Article Figures and data Abstract Editor's evaluation eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Viral infection involves complex set of events orchestrated by multiple viral proteins. To identify functions of SARS-CoV-2 proteins, we performed transcriptomic analyses of cells expressing individual viral proteins. Expression of Nsp14, a protein involved in viral RNA replication, provoked a dramatic remodeling of the transcriptome that strongly resembled that observed following SARS-CoV-2 infection. Moreover, Nsp14 expression altered the splicing of more than 1000 genes and resulted in a dramatic increase in the number of circRNAs, which are linked to innate immunity. These effects were independent of the Nsp14 exonuclease activity and required the N7-guanine-methyltransferase domain of the protein. Activation of the NFkB pathway and increased expression of CXCL8 occurred early upon Nsp14 expression. We identified IMPDH2, which catalyzes the rate-limiting step of guanine nucleotides biosynthesis, as a key mediator of these effects. Nsp14 expression caused an increase in GTP cellular levels, and the effect of Nsp14 was strongly decreased in the presence of IMPDH2 inhibitors. Together, our data demonstrate an unknown role for Nsp14 with implications for therapy. Editor's evaluation The paper shows that expression of the SARS-CoV-2 Nsp14 protein, which is involved in viral RNA replication, provokes a transcriptional profile that strongly resembles that observed following SARS-CoV-2 infection. Moreover, Nsp14 expression alters the splicing of many genes, increases the number of circRNAs, and activates the NFkB pathway. This surprising observation gives new insight into the biology of SARS-CoV-2 and may have implications for therapy. https://doi.org/10.7554/eLife.71945.sa0 Decision letter Reviews on Sciety eLife's review process eLife digest Viruses are parasites, relying on the cells they infect to make more of themselves. In doing so they change how an infected cell turns its genes on and off, forcing it to build new virus particles and turning off the immune surveillance that would allow the body to intervene. This is how SARS-CoV-2, the virus that causes COVID, survives with a genome that carries instructions to make just 29 proteins. One of these proteins, known as Nsp14, is involved in both virus reproduction and immune escape. Previous work has shown that it interacts with IMPDH2, the cellular enzyme that controls the production of the building blocks of the genetic code. The impact of this interaction is not clear. To find out more, Zaffagni et al. introduced 26 of the SARS-CoV-2 proteins into human cells one at a time. Nsp14 had the most dramatic effect, dialing around 4,000 genes up or down and changing how the cell interprets over 1,000 genes. Despite being just one protein, it mimicked the genetic changes seen during real SARS-CoV-2 infection. Blocking IMPDH2 partially reversed the effects, which suggests that the interaction of Nsp14 with the enzyme might be responsible for the effects of SARS-CoV-2 on the genes of the cell. Understanding how viral proteins affect cells can explain what happens during infection. This could lead to the discovery of new treatments designed to counteract the effects of the virus. Further work could investigate whether interfering with Nsp14 helps cells to overcome infection. Introduction Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for the COVID-19 pandemic that began in 2019. As of early February 2022, COVID-19 has caused 5.7 million deaths worldwide. Coronaviruses are enveloped, relatively small (60–140 nm diameter), positive-stranded RNA viruses belonging to the Coronaviridae family. They derive their name from the crown-like appearance (corona means crown in Latin) that results from the spike glycoproteins in their envelope (V’kovski et al., 2021). The SARS-CoV-2 RNA genome is 30 kb long and has 14 open reading frames (ORFs) that encode 29 proteins (16 non-structural proteins, 4 structural proteins, and 9 accessory factors, Kim et al., 2020). During the first step of the viral infection, the spike glycoprotein on the viral envelope mediates attachment and fusion with the cellular membrane. Once the virus is in the cytoplasm of the host cells, the host ribosome machinery is recruited for the synthesis of viral proteins. Non-structural proteins are required for viral genome replication and are generated by proteolytic cleavage of the polyprotein encoded by ORF1a and ORF1ab. Once the viral genome is replicated, virions are assembled in the host endoplasmic reticulum-Golgi intermediate complex. Finally, new viral particles are incorporated into vesicles and secreted by the host cells (V’kovski et al., 2021). Viral infection triggers a variety of pathways in the host cells that ultimately lead to the hijacking of the cellular machineries escape from immune surveillance. SARS-CoV-2 infection elicits a peculiar gene expression response that first involves activation of interferon pathway (Blanco-Melo et al., 2020; Vanderheiden et al., 2020; Wyler et al., 2021), and then the NFkB pathway (Kircheis et al., 2020; Hariharan et al., 2021; Wyler et al., 2021), as well as expression of specific cytokines such as IL6 and IL8 (Wang et al., 2007; Blanco-Melo et al., 2020; Coperchini et al., 2020; Park and Lee, 2020). Recent and intense research on SARS-CoV-2 characterized the role of viral proteins during viral replication and showed that these functions are often conserved across coronaviruses (V’kovski et al., 2021). Less is known about the roles of the individual proteins in modulating host cell pathways (Gordon et al., 2020a; Gordon et al., 2020b). For instance, recent studies have proposed that Nsp16 is a splicing modulator (Banerjee et al., 2020) and that Nsp1 and Nsp14 are translational repressors (Schubert et al., 2020; Hsu, 2021). Nsp14 is a 60 kDa protein conserved among coronaviruses that is involved both in viral replication and in immune surveillance escape (Ogando et al., 2020). The N-terminal region of Nsp14 contains an exonuclease (ExoN) domain that excises mismatched nucleotides to ensure accurate replication of the viral genome (Ogando et al., 2020). As a result of this proofreading mechanism, coronaviruses have a lower mutation rate than other RNA viruses (error rate of 106–107 vs. 103–105) (Sanjuán et al., 2010; Robson et al., 2020). Loss of function of the ExoN domain results in increased sensitivity to the RNA mutagen 5-fluorouracil (Eckerle et al., 2010) and attenuated virulence (Graham et al., 2012). Furthermore, the interaction with Nsp10 augments Nsp14 ExoN activity up to 35-fold, and inhibition of the interaction between Nsp10 and Nsp14 leads to reduced replication fidelity (Ma et al., 2015; Smith et al., 2015). Nsp14 is also involved in assembly the cap at the 5’ end of the viral RNA genome, which is crucial for evading immune surveillance. The C-terminal region of Nsp14 functions as an S-adenosyl methionine-dependent guanine-N7 methyl transferase that is independent of the ExoN activity (Chen et al., 2009). Both enzymatic domains are essential for successful viral replication, making Nsp14 an appealing drug target (Otava et al., 2021; Saramago et al., 2021). Nsp14 is part of the replication complex, therefore it interacts with other SARS-CoV-2 proteins. As for other coronaviruses, replication of SARS-CoV-2 genome takes place in replication organelles that provide a protective environment for the newly synthesized viral genome (V’kovski et al., 2021). Notably, these organelles are formed in the cytoplasm and present convoluted double layered membranes that likely exchange material with the cytoplasm through pores (Wolff et al., 2020). Furthermore, Nsp14 might mediate immune surveillance escape by activating the interferon pathway and activating the pro-inflammatory response through NFkB transcriptional activity and CXCL8 expression (Yuen et al., 2020; Hsu, 2021; Li et al., 2021). However, the biological mechanism behind these events has not fully characterized. Furthermore, a global interactome study showed that Nsp14 interacts with the cellular enzyme inosine-monophosphate dehydrogenase 2 (IMPDH2) and that this interaction is conserved also in SARS-CoV-1 and MERS-CoV viruses (Gordon et al., 2020a; Gordon et al., 2020b). IMPDH2 catalyzes the conversion of inosine-5'-monophosphate (IMP) to xanthine-5’-monophosphate (XMP) (Hedstrom, 2009), which is the rate-limiting step of de novo guanine nucleotides biosynthesis. Guanosine-5'-triphosphate (GTP) is necessary for DNA replication and transcription and is used as energy source for translation and as mediator of signal transduction (Hesketh and Oliver, 2019). How the physical interaction between Nsp14 and IMPDH2 impacts the host pathways is not completely understood (Li et al., 2021). Interestingly, a recent study has shown that expression of Nsp14 results in global translation inhibition, but it is not clear if this is a direct effect or a downstream consequence of the changes that the expression of this protein provokes to the cellular environment (Hsu, 2021). Indeed, no direct interaction between Nsp14 and ribosomes or a known translational modulator has been reported, suggesting that the potential translational inhibition might be a downstream effect. Here, we undertook transcriptome analyses in cells that express each SARS-CoV-2 protein individually. Expression of Nsp14 altered the expression of about 4000 genes, mostly involved in splicing, RNA metabolism, and cell-cycle control. Importantly, the effect of Nsp14 on cellular gene expression resembled the transcriptional changes that occur upon SARS-CoV-2 infection and included the activation of the NFkB pathway and the expression of CXCL8 (encoding IL8), a marker of acute severe respiratory distress syndrome in COVID-19 patients (Adcock et al., 2015; Blanco-Melo et al., 2020; Kircheis et al., 2020). Intriguingly, we also detected an increase in circRNAs expression upon Nsp14 expression; recent studies indicate that circRNAs can act as modulators of the innate immune response during viral infections (Li, 2017; Liu, 2019; Chen et al., 2020; Yan and Chen, 2020). Moreover, we showed that the cellular enzyme IMPDH2 mediates the gene expression response induced by Nsp14. We found that IMPDH2 mRNA is downregulated upon Nsp14 expression and that the cellular GTP concentration strongly increases, indicating that Nsp14 might activate IMPDH2 enzymatic activity. In accordance with our hypothesis, we showed that treatment with IMPDH2 inhibitors (mycophenolic acid [MPA] and mizoribine [MZR], Lee et al., 2020a), partially rescued the changes in gene expression induced by Nsp14. Results Expression of individual SARS-CoV-2 proteins specifically remodels the transcriptome Infection of cells with SARS-CoV-2 induces strong and specific changes in the transcriptome of host cells and tissues (Blanco-Melo et al., 2020; Wyler et al., 2021). It is assumed that this response results from the hijacking of the cellular systems by the virus as well as from the defense by the host. To identify unknown functions of the individual SARS-CoV-2 proteins and to determine how much each protein contributes to the takeover of cellular systems, we determined how the transcriptome changed when we individually express each viral protein in a human cell line. Specifically, we expressed individual SARS-CoV-2 proteins (Gordon et al., 2020b) in HEK293T cells, and after 48 hr we purified RNA, generated and sequenced 3’ RNA sequencing (RNA-seq) libraries, and identified differentially expressed genes (DEGs; Figure 1A). Extensive cell death or changes in morphology did not occur upon expression of individual proteins, as assessed visually. Figure 1 Download asset Open asset Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteins alter gene expression distinctively. (A) Scheme of the experimental approach. DEGs stands for differentially expressed genes and GO for Gene Ontology. (B) Heatmap showing the number of DEGs detected in 3’ RNA sequencing for each expressed SARS-CoV-2 protein. ‘Up’ stands for upregulated genes, ‘Down’ for downregulated genes. Lfc < 0.5, corrected p-value < 0.05. (C) Heatmap showing the GO analysis (colors represent the significant normalized enriched score). Interestingly, expression of most proteins resulted in modest or no changes in the transcriptome of the HEK293T cells. Indeed, we detected less than 300 DEGs upon expression of 17 of the 25 tested proteins (Supplementary file 1a and Figure 1B). Expression of seven viral proteins, M, Nsp9, E, ORF9b, ORF3a, Nsp13, and Nsp1, modestly altered the transcriptome (between 300 and 700 DEGs). Interestingly, these DEGs tended to be upregulated rather than downregulated (Figure 1B). Striking, Nsp14 altered the expression of more than 4000 RNAs (1862 upregulated and 2161 downregulated; Figure 1B). The profound impact of Nsp14 expression on the transcriptome of HEK293T cells suggests that this protein has roles beyond its known functions in viral genome proofreading and immune system escape. To identify cellular pathways affected by the expression of the individual SARS-CoV-2 proteins, we performed Gene Ontology (GO) analysis of the DEGs upon expression of the different viral proteins (Supplementary file 1b and Figure 1C). Expression of the viral proteins impacted mRNAs encoding proteins related to different aspects of gene expression (regulation of transcription, translation, and RNA metabolism), cell metabolism, cell division, and innate immunity. For example, expression of Nsp7, an accessory protein of the RNA-dependent RNA polymerase (Kirchdoerfer and Ward, 2019; Hillen, 2020), deregulated expression of genes encoding proteins involved in DNA and RNA metabolism (Figure 1C). Expression of Nsp9 and Nsp13, known to bind RNA and to regulate RNA metabolism, respectively (Egloff et al., 2004; Shu et al., 2020), resulted in the mis-regulation of mRNAs encoding proteins involved in RNA metabolism and translation (Figure 1C). Furthermore, expression of the protein ORF3d, known to bind STOML2 mitochondrial protein, may be a unique antigenic target upon SARS-CoV-2 infection (Gordon et al., 2020b; Hachim et al., 2020; Nelson et al., 2020; Jungreis et al., 2021), resulted in alteration of genes involved in cell metabolism and immunity (Figure 1C). In general, expression of the viral proteins mainly impacted pathways related to RNA metabolism, translation, and cell metabolism that were previously reported to be affected upon viral infection (Blanco-Melo et al., 2020; Gardinassi et al., 2020; Wyler et al., 2021). Expression of Nsp14 affected the expression of genes involved in RNA splicing, metabolism, and processing, translation, cell-cycle control, and the cytoskeleton. Nsp14 also impacted the expression of genes involved in general metabolism, especially on genes implicated in nucleotide metabolism (Figure 1C). Nsp14 expression induces transcriptional changes that resemble SARS-CoV-2 infection We decided to focus on Nsp14, as expression of this protein resulted in significantly more DEGs than any other tested protein. To obtain a more comprehensive view of the transcriptome changes provoked by Nsp14, we complemented the 3’ RNA-seq data with total RNA-seq data generated from cells transfected with Nsp14. The new dataset strongly resembled the one obtained by 3’ RNA-seq (Figure 2A, Supplementary file 1c, and Figure 2—figure supplement 1A) but also contained information about the full-length RNAs, non-poly-adenylated RNAs, and pre-mRNAs. Figure 2 with 2 supplements see all Download asset Open asset Expression of Nsp14 induces transcriptional changes like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. (A) MA plot showing the fold change of expression in samples expressing Nsp14 compared to control detected in the total RNA sequencing (RNA-seq). In red significantly downregulated genes, in blue upregulated genes, and in gray non significantly deregulated genes. (B) Scheme representing the approach to determine the overlap with our total RNA-seq data and already published dataset (top). Table reporting the gene set enrichment analysis (GSEA) terms, up- or downregulation, publication, the normalized enriched score (NES), and adjusted p-value (p-adj) when comparing our total RNA-seq data with previously published datasets. Significant terms related to SARS-CoV-2 and MERS infection are indicated in blue, non-significant terms related to influenza A infection are indicated in orange (bottom). (C) Example of GSEA. (D) Nsp14 expression vs. control fold change of intronic signal from total RNA-seq vs. 3’ RNA-seq signal in logarithmic scale for each detected gene. Colored dots represent significantly changing genes (fold change = 2, adjusted p-value < 0.05, N = 3). (E) Nsp14 expression vs. control fold change of intronic signal from total RNA-seq vs. exonic signal from total RNA-seq in logarithmic scale for each detected gene. Colored dots represent significantly changing genes (fold change = 2, adjusted p-value < 0.05, N = 3). (F) RT-qPCR showing the abundance of FGF-18, CXCL8, SH2D2A, and COL13A in the chromatin-bound RNA fraction in cells transfected with an empty plasmid (control) or with Nsp14 (Nsp14). Data represented as mean ± SEM, N = 3. To gain further insights into the mechanism and pathways altered by Nsp14, we performed gene set enrichment analysis (GSEA) of the total RNA-seq data from Nsp14-expressing cells. Strikingly, we found that for genes upregulated upon expression of Nsp14, three of the four most highly enriched GSEA datasets were those of cells infected with SARS-CoV-2 (Blanco-Melo et al., 2020; Figure 2B and C, and Figure 2—figure supplement 1B). Moreover, we observed a smaller but significant enrichment of genes upregulated upon infection with MERS, a related virus (Blanco-Melo et al., 2020). Further, the mRNAs downregulated upon expression of Nsp14 tended to be strongly enriched for those downregulated following SARS-CoV-2 viral infection (Figure 2B). We did not detect enrichment when our dataset were compared to data from cells infected with influenza A virus (Blanco-Melo et al., 2020; Figure 2B). These results demonstrate that expression of a single viral protein can recapitulate a considerable portion of response of a host cell to SARS-CoV-2 infection and highlights the potential importance of Nsp14 in hijacking host gene expression. Nsp14 alters gene expression mostly at the transcriptional level To evaluate whether the transcriptome changes were due to alterations at the transcriptional or post-transcriptional level or a combination of both, we utilized intronic signals from the total RNA-seq experiment as a proxy for transcriptional activity (Lee et al., 2020b). For each DEG in the 3’ RNA-seq dataset, we determined whether the intronic signal in the total RNA-seq dataset was altered in the same direction. We observed a strong correlation (R = 0.73 and p-value = 2.2e−16) between these two measures (Figure 2D), indicating that a large part of the response is transcriptional. For example, of the 1862 genes that were upregulated upon Nsp14 expression, 1006 also had higher intronic signal (at least 20% signal increase), whereas only 57 of the showed decreased intronic signal. Similarly, of the 2161 genes downregulated upon Nsp14 expression, 1242 displayed lower intronic signal (at least 20% signal decrease), whereas only 109 showed higher intronic signal (Supplementary file 1d). We then performed a similar analysis using the exonic signal of DEGs in the same total RNA-seq dataset. We obtained an even stronger correlation between the changes in exonic signal and total RNA signal for each gene (R = 0.87 and p-value = 2.2e−16, Figure 2E). In sum, we observed that more than 50% of the changes in the transcriptome upon Nsp14 expression are transcriptional. Notably, this might be an underestimation, as changes in intronic signal could be lower than the steady-state RNA levels or some introns could be very efficiently and quickly removed, so that splicing intermediates are not detected. To further confirm the transcriptional effect, we determined the levels of a subset of DEGs from chromatin-bound nascent RNA from cells transfected with a control or a Nsp14-expressing plasmid. As expected, a pre-mRNA (pre-TBP), was enriched in the chromatin-bound fraction, U6 was abundant in the nuclear compartment (nucleoplasm and chromatin bound), whereas 18S rRNA and a circRNA (circVKR1) were more abundant in the cytoplasm (Figure 2—figure supplement 2A). Then, we checked the expression of some genes that were up or down regulated upon Nsp14 expression in our dataset in the chromatin-bound fraction. Genes upregulated upon Nsp14 expression (FGF-18 and CXCL8) were also upregulated in the chromatin-bound fraction, while the downregulated ones (SH2D2A and COL13A) were downregulated indicating that at least those mRNAs are regulated at the transcriptional level by Nsp14. These results verify the genomic observations and strongly suggest that the gene expression changes observed upon Nsp14 are mainly transcriptional (Figure 2F). Interestingly, we also observed that there are more than 1000 genes that display higher intronic signals with no changes in gene expression, indicating that, in addition to the transcriptional effects, Nsp14 might also affect splicing (Supplementary file 1e). Nsp14 expression provokes changes in alternative splicing and circRNAs production Genes upregulated upon Nsp14 expression are enriched in genes encoding proteins with GO terms related to RNA metabolism and, more specifically, splicing (Figure 1C). Moreover, for more than 1000 genes, there were significant increases in intron signal upon expression of Nsp14 without changes in mRNA levels, suggesting that Nsp14 alters the splicing of these pre-mRNAs (Supplementary file 1e). Indeed, we found that expression of Nsp14 strongly altered the inclusion patterns of almost 2300 exons, with more than 2000 exons displaying lower inclusion in the mature mRNA and 238 showing higher levels of inclusion when we expressed Nsp14 (Figure 3A, Supplementary file 1e, and Figure 3—figure supplement 1A). Furthermore, we also identified genes which used alternative acceptor or donor splice sites upon expression of Nsp14 (Figure 3A and Supplementary file 1e). Moreover, we observed an increase in the retention of more than 2000 introns following Nsp14 expression (Figure 3A and C). Although the effects on exon inclusion and use of alternative splice sites clearly indicate that Nsp14 influences splicing, the increase in intron retention could be secondary to changes in transcription. However, as most of the introns with increased retention are within genes that were not differentially expressed (Figure 3B and Figure 3—figure supplement 1B), we reasoned that expression of Nsp14 leads to changes in splicing in this subset of genes as well. Moreover, the effect of Nsp14 on alternative splicing appears to be specific to particular introns and exons in each gene, as the majority (~62%) of identified genes had a single spicing event altered (Figure 3D and Supplementary file 1e). Notably, most genes with altered splicing do not show expression changes upon Nsp14 expression, further indicating that the detected alternative splicing events are independent to transcriptional changes (Figure 3—figure supplement 1B). Figure 3 with 1 supplement see all Download asset Open asset Nsp14 expression alters the splicing of a subgroup of genes and increases circRNAs expression. (A) Table summarizing splicing analysis comparison between Nsp14 expression and control. Thresholds used: ∆PSI (percentage of inclusion) > 15% and a non-overlapping distribution with minimum of 5% difference (N = 3). (B) Fold change vs. expression in logarithmic scale for the genes with upregulated intron retention. In red genes with increased expression and in blue the ones with downregulated expression (fold change = 2, adjusted p-value < 0.05, N = 3). (C) Representative IGV alignment tracks of on gene (PAXIP1) with intronic events differentially changing between conditions (control and Nsp14 expression). The box marks the changing event. On the right, quantification of PSI. (D) Pie chart representing number of alternative splicing events deregulated upon Nsp14 expression by gene; 1772 genes have only one alternative splicing event changing between conditions, 615 has two events and 243 genes have three alternative splicing events changing. (E) Number of circRNAs reads detected in the total RNA sequencing (RNA-seq) experiment. Data represented as mean ± SEM, N = 3, t-test, ***p-value < 0.0005. (F) Fold change vs. expression in logarithmic scale for circRNAs in Nsp14 expression vs. control. In red upregulated genes and in blue downregulated genes (fold change = 2, adjusted p-value < 0.05, N = 3). (G) Plot of fold change vs. expression in logarithmic scale for exonic signal detected in the total RNA-seq dataset in Nsp14 vs. control for genes with upregulated circRNA expression. In red genes with increased expression and (fold change = 2, adjusted p-value < 0.05, N = 3). (H) Plot of fold change vs. expression in logarithmic scale for intronic signal detected in the total RNA-seq dataset in Nsp14 vs. control for genes with upregulated circRNA expression. In red genes with increased expression and in gray non-significant ones (fold change = 2, adjusted p-value < 0.05, N = 3). To further characterize the effects of Nsp14 expression on alternative splicing, we looked for genomic features associated with the altered patterns of splicing in the presence of Nsp14. Interestingly, we found that the affected introns tended to be at the 5’ end of the transcript and were embedded in genomic regions with higher-than-average GC content (Figure 3—figure supplement 1C and Supplementary file 1f). The GC content may be a confounding factor of the location of these introns, as the GC content is higher at the 5’ end of genes and around the transcription start sites (Zhang, 2004). Therefore, we concluded that Nsp14 expression has a strong and specific effect on splicing efficiency for a subset of genes. Furthermore, most of the affected exons are shorter and have higher GC content around their splice sites than a randomized subset of exons not affected by Nsp14 (Figure 3—figure supplement 1D and Supplementary file 1f). The higher GC content suggests that stable RNA structures form around the splice sites in these exon, which correlates with alternative splicing propensity (Zhang et al., 2011; Lin et al., 2016). Previous research showed that SARS-CoV-2 infection disrupts splicing, mostly by inducing intron retention (Banerjee et al., 2020). To check whether the effects on splicing induced by Nsp14 were comparable to the ones that happen during SARS-CoV-2 infection, we re-analyzed a published dataset of total RNA-seq from HEK293T cells expressing human ACE2 and infected with SARS-CoV-2 (Sun et al., 2021). We found that there is a significant overlap (p-value < 0.01, see Materials and methods) between the alternative splicing events during the infection and in our model. Specifically, 10% of the alternative splicing events changing with SARS-CoV-2 infection (Supplementary file 1g) also change (and in the same direction) when we express Nsp14 (Supplementary file 1e). In sum, we showed that expression of Nsp14 partially recapitulates the gene expression changes, as well as some of the alternative splicing events that occur upon SARS-CoV-2 infection. As circRNAs are generated by back-splicing, a process that competes with linear pre-mRNA splicing (Ashwal-Fluss et al., 2014), we checked whether Nsp14 also alters circRNAs expression. Using the total RNA-seq data, we found that there is a strong increase (more than twofold) in the total number of circRNA reads upon Nsp14 expression (Figure 3E). Most of the 246 circRNAs that were differentially expressed upon expression of Nsp14 were upregulated (put the number of upregulated; Figure 3F and Supplementary file 1h). These deregulated circRNAs were contained within 190 loci (some loci host multiple circRNAs). Interestingly, the levels of most of the mRNAs that host these circRNAs were unchanged (Figure 3G and Supplementary file 1d). Indeed, Nsp14 did not increase the transcription of loci hosting the upregulated circRNAs (we observed increased levels of intronic sequences in only 20 out of the 190 loci with upregulated circRNAs; Figure 3H and Supplementary file 1d). Together, these results strongly suggest that the increased circRNA levels are caused by increased biosynthesis or stability of the circRNAs. In sum, our data shows that expression of Nsp14 influences alternative splicing and back-splicing on the host cells. The effect of Nsp14 on gene expression is independent of the ExoN activity but requires the N7-guanine-methyltransferase domain Nsp14 has two separated enzymatic activities: (1) works as a proofreading ExoN and (2) it is a N7-guanine-methyltransferase required for the modification of the viral RNA cap. To determine whether the ExoN activity is required for the strong effects of Nsp14 on gene expression, we performed two different experiments. First, we tested whether co-expression of Nsp10, which dramatically increases the ExoN activity of Nsp14 (Bouvet et al., 2012; Bouvet et al., 2014; Ma et al., 2015), resulted in an enhanced effect of Nsp14. Briefly, we transfected HEK293T cells with plasmids for expressing Nsp14 and/or Nsp10. As a control, we used c
