The enzyme that makes triglycerides affects the formation of the hepatitis C virus replication site

To study the influence of DGAT2 on the replication of HCV, we utilized the hepatoma cell line Lunet N hCD81 and generated stable cell lines overexpressing human DGAT2. By using the full-length Renilla luciferase reporter virus JcR2a, we assessed the effect of DGAT2 expression on the whole HCV replication cycle (Fig 1A). Surprisingly, the overexpression of DGAT2 strongly reduced reporter gene expression with a 13-fold reduction in the first and a 100-fold reduction in the second round of infection as compared to the control. Mutations within a putative neutral lipid binding site (L83A) or a highly conserved acidic sequence (HPH161-163AAA), both previously shown to impair the enzymatic activity of DGAT2 [35], partially or completely alleviated this effect (Fig 1A). Note that the DGAT2- or DGAT2 mutant-expressing cell lines had slightly impaired cell growth (S1 Fig), consistent with previous reports [36]. However, this mild effect was unlikely to account for the strong HCV replication inhibition. As expected, we could confirm DGAT2 mRNA upregulation by RT-qPCR, except for the triple mutant, which could not be detected due to the impaired binding of the antisense qPCR primer at the mutated site. Remarkably, DGAT2 mRNA overexpression was mild since it did not exceed endogenous DGAT2 RNA levels within primary human hepatocytes (Fig 1B). Note that the protein abundance of endogenous or ectopically expressed untagged DGAT2 is difficult to detect due to lack of useful commercially available antibodies [37].

Next, we wondered, whether the impact of the increased DGAT2 levels on HCV replication can be reversed by DGAT2 small molecule inhibitors (DGAT2i) and, secondly, if HCV replication benefits from blocking the endogenous DGAT2 activity. To address these questions, we applied the inhibitor to our cell lines and inoculated them with JcR2a (Fig 1C). Inhibition of endogenous DGAT2 in the control cell line did not significantly affect viral replication, indicating that the endogenous levels of DGAT2 did not restrict HCV replication. However, treatment of DGAT2-overexpressing cells with the DGAT2 inhibitor partially reverted the DGAT2 antiviral phenotype and increased viral replication up to 3-fold compared to the untreated control. Together with the observed phenotype of the DGAT2 mutants (Fig 1A), these results indicate that DGAT2 enzymatic activity is important for the protein antiviral effect.

We then wanted to pinpoint the step of the HCV replication cycle hindered by the excess of DGAT2. As the overexpression of DGAT2 inhibits already the first round of HCV infection (Fig 1A), we concluded that the antiviral activity of DGAT2 most likely targets a pre-assembly step of the virus life cycle. We therefore circumvented HCV entry and monitored the replication of transfected full-length JcR2a reporter virus in DGAT2-overexpressing cells (Fig 1D). DGAT2 expression delayed the onset of JcR2a replication and decreased the replication efficiency about 100-fold at 72 h post transfection (hpt) (Fig 1D). We could reproduce this antiviral effect with the corresponding JFH1-NS3-5B subgenomic replicon (SGR) (Fig 1E). Furthermore, to investigate the HCV genotype-specificity of the DGAT2 antiviral activity, we also tested NS3-5B SGRs of genotypes 1b (Con1) and 3a (DBN3a) (Fig 1F and 1G). While the replication kinetics of all SGRs differed, we found that increased DGAT2 expression impaired the replication of all tested constructs. The replication of the highly steatogenic genotype 3a (Fig 1G) was reduced to a lesser extent (~3 to 4-fold) as compared to JFH1 SGR (Fig 1E) but statistically significant. In all cases, mutation of the lipid binding site or of the conserved HPHG motif decreased or abolished the antiviral effect of DGAT2, respectively (Fig 1D–1G). In summary, DGAT2 impairs a post-entry and pre-assembly step of HCV replication in a mechanism that is conserved across all tested genotypes.

By utilizing a dual luciferase reporter system [38], we then examined the effect of DGAT2 on the IRES-mediated translation of HCV (Fig 1H). The reporter construct allowed us to assess the IRES-mediated translation of Renilla luciferase and cap-controlled translation of Firefly luciferase in the cell lines of interest. The expression of DGAT2 did not impair cap- or IRES-mediated translation of the dual luciferase reporter. We therefore concluded that DGAT2 antiviral activity is probably related to a deficiency in virus genome replication.

To further specify the timing of DGAT2 antiviral activity, we generated Lunet N hCD81 cell lines with inducible HA-tagged DGAT2 expression. We confirmed HA-DGAT2 protein expression (Fig 2A) and observed an increasing LD content upon Doxycycline treatment (S2 Fig), which was expected due to DGAT2’s role in the LD biogenesis [39]. After verifying the antiviral activity of the HA-tagged DGAT2 construct (S3 Fig), the system allowed us to study the antiviral effect of DGAT2 when induced at different times prior to and post infection (Fig 2B). Note that the used JcR2a virus has a rather low kinetics so that we do not expect reinfection to play a major role in this setting. As expected, inducing HA-DGAT2 expression prior to infection remarkably reduced the viral replication already at 24 hours post infection (hpi) as compared to the non-induced control. However, inducing DGAT2 expression 4 or 24 hpi also hampered HCV replication (starting from 32 or 48 hpi, respectively), indicating that DGAT2 expression decreases viral replication even after its onset.

To get a better understanding of the mechanism behind the DGAT2-mediated inhibition of HCV replication, we analyzed the formation of HCV replication complexes and replication organelles in DGAT2-overexpressing cells. As a marker for HCV replication complexes [40] we focused on NS5A. Using our inducible expression system, we found that NS5A puncta partially co-localized with HA-tagged DGAT2 in infected cells (Fig 2C). We also measured the formation of NS5A puncta in three-dimensional z-stacks of HCV-transfected cells (Fig 2D). In Lunet N hCD81 DGAT2-overexpressing cells, the NS5A puncta density was significantly reduced as compared to the control cells (Fig 2E). Matching our earlier results, the reduction was dependent on the catalytic activity of DGAT2, since both L83A and HPH161-163AAA mutants decreased the NS5A puncta density to a lesser extent than catalytically active DGAT2.

In this last setup however (Fig 2D and 2E), replication inhibition led to an overall decrease of the NS5A signal. This low amount of viral proteins could account for the decreased number of replication complexes, independent of the proteins capacity to form replication factories. To distinguish replication efficiency from the ability of HCV NS proteins to reshuffle membranes, we used a pTM-based expression construct encoding the HCV NS3 to NS5B polyprotein under the control of the T7 RNA polymerase [41]. This allowed us to study HCV membranous web formation in a replication-independent system. To test whether DGAT2 expression affected the formation of HCV replication organelle, we transfected Lunet T7 cells stably expressing the DGAT2 constructs with the pTM construct comprising a GFP-tagged version of NS5A, so that we could locate NS5A-positive cells by fluorescence prior to transmission electron microscopy [10].

We found membrane rearrangements in the cytoplasm of transfected Lunet T7 [empty] cells, including DMVs and multi membrane vesicles (MMVs), which are typical features of the HCV membranous web (Fig 3A). In contrast, the DMV number was reduced by DGAT2, but not by DGAT2_HPH161-163AAA expression (Fig 3A and 3B). There was no major shift in the DMV size distribution visible (Fig 3C). Instead, we observed increased size of LDs in DGAT2-overexpressing cells (Fig 3A and 3D) and therefore inquired whether accumulation of large LDs physically prevented DMV accumulation. Arguing against this hypothesis, control cells fed with oleic acid (OA) which is known to stimulate LD growth [42] had unchanged DMV numbers (Fig 3E and 3F) and size distribution (Fig 3G), although they also accumulated enlarged LDs (Fig 3H). Consistently, OA treatment only mildly inhibited HCV infection at high doses (S4 Fig). We therefore concluded that the dramatic impairment of HCV membranous web formation was DGAT2-specific and not merely driven by LD accumulation. Interestingly, as described earlier [30], we observed occasional ER-enwrapped LDs in close proximity to DMVs (S5A Fig). These enwrapped LDs were even more frequent in DGAT2-overexpressing cells (S5A and S5B Fig), which points towards increased ER-LD interorganellar contact sites in the DGAT2 expressing cells.

Since we related the inhibitory phenotype of DGAT2 overexpression to the formation of the HCV replication organelle, we were interested in the DGAT2-sensitivity of other RNA viruses relying on the formation of a membrane-derived replication compartment. Therefore, we tested ZIKV and Langat virus (LGTV, a close relative of TBEV), both belonging to the virus family Flaviviridae, as well as human common cold coronavirus (HCoV) 229E and hepatitis E virus (HEV) for their capacity to replicate in the stable DGAT2 expressing cell lines (S6 Fig). Both ZIKV and LGTV replications were significantly impaired by DGAT2 overexpression (S6A and S6B Fig). For ZIKV, the antiviral activity across the DGAT2 constructs showed a very similar trend compared to HCV replication. In contrast, DGAT2 did not significantly affect HCoV 229E or HEV infection (S6C and S6D Fig). Altogether, this indicates that DGAT2 regulates HCV replication but also more broadly the flaviviral replication cycle. Due to the stronger effects observed, we further unraveled DGAT2 antiviral effect in the HCV model.

Since DGAT enzymes are rate-limiting in the TAG synthesis [39,43], we explored LD accumulation in our DGAT2-overexpressing cell lines using flow cytometry and microscopy (Fig 4). In both cases, we utilized the Lunet N hCD81/mRuby2 cells as an internal reference population as described earlier ([28,29], Material and Methods part) and stained LDs with the BODIPY 493/503 neutral lipid dye. DGAT2 expression triggered a strong LD accumulation with over 60% increase in BODIPY signal as measured by flow cytometry, an effect comparable to a high dose oleic acid (OA) induction (Fig 4A and 4B). LD accumulation upon expression of the DGAT2 mutants correlated with their antiviral effect (Fig 1A): DGAT2_L83A moderately increased the LD content while DGAT2_HPH161-163A mutant did not show any effect (Fig 4B). Interestingly, DGAT1 and 2 have been proposed to give rise to two distinct populations of LDs, with DGAT1 triggering LD formation and DGAT2 promoting LD growth. Hence, in Drosophila and rat hepatoma cells, many small or fewer large LDs accumulate respectively upon DGAT1 and DGAT2 overexpression [44]. We therefore wondered whether the different roles of DGAT2 and DGAT1 in HCV replication could be explained by the characteristics of the induced LDs. We quantified LD numbers and sizes in the DGAT2 cell lines by automated image analysis and co-seeded red fluorescent Lunet N hCD81/mRuby2 cells as internal reference (Fig 4C–4F). Supporting our electron microscopy observations (Fig 3D), overexpression of DGAT2 induced a remarkable shift of the LD population towards large LDs (Fig 4C and 4D), which consequently increased the total cellular LD area (Fig 4E), consistent with the flow cytometry results (Fig 4B). This effect was dependent on the catalytic activity of DGAT2, as shown by the two DGAT2 mutants (Fig 4C–4E). On the opposite, LD numbers were unchanged by DGAT2 overexpression (Fig 4F), which is consistent with the reported role of DGAT2 in LD growth rather than LD formation [44].

Taken together, overexpression of DGAT2 increased the average LD size and overall amount. This correlated with a strong decrease in HCV replication, a striking observation considering that LDs and triglyceride synthesis are usually regarded as supporting HCV infection [45,46,26,27].

While endogenous DGAT2 is difficult to detect due to its low cellular abundance and lack of useful antibodies [37], overexpressed DGAT2 has been reported to localize at the ER and in close proximity to LDs and mitochondria [35,47]. We verified the localization of HA-tagged DGAT2 at these organelles in Lunet N hCD81 cells by counterstaining ER (Calnexin), mitochondria (CoxIV) and LDs (neutral lipids, ADRP) (Fig 5). While association of HA-tagged DGAT2 with the ER and enrichment at the nuclear envelope were clearly observed (Fig 5A), localization at mitochondria was more difficult to detect in our hands (Fig 5B). The localization of HA-tagged DGAT2 at LDs, leading to the characteristic ring structures, was most pronounced in cells which had been fed with OA, supporting previous findings (Fig 5C–5F) [47].

We then wondered whether the subcellular localization of DGAT2 plays a role in the antiviral activity. Although the tertiary structure of DGAT2 has not been solved until now, several studies identified protein domains responsible for the mouse DGAT2 ortholog association with different organelles [35,47,48]. We generated the corresponding HA-tagged human DGAT2 mutants (Fig 6A), validated their expression by Western blot (Fig 6B) and inspected their association with the ER and LDs (Fig 6C–6D). Note that we did not analyze their mitochondrial localization further, since it was not clear in our hands (Fig 5B), but still tested mutations reported to abrogate this association [47]. We also assessed the ability of DGAT2 mutants to drive LD accumulation (Fig 6E) and to inhibit HCV replication (Fig 6F). DGAT2 del66-115 mutant (ER mut) did not localize to the ER or nuclear envelope, as observed by microscopy (Fig 6C) and validated by subcellular fractionation (Fig 6G) and was inactive in terms of LD accumulation (Fig 6E) or HCV inhibition (Fig 6F), although the mouse homolog of this mutant was catalytically active in vitro [48]. Moreover, we identified two DGAT2 mutants (LD mut1 and mito mut1) that efficiently induced LD accumulation (Fig 6E), showed similar ER accumulation as compared to the wildtype (WT) (Fig 6C), but lacked association with LDs (Fig 6D) or mitochondria (as suggested in [47]). Expression of these mutants potently inhibited HCV replication (Fig 6F), which supports the hypothesis that the DGAT2-mediated LD accumulation is a prerequisite for the inhibition of HCV replication while LD or mitochondria association is not. The other DGAT2 mutants (LD mut2, mito mut2) did not or only partially (mito mut2) impair HCV replication (Figs 6F and S7). Based on these findings, we concluded that both the ability to trigger LD accumulation and the localization at the ER but not at the LD are crucial for the inhibitory effect of DGAT2 on HCV replication.

By esterifying DAG to TAG and connecting to numerous other lipid metabolism pathways [49], DGAT2 plays an important role in the host cell lipid metabolism. Since we could relate DGAT2 antiviral activity to the HCV DMV formation, we hypothesized that DGAT2 altered the lipid content of the host ER membrane in a way that it cannot easily be reshuffled during HCV infection. DAG is the substrate of DGAT2 and an important precursor for both triacylglycerides (TAGs) and phospholipids (PLs). Therefore, and although DAG has to our knowledge not been involved in HCV replication, we next investigated the effect of DGAT2 on DAG stores using a specific biosensor [50]. After verifying its functionality by comparison with a mutant version (S8 Fig) we tested the localization of the sensor in the HA-tagged DGAT2-overexpressing cells (Fig 7A and 7B). Strikingly, upon DGAT2 expression in Lunet N hCD81 cells, the DAG-sensor relocalized from the perinuclear region (Fig 7A and 7J–7K) to form speckles in the cytoplasm (Fig 7B and 7J–7K). Interestingly, some of these speckles localized around LDs (Fig 7B). Across this study, we identified HuH6 cells as a hepatoma cell line, in which DGAT2 overexpression does not hamper HCV replication, despite LD induction (Fig 7C–7G), suggesting slight differences in lipid metabolic pathways or rates between these cell systems. We therefore hypothesized that the localization of the DAG sensor upon DGAT2 overexpression would differ in HuH6 cells as compared to Lunet N hCD81 cells, if DAG relocalization was critical for the antiviral effect of DGAT2. However, we could clearly see the same effect of DGAT2 overexpression on the localization of the DAG sensor in the HuH6 as compared to the Lunet N hCD81 cells (Fig 7H–7K), suggesting that DAG relocalization was not the key determinant of DGAT2 antiviral phenotype.

To gain a broader overview of possible lipid changes responsible for DGAT2 antiviral phenotype, we next used the Lipidyzer platform to analyze lipid concentrations of 13 lipid classes including phospholipids, sphingolipids, glycerolipids, sterols and free fatty acids. We examined the lipidome of the cytoplasmic extracts of Lunet N hCD81 cells expressing DGAT2 or infected with HCV for 48 h (Fig 8A and 8B) and analyzed differences at the levels of the lipid classes (Fig 8C–8D) and species (Fig 8E–8I). Thereby, we detected 859 lipid species in 6 biological replicates per condition. Note that we excluded free fatty acid species for technical reasons and considered 667 lipid species for further analysis, which were measured in more than 75% of the samples. Unsupervised principal component analysis (PCA) overall confirmed the clustering of our replicates and the intermediate phenotypes obtained for the DGAT2 mutants. It also clearly segregated the OA treatment control from the other conditions (Fig 8B). At the lipid class level (Fig 8C and 8D), HCV infection led to a substantial increase in membrane lipids except for DAG. Accumulations of ceramide (CER), phosphatidylcholine (PC) and phosphatidylethanolamine (PE) classes were statistically significant. These observations nicely corroborate the lipidomic changes reported by Hofmann et al. [20] and Diamond et al. [51] in Huh-7.5 cells. As expected, DGAT2 expression and OA induction led to a drastic increase of the TAG neutral lipid class, the main lipid stored in LDs. Furthermore, similar to HCV infection, various membrane lipid classes were upregulated through DGAT2 overexpression, although not statistically significant at the lipid class level. These effects were attenuated for the DGAT2 mutants, indicating that they relied on DGAT2 catalytic activity. As an exception, DAGs were regulated in an opposite direction by HCV infection and DGAT2 overexpression.

At the lipid species level (Fig 8E–8I) and focusing on membrane lipids, we observed drastic increases of CER, PC and PE, but decreased DAG lipid species in the HCV-infected cells (Fig 8E). The membrane lipid species profile of DGAT2-overexpressing cells seemed overall less affected (Fig 8F). However, we found significant trends for specific PC and PE species and observed that especially lipids with polyunsaturated fatty acyl (PUFA) chains were upregulated, whereas the amounts of saturated and monounsaturated lipids were mostly reduced upon DGAT2 overexpression. These trends were attenuated in DGAT2_L83A expressing cells and blurred for the DGAT2_HPH161-163AAA mutant (Fig 8H and 8I). Importantly, OA induction had a completely different effect on the membrane lipid profile and mostly enhanced monounsaturated fatty acyl-phospholipids (MUFA-PL) whereas several PUFA-PLs were downregulated (Fig 8G).

Overall, HCV infection and DGAT2 overexpression significantly regulated 68 and 35 lipid species, respectively (Fig 9A). Among the 16 lipid species significantly regulated in both conditions, the majority (15) was significantly regulated in the same direction (Fig 9B). Given the abundance of PC and PE in cell membranes (58 and 26% of the membrane lipids in our Lunet N hCD81 cell line, Fig 8C) and their importance in membrane biogenesis, as well as the observed trends of saturated and MUFA- versus PUFA-lipid species (Fig 8E–8I), we then analyzed the differential regulation of these lipid classes on the fatty acid subspecies level, within the membrane lipids (Fig 9C and 9D). In line with the observations made by Hofmann et al. [20], we found that HCV infection strongly increased PLs with long chain PUFAs, including (C20:4), (C20:5), (C22:5) and (C22:6) fatty acyl lipids in both PC and PE species. Interestingly, DGAT2 overexpression also increased the above mentioned PUFA-PLs, especially eicosapentaenoyl (EPA, C20:5) fatty acyl harboring lipids. This effect was attenuated for the L83A mutant and nearly disappeared for the triple mutant. Additionally, and in contrast to HCV infection, DGAT2 overexpression upregulated (C18:3) fatty acyl -containing PEs, but downregulated (C18:1) fatty acyl-containing PCs. Most strikingly, the highly abundant PC [18:1/18:1] species was 2.39 times reduced in DGAT2-overexpressing cells compared to the control (Fig 9C). Of note, as expected, PC [18:1/18:1] was strongly upregulated in OA-treated cells, where levels of (C18:1) in general greatly increased due to the higher abundance of the oleyl fatty acid. The fatty acyl incorporation into PLs is dependent on the overall abundance of specific fatty acid species and on the substrate preferences of the involved lipid metabolizing enzymes and transporting proteins [52]. The changes observed suggest that fatty acyl substrate channeling differs between HCV-infected and DGAT2-overexpressing cells, as a result of the substrate specificity of DGAT2 [53,54] or indirectly via the regulation of other metabolic pathways.

In conclusion, we found a large overlap of the lipid profile changes between HCV infection and DGAT2 overexpression, apart from specific lipid and fatty acyl species, suggesting that depletion of some lipid species and competition for others may explain how excessive DGAT2 activity inhibits the formation of the HCV replication organelle. Altogether, our results evidence that lipid droplet biogenesis can affect the lipid composition of intracellular membranes and thereby their reshuffling into the HCV replication organelle. As detailed in the discussion, these findings open new perspectives to understand the effect of pathological LD accumulation on virus infections but also to comprehend the spatial coordination of LD biogenesis and replication organelle formation at the suborganellar level.

All tissue donors gave written informed consent for experimental use of clinical data and liver specimen prior to surgery. The protocol was approved by the ethics commission of Hanover Medical School (#252–2008 and #2148–2014).

All plasmids used in this study are listed in S1 Table. For this study, we ordered the human DGAT2 sequence as a gBlock (Integrated DNA Technologies, IDT) and cloned it between the AscI and SpeI restriction sites in the pWPI-Puro vector. We cloned the HA-tagged DGAT2 by insertion of a double HA tag (YPYDVPDYA, twice) preceded by a linker (GGGGSG) by PCR. Furthermore, we generated the point mutants DGAT2_L83A, DGAT2_HPH161-163AAA by fusion PCR. For the panel of further DGAT2 mutants, we split the DGAT2 sequence in three fragments by PCR amplification (N-terminal, middle part, C-terminal) and ordered gBlock (IDT) carrying the desired deletions within the respective fragment. The fragments were inserted into the pWPI_Puro vector by 3-insert-Gibson assembly (Gibson Assembly Master Mix, New England BioLabs (NEB) #E2611L) to generate pWPI_HAHA-L-DGAT2-del30-67_Puro, pWPI_HAHA-L-DGAT2-del66-115_Puro, pWPI_HAHA-L-DGAT2-mito4A_Puro, pWPI_HAHA-L-DGAT2-del327-350_Puro and pWPI_HAHA-L-DGAT2-insert-HA_Puro. We generated pLenti_CMV-TO_HAHA-DGAT2_Puro by restriction cloning into the pLenti_CMV-TO_Puro_DEST backbone. The DAG-sensor pWPI_mRuby3_PKCe_C1a_C1b_Puro was cloned as described in [50]. We ordered the sequence of the human protein kinase C epsilon (PKCe) (NM_005400.3↗) C1a-C1b (amino acids 170–294) cassette fused with mRuby3 as gBlock (IDT) and inserted it between the AscI and SpeI sites in the pWPI_Puro vector. We introduced the point mutation W264G [50,80] by fusion PCR. All cloned constructs were verified by multiple restriction analyses and by sequencing (Microsynth Seqlab). Primer sequences and detailed cloning procedures are available upon request.

All antibodies used in this study are listed in S2 Table. Cell culture reagents and chemicals are detailed in S3 Table, except enzymes and kits which are given in the text. We dissolved and stored DGAT2i (PF-06424439) as 10 mM stock in DMSO. For lipid droplet induction, we mixed oleic acid (OA) and bovine serum albumin as described before [28] with the final concentration of OA indicated in the respective figure. We dissolved Daclatasvir, Doxycycline (Dox) and Cycloheximide (CHX) in DMSO as 10 mM stock solutions before further dilution. We dissolved BODIPY 493/503 as 1 mg/mL stock in DMSO. We prepared DAPI as 5 mg/mL stock in water and LD540 as 2.5 mg/mL stock in ethanol.

In this study, we used Lunet N hCD81 [81], Lunet N hCD81 FLuc [28], Lunet N hCD81/mRuby2 [29], Huh-7.5 [82], Huh-7.5.1 [83], HuH6 [84], HEK 293T [85], A549 [86] and Vero E6 [87] cells and cultured them using the previously described conditions. Note that the Lunet N hCD81 cells are a human hepatoma cell line derived from Huh7 cells and are highly permissive for HCV RNA replication [88]. We generated the Lunet N hCD81 [empty], [DGAT2], [DGAT2_L83A], [DGAT2_HPH161-163AAA] and [HA-DGAT2] cell lines by lentiviral transduction of the according constructs and puromycin selection (2.5 μg/mL). We generated the Dox-inducible cell line Lunet N hCD81/TetR [HA-DGAT2] by lentiviral transduction of pWPI_TetR_BLR (and selection with 5 μg/mL blasticidin for three passages) followed by transduction of the pLenti_CMV-TO_HAHA-DGAT2_Puro expression vector and Puromycin selection (as above).

All cell lines were cultivated at 37°C with 5% CO₂ in Dulbecco’s modified Eagle’s medium (DMEM) supplemented with 2 mM L-glutamine, non-essential amino acids, 100 U/mL penicillin, 100 μg/mL streptomycin and 10% fetal bovine serum (FBS). In addition to this, we kept the cell lines under the relevant selection. We cultivated all Lunet N hCD81 cell lines in presence of blasticidin (5 μg/mL) to maintain CD81 expression. Additionally, Lunet N hCD81/mRuby2 and the newly generated Lunet N hCD81 DGAT2 cell lines were supplemented with puromycin (as above). The 8 PHH samples used in this study were the same as previously reported and therefore were isolated following the same procedure [29].

We used Huh-7.5 or Huh-7.5.1 cell lines for HCV Jc1 and JcR2a virus production and HEK 293T cells for lentivirus production following previously described protocols [28]. We used Vero E6 cells to amplify ZIKV (strain H/PF/2013, kindly provided by the Centre National de Référence des arbovirus IRBA at the Aix-Marseille University, France, and distributed via the European Virus Archive Global, EVAg Ref-SKU:001v-EVA1545) and LGTV (strain TP21, a kind gift from Gerhard Dobler) virus stocks. HCoV 229E RLuc was kindly provided by Volker Thiel and amplified on Huh-7.5 cells. Stocks of HEV Kernow-C1 p6 were produced as described before [89].

HCV in vitro transcripts (IVTs) of pFK_i389_JcR2a_dg_Jc1 (JcR2a) [17], pFK_JFH1/J6/XbaI/C-846_dg (Jc1) [90], dbn3acc-sgr-cpg-low-luc2-ns5ac (SGR-DBN3A, a kind gift from Mark Harris) [91], pFK_i389LucNS3-3´’_JFH_dg.gb (SGR-JFH1) [92] and pFKi_341_PiLuc_NS3-3´_Con1 ET (SGR-Con1) [93] were generated. In brief, we linearized the plasmids with MluI or XbaI (for SGR-DBN3A) or SpeI (SGR-Con1). Digested plasmids were extracted using the Qiaquick Spin mini prep kit (Qiagen #27106) and dissolved in RNAse-free water. In vitro transcription mixtures comprised 80 mM HEPES [pH7.5], 12 mM MgCl2, 2 mM spermidine, 40 mM dithiothreitol (DTT), each nucleotide triphosphate at a concentration of 3.125 mM, 1 U RNasin/μL (NEB #M0314) of reaction volume, 0.2 μg restricted plasmid DNA/μL, and 0.6 U T7 RNA polymerase/μL (NEB #M0251). We incubated the reactions for 2 h at 37°C and added additional 0.3 U T7 RNA polymerase/μL to the mixture following another 2 h incubation. We terminated the transcription by addition of 3.25 U of RNase free DNase (NEB #M0303) per μg of plasmid DNA and incubation for 30 min at 37°C. We extracted the RNAs using the NucleoSpin RNA Clean-up Kit (Macherey-Nagel #740948.250), eluted them in RNAse free water and stored them at—80°C after concentration determination with a spectrophotometer (Implen). pIRF1b [38] IVTs were generated as described above but with an additional capping step during the in vitro transcription using the Ribo m7G Cap Analog (Promega #P1711).

For Renilla (RLuc) and Firefly (FLuc) luciferase measurements we lysed the cells in Milli-Q water (400 μL per well for 6-well dishes, 150 μL per well for 12- or 24-well dishes, 40 or 50 μL per well for 96-well dishes) and froze the plates at—20°C or—80°C until luciferase readout. We performed the assays by following previously published protocols [94].

For HEV progeny particle production in stable Lunet N hCD81 cell lines we seeded 5x10⁴ cells per well in a 24-well plate, followed by infection with non-enveloped HEV Kernow-C1 p6 at a multiplicity of infection of 0.5. We removed the supernatant 24 hpi and added fresh culture medium. We trypsinized the cells 3 days post infection, neutralized with complete DMEM and centrifuged for 5 min at 500 g. After resuspension of the cell pellet in 100 μL cell culture media, we harvested intracellular progeny virus by lysing the cells via three freeze-thaw cycles. To remove cell debris, we centrifuged the lysate for 10 min at 10,000 g. For quantification of recovered HEV particles, we titrated the supernatant in duplicates on HepG2/C3A cells, which we seeded 24 h before titration with 10⁴ cells per well on 96-well plates. We fixed the cells 7 days post infection with 3% PFA and permeabilized with 0.5% TritonX-100 as described below. To count the focus-forming units per well, we performed immunofluorescence staining using an HEV ORF2-specific polyclonal rabbit hyperimmune serum (kindly provided by R. Ulrich, Friedrich Loeffler Institute, Germany) targeting the HEV capsid protein followed by staining with a secondary antibody (goat anti-rabbit IgG, AlexaFluor (AF) 488) and DAPI (0.5 μg/mL).

To assess the whole replication cycle of HCV, we seeded 5x10⁴ cells of the stable Lunet N hCD81 cell lines in 12-well plates and infected the cells on the next day with 350 μL HCV JcR2a virus stock. We changed the medium 4 hpi. We harvested the cell lysates 48 hpi for luciferase readout (producers) and transferred the supernatant onto Huh-7.5 target cells in triplicates in 24-well plates. We harvested the cell lysates of target cells at 72 hpi.

For the translation reporter assay, we seeded Lunet N hCD81 cell lines in 96-well plates (10⁴ cells per well). On the next day, we changed the medium with 20 μM CHX or DMSO control 1 h before transfection with IVTs obtained from the pIRF1b construct (a kind gift from Jean Dubuisson and Annie Cahour). We lysed the cells 8 hpt for FLuc and RLuc luciferase readout.

We seeded 2x10⁴ Lunet N hCD81/TetR [HA-DGAT2] and [empty] cells in 24-well plates and infected the cells with JcR2a virus on day 2. We changed the medium of the infected cells 4 hpi and harvested the cell lysates for luciferase readout at 24, 32, 40 and 48 hpi. We induced HA-DGAT2 expression in the Lunet N hCD81/TetR [HA-DGAT2] cells 24 hours before infection or 4 or 24 hpi by 10 μM Dox treatment.

Unless otherwise stated, the images were taken with a 60x Nikon CFI Apochromat TIRF objective (CFI Apochromat TIRF 60x Oil/ 1.49/ 0,13). We acquired the fluorescence microscopy images for LD and NS5A quantification with a Nikon Ti-E microscope equipped with a Yokogawa CSU-X1 spinning disc and an EMCCD DU-888 camera from Andor and an additional 2x magnification lens inside the spinning-disc unit. We acquired the NS5A and HA-DGAT2 localization images with a Nikon AX microscope equipped with a 60x oil objective and a DUX-VB4 DUVB 4Ch detector and using the Galvano scanning mode. All other images were taken with a Nikon Ti2 microscope equipped with an Ai plus laser scan confocal unit.

We prepared the depicted images in Fiji [96] with equal background subtraction and contrast enhancement parameters for all samples of a figure panel. We measured intensity profiles along the indicated lines in Fiji, normalized intensities to the maximal intensity of the fluorochrome along the given line and plotted them with GraphPad Prism.

NS5A puncta were quantified using a self-written Fiji macro. We first automatically segmented nuclei and NS5A puncta in all z-slices of the pictures using the same parameters throughout all conditions. We then filtered out duplicate NS5A puncta of consecutive slices of the z-stack to obtain the total number of NS5A puncta per field of view. We measured the perinuclear NS5A signal by dilating the area of the segmented nuclei, which allowed us to identify HCV-positive cells and to calculate their total nuclear area per field of view—a convenient surrogate for the total cellular area of the infected cells. With this, we could normalize the number of NS5A puncta for the nuclear area of HCV-positive cells for each field of view. Finally, we obtained the puncta density by multiplying this value with an arbitrary average nuclear area of 30,000 pixels.

For the LD quantification, we first automatically segmented mRuby2-positive cells with a Fiji macro to generate binary masks in order to distinguish mRuby2-positive and negative cells. Nuclei and LDs of both populations were then automatically segmented. Images with successful segmentation were further analyzed with CellProfiler [97] using the same parameters throughout all conditions.

For ZIKV and LGTV plaque assays, 2.5x10⁴ Vero E6 or A549 cells per well were seeded in 96-well plates. On the next day, we applied the infectious supernatants in serial dilution to the cells. Two hours after infection, we replaced the medium with overlay medium (DMEM with 1.5% CMC and 5% FBS for ZIKV, DMEM with 0.75% CMC and 1% FBS for LGTV) and incubated the cells for 96 h. We fixed the cells with 10% formaldehyde and visualized the plaques by crystal violet staining (1% crystal violet, 10% ethanol) and counted them manually.

For the DMV characterization by CLEM microscopy, we transfected Huh7-Lunet/T7 [empty], [DGAT2], or [DGAT2_HPH161-163AAA] cells with HCV NS3-5B/5A^EGFPexpression plasmid by lipofectamine transfection according to the manufacturer protocol. After 24 h, we identified transfected cells by GFP signal (wide field fluorescence microscope) and fixed the cells for CLEM analysis. We acquired TEM images x4 k magnification and utilized systematic random sampling and placed ~100 μm² rectangle areas on whole cell images to count and measure DMVs and LDs manually. We counted at least 10 GFP-positive cells in each sample (n ≥ 10).

To quantitatively assess the LD content by flow cytometry we adapted our previously published protocol [29] with the following changes. For Figs 4B, 6E and S2 we transduced the cells in 12-well dishes on day 2 with the respective DGAT2 expression constructs or the empty vector control and changed the medium 4 h post transduction. We triggered LD accumulation in the dedicated samples by OA addition on day 3 overnight, with the indicated concentration (Fig 4B). Cell harvest, addition of reference cells, fixation and staining was performed as before [29] and analysis was done with the BD Accuri C6 flow cytometer (Fig 4A and 4B) or the BD LSR Fortessa Cell Analyzer (Figs 6E and S2).

For Fig 7E and 7F we followed the same protocol except that we seeded the cells in 6 cm cell culture dishes (10⁵ Lunet N hCD81, 2x10⁵ HuH6) and upon cell harvest kept two third of the cells for RT-qPCR before spiking in the reference cells. Samples were analyzed with the Sony Spectral Analyzer.

In all cases, we set gates to exclude cell debris by using the FSC-A and SSC-A channels as well as doublet cells using the FSC-A and FSC-H channels. We obtained BODIPY 493/503 and mRuby2 fluorescence signals by using the FL1 and FL3 (BD Accuri) or B2 and YG3 (BD Fortessa) channels, or the Spectral Analyzer (Sony) respectively.

We performed color compensation or spectral unmixing following the manufacturer´s instructions. We distinguished test cells from the spiked-in control cells by their red fluorescence as shown in Fig 4A and compared the ratios of the BODIPY fluorescence between the test and the control cells as explained in the main text. Further analysis was performed with FlowJo (BD Biosciences).

To analyze the expression levels of DGAT2, RT-qPCR was performed. We extracted cellular RNA using the NucleoSpin RNA extraction kit (Macherey-Nagel #740955) according to the manufacturer’s instructions and assessed the quality of the extracted RNA by gel electrophoresis. RNA transcripts of GAPDH and DGAT2 were quantified by one-step primer-probe RT-qPCR using the LightCycler 480 RNA Master Hydrolysis Probes kit (Roche # 04991885001, Fig 1B) or the Luna Universal Probe One-Step RT-qPCR kit (NEB # E3006, Fig 7E) following the manufacturer’s instructions. Utilized primers and probes can be found in S4 and S5 Tables. Within one reaction, we combined primers and probes for GAPDH and DGAT2 and optimized the concentrations of all oligonucleotides within one reaction by titration. We performed four biological replicates of sample preparation and measured each sample in technical triplicates on a Lightcycler 480 instrument (Roche) or with the 7900HT Fast Real-Time PCR system (Applied Biosystems). We analyzed the data by the 2^{- ΔΔCt} method.

To analyze whether HA-DGAT2 and HA-DGAT2_del66-115 were present in the microsomal fractions, we seeded Lunet N hCD81 in 15 cm dishes to be confluent on day 4. We transduced the cells with lentiviruses to express empty, HA-DGAT2 or HA-DGAT2_del66-115 and changed the medium 6 hours later. When relevant, we treated the cells with 360 μM OA combined with BSA on day 3 overnight. On day 4, we harvested the cells by trypsinization and adjusted the cell number equally throughout the conditions. We washed the cells with PBS (500 g, 5 min) and resuspended them in sucrose-based medium (0.25 M sucrose, 10 mM Hepes, 1 cOmplete Mini Protease Inhibitor Cocktail tablet per 10 mL medium). We lysed the cells with a Dounce homogenizer on ice and controlled the cell rupture by Trypan Blue staining (same stroke number per cell type for all conditions). We removed the cell debris and nuclei from the lysate by centrifugation (2x 500 g, 5 min). For the microsome extraction, we centrifuged the remaining supernatant at 10,300 g for 10 min at 4°C to separate crude mitochondria. The procedure was repeated three times before transferring the remaining lysate into ultracentrifugation tubes filled with the sucrose-based medium. We centrifuged the samples at 100,000 g for 1 h at 4°C. Afterwards, we discarded the supernatants and resuspended the pellets containing the microsomal membranes in sucrose-based medium. We added Western blot sample buffer to both cytoplasmic and microsomal extracts and stored the samples at—20°C.

We seeded Lunet N hCD81 stable DGAT2 cell lines in 10 cm dishes to be confluent on day 4. When relevant, we infected the cells on day 2 with Jc1 and changed the medium 4 hpi or incubated the cells on day 3 overnight with 360 μM OA combined with BSA (as above). We harvested the cell pellets on day 4 (48 hpi) by trypsinization and counted them with a Neubauer chamber. We performed Dounce homogenization to lyse the cells as described above and separated the cell debris and nuclei from the homogenate by centrifugation (2x 500 g, 5 min). Cleared cell lysates were stored at—80°C until lipid extraction.

Lipidomic analysis was done with the Lipidyzer platform. This included a triple quadrupole mass spectrometer (QTRAP 5500; AB SCIEX, Darmstadt, Germany) equipped with a differential mobility spectrometer (DMS) interface operating with SelexION technology. In this case, an ultra-high pressure liquid chromatography system (Nexera X2, Shimadzu, Japan) was used as an autosampler. The Lipidyzer Platform was tuned using the SelexION Tuning Kit (AB SCIEX) and a system suitability test was performed using the System Suitability Kit (AB SCIEX) according to the manufacturer’s instructions. To the cell lysates, 100 μL of water was added and shortly vortexed. The lipid extraction process was then carried out as previously described [98]. The generated data was processed using Lipidomics workflow manager (AB SCIEX) and Shotgun Lipidomic Shortgun Assistant (SLA) software according to the SLA guidelines [99].

To monitor growth and viability of the DGAT2-overexpressing cell lines, each cell line was seeded with 10⁴ cells per well in 96-well dishes and an MTT assay was performed at 4, 24, 48, 72 and 96 h post seeding. MTT was purchased from Sigma Aldrich (#M5655), dissolved in PBS at 5 mg/mL and this stock was diluted 10 times in complete DMEM before usage. At each time point, the cell supernatant was discarded, and the cells incubated with 50 μL per well of MTT-containing complete medium, previously prewarmed at 37°C. After 1 h incubation at 37°C, the medium was discarded, MTT precipitates were dissolved by adding 50 μL per well of DMSO, and absorbance was read at 570 nm in a Biotek Synergy 2 plate reader.

We depicted mean ± standard error of the mean (SEM) values in bar plots and mean ± standard deviation (SD) in all other plots, if not indicated differently. For statistical analysis we used GraphPadPrism, R [100] and RStudio [101]. We performed statistical analysis on absolute or log-transformed values using repeated-measured ANOVA test followed by Dunnet’s multiple comparison test in case of significant changes. For normalized data, we performed two-tailed unpaired t-test with Welch’s correction. Significant changes are indicated by asterisks in the respective figures and shown as *P < 0.05; **P < 0.01; ***P < 0.005; ****P < 0.001. We tested the lipidomics results by two-tailed students t-test with unequal variances and adjusted for multiple testing using the Benjamini-Hochberg procedure. We determined statistically significant values if the adjusted p-value (q-value) < 0.1.