA molecule. Instead, a reversed linkage between two ends of the molecule forms its looping structure . This crThe rapid growth of recent studies on circRNA is attributed to the availability of advanced RNA-sequencing technologies that allow to sequence total RNAs including circRNAs . In totaAlthough the cost of PE RNA-Seq has significantly decreased recently, certain RNA-Seq methods allow only SE reads. For example, cross-linking immunoprecipitation sequencing (CLIP-seq) is used to analyze the interactions between RNAs and RNA-binding proteins (RBPs). CLIP-Seq methods generally start with the cross-linking process of RBPs to RNA-binding sites, followed by the sequencing of binding RNA fragments . Thus, iThe key challenge to the methods to detect circRNAs from RNA-seq data is identifying genuine back-splicing junction (BSJ) reads, which cover the linkage of the downstream-3’-splice-donor exon attached to the upstream-5’-splice-acceptor exon of a circRNA. The identification of a BSJ from RNA-Seq data does not always assure a true circRNA. Indeed, exon repetition, genomic tandem duplication, trans-splicing, and reverse-transcriptase template-switching  can geneA common approach to identify FP BSJs caused by tandem RNAs is utilizing the information of two reads of a pair from the PE RNA-Seq data, following a simple rule: if the paired mate of a supporting-BSJ read is mapped outside the putative region of the circRNA candidate, the reads likely originated from a tandem RNA. However, this rule is not applicable in the SE RNA-Seq situation wherein the mate pair is missing. Theoretically, circRNA detection methods can achieve higher precision in PE RNA-Seq rather than SE RNA-Seq. Read length is another factor that has a great impact on circRNA detection. Some circRNA detection tools such as CIRI2  are repoIn this study, we present a systematic evaluation of eight advanced circular RNA detection tools including CIRI2 , CIRCexpMultiple tools and software packages  have beeCIRI2  is one oFind_circ2  performsCIRCexplorer  is a cirDCC  implemenCircRNA_finder  is a STAUROBORUS  utilizesBoth Clirc  and circ%.Using another approach, CircScan maps input RNA data to both genome and transcriptome sequences using Bowtie . Next, tWe take into account circRNAs, tandem RNAs, and linear RNAs in the simulation for evaluating circRNA detection methods. The FP BSJs in the simulated datasets are controlled by the ratio between the numbers of tandem RNAs and circRNAs to investigate the robustness of the methods. We consider four ratio settings: 5-95, 30-70, 50-50, 80-20, with the proportion of FP BSJs ranging from low to high. For each FP ratio setting, we simulate both SE RNA-Seq data and PE RNA-Seq data using eight different read lengths including short reads , long reads , and very long reads (200 and 250bp) to investigate their impact on the performances of circRNA detection tools. The short reads of 25 and 42bp indicate the minimum and median read lengths across samples of the CLIP-seq dataset, respectively.https://github.com/datngu/Circall), a simulation tool allowing to simulate RNA-Seq data for both circular RNAs and tandem RNAs [The simulated data are created by Circall-simulator  datasets from three cell lines, HELA (N = 63), HEK293 (N = 42), and HEK293T (N = 19), for evaluation, Table Shttps://www.bioinformatics.babraham.ac.uk/projects/fastqc/). We exclude 16 CLIP-Seq samples which do not pass the quality scores per sequence qualification of FastQC from downstream analysis. The information of quality control for individual samples are provided in Table SThe fastq files of both the experimental RNA-Seq and CLIP-Seq datasets are subjected to quality control by FastQC , we follow the common approach  that useSince both the CLIP-Seq based methods CircScan and Clirc are developed for short-read CLIP-Seq data, not long-read RNA-Seq data, we do not use the non-depleted circRNAs for the assessment in the CLIP-Seq datasets. For a fair comparison, we build a set of “true positives” for each cell line from the circRNAs, which are discovered from the RNase R+ samples by at least two methods. Then, all the methods are evaluated based on these "true positive" sets.Figure CLIP-Seq based methods and Find_circ2 perform better than the rest of the methods with the short-read datasets. None of the RNA-Seq based methods reports circRNAs for the read length of 25bp, and among the methods, only Find_circ2 and UROBORUS discovers circRNAs from the data with 42bp read length. For the shortest read length (25bp), CircScan outperforms Clirc in sensitivity, precision, and F1 score across all FP ratio settings. However, Clirc performs better in terms of both sensitivity and F1 score than CircScan in other cases of the short reads (42bp and 50bp); see Fig. For the longer-read datasets, UROBORUS and Clirc achieve the worst and best precision respectively. The precision of other methods is not significantly different, making their F1 scores across read lengths highly dependent on their sensitivity. Thus, for those methods, increasing read length generally improves the F1 score. The performances of CIRI2, CircExplorer, and Find_circ2 are comparable in most FP ratio settings. The details of their performances with the simulated datasets are provided in Table SWe assess the robustness of circRNA detection methods with regard to the FP BSJs using four FP ratio settings covering different proportions of tandem RNAs from low to high. Figure L=89M reads, we use the same setting to generate three extra simulated datasets with the fold-changes of 0.25, 0.5, and 2 between their library sizes and L, resulting 22M, 45M, and 178M reads, respectively. We perform all methods using the same parameters for these SE simulated datasets. The results of all methods are summarized in Fig. To investigate the impact of sequencing depth, we simulate more data with different library sizes for all simulated SE datasets with the ratio setting 30-70. Particularly, for each dataset with a library size of We further evaluate the impact of the PE mapping information by comparing the results of the simulated SE data with the output of corresponding simulated PE datasets. CircScan and Clirc can run only on SE RNA-Seq data, so they are excluded from any PE data analysis. For each simulated PE dataset, we compute the precision difference of a method from the corresponding simulated SE dataset. Thus, the difference indicates that a method has an improvement in precision for the simulated PE data. The calculation is done to all datasets across read lengths and FP ratio settings, as depicted in Figures SSince Find_circ does not take into account the paired-end mapping information , its resFigure Most methods achieve substantially fewer circRNAs with the PE RNA-Seq datasets; see Table N = 678), while Clirc reports only N = 357 true positives. However, Clirc achieves the best precision (0.371), a bit higher than the precision of CircScan (0.327); see Table N = 88,325), making it the method with the lowest precision (0.004). Similarly, UROBORUS identifies a large number of circRNAs (N = 10113) with a small precision = 0.011. The remaining methods report only a few true positives (<30) across 108 samples; thus, they are not practically efficient for the CLIP-Seq data.From the results of the simulation study, the CLIP-Seq based methods are superior to RNA-Seq based methods with the short-read simulated datasets. In the CLIP-Seq datasets, 80% samples constitute short-read ≤50bp) data Table S, making 0bp data cScan 0.37; see Ta% of the CLIP-Seq samples; see Table Only Find_circ2 reports circRNAs from all 108 CLIP-Seq samples, followed by Clirc, UROBORUS and CircScan with 69, 56 and 53 samples, respectively; the other methods identify circRNAs in less than <20N = 39), HITS-CLIP (N = 9), and irCLIP (N = 7). RNA-Seq based methods do not perform well for irCLIP even though all samples of the protocol contain long-read RNA-Seq data (with 76bp read length).Table SThe Venn chart in Figure SIn this study, we evaluate the performances of five RNA-Seq based methods and two CLIP-Seq based methods in the detection of circRNAs from both simulated and experimental SE RNA-Seq data. In the simulation study, we take into account the impacts of read length and the ratio of FP BSJs caused by tandem RNAs, and sequencing depth on the performances of the methods. For their assessment using real data, four experimental RNA-Seq datasets with long reads (≥100bp) and 124 CLIP-Seq samples with mostly short reads (≤50bp) from 45 different studies are utilized. A comparison with the results of PE RNA-Seq data is also done for the simulated datasets and the experimental RNA-Seq datasets.The simulation study shows that increasing either read length or sequencing depth can improve the sensitivities of the methods for the SE RNA-Seq data. Only Clirc’s sensitivity reduces when the read length is greater than 75bp. The sensitivities are not greatly affected by the changes in the ratio of FP BSJs, indicating that most methods detect the BSJs efficiently. However, the ratio of FP BSJs significantly affects the precision of all methods with the simulated SE data. The PE mapping information indeed improves the precision of most RNA-Seq based methods for the simulated PE datasets. However, in the cases of the very long-read data (read length >150bp), CircExplorer, DDC, and CircRNA_finder show the substantial reduction of sensitivities and F1 scores with the PE data in the comparison with the SE data. Therefore, these methods perform better with the SE read rather than the PE read for the very long-read data. In contrast, UROBORUS performs better for the very-long PE read data, but it does not utilize well the PE mapping information for the shorter PE read data.The results in this study are also concordant with the findings from the previous benchmark studies , 22 whicThe CLIP-Seq based methods outperforms the RNA-seq based methods for both the short-read simulated datasets and the CLIP-Seq dataset. We note that the developers of RNA-Seq based methods might not have applied the methods for SE short-read RNA-Seq like the CLIP-Seq data, so their uses in this study are purely for comparative purposes. Neither Clirc nor CircScan is dominant for all datasets. Clirc is better than CircScan for the simulated data with read lengths of 42bp and 50bp but not 25bp. Regarding the CLIP-Seq protocols, CircScan outperforms Clirc in the PAR-LIP protocol, while Clirc performs better than CircScan in iCLIP and HITS-CLIP protocols. Find_circ2 outperforms the other RNA-Seq based methods with the short-read datasets. However, it reports a great number of false positives with the CLIP-seq datasets. In addition, integrating the results of CircScan, Clir, and Find_circ2 can significantly improve precision.One of the study’s limitations is that we evaluated the circRNA detection methods based only on human data. Thus, performances of these methods on the SE RNA-Seq data of other species, such as mouse and plants, were not taken into account. Such an investigation is out of the scope of the current study and can be considered in the future. The validation of circRNAs using the RNase R+ samples in this study is widely used in circRNA studies, but it is not a perfect method. The digestion of linear RNAs in the RNase R+ samples does not always perform well . TherefoAdditional file 1 The supplementary document contains all supplementary figures and tables.


Although dozens of terminal selectors have been described thus far for individual neuron types of the nematode C. elegans , the identification of their target genes has primarily relied on candidate approaches and availability of markers for neuronal terminal identity. Hence, unbiased methods are needed to identify the full spectrum of terminal selector target genes in individual neuron types. This study focuses on the phylogenetically conserved terminal selector UNC-3/Ebf (member of the Collier/Olf/Ebf family), which controls cholinergic motor neuron (MN) identity in the ventral nerve cord of the nematode C. elegans. To identify novel UNC-3 target genes, we took advantage of the genome-wide binding map of UNC-3 from our previous Chromatin Immunoprecipitation followed by Sequencing (ChIP-Seq) analysis . We generated transgenic reporter lines for ten putative terminal identity genes , whose expression patterns were largely unknown in C. elegans. Six of these reporter lines showed expression in ventral nerve cord MNs , whereas the remaining four  showed expression in head and tail neurons, as well as some non-neuronal cells. Importantly, the number of ventral nerve cord MNs showing expression of the nep-21, D2007.2, and dmsr-2 reporters was significantly reduced in unc-3 null mutant animals, thereby expanding the repertoire of known UNC-3 target genes in these cells. Altogether, this study demonstrates that transgenic reporter analysis guided by ChIP-Seq results is a relatively efficient approach for the identification and validation of transcription factor target genes.Terminal selector-type transcription factors are key regulators of neuronal identity and function . Mechanistically, terminal selectors are thought to act directly through binding at the  Through a candidate approach, more than 50 terminal identity genes have been identified genetically as downstream targets of UNC-3. These genes encode proteins essential for the proper functions of cholinergic MNs and include acetylcholine biosynthesis components, ion channels, neurotransmitter receptors, and neuropeptides . To test whether UNC-3 directly controls the expression of these genes, we recently performed Chromatin Immunoprecipitation followed by Sequencing (ChIP-Seq) analysis for UNC-3. Indeed, UNC-3 directly binds to the cis-regulatory region of these ~50 known target genes via a consensus DNA binding site, termed COE motif . This suggests that activating terminal identity genes through physical binding to their loci is a key strategy employed by UNC-3 to regulate cholinergic MN identity.The role of UNC-3 in establishing and maintaining the cell identity of cholinergic motor neurons (MNs) has been investigated in several studies . We focused on testing 10 putative terminal identity genes  that showed strong UNC-3 binding signal in their cis-regulatory region . To test the hypothesis that UNC-3 binding is required for gene expression, we first generated transgenic reporter lines for these 10 genes by amplifying the genomic region bound by UNC-3 and fusing it with a fluorescent reporter tagRFP. We found 6 reporter lines  with strong expression in ventral nerve cord MNs. Intriguingly, all these six genes have been independently validated by the CeNGEN consortium ; RNA-Sequencing analysis shows high expression levels of nep-21, D2007.2, dmsr-2, ncs-2, npr-29, and drn-1 in ventral cord MNs. To assess whether their expression in MNs is dependent on UNC-3, we crossed these reporter lines with unc-3(n3435) null mutants .Here, we sought to expand the list of UNC-3 targets by taking advantage of the genome-wide binding map of UNC-3 from our previous ChIP-Seq analysis , (b) dmsr-2 is predicted to encode a protein that enables G protein-coupled peptide receptor activity , and (c) D2007.2 is an uncharacterized gene encoding a protein with an Immunoglobulin-like domain . The number of cholinergic MNs showing expression of nep-21::RFP, dmsr-2::RFP and D2007.2::RFP is significantly decreased in unc-3(n3435) animals  when compared to wild-type animals   animals -C, sugge animals -F. This  do not show expression in ventral nerve cord MNs, despite UNC-3 binding on their cis-regulatory regions . Future studies are needed to determine whether pxd-1, cal-2, lgc-4, and ldb-1 are expressed in any of these unc-3-expressing neurons. Lastly, our observations suggest that transgenic reporter analysis guided by ChIP-Seq can be used for the generation of tissue and neuron-specific reporter lines.We also found that RFP reporter lines for the remaining four genes  regions . Since t regions . UNC-3 iC. elegans, whose expression patterns were largely unknown. These tagRFP reporter lines will be useful tools for researchers who intend to investigate further the functions of these genes in the C. elegans nervous system. Lastly, our reporter analysis of ChIP-Seq-defined enhancer regions identified three novel target genes  of the terminal selector UNC-3 in cholinergic MNs, expanding the repertoire of its target genes.Altogether, we generated transgenic reporter lines for ten putative terminal identity genes in Generation of transgenic animals carrying transcriptional fusion reporterscis-regulatory analyses and validation of newly identified UNC-3 target genes were made with PCR fusion . Genomic regions were amplified and fused to the coding sequence of tagrfp followed by the unc-54 3’ UTR. PCR fusion DNA fragments were injected into young adult pha-1(e2123) hermaphrodites at 50 ng/µl together with pha-1 (pBX plasmid) as co-injection marker (50 ng/µl).Reporter gene fusions for


Flaviviruses are vector-borne RNA viruses, many of which are clinically relevant human viral pathogens, such as dengue, Zika, Japanese encephalitis, West Nile and yellow fever viruses. Millions of people are infected with these viruses around the world each year. Vaccines are only available for some members of this large virus family, and there are no effective antiviral drugs to treat flavivirus infections. The unmet need for vaccines and therapies against these flaviviral infections drives research towards a better understanding of the epidemiology, biology and immunology of flaviviruses. In this review, we discuss the basic biology of the flavivirus replication process and focus on the molecular aspects of viral genome replication. Within the virus-induced intracellular membranous compartments, flaviviral RNA genome replication takes place, starting from viral poly protein expression and processing to the assembly of the virus RNA replication complex, followed by the delivery of the progeny viral RNA to the viral particle assembly sites. We attempt to update the latest understanding of the key molecular events during this process and highlight knowledge gaps for future studies. One large clade of known viruses is the positive-sense single-stranded RNA (+ssRNA) virus class, which belongs to group IV in the Baltimore classification . These vFlavivirus is a genus of +ssRNA viruses that includes many clinically serious human pathogens, including dengue virus, West Nile virus, Zika virus, Japanese encephalitis virus, yellow fever virus and tick-borne encephalitis. These viruses are typically transmitted to humans through arthropods (such as mosquitoes or ticks), and thus, are classified as arboviruses . When coFlavivirus virions enter a susceptible cell through the process of receptor-mediated endocytosis. Once the virion is internalised, it is released from the receptor, and its membrane fuses with the endosomal membrane, releasing the ribonucleocapsid into the cytoplasm . The nucThe key function of the replication organelle is to replicate the viral RNA. The replication organelle achieves this replication by producing a complementary negative strand RNA that acts as an intermediate for the generation of many new + strand viral genomes. Additionally, the RO acts to facilitate the packaging of this RNA into new virions. The multiple biosynthetic steps involved in this process require a close association of the various necessary factors. The compartmentalisation of the process in this way ensures the spatiotemporal synchrony of these steps, dramatically improving their efficiency and speed . FurtherOnce the +ssRNA genome of flaviviruses enters the cell, it is translated into a large single polyprotein by the host ribosomes on the endoplasmic reticulum (ER). This contains both the structural proteins that form the capsid  and the nonstructural proteins  . These nNS4a has been identified in some studies as the key driver of these membrane alterations, inserting itself into the ER membrane and undergoing oligomerisation to construct a scaffold onto which the replicase complex assembles. Membrane topological studies of NS4a reveal a luminal helix that lies parallel to and closely associates with the ER membrane, flanked by transmembrane helices. This topology may function as a wedge that, when polymerised, induces the cytosolic facing curvature seen in the RCs . MembranFlaviviruses depend upon many host factors to perform a diverse array of functions in RC formation. One key group in this coalition is host lipids, which are essential in many stages of the flaviviral life cycle. A crucial lipid in membrane biogenesis is fatty acid synthase, which is recruited and co-opted by flaviviruses to produce lipids that are integrated into the membrane to provide curvature and fluidity . FlaviviIn recent years, electron microscopic, tomographic and immuno-EM analysis studies have greatly enhanced our understanding of the flaviviral replication complex and the network of membranes in which it resides. Once the altered cellular membranes of infected cells were identified, many subsequent studies were conducted to unravel their mysteries. Early EM research allowed their discovery and categorisation into VPs and CMs. Successive studies have localised viral proteins within these networks, indicating that the VPs correspond to the site of viral RNA replication and that CMs contain the site of polyprotein processing.A study by Welsch et al. was key in developing our understanding . Here, tConvoluted membranes, on the other hand, consist of a network of much less structured membranes in smooth ER bundles associated with ROs and mitochondria A. The fuIn addition to the host factors required for RO assembly, flaviviruses hijack many other host factors that they rely on to reconfigure the infected cell. These factors are used to rewire cellular signalling pathways and traffic proteins and organelles to create a favourable environment for replication. Typically, these factors interact directly with a viral protein or the vRNA and their functions are often similar to those regularly used to support the cell, but are subverted for viral purposes. Recently, several studies have identified key host factors involved in flavivirus replication by combining affinity purification of viral proteins or RNA with mass spectrometry (MS) of the resulting isolates. This can be combined with small interfering RNA (siRNA) screening or CRISPR-Cas9 knockout production to identify the possible functions of these proteins in replication.One study using affinity purification MS in combination with RNAi screening to produce a virus–host protein–protein interaction map made several interesting discoveries. The authors found that the chromatin-associated complex PAF1C, which is key in transcriptional elongation, interacted with NS5 in all four DENV serotypes, as well as West Nile virus (WNV) and ZIKV. Through this interaction, NS5 inhibits the recruitment of this transcription complex to interferon-stimulated genes, thereby inhibiting their expression and diminishing the host immune response. Additionally, they found that SEC61, a protein involved in ER function and insertion of transmembrane proteins into the ER, interacted highly specifically with NS4a. They demonstrated that the pharmacological modulation of this translocon inhibited DENV and ZIKV replication in human and mosquito cells. Finally, they identified an interaction between NS4a of ZIKV and ANKLE2, a gene previously associated with microcephaly, and showed that inhibition of ANKLE2 by NS4b likely contributes to the microcephaly induced by ZIKV .RNA-centric approaches have also identified several flaviviral host factors involved in replication. Protein–viral RNA interactions are at the core of the molecular pathogenesis of flaviviruses and are essential for translation, replication and packaging. Mass spectrometry of proteins that bind to the viral RNA is therefore a powerful approach to identify host proteins involved in flaviviral replication. This approach has identified ER-localised ribosome-binding proteins (RBPs) as being implicated in replication. One such protein, RRBP1, which promotes ribosome-independent association of mRNAs with the ER, is likely co-opted to stimulate translation of the viral polyprotein. Furthermore, the RBP vigilin, a protein that binds to ribosomal RNA to promote mRNA translation, was also highly enriched in the identified interactome. While RRBPI activity is most pronounced in the early stages of infection, that of vigilin is more prominent in the later stages. Taken together, these results provide a basis for the host involvement in viral RNA translation and indicate their distinct roles . Using aCRISPR-Cas9 genetic screens have also recently come into the fore as a method to study flaviviral pathogenesis. These have enormous potential to both recognise and validate host factors involved in infection, as they can identify candidate genes without bias, and reliably knockout the gene to study their impact. Astonishingly, in studies where enriched host factors identified in CRISPR screes were knocked out, viral replication was shown to decrease 100–10,000-fold. These studies have identified many proteins that are hijacked in flaviviral infections. These include ER proteins such as ERAD, which is an ER protein that normally acts to target misfolded proteins for degradation . SimilarThese studies have given us great insights into the complex and interconnected network of interactions between the host and the virus and demonstrate the scale of the overhaul the virus performs on cellular systems. Flaviviruses and hosts have coevolved for millennia and have developed strategies over time to co-opt a multitude of cellular proteins to aid in viral replication, becoming reliant on them. Therefore, the concept of targeting host factors to arrest viral replication has garnered support and could provide a higher resistance barrier and even protect against infections from multiple different viruses. However, this is not necessarily the case. Although replication can be impeded by targeting a host factor the virus depends on, the virus may evolve to circumvent its reliance on these factors. This is the case for the host factor TMEM41B, which induces curvature in RO formation. Mutations in NS4a and NS4b allowed ZIKV and YFV to continue replicating in TMEM41B KO cells . High reThe viral genome is translated into a single polyprotein that will be cleaved by both host and viral proteases into three structural proteins: capsid (C), precursor membrane (prM) and envelope (E) and seven nonstructural (NS) proteins: NS1, NS2A, NS2B, NS3, NS4A, NS4B and NS5. The viral polyprotein is represented in In recent decades, biochemical and functional studies of the nonstructural proteins have been well characterised. The following sections will only focus on highlighting the roles of the nonstructural proteins in the formation and functioning of the replication complex.NS1 is a glycosylated protein with a molecular weight of approximately 48 kDa. It exists as a homodimer after post-translational modification in the ER lumen. Upon secretion into the extracellular space, it exists as hexameric lipoprotein particles. Within each NS1 monomer is contained twelve conserved cysteines that form six pairs of disulphide bonds and two N-linked glycosylation sites at residues N130 and N207, with a third glycosylation site at N175 for DENV and WNV . A detaiBoth the dengue and Kunjin virus NS1 proteins were also observed to co-localise with the dsRNA ,50. DeleNS2A is a transmembrane protein with a molecular weight of approximately 22 kDa. The N-terminus of the protein is cleaved by an unknown host protease and localised on the ER lumen, while the C-terminus is found in the cytoplasm and cleaved by viral NS2B-3 protease.Similar to NS1, Kunjin NS2A was shown to be co-localised with the double-stranded RNA in the VPs . MutagenNS2B is made up of 130 amino acid residues and has a molecular weight of approximately 14 kDa. It consists of a central hydrophilic region at the cytoplasmic side of the ER, that is flanked by two transmembrane helices at both the N and C termini of the proteins ,70,71. TIn addition to acting as the cofactor for NS3, NS2B also helps to anchor NS3 onto the ER membrane . NS2B isNS3 is a 68 kDa multifunctional protein. It consists of two main domains, an N-terminal protease and a C-terminal helicase. Together with the NS2B cofactor, the NS3 N-terminal protease forms a functional viral protease essential for the processing of the viral polyproteins. The protease cleaves the viral polyprotein at the capsid, NS2A/2B, NS2B/3, NS3/4A, NS4A/2K and NS4B/5. The viral protease adopts a chymotrypsin-like fold with two β-barrels and has a catalytic triad  located at the cleft between these two β-barrels ,77. The The NS3 C-terminal helicase belongs to the superfamily 2 (SF2) helicases. The helicase is essential for unwinding the duplex RNA into single-stranded RNA for NS5 polymerase activity. It also possesses NTPase and RTPase activity. The helicase is composed of three domains. Domains 1 and 2 have α/β RecA-like folds, which is a characteristic of superfamily 1 (SF1) and SF2 helicases ,81,82. TUpon RNA binding, subdomain 3 rotates about 10° away from the RNA binding tunnel, enlarging the groove to accommodate the ssRNA ,84. FurtStructural studies of the full-length NS3 protein have revealed that it adopts an elongated structure with a protease domain position near the NTP binding site of the helicase ,86,87. TMost studies are in consensus and have revealed that the helicase domain has no effects on the protease activity ,87,88. HA dimeric model for NS3 protein was also proposed . The dimNS4A is a membrane protein with three N-terminal amphipathic helices and four C-terminal membrane helices ,95. The Dengue and Kunjin NS4A have also been found to be co-localised with dsRNA, suggesting a role in viral RNA replication ,64. StudNS4B is the largest membrane protein found in the flavivirus genome. It consists of nine helices with helices 2, 3, 5, 7 and 9 forming transmembrane domains 1–5, respectively ,100,101.NS4B has also been suggested to play a role in viral RNA replication as it is found localised with the other NS proteins that are involved in viral replication . NS4B prN7MGpppA-RNA > N7MGpppA2′OM-RNA). The RNA capping mechanism is illustrated in NS5 protein carries two enzymatic domains, an N-terminal methyltransferase (MTase) domain and a C-terminal RNA-dependent RNA polymerase (RdRp). The MTase domain methylates the RNA sequentially to form the type I capped structure using S-adenosylmethionine (SAM) as the methyl donor . The MTaThe crystal structures of the MTase domain of various flaviviruses have been determined, which adopt a similar globular fold, that can be divided into three subdomains . The firThe crystal structure of the RdRp domain revealed a right-hand architecture consisting of a palm subdomain, a thumb subdomain and a fingers subdomain  113,114,116,117.Numerous X-ray crystallography studies have revealed a series of different global conformations and different modes of interaction between the MTase domain and the RdRp domain for full-length NS5 proteins from different flaviviruses  15,115,,118,119.10 helix structure comprising of four residues . G. G158]. Through numerous functional studies of the elements in the flavivirus genome, genome cyclisation has been proposed to be essential for negative-sense viral RNA replication . Genome In addition to genome cyclisation, defined secondary and tertiary RNA structures mediated by long-range RNA–RNA interactions can also be found within the coding regions of the viral genome ,167,168.Small subgenomic flaviviral RNAs (sfRNAs) are formed from the incomplete digestion of the viral genomic RNA at the 3′ UTR by host 5′-3′ exoribonuclease Xrn-1 ,155,156.During a flaviviral infection, the virus stages a complete overhaul of the cellular milieu, vastly altering and co-opting innumerous host cell functions. The formation of replication organelles is just one of these alterations, albeit a key alternation, and the wider restructuring of the cell is intrinsically linked to the RC function. To effectively target flaviviral infections, we must obtain a comprehensive understanding of virus’s methods of hijacking cellular processes to create a favourable environment for replication. The other drastic changes to the cell brought about by the virus include the establishment of the network of convoluted membranes, the functional and morphological perturbation of multiple cellular organelles and the reorganisation of the cytoskeleton. The full functional significance of these changes and the mechanisms of their formation remain somewhat elusive, although links to the nonstructural proteins have emerged. As mentioned above, the convoluted membranes are enriched with NS3 and NS2b, and NS4b is thought to elicit structural changes in the mitochondria. Furthermore, NS4a is known to interact with the intermediate filament vimentin, likely as part of the cytoskeletal manipulations . It is pAs described earlier, the membrane association of the viral replication complex is mediated by NS2A, NS2B, NS4A and NS4B. For the cytoplasmic proteins, NS3 will be anchored to the ER membrane via NS2B while NS5 will be localised to the ER membrane through its interaction with NS3. However, to date, most functional characterisations of viral enzymatic proteins have been carried out in the absence of a membranous system. Through the development of a model membrane system, it can help to limit diffusion and arrange the NS protein on the membrane to trigger the assembly of the replication complex. In doing so, this type of model will be able to provide a more accurate understanding of the intrinsic membrane activity of the viral NS proteins.Another significant gap in our understanding is the overall structure of the replication complex. Although the structures of key proteins such as NS1, NS3 and NS5 are known, the structures of the other four nonstructural proteins remain elusive, as well as the way they assemble. Additionally, the number of copies of each nonstructural protein within one RC is not completely certain, with some conflicting data on the matter. Furthermore, little is known about the temporal changes to the RC throughout the RNA synthesis process and the life cycle of flaviviruses. These unknowns hamper our understanding of the mechanisms involved in the biogenesis of the complexes, as well as their functioning. Since these processes are pivotal to the replication cycle, they provide key targets in the treatment of flaviviral infections. There is a wealth of literature on the host factors that are subverted by flaviviruses; however, some key questions remain unanswered here. We have yet to fully understand which host factors are incorporated into the complex, and how they contribute to its overall structure. Furthermore, their precise impacts on the processes occurring in the complex and the wider cell are in many cases poorly understood. To effectively design methods of arresting viral replication we must fully comprehend the cumulative effects of these factors. With advancements in electron microscopy, it is now possible to capture multimeric protein complexes that were previously challenging with X-ray crystallography. Using high-resolution cryo-electron tomography, Unchwaniwala et al. revealed the membrane structure and also captured a multimeric Protein A assembly replication complex of the flock house virus . NumerouWhen do the proteins know to transition from negative-sense RNA synthesis, to positive-sense RNA synthesis, to RNA capping? What are the molecular switches? How does NS5 recognise the viral double-stranded replication form and distinguish the negative from the positive strand in the RNA replication form/intermediate? Currently, there is a need for a robust in vitro replication system to segregate various molecular events, particularly the positive-sense RNA synthesis and RNA capping. With a robust system, it will also allow scientists to characterise the molecular architectures of the replication complex during the different stages of replication, and the dynamic changes from one process to another.


IKKβ) by changing the genetic code from AGU to GGU. The results showed that the eRESCUE editor mediates more efficient A-to-I and C-to-U RNA editing than the RESCUE RNA editor, as was previously reported. The 177Ser/Gly conversion of IKKβ, accomplished by converting the genetic code from AGU to GGU, resulted in a decrease in the phosphorylation of IKKβ and downregulation of downstream IKKβ-related genes. In summary, we developed a more efficient RNA base editor, eRESCUE, which may provide a useful tool for biomedical research and genetic disease treatment.RNA base editing is potential for cellular function research and genetic diseases treating. There are two main RNA base editors, REPAIR and RESCUE, for in vitro use. REPAIR was developed by fusing inactivated Cas13 (dCas13) with the adenine deaminase domain of ADAR2, which efficiently performs adenosine-to-inosine (A-to-I) RNA editing. RESCUE, which performs both cytidine-to-uridine (C-to-U) and A-to-I RNA editing, was developed by fusing inactivated Cas13 (dCas13) with the evolved ADAR2. However, the relatively low editing efficiency of the RESCUE system limits its broad application. Here, we constructed an enhanced RESCUE (eRESCUE) system; this dPspCas13b-RESCUE-NES system was generated by fusing inactivated PspCas13b with the evolved ADAR2. We determined the endogenous mRNA A-to-I and C-to-U editing efficiency mediated by the dPspCas13b-RESCUE-NES system in HEK-293T cells. This new RNA base editor was then used to induce 177Ser/Gly conversion of inhibitor kappa B kinase β (Video AbstractThe online version contains supplementary material available at 10.1186/s12964-021-00716-z. Prevotella sp. (dPspCas13b) fused with the adenosine deaminase acting on RNA type 2 (ADAR2) [Riemerella anatipestifer (dRanCas13b) [Previous studies have reported several tools that mediate adenosine-to-inosine (A-to-I) RNA editing in vivo –3. Curre (ADAR2) . To expanCas13b) . HoweverIn this study, we tried to improve the RNA editing efficiency of the RESCUE system by using a Cas13 ortholog, dPspCas13b, with a nuclear export sequence (NES) to guide RNA base editors to edit mRNA in the cytoplasm. We successfully developed a PspCas13b-based enhanced RESCUE system, eRESCUE, with efficient RNA base editing abilities.https://www.addgene.org/). RNA editing sites and the sgRNA sequences could be found in Additional file Several plasmids, including pC0078 RESCUE #130661) , contain30661 , c2 under standard humidity conditions.293T cells were cultured in Dulbecco’s modified Eagle’s medium (Gibco) with 10% foetal bovine serum (FBS) (v/v) (Gemini), and maintained at 37 °C with 5% COBefore transfection, 293T cells were seeded in 24-well plates which have been coated by D-lysine, and maintained at approximately 60–70% confluence. Then cells were transfected using EZ Trans Reagent (Shanghai Life iLab) according to the manufacturer’s protocols. For transfection, dPspCas13b-RESCUE or the dRanCas13b-RESCUE- (800 ng) and gRNA-expressing plasmids (400 ng) were mixed and added to each well. DNA (1.2 µg) and 3.6 µL EZ Trans Reagent were diluted in 50 µL DMEM. The diluted EZ Trans Reagent was then added into the diluted DNA solution, mixed gently, and incubated for 15 min at room temperature (20–25 °C) to form DNA-EZ Trans Reagent complexes. After 15 min of incubation, the DNA-EZ Trans Reagent complexes were directly added to each well and mixed gently by rocking the plate back and forth. At 6 h post-transfection, the complexes were removed, and 0.5 mL complete growth medium was added to the cells. Post-transfection 48 h, GFP-positive cells were collected by fluorescence-activated cell sorting (FACS).4) with positive GFP signals were collected and used to extract total RNA for editing efficiency analysis. More than 5 × 105 GFP-positive cells were harvested and used to extract total RNA for off-target analysis.Cells were collected and subjected to FACS at 48 h after transfection. The GFP signal was detected via FACS. Cells (2 × 10https://moriaritylab.shinyapps.io/editr_v10/) was used to calculate editing efficiency by analysing the Sanger sequencing results of the PCR-amplified fragments.GFP-positive cells were sorted by FACS. Total RNA of the collected cells was immediately extracted by using the TRIzol reagent (Invitrogen) according to the manufacturer’s instructions. cDNA was generated by using the HiScript II Q RT SuperMix (Vazyme). Phanta® Max Super-Fidelity DNA Polymerase (Vazyme) was used for PCR amplifying. The PCR amplification primers are listed in Additional file Briefly, cells were fixed in 4% (w/v) paraformaldehyde  for 10 min at room temperature (20–25℃), permeabilized, and blocked for 30 min with 1% (w/v) bovine serum albumin , and then permeabilized with 0.1% (v/v) Triton X-100. Fixed cells were washed and incubated with a primary antibody (ab16502) at 4 °C overnight. The cells were then incubated with a secondary antibody, goat anti-rabbit IgG H&L (HRP) (abcam: # ab97051) for 2 h, and the nuclei were stained with DAPI. TRITC-phalloidin staining was used to visualise the cytoskeleton. Imaging was performed by confocal microscopy (Nikon A1R).Total RNA from GFP-positive cells was extracted using TRIzol reagent. cDNA was synthesised using oligo d (T) primers and used as the templates for real-time PCR. SYBR green-based real-time PCR was performed to evaluate the mRNA expression level. PCR primers were showed in Additional file To examine RNA off-target effects across the transcriptome, each selected sample was comprised of two biological repeats, and total RNA was extracted using TRIzol. A total amount of 1 µg RNA per sample was used as input material for the RNA sample preparations. Sequencing libraries were generated using NEBNext® UltraTM RNA Library Prep Kit for Illumina®  following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. All the cDNA samples were sequenced by Novogene Co., Ltd.GATK2 (v3.7) software was used to perform SNP calling. Raw vcf files were filtered with GATK standard filter method and other parameters . The statistical difference between the two groups was evaluated using one-way ANOVA. All data are expressed as arithmetic mean ± SEM. The level of significance was set at KRAS compared to other optimised Cas13b systems or hairpin-mediated RNA (shRNA) [KRAS site 1 and 2, CTNNB1, and NF2, which showed relatively high A-to-I or C-to-U editing efficiency in the dRanCas13b-RESCUE system [KRAS site 1 and site 2, CTNNB1, and NF2). At 48 h post-transfection, we collected 2 × 104 GFP-positive cells by FACS. We extracted the total RNA of the 2 × 104 GFP-positive cells and obtained cDNA by reverse transcription. The targeted sequences were amplified by PCR and subjected to Sanger sequencing. We used the general analytic tool, EditR (https://moriaritylab.shinyapps.io/editr_v10/) [KRAS site 1 mediated by dPspCas13b-RESCUE-NES was up to 78%  is synthesised from a DNA template in the cell nucleus by transcription, and the pre-mRNA is completely processed to mature messenger RNA (mRNA) in the cytoplasm . The dRa (shRNA) , we geneE system . We comptr_v10/)  to analyKRAS site 1 and 2 . The phosphorylation of various IκB and NF-κB proteins are catalysed by IKK complex integrates signals which are from NF-κB activating stimuli [IKKβ determine the activation of IKK [IKKβ. We designed three dPspCas13b-RESCUE-NES guides for IKKβ 177Ser (AGU)/Gly (GGU) substitution by mediating IKKβ mRNA A-to-I editing. We constructed three sgRNA expression vectors in which the target base A is positioned at location 24, 25, and 26 for IKKβ 177Ser (AGU)/Gly (GGU) substitution. We then detected the A-to-I efficiency of the three sgRNAs that were mediated by the dPspCas13b-RESCUE-NES system in 293T cells. The results showed that the A-to-I editing efficiency of three replicates were 23%, 26%, and 19% for position 24 of sgRNA1; 36%, 32%, and 37% for position 25 of sgRNA2; and 29%, 30%, 34%, for position 26 of sgRNA3, respectively (Fig. IKKβ mRNA A-to-I editing.Given the success of the dPspCas13b-RESCUE-NES RNA base editor in vitro, it was next examined in biological studies. Diverse cellular stresses, such as inflammatory cytokines, bacterial or viral products and DNA damage could activate the  pathway . Genes i stimuli . Phosphon of IKK . Taking p65 subunit, which is a major component of NF-κB complexes and is responsible for trans-activation [p65 proteins shifted into the cytoplasm in the sgRNA2 and dPspCas13b-RESCUE-NES co-transfection groups compared to that with the control group or the non-targeting sgRNA and dPspCas13b-RESCUE-NES co-transfection groups (Fig. p53 and GADD45, which function in cell cycle regulation, c-Myc and Bcl2 for cell proliferation, and TRAF1 and TRAF2 for apoptosis were significantly decreased (Fig. IKKβ 177Ser by changing the genetic code from AGU to GGU. The dephosphorylation of IKKβ 177Ser further downregulated IKKβ-related genes. These results indicate that the dPspCas13b-RESCUE-NES RNA editor is a versatile tool for regulation of protein phosphorylation and functional amino acid mutations.The sgRNA2 expression construct and dPspCas13b-RESCUE-NES editor were co-transfected into 293T cells. We then performed immunostaining of the tivation . The resKRAS site 1, CTNNB1, and RAF1. The RNA base editing efficiency of KRAS site 1, CTNNB1, and RAF1, which are mediated by dPspCas13b-RESCUE-NES and dRanCas13b-RESCUE-NES systems were detected. The results showed that the A-to-I on-target efficiency of the dPspCas13b-RESCUE-NES system were 68% and 72% for KRAS, 53% and 51% for CTNNB1, and 30% and 31% for RAF1, respectively; additionally, the dRanCas13b-RESCUE-NES system results were 35% and 40% for KRAS, 44% and 46% for CTNNB1, and 28% and 29% for RAF1, respectively (Fig. KRAS, 45% and 53% for CTNNB1, 29% and 31% for RAF1, respectively, whereas the dRanCas13b-RESCUE-NES system were 20% and 21% for KRAS, 20% and 22% for CTNNB1, and 19% and 12% for RAF1, respectively (Fig. 6 GFP+ positive cells were collected by FACS, and total RNA was extracted from these cells for RNA-seq analysis. We evaluated transcriptome-wide off-targets by RNA-seq over all mRNAs with 50× coverage. Data from the dPspCas13b-RESCUE and target sgRNA transfection groups, as well as the dRanCas13b-RESCUE-NES and target sgRNA transfection groups were filtered by the data of the EGFP expression plasmid transfection groups. We found that there were substantial A-to-I off-target events (Fig. Given that RNA editors usually induce off-target effects, we checked the possible off-targets resulting from the dPspCas13b-RESCUE-NES and dRanCas13b-RESCUE-NES systems at three endogenous sites, including RESCUE is a potential RNA base editing technology which can mediate both A-to-I and C-to-U conversion in RNA . HoweverIKKβ, thereby mediating the conversion of site 177 from Ser to Gly, allowing us to explore the impact of IKKβ dephosphorylation. As expected, our results showed that more p65 proteins were arrested in the cytoplasm (Fig. IKKβ-regulated genes related to cell proliferation, apoptosis, and cell cycle decreased (Fig. To demonstrate the versatility of RNA editing, we applied the more efficient RNA editor, dPspCas13b-RESCUE-NES, to alter the genetic code from AGU to GGU for Here, we found higher levels of A-to-I and C-to-U RNA off-target SNPs in this study than was previously reported , especiaIn summary, we developed an efficient RNA base editor, dPspCas13b-RESCUE-NES, providing a potentially useful tool for biomedical research and genetic disease. Despite its high efficiency, however, higher numbers of off-target events were detected with the dPspCas13b-RESCUE-NES system relative to the control, given that further optimisation is still needed.Additional file 1.Table S1. Guide sequences used for endogenous gene editing. Table S2. Primers used in this study. Table S3. Q-PCR primers used in this study.Table S3. Q-PCR primers used in this study. Table S4. RNA base editor expression vectors.


Cellular RNA transcripts in endothelial cells, especially the SINE RNAs, need extensive editing by the A-to-I RNA editing enzyme ADAR1, which is essential for neonatal survival by regulating the MDA-5–mediated RNA-sensing signaling pathway. The RNA-sensing signaling pathway has been well studied as an essential antiviral mechanism of innate immunity. However, its role in non-infected cells is yet to be thoroughly characterized. Here, we demonstrated that the RNA sensing signaling pathway also reacts to the endogenous cellular RNAs in endothelial cells (ECs), and this reaction is regulated by the RNA-editing enzyme ADAR1. Cellular RNA sequencing analysis showed that EC RNAs endure extensive RNA editing, especially in the RNA transcripts of short interspersed nuclear elements. The EC-specific deletion of ADAR1 dramatically reduced the editing level on short interspersed nuclear element RNAs, resulting in newborn death in mice with damage evident in multiple organs. Genome-wide gene expression analysis revealed a prominent innate immune activation with a dramatically elevated expression of interferon-stimulated genes. However, blocking the RNA sensing signaling pathway by deletion of the cellular RNA receptor MDA-5 prevented interferon-stimulated gene expression and rescued the newborn mice from death. This evidence demonstrated that the RNA-editing/RNA-sensing signaling pathway dramatically modulates EC function, representing a novel molecular mechanism for the regulation of EC functions. The cytosolic RNA-sensing signaling pathway is an important antiviral innate immune mechanism that responds to invading viral RNAs, leading to type I IFN and interferon stimulated gene (ISG) expressions , 2. DereADAR1 has been shown to edit the transcripts for smooth muscle myosin heavy chain and α-actin to suppress their expression in vascular smooth muscle cells in phenotypic modulation and vascular remodeling in a mouse model . ADAR1’sVE-Cadherin-Cre (Chd5-Cre)   and floxse lines . From F1approach . The gen5-12.0 d , 24, 25,hin 3 wk . Obvioushin 3 wk . Genotyptermates . Those AADAR1 Lox/Lox; Cdh5-Cre+ pups survived beyond 3 wk while others perished, we assessed ADAR1 deletion efficiency among ADAR1 Lox/Lox; Cdh5-Cre+ pups. Although the activity of Chd5-Cre was reported to start as early as E7.5 d during embryogenesis and progress to nearly complete penetration by E14.5 d  mouse model described previously (ADAR1 gene in vitro by adding tamoxifen (TM) to the culture medium  were analyzed in parallel . All the editing sites fell into three groups: CON > TM, not significantly different, and CON < TM . We considered only the sites with different editing rates as reliable editing sites in our analysis. There were 6,915 and 5,171 sites with higher editing levels in control cells (CON > TM) detected in the first and second mouse, respectively , and amoNext, we focused our analysis on RNA transcripts annotated to RRs. In each mouse, the total editing sites in SINE, LINE, and LTR were counted in both CON and TM-treated ECs. Notably, the numbers of editing sites in these three major subgroups of RRs were well conserved between mouse 1 and mouse 2, and most of the editing sites fell in SINE . In addiWe further explored the editing levels of these RRs in CON and TM ECs, considering both the editing efficiency of each editing site and the total number of editing sites in each RR. If an RR contains more editing sites and the average editing rate was higher in control cells than in the corresponding TM-treated cells, we defined it as a high editing RR (CON > TM). On the contrary, a RR with less editing sites and a lower average editing rate was defined as a low editing RR (CON < TM). Using these definitions, we identified 2,188 and 1,417 high editing RRs in each mouse; among them, 467 RRs were shared by the ECs from the two mice . SimilarEC-KO mice, causing severe organ injuries.Among the high editing B1 RNA transcripts, multiple editing sites were often found in each B1 element (Table S3). These editing sites found by RNA-seq analysis were confirmed with three selected B1 SINE elements through Sanger sequencing experiments, including that in the intron of the Sppl2a gene (chr2: 126892815-126892950), 3′ UTR of the Nipa1 gene (chr7: 55977578-55977700), and 3′ UTR of the Slfn5 gene (chr11: 82962556-82962680). RNAs from wild type ECs were subjected to Sanger sequencing analysis after RT-PCR amplifications. Significant editing at multiple sites in these three B1 elements was successfully validated . This reMultiple editing sites in high editing short interspersed nuclear element elements. Excel file listing the high editing sites.Table S3 EC-KO mice. It has been shown that the cellular RNA receptor MDA-5 mediates innate immune activation in ADAR1-deficient cells   mice survived to adulthood without obvious abnormalities  . We founmalities . ADAR1 dmalities . Notably-deficient ECs, we examined whether RNA editing was altered in both MDA-5– and ADAR1-deficient ECs. Again, we used ADAR1-inducible KO ECs and crossed the ADAR1 i-KO mouse with the MDA-5−/− mouse (ADAR1 i-KO/MDA-5−/− double KO) to generate inducible double KO ECs. RNAs isolated from TM-induced ADAR1 i-KO, ADAR1 i-KO/MDA-5−/− double KO, and wild-type ECs were subjected to Sanger sequencing after RT-PCR amplification. As expected, editing on the B1 RNAs was decreased in TM-induced i-KO cells compared with the controls, and the editing level in the double i-KO ECs (i-d-KO) was the same as that in cells from the induced i-KO cells, as shown by the B1 RNA in the 3′ UTR of Slfn5 mRNA . Therefore, the rescue of ADAR1 EC-KO mice by MDA-5 deletion was due to EC-specific ADAR1 deletion. In ADAR1 EC-KO mice, ADAR1 deletion occurred in half or less of the ECs. It was significant enough to cause severe organ injuries; however, blocking the MDA-5 pathway prevented the ISG expression and restored the critical functions of the EC for supporting the mouse survival. Thus, the homeostasis of innate immunity regulated by ADAR1 is very critical for maintaining EC functions.MDA-5 KO completely rescued the ADAR1EC-KO mice from postnatal lethality,  KO mice . Instead KO mice . The KO  protein , includi domains . In our affected . We prevaffected , 37. Alt5 KO ECs . TherefoA previous study showed that ADAR1 edits on CTSS mRNAs which plays a critical role in the regulation of EC functions, and increased editing on CTSS was found associated with angiogenesis in atherosclerotic vascular diseases in humans . Edited EC-KO mice from death. This finding strongly supports the presence of an ADAR1 RNA-editing/RNA-sensing signaling axis in ECs that regulates innate immune homeostasis and plays a critical role in the regulation of EC functions.The molecular mechanism of ADAR1 in ECs was implicated through RNA editing on specific RNA substrates such as CTSS mRNA or microRNAs. In contrast, we demonstrated in this study that regulation on the RNA-sensing pathway is the key mechanism that underlies the function of ADAR1 in ECs. Most of ADAR1-mediated editing in ECs occurs at noncoding regions of RNAs in introns and 3′ UTRs on repetitive RNA elements, and especially in SINE transcripts, which form dsRNA structures. Deletion of ADAR1 in ECs leads to dramatically elevated ISG expression, and further deletion of the cytosolic RNA receptor MDA-5 reverses ISG expression back to within normal range and completely recues ADAR1ECs play critical roles at multiple stages of inflammatory reactions , 44, 45.EC-KO mouse model, we also noticed that the elevated ISG expression was not completely abolished, Although the MDA-5-mediated RNA-sensing signaling pathway was shown to underlie the detrimental phenotype of our ADAR1EC-KO/MDA-5−/− double KO mice indicated that the recoding activity of ADAR1 on specific protein coding mRNAs is insignificant and loss of the specifically recoded RNAs can be tolerated by the rescued mice. Our RNA-seq analysis showed that most of the RNA editing occurred to SINE RNA transcripts in noncoding regions of mRNAs. Editing on these SINE RNAs is likely a critical regulator for cellular homeostasis. More studies will be necessary for a complete understanding of RNA editing in ECs, whereas the major function in regulation of the MDA-5–mediated RNA-sensing signaling pathway has been demonstrated in this study.It is known that recoding activities of ADAR1 on mRNAs and microRNAs also regulate EC functions. RNA editing in protein coding regions may result in amino acid changes such as the Q/R site editing in filamin A and B mRNAs , 47. FilEditing level at selected editing sites in endothelial cells. Excel file listing the editing sites of CTSS, FLNα, FLNβ, and others.Table S4 MDA-5−/− mice, Stock #015812, were purchased from Jackson Laboratory. VE-Cre mice were first crossed with floxed ADAR1 to produce the EC-specific ADAR1 KO mouse strain. Then, ADAR1 EC KO mice were crossed with MDA-5−/− mice to produce ADAR1/MDA-5 double KO mice. PCR was used for genotypic analysis of all the mice used for this study. PCR conditions and primer sequences were as reported previously for ADAR1  staining for morphologic studies.GAPDH and HPRT as endogenous control, as described previously  antibody . Isolated ECs were stained with anti CD31 antibody to monitor the purities. 400 nM 4-OH-TM  was added to cultured ECs at passage three and culture was continued for 48 h to induce ADAR1 gene deletion. ADAR1 gene deletion was confirmed using PCR analysis. TM-treated cells and untreated control cells were used for cell function analysis, gene expression analysis, and RNA-seq studies.ADAR1-inducible KO mice, prepared as described in our previous studies , 32, 33,4 cells/plate after TM treatment and cultured with EC growth medium for 72 h. Non-treated ECs were cultured in parallel as controls. At 24-, 48-, and 72-h time points, cell numbers from three dishes were counted to monitor growth rate. The cells were also stained with Ki-67 antibody  at the 24 h time point to monitor cell proliferation. For migration assays, the TM-treated and non-treated ECs were plated to 3-cm plates and cultured for 24 h, followed by removing attached cells growing on the bottom of the culture dishes with a cell scraper, leaving a 500 µm-wide area without cells. The dishes were continuously cultured for 24–30 h, followed by 4% formalin fixation and eosin staining of the cells. Cells that migrated to the gap areas were imaged under a microscope. The areas covered by migrated cells were measured, and the ratio of these areas to the original gap areas was calculated as the cell migration rate.Primary i-KO ECs were replated to 3-cm dishes in triplicates at 5 × 105cells/ml. After 6–12 h of culture without stimulation, the tube-like structures were recorded under the microscope. The total tube length was measured using ImageJ software.Tube formation assays were performed following standard methods  with modhttps://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Illumina adapter sequences and low-quality reads were filtered using the tool Trimmomatic  according to the manufacturer’s protocol and sequenced using NovaSeq6000 platform (Illumina) to an average of 100M 101PE reads. The sequencing reads for each library  were first quality-controlled using the FastQC tool  to detect pathways enriched by the gene alterations. Significant pathways were defined by FDR ≤ 5%.Based on the aligned RNA-seq data, gene counts were quantified using the tool HTSeq  for eachhttp://www.repeatmasker.org) and used to annotate the editing sites to repeat and non-repeat regions. Repetitive regions were categorized as SINE, long terminal repeat (LTR), long interspersed nuclear element (LINE), simple repeat, DNA, RNA, low complexity, and some other subtypes, where SINE can be further clustered as B1, B2, B4, and other subcategories.For each RNA-seq library, variations were called based on the aligned file by the BCFtools mpileup function  and thenTo reduce the influence of single nucleotide polymorphisms (SNPs), libraries of the same mouse with control (CON) and TM treatment were compared. Editing sites of CON > TM (editing rate in control greater than TM-treated) were defined using the following criteria: (1) editing rate of CON–editing rate of TM ≥ 0.05; (2) number of total reads covering the CON variation site ≥5; (3) number of altered reads covering the CON variation site ≥3; and (4) editing rate of CON ≤ 95%. Similarly, editing sites of TM > CON (editing rate in TM-treated greater than control) were defined as (1) editing rate of TM–editing rate of CON ≥ 0.05; (2) number of total reads covering the TM variation site ≥ 5; (3) number of edited/altered reads covering the TM variation site ≥3; and (4) editing rate of TM ≤ 95%. Consistent CON > TM (or CON < TM) sites across the two mice were further compared. Gene and repeat region distribution of these selected sites were explored.In addition to editing site analysis, the data were further explored at the repetitive region (RR) level. RepeatMasker library was used to annotate the editing sites of each individual RNA-seq library or differential editing sites, comparing CON and TM libraries. Editing sites annotated to the same RR were grouped together. Editing rate for an RR was calculated by the average editing rates across all the “for-sure” editing sites located in that RR. Among all the RRs, we specifically focused on and explored SINE, LTR, and LINE.GSE174216. Raw read files, gene count quantification, and editing calling can be accessed via the link https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE174216.All bulk RNA sequencing data  were deposited into the NCBI Gene Expression Omnibus with an accession ID P ≤ 0.05 defined as statistically significant. Prism—GraphPad was used to generate publication quality graphs and Stata software version 12.0 (StataCorp) was used to conduct statistical testing. All statistical analyses on RNA-seq data and data visualizations were performed using R programming with the available R/Bioconductor packages.Continuous data were summarized using mean and SD or median and interquartile range. Groups and categorical data were summarized using frequency and percentages. Bar, dot, and line graphs were used to depict differences and relationships in data. Wilcoxon rank sum test was used to test differences between two groups of nonparametric independent data. For differences between more than two groups of not normally distributed data, the nonparametric, Kruskal–Wallis test by ranks was used. Upon the rejecting the null of Kruskal–Wallis test, the post hoc Conover test was used for pairwise multiple comparisons procedure. All tests used in the analysis were of two-sided nature with