Single-cell RNA sequencing highlights moDC heterogeneity
Upon exposure with recombinant HCMV expressing NeonGreen (HCMV-NG) coupled to the IE1 (UL123) protein 17, only a minority of moDCs showed NG expression (Fig. 1a and Supplementary Fig. 1a). To address whether certain transcriptomic profiles determined HCMV permissiveness of moDCs, we studied the heterogeneity of moDCs exposed to HCMV-NG after 8 h of incubation by scRNA-seq. To minimize batch effects, mock- and HCMV-NG exposed cells were labeled with tagged anti-CD45 and anti-HLA-DR antibodies, respectively, and pooled prior to scRNA-seq (Fig. 1b). Both antibodies carried specific DNA oligo tags. The presence of antibody-derived tags (ADT) was used to de-multiplex cells 18. moDCs from two donors were infected each with two independently produced HCMV-NG preparations (V1, V2). Accordingly, data from a total of four separate runs with overall 18,936 cells that passed quality control were combined, analyzed by unsupervised clustering and visualized using non-linear dimensionality reduction (Supplementary Fig. 1b). CD45-ADT+ (Fig. 1c) and HLA-DR-ADT+ cells (Fig. 1d) clustered separately. Each ADT-labeled subset segregated into several clusters, which were primarily defined by variations in host gene expression (Supplementary Fig. 1c). Amongst HCMV-NG exposed cells, only one cluster showed strong expression of UL123 as well as of many other viral RNAs (Fig. 1e and Supplementary Fig. 1d). Accordingly, we defined three groups of moDCs, “mock-exposed” cells (M) that were not exposed to the virus, “bystander” cells (B) that were HCMV-NG exposed but did not show strong viral gene expression (Fig. 1e), and “productively infected” cells (P) that showed high viral RNA levels including UL123. Samples segregated according to the donor origin of the moDCs, whereas batch effects between runs and virus preparations used were minimal (Supplementary Fig. 1b). For further analysis, single clusters that were composed of cells from both donors were manually split according to the donor origin. As a result, moDCs of each donor comprised three mock-exposed clusters (M1-3, CD45-ADT+), four to five bystander clusters (B1-4, HLA-DR-ADT+/UL123low), and one productively infected cluster (P, HLA-DR-ADT+/UL123high) (Fig. 1f, g).
moDCs comprise three transcriptionally defined cell subsets with different susceptibilities to infection
Cluster-specific marker gene expression profiles indicated that, for both donors, bystander clusters B1, B2 and B3 primarily originated from a single mock-exposed cluster, i.e., M1, M2, and M3, respectively (Fig. 2a, b and Supplementary Fig. 2a). This was confirmed by canonical correlation analysis (CCA) predicting for each HCMV-NG exposed cell the most similar mock-exposed cells in an unbiased manner (Fig. 2c, d). The bystander cluster B1/2 from donor #1 originated from M1 and M2. Interestingly, bystander cells in cluster B4, and productively infected cells in P, were composed of cells from all three mock-exposed clusters. Importantly, M1-derived cells were the most abundant ones in cluster P (Fig. 2c, d), even after normalizing for the different cluster sizes of M1-M3 (Supplementary Fig. 2b, c).
Comparing cells from both donors using CCA revealed strong similarities between M1, M2 and M3, respectively (Fig. 2e), which similarly applied for their respective HCMV-NG exposed counterparts (Supplementary Fig. 2d). To address whether moDC clusters represented distinct subsets or different stages of differentiation, we performed RNA velocity analysis that predicts the upcoming gene expression of cells 19. This analysis did not reveal any particular directionality among the clusters M1-3 (Fig. 2f). Instead, pathway analysis of moDC-specific traits revealed that the clusters M1-3 showed differences in metabolic pathways, cytokine production, endocytosis and in their antigen presentation capacity (Fig. 2g, Supplementary Fig. 2e and Supplementary Table 1). Notably, the respective clusters from donors #1 and #2 showed overall very similar profiles of active pathways. Taken together, moDCs comprise three distinct clusters that were similarly detected amongst mock- and HCMV-NG exposed moDCs derived from two independent donors.
Next, we verified via flow cytometry that mock-exposed moDCs showed a similar protein expression profile as detected in the moDC clusters using cluster-specific genes that were manually selected from the scRNA-seq data set, i.e., CLEC12A (CD371), CD1a, CD86, CCL18, CCL17, CCL22, CSF1R (CD115), C5AR1 (CD88), and LILRB2 (CD85d) (Fig. 3a-d and Supplementary Fig. 3a, b). In particular expression of CD1a, CD86 and CLEC12A distinguished the 3 subsets (Fig. 3b). M1 was characterized by CD1a-/CD86-, while showing high expression of CLEC12A. CD1a+ defined M2 and CD86+ defined M3. Analysis of moDCs from sixteen different donors verified the presence of these three subsets and indicated that CD1a-/CD86- cells represented approximately 57%, CD1a+ 28%, and CD86+ 13% of moDCs (Fig. 3c). Furthermore, these markers discriminated the three subsets also in HCMV-NG exposed moDCs (Fig. 3e) and revealed higher percentages of NG+ cells amongst CD1a-/CD86- cells (M1) than amongst CD86+ (M3) and CD1a+ cells (M2) (Fig. 3f), consistent with our scRNA-seq data. Upon sorting, the three moDC subsets showed distinct morphologies (Fig. 3g). After HCMV-NG exposure the sorted CD1a-/CD86- subset (M1) again showed higher infection than CD1a+ cells (M2) (Fig. 3h). Only the sorted CD86+ cells (M3) showed a higher susceptibility to infection than in the mixed moDC cultures, which was similar to CD1a-/CD86- cells. Thus, flow cytometry validated the three moDC subsets with different susceptibilities to HCMV infection as identified by scRNA-seq.
Most HCMV-NG exposed moDCs contain virion-associated transcripts, but only few show de novo viral gene expression
Multiple HCMV genes commonly share a polyadenylation site. As 3' sequencing-based scRNA-seq cannot distinguish those, we manually curated groups of viral transcripts belonging to one polyadenylation site (Supplementary Fig. 4a). Analysis of viral transcripts revealed that most HCMV-NG exposed moDCs contained at least trace amounts of viral transcripts (Fig. 4a and Supplementary Fig. 1d). To distinguish virion-associated RNAs that were delivered to cells by the infection process and viral RNAs that were de novo transcribed, we sequenced the two HCMV-NG preparations V1 and V2 that were used for the infection experiments. In addition to viral transcripts, several thousands of different host transcripts were detected in HCMV-NG preparations (Fig. 4b). The four most abundant host transcripts included the heavy and light subunit of iron storage protein ferritin (FTL, FTH1) and the two polyubiquitin genes UBB and UBC (Fig. 4b). Moreover, we confirmed the late (L) viral transcript UL22A and the early (E) long non-coding RNA2.7 as the most abundant virion-associated transcripts (Fig. 4b, c) 20. Indeed, these transcripts were also the most abundant ones in bystander cells (Fig. 4d and Supplementary Fig. 4b). In contrast, productively infected cells in P showed promiscuous expression of viral transcripts of all kinetics classes. Interestingly, already at 8 hpi we found expression of E (e.g., US22) and L (e.g., UL100) transcripts in certain cells in P (Fig. 4e), which correlated with higher loads of total viral RNAs (Fig. 4a) as well as the virion-associated RNAs UL22A and RNA2.7 (Supplementary Fig. 4c). To estimate for each cluster the percentage of cells that carried virion-associated RNAs as compared to the percentage of cells that started de novo viral gene expression, we analyzed the abundance of UL22A/RNA2.7 versus UL122/UL123 as prototypic virion-associated and de novo expressed RNAs, respectively. This analysis confirmed that close to 100% of cells in P were infected and started viral gene expression (Fig. 4f). Interestingly, up to 70% of the bystander cells in B1-3 had detectable levels of virion-associated transcripts UL22A and RNA2.7 (Fig. 4f, left panel). Some variation of values was detected between clusters and donors and percentages were presumably underestimated due to RNA degradation during the 8 h of infection. In contrast, only 5-10% of cells in B1-3 and 25% of cells in B4 showed expression of UL122 and UL123 (Fig. 4f, right panel). Since percentages of NG+ cells further increased between 8 and 24 h of incubation (Fig. 1a and Supplementary Fig. 1a) and the relative number of cells in P correlated with NG+ cells at 8 hpi (Supplementary Fig. 1a, b), it is very likely that with time at least some of the bystander cells that showed UL122/UL123 expression would have progressed to productive infection. Cells in B4 expressed considerably higher levels of IE genes than cells in the other B clusters (Fig. 4d, f). Furthermore, in the UMAP, B4 was placed in close proximity to P (Fig. 1f, g). However, RNA velocity analysis did not reveal the transition of B4 to productively infected cells in P (Fig. 4g). Thus, upon HCMV-NG exposure, most moDCs are infected by virus particles that deliver viral and human RNAs into these cells, whereas de novo viral gene expression is initiated only in a minor fraction of moDCs.
Increased expression of viral RNAs is associated with downregulation of interferon stimulated genes and upregulation of heat shock proteins
Hallmark pathway analysis indicated that inflammatory pathways were significantly upregulated upon HCMV-NG exposure when compared with mock-exposed cells (Fig. 5a, first panel). Strikingly, inflammatory pathways were significantly downregulated in productively infected cells in P when compared with bystander cells in B1-4 (Fig. 5a, second panel). Moreover, in bystander cells, mRNAs assigned to homeostatic/metabolic pathways were significantly negatively correlated with viral gene expression (Fig. 5a, third panel), whereas in productively infected cells mRNAs assigned to inflammatory and interferon response pathways were negatively correlated (Fig. 5a, fourth panel). Thus, downregulation of host response pathways to infection was qualitatively and quantitatively dependent on viral gene expression.
Interestingly, more host genes were downregulated (n=94) than upregulated (n=29) in productively infected cells (P) when compared with bystander cells (B) (Supplementary Table 2). Downregulated host genes were mostly negatively correlated with expression of viral RNAs and comprised predominantly ISGs (Fig. 5b). Indeed, we identified three ISGs as the most negatively correlated host genes in P, including (i) IFI16 that was previously reported to be a restriction factor of early HCMV infection 21, (ii) RNF213, an ISG15 interactor 22), and (iii) TNFSF10 (TRAIL), the latter two of which so far have not been recognized to directly affect HCMV replication.
In contrast, in the few cases where host genes were upregulated in productively infected cells (P) they were mostly positively correlated with viral gene expression (Fig. 5b). This included the GTP-binding protein RhoB that was described earlier as a pro-viral factor for HCMV replication 23 and a broad range of heat shock proteins (HSPs) (Fig. 5b, c). In particular, the HSPs DNAJB1 and HSPA1A were the host genes that were most positively correlated with viral RNA expression in P. Interestingly, also IFNL1 (the gene encoding IFN-λ1) was one of the few host genes that was upregulated in P and that was positively correlated with viral gene expression. In contrast, IFNB1 (the gene encoding IFN-β) was upregulated in P, but negatively correlated with viral gene expression (Fig. 5b). Thus, we identified putative pro- and anti-viral host factors of HCMV infection in moDCs.
Viral IE gene expression is correlated with IFNB1 expression, whereas progression of viral infection inhibits IFNB1, but not IFNL1 induction
We exposed moDCs to replication competent HCMV-NG and UV-inactivated HCMV-NG and analyzed cell free supernatants for the presence of IFN-α, IFN-β and IFN-λ. Both IFN-β and IFN-λ were mostly secreted within the first 16 hpi, whereas IFN-α secretion started later (Fig. 6a and Supplementary Fig. 5). Accordingly, mainly IFNB1 and IFNL1 expression was detected in the scRNA-seq analysis at 8 hpi. IFNB1 was expressed in some cells of B1-3, B4 and P (Fig. 6b), whereas IFNL1 expression was restricted mainly to B4 and some cells in P (Fig. 6c). In bystander cells, including B1-3 and B4, the expression of IFNB1 and IFNL1 positively correlated with levels of total viral RNAs (Fig. 6d). While IFNL1 expression was also positively correlated with total viral RNA levels in P, IFNB1 was negatively correlated suggesting a different mechanism of regulation for IFNB1 and IFNL1. Therefore, we performed a detailed correlation of viral and host genes with IFNB1 and IFNL1 expression. In B1-B3 overall low correlations were detected (Fig. 6e, f and Supplementary Table 3, 4), including correlations with the most abundant viral RNAs in B1-B3, i.e., the virion-associated RNAs UL22A/RNA2.7. In contrast, the viral IE genes UL122 and UL123 showed a high correlation with IFNB1. In B4, IFNB1 and IFNL1 did not show a significant correlation with most viral genes (Fig. 6e), whereas a large number of host genes was strongly correlated with both IFNs (Fig. 6f). In particular PPP1R15A (GADD34), which was found to mediate IFN-β expression under conditions of anti-viral protein synthesis inhibition in fibroblasts 24, was highly positively correlated with both IFNs in B4. PPP1R15A was also positively correlated with both IFNs in productively infected cells. However, the majority of strongly correlated host genes was either associated with IFNB1 or IFNL1 (Fig. 6f). This similarly applied to viral genes. IFNB1 expression was only positively correlated with the viral IE gene UL122, while it was negatively correlated with all other viral RNAs (Fig. 6e). In stark contrast, in cells from P IFNL1 was positively correlated with the majority of viral RNAs, and in particular with UL22A and RNA2.7. Thus, especially the host gene PPP1R15A seems to play an important role in the induction of both IFNB1 and IFNL1 in moDCs. Moreover, in bystander cells IFNB1 expression was associated with viral IE gene transcription, whereas in P cells IFNB1, but not IFNL1, expression was counter-regulated upon progression of HCMV infection.
STING activation facilitates viral gene expression
To address the anti-viral activity of the different IFNs produced by HCMV-NG exposed moDCs, we treated moDCs with IFN-α2b, IFN-β or IFN-λ1 at the time of (0 dpi), or one day prior (-1 dpi) to HCMV-NG exposure. Treatment of moDCs with cytokines at the time of infection did not change the percentage of HCMV-NG+ cells when compared with infected cells without treatment (Fig. 6g). In contrast, pre-treatment one day prior to HCMV-NG exposure with IFN-α2b and IFN-β, but not IFN-λ1, significantly reduced the percentage of NG positive cells indicating the anti-viral effect of IFN-α and IFN-β, but not IFN-λ1 under such conditions.
cGAS/STING recognition of HCMV DNA leads to activation of type I IFN expression in moDCs 10. Since STING also activates NF-κB signaling 25 and NF-κB transactivates the HCMV major IE promoter 26,27, we hypothesized that cGAS/STING sensing of HCMV activated IE gene transcription, thus correlating IFNB1 and UL122/UL123 expression (Fig. 6e). While pre-treatment with the STING agonist ADU-S100 decreased susceptibility of moDCs to HCMV-NG infection presumably due to STING-mediated IFN induction, treatment at the time of infection significantly increased percentages of HCMV-NG+ moDCs (Fig. 6h). Treatment with TNF-α that activates NF-κB similarly increased HCMV-NG infection suggesting that STING-dependent activation of IE gene expression was mediated by NF-κB.
moDCs reveal a marked downregulation of ISGs upon progression to productive infection
Commonly employed analysis pipelines for scRNA-seq data only consider reads originating from mature RNAs (“spliced reads”). As splicing occurs predominantly co-transcriptionally, the abundance of unspliced reads is a good approximation of nascent RNA that is currently being transcribed in an individual cell 19. All HCMV-NG exposed moDCs, including cells in P, showed higher levels of spliced reads from ISGs than mock-exposed cells (Fig. 7a, left UMAP) suggesting that ISGs were initially induced also in productively infected cells. In contrast, unspliced reads for ISG transcripts were massively reduced in productively infected cells of P (Fig. 7a, right UMAP). Accordingly, the ratio of unspliced vs spliced ISG reads was substantially lower in P than in B1-4 (Fig. 7b) suggesting downregulation of ISG transcription. A separate analysis of unspliced versus spliced transcripts in M1-3, B1-3, B4 and P confirmed that although all moDCs were competent to express ISGs upon HCMV-NG exposure, cells that contained intermediate amounts of viral RNA such as B4 moderately downregulated ISG transcription, and cells with strong viral gene expression in P showed massive downregulation of ISG transcription (Fig. 7c and Supplementary Fig. 6a-c). Notably, a subset of ISGs, including ZC3HAV1 (ZAP) and OASL, were only strongly induced in B4 and P, but not in B1-3, and while their expression in P was inhibited this was not the case in B4 (Supplementary Fig. 6d, e). In P the extent of ISG shut off correlated with overall levels of viral gene expression (Fig. 7d, e). Interestingly, active ISG transcription was positively correlated with UL122, but negatively correlated with all other viral transcripts, in particular UL144-UL145, RNA2.7 and UL22A (Fig. 7f). These correlations indicated that massive suppression of ISG expression was initiated after the IE phase of viral infection.