Abstract
Flavivirus infection is tightly connected to host lipid metabolism. Here, we performed shotgun lipidomics of cells infected with neurotropic Zika, West Nile, and tick-borne encephalitis virus, as well as dengue and yellow fever virus. Early in infection specific lipids accumulate, e.g., neutral lipids in Zika and some lysophospholipids in all infections. Ceramide levels increase following infection with viruses that cause a cytopathic effect. In addition, fatty acid desaturation as well as glycerophospholipid metabolism are significantly altered. Importantly, depletion of enzymes involved in phosphatidylserine metabolism as well as phosphatidylinositol biosynthesis reduce orthoflavivirus titers and cytopathic effects while inhibition of fatty acid monounsaturation only rescues from virus-induced cell death. Interestingly, interfering with ceramide synthesis has opposing effects on virus replication and cytotoxicity depending on the targeted enzyme. Thus, lipid remodeling by orthoflaviviruses includes distinct changes but also common patterns shared by several viruses that are needed for efficient infection and replication.
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Introduction
Orthoflaviviruses are emerging arthropod-borne pathogens belonging to the Orthoflavivirus genus within the family of Flaviviridae. Infections with orthoflaviviruses that are pathogenic to humans, including dengue virus (DENV), Zika virus (ZIKV), yellow fever virus (YFV), West Nile virus (WNV), Japanese (JEV), and tick-borne encephalitis virus (TBEV), substantially contribute to global morbidity and mortality rates1,2. Rising global temperature and geographical factors such as increasing human population densities and urbanization are widening the ranges of the transmitting arthropods, thus increasing the risk of epidemic outbreaks3. In addition, several orthoflaviviruses have just recently emerged as human pathogens such as Powassan virus in the USA4, or increased in its range like Omsk hemorrhagic fever virus that circulates beyond Russia5. While potent vaccines have been developed to prevent YFV, TBEV, JEV, and DENV infection, none are available for other pathogenic orthoflaviviruses such as WNV and ZIKV in humans, for WNV a vaccine for horses exists. As there are no specific antiviral treatments for any of these orthoflavivirus infections, only symptomatic treatment is available.
The orthoflavivirus genome is a single-stranded, positive-sense RNA of ~11,000 nucleotides in length. The viral genomic RNA consists of a single open-reading-frame (ORF) flanked by 5′ and 3′ untranslated regions (UTRs)6. The ORF encodes a single polyprotein that is processed by viral and cellular proteases into three structural proteins (capsid [C], precursor membrane [prM], and envelope [E]) and seven nonstructural proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5). While the structural proteins are important for viral attachment, entry, fusion, virus assembly, and virion secretion7, the nonstructural proteins contribute to viral RNA (vRNA) replication, virion assembly and release, and evasion of innate immunity8,9,10. Orthoflavivirus replication complexes reside in replication organelles (ROs) that are convoluted invaginations of the endoplasmic reticulum (ER) membrane11,12,13,14,15. Accordingly, orthoflaviviruses rely on cellular lipid metabolism and usurp several metabolic pathways to foster efficient RO formation and vRNA replication and in addition, as these viruses are enveloped, virion assembly. Interestingly, the formation of the ROs requires several different host lipid classes, including fatty acids (FAs), cholesterol, glycerophospholipids, and sphingolipids15,16,17.
Most studies investigated single orthoflaviviruses but some already noted differences in host cell metabolic requirements, e.g., the dependency of WNV and DENV replication on ceramides differs remarkably with attenuation or enhancement of viral replication, respectively18. But differences may also relate to the host cell or organism that is infected, as in mosquito cells inhibition of sphingolipid Δ4 desaturase, which synthesizes ceramide, reduces DENV multiplication19. In addition, DENV infection causes an increased abundance of monounsaturated FAs and inhibition of the enzyme catalyzing FA monodesaturation decreases DENV replication20. Further, DENV infection leads to an autophagy-dependent degradation of lipid droplets (LDs) called lipophagy to release FAs, which are then used to increase cellular ß-oxidation16. This orthoflavivirus-induced lipophagy depends on NS4A/B and host cell ancient ubiquitous protein 1 and is conserved among several orthoflaviviruses21. Triglycerides (TAGs) that are stored in LDs increase after infection with ZIKV, and inhibition of the triglyceride-synthesizing enzyme diacylglycerol-O-acyltransferase 1 reduces ZIKV infection in human placenta22 and human neural cells23. Overall, ZIKV infection significantly alters host lipid composition, and in addition to TAGs, particularly relies on a functional sphingolipid metabolic pathway24. With regard to orthoflavivirus-induced remodeling of cellular lipids, different lipidomic studies of mosquito cells have demonstrated changes in the total lipid profile that correlate with intracellular membrane alterations induced by ZIKV and DENV infection25,26.
To extend the knowledge about orthoflavivirus-induced changes of cellular lipid profiles, we performed lipidomic studies of orthoflaviviral-infected human hepatoma cells using high-resolution mass spectrometry. Here, we observe alterations in several lipid classes and lipid species with greater effects on the host cell lipid profile of orthoflaviviruses that are more pathogenic in humans. Many of the altered lipids have characteristic roles in influencing membrane architecture as well as in cellular signal transduction pathways. Specifically, orthoflavivirus infections cause an accumulation of ceramides and decrease levels of total TAGs and diacylglycerols (DAGs). In addition, we identify virus-induced changes in FA desaturation and in glycerophospholipid pathways. Using inhibitors and RNAi, we confirm the requirement of different lipid remodeling enzymes for DENV-, ZIKV-, WNV-, TBEV-, and YFV-infection, indicating that these pathways are essentially required for efficient orthoflavivirus replication.
Results
Cell model of orthoflavivirus infection for lipidomic analysis
To investigate if different members of the Orthoflavivirus genus induce distinct changes in the lipidome of infected cells, we performed a semi-targeted shotgun lipidomic analysis over the course of the infection. We decided to analyze orthoflavivirus family members that are most important to human health: the neurotropic ZIKV, WNV, and TBEV and the viscerotropic DENV as well as YFV-17D, the apathogenic vaccine strain of YFV (Fig. 1a). As host cells we chose Huh7 cells, as they are permissive for all viruses we were interested in. We tested different multiplicities of infection (MOI, titrated on Huh7 cells or BHK21 cells in case of TBEV) to attain 80% virus-positive cells without apparent cytopathic effects, as confirmed by immunofluorescence analysis 48 h post infection (hpi). In order to reach equal infection levels, we had to inoculate the cells with different MOIs: ZIKV, TBEV, and DENV replicate slightly slower in Huh7 cells, thus we needed higher MOIs of 1, 1, and 0.5, respectively, WNV displayed intermediate replication kinetics (MOI 0.1), and YFV-17D replicates fastest (MOI 0.005). These differences may be due to inherent differences as, for example, YFV-17D is adapted to replicate in cell culture, or may be specific for the cell type.
a Huh7 cells were seeded 1 day prior to infection with the different orthoflaviviruses (ZIKV MOI 1, WNV MOI 0.01, TBEV MOI 1, DENV MOI 0.5, and YFV-17D MOI 0.005). 12, 24, and 48 h post infection (hpi) samples were taken for protein and RNA extraction, and fixed for immunofluorescence analysis. b Virus genome equivalents (GE) per µg total cellular RNA normalized to 18S rRNA measured via RT-qPCR (mean ± SEM, n = 3 independent experiments). c Cells were stained with antibodies against orthoflavivirus E protein (magenta), and BODIPY493/503 (green) and Hoechst (blue) were used to visualize lipid droplets (LDs) and nuclei, respectively. Scale bar 10 µm. d Quantification of lipid droplets from more than 45 individual cells from three independent experiments (median ± 95% CI, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, unpaired two-tailed Mann–Whitney U test). e Samples were analyzed by immunoblotting with orthoflavivirus E protein and GAPDH antibodies (shown is one representative experiment of three independent experiments). Source data are provided as a Source Data file.
Next, we infected cells and harvested them at 12, 24, and 48 hpi in three independent experiments. For quality control of the samples, we first characterized replication kinetics by RT-qPCR of viral genomes, immunofluorescence analysis, and immunoblotting of cells infected with the different viruses using the predetermined MOIs. WNV, TBEV, and DENV showed similar infection kinetics by RT-qPCR reaching almost equal plateaus of ~108 genome copies per µg total cellular RNA (Fig. 1b). ZIKV only reached ~106 viral genomes but with a similar kinetic as the other three viruses while YFV-17D reached the highest genome numbers and replicated fastest (Fig. 1b). Similar results were obtained by immunofluorescence analysis of viral E protein in infected cells (Fig. 1c, shown is one representative experiment). Here, only few cells were positive for YFV-17D at 24 hpi compared to the other viruses, but all five viruses analyzed reached ~80% of E-positive cells at 48 hpi. This high infection rate reduces the contribution of uninfected neighboring cells to a minimum thus allowing a detailed analysis of lipid profiles, while at earlier timepoints changes due to signaling events may become detectable. As we are interested in lipid metabolism, we additionally stained LDs which are the neutral lipid storage organelles in cells. In infected E-positive cells we detected fewer LDs than in uninfected controls or neighboring E-negative cells (Fig. 1c). This effect was most striking 48 hpi and confirms the lipophagic degradation of LDs observed by others21. Indeed, quantification of LDs revealed that all orthoflaviviruses except for TBEV reduced the number and total amount of LDs in infected cells, while especially ZIKV and DENV infections also slightly increased the size of individual LDs (Fig. 1d and Fig. S1). Finally, we compared E protein levels by immunoblot analysis. Of note, the detection sensitivity of the anti-orthoflavivirus E protein is not equal for all viruses. Still, in immunoblot analysis we detected a relative increase of E levels over the course of infection that substantiated the previous results (Fig. 1e, shown is one representative experiment).
Distinct changes in the lipidome of cells infected with different orthoflaviviruses
To study the impact of viral infection on the cellular lipidome, we quantified 322 lipids of 16 classes (Supplementary Data 1). Of note, due to different biosafety requirements, BSL2 for ZIKV and YFV-17D, and BSL3 for TBEV, WNV, and DENV, we harvested two mock-infected controls in each independent experiment, but the cells were split just prior to infection from the same culture. A high correlation of all quantified lipids was observed between the BSL2 and BSL3 control samples (r > 0.98 for all time points and independent experiments, Fig. S2) indicating only negligible changes for these two laboratories. Nevertheless, principal component analysis (PCA) of the identified lipids revealed that 12 and 24 hpi infected samples overlapped with each other and the respective BSL2 and BSL3 controls, indicating that the majority of lipids identified stemmed from the uninfected cells within the culture (Fig. 2a). In contrast, the lipidomic samples taken at 48 hpi clearly clustered according to the virus they were infected with and the mock-infected controls clustered with a small distance from each other (Fig. 2a). ZIKV and YFV-17D-infected cells least deviated from their respective controls and showed largest overlap in the lipidome, while WNV and DENV clustered furthest from the controls. Therefore, an influence of the location of cell cultivation can be seen at 12 and 24 hpi but at 48 hpi the influence of viral infection is clearly observed in the PCA analysis.
a Huh7 cells infected with the different orthoflaviviruses were subjected to lipid and protein extraction and analyzed by direct infusion tandem mass spectrometry. Principal component analysis (PCA) of the lipidomics dataset. Relative lipid species abundance (Supplementary Data 1, sheet mol%) was used for the analysis. Single dots represent the different independent experiments. b Hierarchical clustering of lipid species (mol%) and samples of the 48 hpi dataset. Lipid species concentrations were log2-transformed and centered to the mean. Only lipid species that were detected in 90% of the samples (277 lipids) were used for clustering. Hierarchical clustering was calculated for individual samples as well as for lipid species using Euclidean distance metric and complete linkage clustering method.
We then performed hierarchical clustering of the lipid species identified 48 hpi and displayed them as heatmaps to identify lipid species that might distinguish the different orthoflaviviruses and infected cells from controls. As already observed in the PCA analysis, DENV-, WNV-, and TBEV-infected cells clustered according to the virus they were infected with, while ZIKV- and YFV-17D-infected as well as BSL2 and BSL3 controls clustered together (Fig. 2b). Certain molecular species of cholesterol ester (CE) showed a similar pattern and were elevated in DENV, WNV, and TBEV compared to ZIKV, YFV-17D, and the mock-infected controls, clearly setting them apart (Fig. 2b). DENV and WNV infection additionally led to increased levels of ceramides (Cer). Interestingly, DENV infection led to unique elevation of some TAG and DAG species as well as hexosyl-ceramide (HexCer) species containing monounsaturated FAs and a decrease in phosphatidylcholine (PC) species. TBEV infection caused a decrease in certain sphingomyelin (SM) and lyso-phospholipid (PL) species compared to all other samples (Fig. 2b).
Ceramides and some hexosyl-ceramides species accumulate while most other lipids decrease at late time points after orthoflavivirus infection
We next analyzed the lipid class and species content following infection with the different orthoflaviviruses relative to the combined controls to minimize variation among control samples (Fig. 3a, b). One striking phenotype we observed, and that has been reported by others for ZIKV infection24, is the increased abundance of Cer species after 48 hpi, most pronounced for WNV, DENV, and YFV-17D infection, less for ZIKV, and almost absent in TBEV infection (Fig. 3b). Interestingly, a simultaneous decrease in abundance of SM species at 48 hpi was also observable for all orthoflaviviruses including TBEV, but absent in ZKV infection (Fig. 3b). This finding might indicate an increased SMase activity during the viral infection, specifically at later time points. As all orthoflaviviruses analyzed here except for TBEV are cytopathic in Huh7 cells, the increased levels of Cer species likely reflect activated cell death pathways and do not correlate with the ability of the virus to replicate as TBEV replication levels in Huh7 cells are high (Fig. 1). At 48 hpi we observed a virus-specific phenotype for HexCer species for all investigated viruses. For DENV we recognized an increased abundance for a number of species like HexCer 18:2/16:0;0, which was not observed for the other viral infections, and for WNV we observed reduced levels of HexCer 18:1/24:1;0 (Fig. 3b).
a Bar graphs depict the lipid class amount (pmol) per µg protein (mean ± SD, n = 3, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001, FDR-adjusted p value, unpaired two-tailed Welch’s t-test). b Shown is the lipid amount (pmol) per µg protein of all species in lipid class as mean log2 fold change between infected cells and mock controls at 12, 24, and 48 hpi (n = 3 independent experiments). FDR-adjusted p values (unpaired two-tailed Welch’s t-test) are indicated by the size of the points. Lipid species are ordered according to molecular mass from left to right. hpi hours post infection, Chol cholesterol, PC phosphatidylcholine, LPC lyso-PC, PE phosphatidylethanolamines, LPE lyso-PE, PI phosphatidylinositol, LPI lyso-PI, PS phosphatidylserine, PG phosphatidylglycerol, PA phosphatidic acid, SM sphingomyelins, Cer ceramide, HexCer hexosyl-ceramide, DAG diglycerides, TAG triglycerides, CE cholesterol ester. Source data are provided as Supplementary Data S1, sheet pmol_ug.
ZIKV infection induces an early increase in neutral lipids while triglycerides but not cholesterol ester decrease during the infection in all orthoflaviviruses
Early in orthoflavivirus infection neutral lipids tend to accumulate. At 12 hpi, ZIKV induced a significant increase in total TAG and CE content affecting nearly all lipid species (Fig. 3a, b). Later in infection, especially at 48 hpi, TAG levels strongly decreased in WNV-, TBEV-, and DENV-, and to a lesser extent in ZIKV- and YFV-17D-infected cells (Fig. 3a), which correlates to reduced LD content observed by microscopy (Fig. 1c, d). This decrease was observed for nearly all TAG species (Fig. 3b). Concomitant with the decreased levels of TAGs late in infection, DAG species and total levels were similarly affected (Fig. 3a, b), as for example DAG 14:0_18:1, DAG 14:1_16:0, and DAG 14:1_16:1, that were significantly decreased in DENV, TBEV, and WNV at 48 hpi.
In contrast, levels of CE, the other main component of LDs, remained rather stable during infection with the exception for DENV where at 24 and 48 hpi CE 18:1, CE 20:1, CE 20:3, and CE 22:5 were significantly increased (Fig. 3b).
Levels of lysophospholipids are more abundant at early time points post infection
The detailed analysis of membrane lipids revealed that lysophosphatidylcholine (LPC) and lysophosphatidylethanolamine (LPE) are increased in abundance at 12 hpi for ZIKV, WNV, and YFV-17D (Fig. 3b). Individual species like LPE 18:2, LPC 16:1, and LPC 20:4 for ZIKV, LPC 15:0, 16:0, 18:0, and 20:3 for WNV, as well as LPE 16:1, LPE 18:2, LPE 20:4, LPC 16:1, and LPC 20:4 for YFV-17D (Fig. 3b), which were elevated at 12 hpi showed no further alteration later in infection. DENV exclusively showed increased amounts for LPC 18:0 at 48 hpi.
Glycerophospholipid remodeling is a common phenotype in orthoflavivirus infection
Overall, a large portion of the glycerophospholipidome is affected by orthoflavivirus infection. Specifically, WNV, TBEV, and DENV infection led to decreased levels of PC, PE, and PS at 48 hpi (Fig. 3b). While ZIKV induced changes on PE and PC were negligible it was the only case with a slight increase in PS 36:4 at 48 hpi. For all other viral infections, we observed decreased amounts for some PS species at 48 hpi like PS 32:1 and PS 34:1 (Fig. 3b). Of note, the modulation of the membrane phospholipid composition affected cholesterol only for WNV and TBEV infection at 48 hpi (Fig. 3a, b).
To identify lipid metabolic pathways that are dysregulated by infection we next performed lipid ontology analysis utilizing lipid ontology (LION) enrichment analysis web application (LION/web)27. At 48 hpi clear patterns of dysregulated ontology terms were identified (Fig. S3). The top downregulated terms related to the storage of TAG in LDs while sterol and sterol ester terms were upregulated. In contrast, membrane lipids, especially endoplasmic membrane lipid terms like PC and overall glycerophospholipids, were increased for all viruses tested, while DAG terms were significantly less (Fig. S3). This corresponds to the membrane requirement for the formation of ROs in orthoflavivirus-infected cells. In addition, and as already clearly visible in the lipid species quantification (Fig. 3), Cer lipid annotations were enriched (Fig. S3).
As glycerophospholipid abundances and corresponding ontology terms were affected by orthoflavivirus infection (Fig. 3 and Fig. S3), we next analyzed glycerophospholipid remodeling using BioPAN28 that enables the identification of the enzyme activities that may be involved. The BioPAN analysis is based on the conversion of individual lipid species and Z scores of reactions between lipid classes are then calculated. Arrow thickness represents the reaction activity of the individual class conversions while the color of the lipid class circles indicates log2 fold change of lipid class abundance (additionally displayed in a heatmap, Fig. S4). BioPan analysis revealed an early deacylation of diacylglycerophospholipids to form the lyso species which later in infection reverted (Fig. 4a). Accordingly, phospholipase A2 (PLA2) proteins were predicted to have increased activity early in infection (Fig. 4b, upper triangles), mostly without concomitant changes in expression level (Fig. 4b, lower triangles). Of note, all enzymes predicted to catalyze the same enzymatic reaction are listed. An additional characteristic suggested by the BioPAN analysis was the flow of lipids from DAG to phosphatidylethanolamine (PE) and PC (Fig. 4a), which was predicted to be the result of increased activity of choline phosphotransferase 1 (CHPT1) and choline/ethanolamine phosphotransferase 1 (CEPT1) (Fig. 4b). Phosphatidylinositol (PI) levels were salvaged from phosphatidic acid (PA) via CDP-diacylglycerol synthase (CDS)1 and CDS2 as well as CDP-diacylglycerol inositol 3-phosphatidyltransferase (CDIPT) (Fig. 4b). Other reactions were more distinct between the individual orthoflaviviruses. For example, ZIKV progressively displayed increased phosphatidylserine (PS) levels through the conversion of PE to PS by phosphatidylserine synthase 2 (PTDSS2), PC/PE to PS by PTDSS1, and from PA to PS through CDS1 and PTDSS1 (Fig. 4a, b). In contrast WNV, DENV, and YFV-17D caused increased decarboxylation of PS to PE likely via phosphatidylserine decarboxylase (PISD) (Fig. 4a, b). Interestingly, the enzymes that are predicted to have altered activities in orthoflavivirus-infected cells are not differently expressed in transcriptome analysis that was performed on samples from the same experiments as the lipidomics analysis (Fig. 4b, compare triangles). Only PLA2G4C was expressed higher in orthoflavivirus-infected cells at 48 hpi when lysolipids were not elevated any more but single lipid species conversion was still detected.
a Analysis of the lipidomics dataset using BioPan pathway analysis. Lipid species abundance (Supplementary Data 1, sheet pmol_ug) was used for the analysis. Predicted reaction activities between lipid classes are indicated by arrows (red indicates increased and blue decreased reaction activities). Color of lipid classes indicate log2 fold change in abundance per µg protein of infected versus uninfected cells (n = 3 independent experiments). b Upper left triangle: BioPan prediction of Z scores of active (red) and suppressed (blue) enzyme activities using the standard settings (Z > 1.645 at p < 0.05)28,93. Lower right triangle: log2 fold change of expression level determined by transcriptome analysis of the same samples. Source data are provided as a Source Data file.
Fatty acid profile indicates opposing utilization of monounsaturated vs. saturated FA in glycerophospholipids and increased levels of arachidonic acid (C20:4, AA)-containing PE and PS species following flavivirus infection
To analyze if the FA composition of membrane and storage lipids species changes following infection, we determined the FA profile of PC, PE, PS, and TAG from the associated tandem mass spectrometric experiments (Supplementary Data 2). Depicted is the difference in relative amounts of FAs within the lipids class (i.e., ∆ lipid abundance (mol% of infected cells − mol% of mock control, normalized to [−1, 1] in each lipid class), Fig. 5). The most striking effect of infection we observed was changes in the content of monounsaturated vs. saturated FA in the analyzed lipid classes. Distinct modulation of FA 16:1, FA 16:0, FA 18:1, and FA 18:0 was observed for PE with strongest changes in YFV-17D-, TBEV-, and DENV-infected cells, while the response in ZIKV-infected cells was much less pronounced. The increased portion of FA 16:1 and FA 18:1 at 48 hpi may indicate increased activity of stearoyl-CoA desaturases (SCDs) or de novo synthesis of PE 34:1 for membranes required for virus replication, while the opposing effect was observed in PC, PS, and TAGs. The second phenotype was the increased utilization of arachidonic acid (FA 20:4) in PE and PS species. This was more pronounced at later time points after infection and might reflect altered activity of one or more phospholipase A2 (cPLA2) enzymes (Fig. 5).
We determined the relative abundance (mol%) of FAs in PC, PE, PI, PS, and TAG and calculated the difference between infected and uninfected control cells for each lipid class (Δ relative abundance: mol% (infected) − mol% (mock), normalized to [−1, 1]). Heatmaps illustrate the Δ relative abundances of FAs in PC, PE, PI, PS, and TAG. Shown is the mean of three independent experiments. Red and blue depict increases and decreases, respectively, and gray indicates NA. Source data are provided as Supplementary Data 2.
For follow-up studies to investigate potential function in viral replication, we focused on enzymes that were predicted to have increased activity (Fig. 4b), Cer metabolism that was identified through the quantification of lipid classes and species (Figs. 2 and 3), and the changes in the FA profile (Fig. 5). For those enzymes that are targetable using inhibitors, we next performed infection studies. For all other enzymes with altered activities, we used gene knockdown approaches.
Early inhibition of sphingolipid biosynthesis exacerbates the cytopathic effect of orthoflaviviruses
A common phenotype in orthoflavivirus infection with the exception of TBEV is the increase in Cer during the course of infection. This is in line with studies of ZIKV infection where an essential role of Cer biosynthesis for ZIKV replication was delineated24. To determine if replication of other orthoflaviviruses is affected by inhibition of sphingolipid biosynthesis, we made use of the small-molecule inhibitors fumonisin B1 and myriocin to block the activity of ceramide synthase (CerS) and serine palmitoyltransferase (SPT1), respectively (Fig. 6a). We treated cells 48 h prior infection and added inhibitor again to the inoculum during infection (Fig. 6b). We first verified that the inhibitors had no effect on cell viability in concentrations that we used (Fig. 6c). None of the inhibitors affected the viability of Huh7 cells. In immunoblot analysis of infected inhibitor-treated cells, SPTi had minor effects on orthoflavivirus E protein levels (Fig. 6d), but reduced DENV titers (Fig. 6e). Interestingly, for all orthoflaviviruses that cause a cytopathic effect (CPE) in Huh7 cells, SPTi-treated cells displayed less CPE than DMSO-treated control-infected cells with the most significant decrease for DENV (Fig. 6f and Fig. S5). In contrast, CerSi treatment that blocks Cer synthesis both in the de novo and salvage pathway had also little impact on E protein level (Fig. 6d), but significantly enhanced ZIKV and YFV-17D titers (Fig. 6e), and increased cell death in ZIKV, WNV, and YFV-17D infection (Fig. 6f and Fig. S5). These findings imply an opposing effect of de novo Cer synthesis and its salvage pathway on virus-induced cell death pathways and an antiviral function of Cer in ZIKV and YFV infections.
a Scheme of the target enzymes and respective inhibitors. b Huh7 cells were treated with the inhibitors 48 h prior to infection with the different orthoflaviviruses (ZIKV MOI 0.1, WNV MOI 0.001, TBEV MOI 0.05, DENV MOI 0.05, and YFV-17D MOI 0.005). After infection, the respective inhibitors were added again, followed by analysis of viral protein expression level by immunoblot, determination of viral titers (TCID50), or analysis of cytopathic effects (CPE). c Cell viability was analyzed 72 h post treatment with different inhibitors. Treatment with 10% DMSO served as dead control (mean ± SEM, n = 3 independent experiments). d Intracellular levels of orthoflavivirus E protein were assessed by immunoblotting at 2 dpi. Shown is one representative blot (n = 4 (ZIKV, YFV-17D, WNV) or n = 5 (TBEV, DENV) independent experiments). e Virus titers in inhibitor-treated infected cells were determined by TCID50 titration at 2 dpi (mean ± SEM, n = 5 (DENV, TBEV, YFV-17D, ZIKV) or n = 4 (WNV) independent experiments, except for SPTi (all viruses), DENV (cPLA2i) and TBEV (SPTi): one experiment excluded due to contamination, *p ≤ 0.05, **p ≤ 0.01, unpaired two-tailed Mann–Whitney U test). f Cells were fixed at 3 dpi, surviving cells stained with crystal violet, and CPE was quantified using ImageJ. Box-and-whisker plot indicates CPE as log2 fold change infected over mock, normalized to DMSO control (center line: median, box limits: upper and lower quartiles, whiskers: 1.5 × interquartile range, points: outliers, n = 4 (ZIKV, DENV, WNV) or n = 5 (YFV-17D) independent experiments, *p ≤ 0.05, **p ≤ 0.01, unpaired two-tailed one sample Student’s t-test). dpi days post infection. Source data are provided as a Source Data file.
SCD activity is required for efficient flavivirus infection
In our analysis of lipid species (Fig. 2) and of the FA profile of glycerophospholipids (Fig. 5), we detected features of enhanced SCD activity. Earlier reports showed that SCD activity is required for DENV, ZIKV, and JEV RNA replication29 and DENV virion production20 as well as HCV replication30. In line we confirmed the antiviral activity of SCDi on orthoflaviviruses (Fig. 6d–e and Fig. S5). Viral titers were slightly reduced for WNV and TBEV, and CPE reduced in ZIKV, WNV, DENV, and YFV-17D.
Phospholipase A2 activity is dispensable for orthoflavivirus infection
In our analysis of membrane lipid remodeling, increased activities of PLA2 enzymes and decreased activities of PLD1/2 were predicted. As several PLA2 isoforms are expressed in Huh7 cells, we addressed if formation of lyso-PL blocks orthoflavivirus infection by using an inhibitor targeting cPLA2 enzymes, and investigated if pre-treatment with PLDi can boost infection. However, PLDi as well as cPLA2 inhibitor treatment had no effect on orthoflavivirus infection, replication, or virion production (Fig. 6d–e and Fig. S5).
Impact of impaired glycerophospholipid remodeling on orthoflavivirus replication
For other enzymes that were identified in the BioPAN analysis to have altered activity in orthoflavivirus infection (Fig. 4), no specific inhibitors are available. Therefore, we designed small hairpin (sh)RNAs to downregulate target mRNAs and proteins (Fig. 7a). We isolated total cellular RNA from shRNA-transduced cells 5 days post transduction (dpt) to quantitate the knockdown and performed viability assays (Fig. 7b). All shRNAs reduced mRNA expression levels of the target enzymes more than 50% compared to non-targeting shRNA (shNT) control cells (Fig. 7c) and transduced cells displayed viability within the range of the controls (Fig. 7d). We then analyzed the impact of knocking down enzymes involved in glycerophospholipid remodeling on viral protein expression in infected cells but did not observe strong differences on E protein levels between knockdown and control cells (Fig. 7e).
a Scheme of the synthesis of glycerolipids and glycerophospholipids. Target enzymes are indicated in blue. b Huh7 cells were transduced with lentiviruses carrying shRNAs targeting the different enzymes or a non-targeting (NT) shRNA followed by an infection with different orthoflaviviruses 4 dpt (ZIKV MOI 0.1, WNV MOI 0.001, TBEV MOI 0.05, DENV MOI 0.05, and YFV-17D MOI 0.005). Cells were used for validation of the lentiviral constructs and for analysis of viral protein expression level by immunoblot, determination of viral titers (TCID50), or analysis of cytopathic effects (CPE). c shRNA-knockdown efficiency of the targets was determined by RT-qPCR 4 dpt. Shown are mRNA expression levels of the corresponding enzymes relative to shNT and normalized to 18S rRNA (mean ± SEM, n = 3 independent experiments). d Cell viability was determined 5 dpt. Treatment with 10% DMSO served as non-viable control (mean ± SEM, n = 3 independent experiments). e Intracellular levels of viral E protein were assessed by immunoblotting at 2 dpi. Shown is one representative immunoblot (n = 3 (TBEV) or n = 4 (ZIKV, WNV, DENV, YFV-17D) independent experiments). f Virus titers in shRNA-transduced infected cells were determined by TCID50 titration at 2 dpi (mean ± SEM, n = 3 (ZIKV, TBEV, YFV-17D, WNV) or n = 4 (DENV) independent experiments, *p ≤ 0.05, unpaired two-tailed Mann–Whitney U test). g Cells were fixed at 3 dpi and cells were stained with crystal violet staining. CPE was quantified using ImageJ. Box-and-whisker plot indicates CPE as log2 fold change of infected over mock control, normalized to shNT (center line: median, box limits: upper and lower quartiles, whiskers: 1.5 × interquartile range, points: outliers, n = 2 (DENV), n = 4 (WNV, YFV-17D), or n = 6 (ZIKV) independent experiments, *p ≤ 0.05, unpaired two-tailed one sample Student’s t-test). dpt days post transduction, dpi days post infection. Source data are provided as a Source Data file.
Next, transduced Huh7 cells were infected with orthoflaviviral stocks at 4 dpt. 48 hpi, we analyzed viral titers by TCID50 titration on BHK21 cells. Overall, titers of ZIKV and YFV-17D were less affected in the different knockdown cells than WNV, TBEV, and DENV titers (Fig. 7f). Despite the variability between independent experiments, we identified proviral enzymes important for the replication of several orthoflaviviruses. For instance, knockdown of PTDSS2, but not PTDSS1, reduced WNV, DENV, and to a lesser extent TBEV and YFV-17D virus titers (Fig. 7f). While PTDSS1 catalyzes the conversion of PC and PE to PS in the ER, PTDSS2 is specific for PE and has a high affinity for docosahexaenoic acid (DHA) and thus creates DHA-containing PS. Likewise, the CPE of orthoflavivirus infection was reduced in cells lacking PTDSS2 (Fig. 7g), even though the knockdown itself caused some growth defect (Fig. S6). Depletion of PISD that decarboxylates PS at the inner mitochondrial membrane to produce PE led to reduced titers of WNV, TBEV, and DENV, but only slightly rescued cells from CPE induced by the infection (Fig. 7e, g). Finally, de novo synthesis of PI from CDP-DAG by CDIPT is required for WNV, TBEV, and, to a lower extent, for ZIKV and DENV infection, as both virus titers and virus-induced CPE in CDIPT-knockdown cells were reduced (Fig. 7e, g). CDS1 and 2 that catalyze the upstream reaction from PA to CDP-DAG also negatively affected viral replication and CPE, with the broadly acting CDS1 having a slightly stronger effect on CPE. Increased PA to PI reaction activities were found for all orthoflaviviruses at some point after infection (Fig. 4a). Regarding unique dependencies, DENV is the only analyzed orthoflavivirus that requires PLD2, but not PLD1 expression. PLD1 is active in the ER, Golgi, and endosomal membranes while PLD2 localizes to the plasma membrane. The dependency fits to the uniquely increased PA levels 24 and 48 hpi in DENV-infected cells (Fig. 4 and Fig. S4). The CEPT/CHPT-dependent synthesis of PE and PC as well as the methylation of PE to PC by PEMT are not required for efficient orthoflavivirus infection.
Disruption of PS and PI metabolism does not impact virus entry, viral RNA replication, or translation, but impairs the formation of infectious particles
In order to decipher which step of the viral replication cycle is affected by altered glycerophospholipid metabolism, we first investigated viral entry. We focused on six of our initial targets that showed the most prominent effect on viral infectivity and altered CPE, namely PTDSS1 and 2, PISD, PLD1 and 2 as well as CDIPT. We infected Huh7 cells expressing the different shRNAs with a high MOI of the different orthoflaviviruses and determined viral genome equivalents (GE) via RT-qPCR at 4 hpi. Interestingly, in contrast to a strong effect on viral titers, viral entry was unaffected in knockdown cells (Fig. 8a). Next, we analyzed vRNA replication and protein translation by quantitating intracellular vRNA copy numbers by RT-qPCR and intracellular viral protein levels by immunoblot analysis. We only observed minor changes in intracellular vRNA levels for the knockdown of PLD2 in WNV infection and slightly decreased viral protein levels for the knockdown of PTDSS2 in DENV infection, but overall, depletion of these lipid remodeling enzymes had no effect on vRNA replication and translation (Fig. 8b). To test the hypothesis of altered virus assembly or release, we investigated vRNA as well as viral E protein in the supernatant of infected knockdown cells. Correlating to minor effects on viral titers in YFV-17D and ZIKV infection, we did not observe major changes in vRNA and E protein levels in the supernatant for these viruses (Fig. 8c). In comparison, we detected significantly lower viral E protein in WNV-infected knockdown cells for shPTDSS1 and shPTDSS2 as well as shPLD2 and shCDIPT, while the extracellular viral copy numbers were only slightly altered. Even though the variability of vRNA in TBEV-infected knockdown cells is relatively high, E protein levels of shPTDSS2 and shPLD2 cells were drastically reduced, leading to the conclusion that defects in assembly or release might be the cause for altered TBEV infectivity in the culture supernatants.
a shRNA-transduced Huh7 cells were infected at 4 dpt with high MOIs (ZIKV MOI 2, WNV MOI 5, DENV MOI 2, TBEV MOI 10, and YFV-17D MOI 5). Virus entry was determined by measuring viral genome equivalents (GE) 4 h post infection using RT-qPCR (mean ± SEM, technical duplicates from 2 to 3 independent experiments, non-significant in unpaired two-tailed Welch’s t-test). b, c Transduced Huh7 cells were infected with low MOIs 4 dpt (ZIKV MOI 0.1, WNV MOI 0.001, TBEV MOI 0.05, DENV MOI 0.05, and YFV-17D MOI 0.005) and analyses were performed at 2 dpi. b Intracellular viral RNA (vRNA) was quantified using RT-qPCR (mean ± SEM, n = 4 (DENV), or n = 5 (ZIKV, TBEV, WNV, YFV) independent experiments, non-significant in unpaired two-tailed Welch’s t-test) and the viral envelope/E protein level was determined by immunoblot analysis. Box-and-whisker plot indicates E protein expression as log2 fold change over shNT (center line: median, box limits: upper and lower quartiles, whiskers: 1.5 × interquartile range, points: outliers, n = 3 (TBEV, YFV-17D) or n = 4 (ZIKV, WNV, DENV) independent experiments, non-significant in unpaired two-tailed one sample Student’s t-test). c Extracellular vRNA was quantified by RT-qPCR (mean ± SEM, n = 4 (ZIKV, YFV-17D) or n = 5 (TBEV, WNV, DENV) independent experiments, non-significant in unpaired two-tailed Welch’s t-test) and E protein levels in the supernatant by immunoblot analysis. Box-and-whisker plot indicates E protein levels as log2 fold change over shNT (center line: median, box limits: upper and lower quartiles, whiskers: 1.5 × interquartile range, points: outliers, n = 2 (YFV-17D) or n = 5 (ZIKV, WNV, TBEV) independent experiments, *p ≤ 0.05, **p ≤ 0.01, ***p ≤ 0.001 unpaired two-tailed one sample Student’s t-test). dpt days post transduction, dpi days post infection. Source data are provided as a Source Data file.
Although DENV showed a great loss of infectivity due to the knockdown of proteins involved in glycerophospholipid remodeling, we did not detect changes in viral copy numbers in the supernatant. Due to the size of DENV E protein and low levels of infectious virus in the supernatant, we were unable to quantify viral protein E levels.
Impaired glycerophospholipid remodeling reduces the replication of neurotropic orthoflaviviruses in microglia cells
Since hepatoma cells such as Huh7 are not the ideal model for neurotropic orthoflaviviruses, we aimed to confirm our results in a more relevant model system and chose immortalized human microglial cells (HMC3). We first transduced HMC3 cells with our shRNA-encoding lentiviral particles, validated knockdowns via RT-qPCR, and confirmed viability of the transduced cells (Fig. 9a–c). Unfortunately, we were unable to obtain a decent knockdown of both PLD isoforms, which is reflected by their limited effects on virus replication as determined by immunoblot of orthoflavivirus E protein and by TCID50 analysis (Fig. 9d, e). Whereas in Huh7 cells ZIKV viral titers were only marginally affected by the knockdown of PTDSS1 and PTDSS2 (Fig. 7f), CPE was significantly reduced by the depletion of these enzymes (Fig. 7g). In HMC3 cells, we detected an even more prominent effect on viral titers as well as viral E protein levels (Fig. 9d, e), indicating the importance of PS synthesis for ZIKV infection. In addition, PTDSS knockdown negatively impacted WNV and TBEV infectivity and intracellular protein level. Similar to Huh7 cells knockdown of CDIPT strongly affected WNV and TBEV infection but only had a minor impact on ZIKV.
a HMC3 cells were transduced with shRNAs targeting enzymes of the phospholipid pathway followed by infection with neurotropic orthoflaviviruses. b Knockdown efficiency was validated by RT-qPCR (mean ± SEM, n = 2 (shPTDSS1), n = 3 (shPLD1), n = 4 (shCDIPT, shPISD, shPTDSS2), or n = 5 (shPLD2) independent experiments). c Cell viability of shRNA-transduced HMC3 cells was determined at 4 dpt. shNT served as control and 10% DMSO-treated cells as non-viable control (mean ± SEM, n = 3). d Transduced HMC3 cells were infected at 4 dpt with neurotropic orthoflaviviruses (ZIKV MOI 0.005, WNV MOI 0.25, TBEV MOI 0.5) and E protein levels were determined by immunoblotting at 2 dpi. Shown is one representative immunoblot of three (TBEV, WNV) or four (ZIKV) independent experiments. e Determination of viral titers by TCID50 assays (mean ± SEM, n = 3–4, *p ≤ 0.05, unpaired two-tailed Mann–Whitney U test). dpt days post transduction, dpi days post infection. Source data are provided as a Source Data file.
PS and PI metabolism are important for DENV and YFV replication in differentiated THP-1 cells
To gain more insight into the physiological relevance of glycerophospholipid remodeling for YFV-17D and DENV replication, we next transduced THP-1 cells and treated them with phorbol-12-myristate-13-acetate (PMA) and interleukin 4 (IL-4) to obtain CD209/DC-SIGN-positive differentiated THP-1 cells (Fig. 10a). Differentiated THP-1- cells can be used as model systems for DENV and YFV-17D infection in immune cells. In comparison to THP-1 cells, which have limited susceptibility for DENV and YFV-17D infection, induced expression of the CD209/DC-SIGN receptor can facilitate orthoflavivirus infection31. Validation of shRNA-mediated knockdown efficacy by RT-qPCR revealed that we were not able to achieve sufficient reduction of PISD and PLD 1 and 2 mRNAs (Fig. 10b), which may in part be due to overall low expression levels of these enzymes in THP-1 cells. For the well-expressed PTDSS1, PTDSS2, and CDIPT we were able to substantially reduce expression levels using the lentiviral shRNA delivery system. Next, we verified the induction of CD209/DC-SIGN expression through differentiation by treatment with IL-4 and PMA by flow cytometry. As reported by others32,33, more than 90% of differentiated THP-1 cells were positive for CD209/DC-SIGN compared to virtually no expression in undifferentiated THP-1 cells (Fig. 10c). Viability assays of the knockdown cells indicated lower metabolic activity of PTDSS1 and PTDSS2 knockdown cells, whereas shPISD-expressing cells displayed higher metabolic activity (Fig. 10d). Viral protein levels of YFV-17D were undetectable in PTDSS1 and 2 and CDIPT-knockdown cells and strongly reduced by PISD and PLD1 knockdown. Correlating to the reduced protein levels, we observed a strong reduction in YFV-17D titers for all knockdown cells except for PLD2 (Fig. 10f). Although DENV E protein was not detectable in immunoblot analysis, we were able to analyze viral titers. Here we detected a strong reduction of DENV titers for all target shRNAs tested, but titers were close to the limit of detection (Fig. 10f).
a THP-1 monocytes were transduced with shRNAs targeting proteins of the glycerophospholipid pathway. 4 dpt, cells were differentiated using IL-4 (20 ng/ml) and PMA (20 ng/ml) for 4 days prior to infection. b Knockdown efficiency was validated using RT-qPCR (mean ± SEM, n = 2 (shPTDSS1, shPTDSS2), n = 3 (shPISD, shPLD2), n = 4 (shCDIPT), or n = 5 (shPLD1) independent experiments). c Differentiation into CD209-positive THP-1 cells was confirmed 4 days after IL-4 and PMA treatment by flow cytometry using a CD209-specific antibody. Shown is one representative experiment. d Cell viability was analyzed 8 dpt and 4 days post differentiation (mean ± SEM, n = 3 independent experiments). e Knockdown cells were infected with YFV-17D (MOI 1) and the amount of E protein was analyzed by immunoblotting at 2 dpi. Shown is one representative blot of three independent experiments. f Infectivity in the supernatant of DENV (MOI 2) and YFV-17D (MOI 1) infected cells was determined using TCID50 assays at 2 dpi (mean ± SEM, n = 4 (YFV-17D) or n = 3 (DENV) independent experiments, except for shCDIPT: one experiment excluded due to contamination, *p ≤ 0.05, unpaired two-tailed Mann–Whitney U test). dpt days post transduction, dpi days post infection. Source data are provided as a Source Data file.
Taken together, we observed the dependency of orthoflavivirus infection and replication on monounsaturated FA production through SCD, PS turnover, and de novo synthesis of PI. Inhibiting the synthesis of Cer, which are accumulating during infection, has opposing effects depending on the target enzyme: SPTi that targets the rate-limiting step of sphingolipid de novo synthesis impairs virus-induced cell death but has only antiviral activity against DENV, while CerSi, that blocks both the de novo and the salvage pathway, boosts ZIKV and YFV-17D replication and the cytopathic effect of both viruses and WNV. Effects of diminished PS and PI metabolism were substantiated by experiments in HMC3 microglia and differentiated THP-1 cells.
Discussion
Previous studies investigated the lipidome of flavivirus infection using unbiased mass spectrometry but mostly focused on one prototype virus in one cell line19,24,25,34,35. Here we compared the lipidome in a time course of infection with five different pathogenic orthoflaviviruses that cover viscerotropic (DENV and YFV) and neurotropic (WNV, TBEV, and ZIKV) viruses transmitted by mosquitoes or ticks. In order to allow for comparison, we chose Huh7 cells that are permissive for all these orthoflaviviruses. We observed a strong remodeling of lipid metabolism during infection with some trends observed in all viruses, and other changes being specific to certain viruses. Fourty-eight hours post infection, when more than 80% of cells were infected, principal component as well as hierarchical cluster analysis clearly indicated distinct lipidome changes in cells infected with DENV, WNV, and TBEV, whereas ZIKV and YFV-17D diverged less from the controls and overlapped with each other.
One of the most striking phenotypes we observed was the increase in Cer and some HexCer species at late time points after infection. This phenomenon has been observed previously and linked to a proviral role of Cer during ZIKV infection24. Interestingly, we only detected the accumulation in Cer for viruses that are cytopathic in Huh7 cells (ZIKV, WNV, DENV, and YFV) but not for TBEV, which replicates to high levels, but is not cytotoxic. In addition, in follow-up experiments, the inhibition of Cer synthesis was not broadly antiviral. In detail, SPT inhibition that targets the rate-limiting step of sphingolipid de novo synthesis reduced virus cytotoxicity and DENV infection. In contrast, CerS inhibition that blocks both the de novo and the salvage pathway boosted viral replication and cell death, especially for ZIKV and YFV-17D. These results are contrary to what has been shown in ZIKV infection in earlier studies24 despite similar experimental conditions. One difference however relates to the ZIKV strain, i.e., the Brazilian isolate strain FSS130253624 compared to the PRVABC59 strain produced using reverse genetics. Inhibition of Cer biosynthesis has been additionally investigated for WNV and DENV replication in Vero cell lines18. Here, opposing effects were observed with lower concentrations of the SPT inhibitor fumonisin B1 slightly increasing DENV titers and not affecting WNV. However, in higher concentrations, like the ones we used, SPTi had no proviral function. In our hands high concentrations decreased DENV titers and cytopathic effects, clearly indicating an antiviral effect in DENV infection that was not observed for WNV. Inhibition of CerS increased WNV-induced CPE but had no effect on DENV in contrast to earlier reports where CerSi increased DENV but decreased WNV titers18. Interestingly, it has also been shown that SMs are enriched in WNV virions and inhibition of knockdown of SMase reduced viral titers34. As we did detect remarkable differences between the chosen orthoflaviviruses, the strain used for analysis as well as the cell lines could of course influence the results.
For DENV infection some studies analyzed lipid metabolism in mosquito cells, the midgut of mosquitoes, and complete mosquitoes19,25,35. The increase in Cer and lyso-PL as well as decrease in TAG is a phenotype that is not restricted to mammalian cells, but in a similar manner observed in mosquito cells25. In contrast, in Huh7 cells SM and DAG species tend to decrease in abundance in response to DENV infection while they increase in mosquito cells. Thus, lipidomic remodeling induced by DENV infection is in part independent of the host cells.
In whole mosquitoes, metabolomics and lipidomics indicated that DENV replication causes phospholipid remodeling35. Early in infection several PL and lyso-PL species increased while later in infection those levels tended to decrease, a phenomenon similarly noted in our study in Huh7 cells. On a molecular level this was linked to decreased 1-acylglycerol-3-phosphate O-acyltransferase 1 (AGPAT1) expression in DENV-infected mosquitoes. In our analysis, we noticed a slight ~0.5-fold decrease in AGPAT1 expression 24 and 48 hpi and a slight increase in abundance of some PA species but were unable to detect lyso-PA species. However, the dependency on PLD2 expression that might also lead to increased PA levels points to similarities between mammalian cells and mosquitoes18.
In general, lyso-PL species, especially LPI levels, were elevated early in infection but decreased during the course of infection for all orthoflaviviruses analyzed, suggesting elevated PLA2 activities required for initiation of replication. For WNVKUN a similar accumulation of LPC was detected 24 hpi and treatment with a broad PLA2 inhibitor decreased WNVKUN replication, likely through inhibition of RO formation36. In our study treatment with a broad cPLA2 inhibitor slightly increased ZIKV and decreased DENV titers but had no effect on WNV NY99, TBEV, or YFV-17D, indicating the effects observed for WNVKUN might not be generalizable for other orthoflaviviruses. Inhibition of cPLA2 or knockdown of PLA2G4C also inhibited HCV replication and morphogenesis37 while knockdown of PLA2G4A or treatment with a different broad inhibitor essentially blocked HCV virion formation, and this block was rescued by addition of arachidonic acid38. Interestingly, in the same study decreased DENV titers were noted after cPLA2 inhibition, but the rescue of virion production was only minor, indicating a specific function of the lysolipids in DENV infection.
SCD inhibitors potently block HCV replication by inhibiting the formation of ROs30,39. Regarding orthoflaviviruses, inhibition of SCD was also linked to lower levels of DENV, ZIKV, and JEV replication29 and the formation of DENV particles20. While in our hands the titers were marginally affected by SCD inhibition, the cell pathogenicity of all viruses was strongly reduced.
As for most of the enzymes that were identified using the BioPan analysis no specific inhibitors are readily available, knockdown approaches were used to identify common or distinct virus dependencies. Knockdown of PTDSS2, but not PTDSS1, reduced viral titers most strongly for WNV and DENV and reduced the CPE of all investigated orthoflaviviruses. Both enzymes synthesize PS but have different substrate specificities, as PTDSS1 prefers PC over PE whereas PTDSS2 is specific for PE and in addition has a high affinity for DHA40,41. Simultaneous depletion of PTDSS1 and PTDSS2 has been previously shown to negatively impact DENV infection and linked to the entry process42, although lowered PS levels could additionally contribute to decreased infectivity of viral particles as they mediate particle entry by apoptotic mimicry43. We demonstrate that interference with PS synthesis in the host cells through PTDSS depletion does not impact orthoflavivirus entry or vRNA replication and translation but virion morphogenesis or secretion. It remains to be elucidated if the incorporation of PS in the lipid envelope is altered by the knockdown of PTDSS1 or 2 and thereby reduces virus binding to TIM and TAM receptors, which are known to facilitate orthoflavivirus infection44.
In our study, not only inhibition of PS synthesis, but also prevention of PS turnover catalyzed by PISD led to reduced viral titers, although only slightly rescuing cells from CPE induced by the infection. These data indicate that the balance of synthesis and turnover is critical to successful infection and replication. Again, WNV and DENV were the most susceptible orthoflaviviruses.
De novo synthesis of PI by CDIPT and CDS1 and 2 is required for WNV, TBEV, ZIKV, and DENV infection, as both virus titers and virus-induced CPE in CDIPT-, and to a lower extent and less broadly, in CDS1- and CDS2-knockdown cells decreased. For the knockdown of CDIPT we also detected significantly lower viral E protein in the supernatant of WNV-infected cells implying the importance for the late steps in orthoflavivirus replication cycle. These findings correlate with increased PA to PI reaction activities in all orthoflavivirus infections. While neither CDIPT nor CDS enzymes have been implicated in orthoflavivirus infection, PI and its phosphorylated forms, phospho-inositides (PIPs), have plenty of different functions in replication cycles of a broad range of viruses45. One limitation of our lipidomic study is that we did not analyze PIPs and thus cannot correlate the requirement of intact PI biosynthesis to an increase in different PIP species. One phenotype we observed, however, was the enrichment of LPI species common to all investigated viruses early in infection indicating that LPI might be important to establish infection.
We validated our findings in other cell types. ZIKV, WNV, and TBEV have a neurotropism, therefore we used immortalized human microglia cells (HMC3), a cell type that is important for orthoflavivirus infection46,47,48,49. Depletion of PTDSS1 and PTDSS2 in HMC3 cells decreased orthoflavivirus replication to an even stronger extent compared to Huh7 cells, highlighting a greater dependency of the neurotropic viruses we investigated on PS in more relevant non-cancer cells. Furthermore, our data indicate that the role of these enzymes is cell type independent. Correlating to the role of CDIPT in Huh7 cells, defects in PI synthesis impair WNV and TBEV infection, whereas ZIKV replication is not affected. It has been shown that ZIKV infection in microglia leads to altered levels of numerous metabolites, including lyso-phospholipids and phospholipids50. Here we demonstrate not only the importance of lipid metabolizing enzymes for ZIKV infection but also for WNV and TBEV infection in microglia cells.
For YFV-17D and DENV we confirmed our results in differentiated THP-1 cells that express DC-SIGN. Overall, depletion of glycerophospholipid remodeling enzymes remarkably reduced DENV and YFV-17D infection rates in our differentiated THP-1 cells, confirming the relevance of a functional glycerophospholipid metabolism in orthoflavivirus infection.
Taken together, lipid remodeling by different orthoflaviviruses includes distinct changes but also common themes shared by a variety of viruses that are needed for efficient infection and replication. Inhibition of monounsaturation of FAs rescued from virus-induced cell death and depletion of enzymes involved in PS and PI biosynthesis, as well as PS turnover was detrimental to orthoflavivirus infection in different cell types. Interestingly, inhibition of Cer synthesis had opposing effects depending on the target enzyme.
Methods
Cell lines, culture conditions, and viability assays
HEK293T and Vero E6 were obtained from the American Type Culture Collection, BHK21 from C. Munoz-Fontela, Huh7 from R. Bartenschlager, HMC3 from A. Slowik, and THP-1 from the German Collection of Microorganisms. All cells were grown under standard cell culture conditions in either RPMI (THP-1) or high glucose DMEM (all other cells) supplemented with 10% FCS and GlutaMax, as well as Pen/Strep (Gibco). Cell cultures were frequently tested for mycoplasma contaminiation. Cell viability was determined by CellTiter96 Aqueous One Solution Reagent (Promega). Transfection for lentivirus production was performed by calcium phosphate precipitation.
Plasmids
The following plasmids were described previously: pFK-DVs encoding DENV-2 1668151, pACNR-FLYFV-17Da encoding YFV-17D52,53, pWN-AB and pWN-CG encoding WNV NY9954, pJW231 and pJW232 encoding ZIKV PRVABC5955, and pTNd/c encoding TBEV Neudörfl strain56.
Lentiviral shRNA constructs were cloned into pSicoR-MS1 as described57,58 using the primers listed in Supplementary Data 3 as described previously59.
Antibodies and reagents
The following antibodies were obtained commercially: orthoflavivirus group antigen D1-4G2-4-15 (Novus Biologicals, 1:100 IF, 1:1000 WB), GAPDH (Santa Cruz, 1:500 WB), Alexa 555-conjugated IgG (donkey, (H + L), Invitrogen, 1:2000 IF), HRP-labeled secondary antibodies (Jackson Laboratories, 1:10000 WB), and FITC-conjugated CD209 antibody (Thermo Fisher, 1:20). FIPI (PLDi, 7.5 mM stock in DMSO, f.c. 150 nM) was purchased from Merck, fumonisin B1 (CAY62580-1, CerSi, 5 mM stock in DMSO, f.c. 10 µM) and myriocin (CAY63150-1, SPTi, 15 mM stock in DMSO, f.c. 30 µM) from Biomol, ASB14780 (cPLA2i 20 mM stock in DMSO, f.c. 5 µM) from Biotechne, and A939572 (SCDi,10 mM stock in DMSO, f.c. 5 µM) from MedChem. Of note, as myriocin is not fully soluble at 15 mM in DMSO, stocks were thawed at room temperature, then heated for 15 min at 55 °C immediately prior to addition to media. Enzymes for molecular cloning were from New England Biolabs, cell culture reagents from Gibco/Life Technologies, and fine chemicals, if not noted otherwise, from AppliChem or Sigma. LDs were stained with BODIPY493/503 (Life Technologies).
In vitro transcription of orthoflavivirus RNA, production of virus stocks, and infection
For the preparation of DENV, TBEV, and YFV-17D viral stocks, respective plasmids were digested for linearization and purified by phenol-chloroform extraction. For WNV and ZIKV a two-plasmid system with an overlap PCR strategy was used with the primers listed in Supplementary Data 3. The overlap PCR products were purified by gel extraction. For in vitro transcription we used the MegaScript SP6 Transcription Kit and Cap Analog (m7G(5′)ppp(5′)G) (Thermo Fisher) for DENV and YFV-17D, or HiScribe T7 ARCA mRNA Kit (NEB) for all other viruses. Virus stocks were produced in BHK21 cells (TBEV) or Vero E6 cells (all other viruses). 4 × 106 cells were washed in Opti-MEM (Life Technologies), and resuspended in 400 µl cytomix buffer (120 mM KCl, 5 mM MgCl2, 0.15 mM CaCl2, 2 mM EGTA, 1.9 mM ATP, 4.7 mM GSH, 25 mM HEPES, 10 mM potassium phosphate buffer, pH 7.6). The cell suspension was added to 10 µg in vitro transcribed orthoflavivirus RNA and pulsed at 260 V and 950 µF using the Gene Pulser II (Biorad). For P1 virus stock production, naïve BHK21 or Vero E6 cells were infected with P0 virus stock. For infection of Huh7, virus stocks were diluted in DMEM containing 10% FBS and added to cells for 1 h if not stated otherwise.
Determination of viral titers (TCID50)
Viral titers were determined with tissue culture infectious dose titration (TCID50) using Huh7 cells for virus stocks (except TBEV) and BHK21 cells for cell supernatants in infection experiments and TBEV viral stocks. Briefly, cells were seeded in 96-well plates and 1 day later infected with viral stocks or infectious supernatant in a serial dilution of 1:101–1:107. Five days post infection cells were fixed and stained with crystal violet. TCID50/ml was calculated with the Reed and Muench calculator60.
Lipid extraction and shotgun lipidomics
For each experiment 2.1–2.7 × 105 cells were harvested and inactivated with 640 µl acidified methanol (3% acetic acid, 0.3 μg/ml butylated hydroxytoluene) and 320 µl chloroform. The samples were dried and afterwards a mix of internal standards (Table S1) was added prior to a methyl tert-butyl ether extraction61. Organic phases were pooled, and lipids were dried using a vacuum concentrator and resuspended in 100 µL MS-storage solution chloroform/methanol/water (60/30/4.5; v/v/v) until data acquisition. Cholesterol was determined after acetylation as described earlier62. Shotgun lipidomics measurements were performed as described earlier63 using a Q Exactive Plus (Thermo Fisher Scientific) mass spectrometer coupled with the TriVersa NanoMate (Advion). For the chip-based nano-ESI measurements, a flow rate of ~300 nl/min is achieved using 1.1 kV spray voltage and back pressure of 1.1 psi. Data acquisition for one sample was performed over 10 min starting with positive ion mode and switching to negative ion mode after 5 min. Tandem mass spectrometric experiments were performed with a precursor selection in unit resolution using a predefined inclusion list. MS1 experiments were recorded with a resolution of 280,000 (at m/z 200, FWHM) and MS2 with a resolution of 70,000 (at m/z 200, FWHM) in both ionization modes. For tandem mass spectrometric experiments, a normalized collision energy of 30 was utilized (details on scan events and inclusion list are summarized in Supplementary Data 4).
Lipid identification was performed with LipidXplorer 1.2.864 and post processing including quality control and quantitation was executed with lxPostman. The data processing pipeline including LipidXplorer import settings, MFQL-queries and post-processing parameters will be made available via LipidCompass (accession number LCE00000015) and are also summarized in the report file (Supplementary Data 5) according to the minimal reporting checklist65. All lipid amounts were either normalized to the total lipid content (mol%) or protein content of the extracted cells (pmol/µg protein) as indicated in the text and figure legends and are the basis for further multivariate data analyses (Supplementary Data 1).
FA content of PE, PC, PS, and TAG were determined with a dedicated data analysis strategy using LipidXplorer and lxPostman. FA content of TAGs was determined by the specific neutral loss observed for ammonium adducts in positive ion mode as described earlier66,67. For PE, PC, and PS the fragmentation in negative ion mode was utilized to determine lipid species that were evaluated with lxPostman according to the intensity ratio of sn 1/2 FA signals of the respective internal standard. In the next step, the responses of the FA were normalized according to the lipid class-specific internal standard and the FA 18:1D7 (Table S1). Finally, all FA of the specific class were summed up and calculated in mol% (Supplementary Data 2). Total protein content was determined from the dried pellet of the water phase after extraction using the bicinchoninic acid assay (Thermo Fisher Scientific). Pellets were resuspended in 150 μl sample buffer, mixed well, and sonicated for 2 min. After a short centrifugation step, the samples were incubated for 30 min at 99 °C and shaking at 1400 rpm (Thermomixer, Eppendorf) and were sonicated every 5 min for 30 s. After cooling to 25 °C, the assay was carried out according to the manufacturer’s instructions and absorbance was measured at 562 nm with an Infinite M200 Pro plate reader (Tecan).
RNA isolation and transcriptomics
For transcriptomic analysis, total RNA was isolated using TriReagent (Sigma-Aldrich) following the manufacturer’s protocol followed by DNA digestion with the TURBO DNA-free DNase kit (Ambion). Concentration of RNA was measured on an Invitrogen Qubit 3 Fluorometer using Qubit RNA High Sensitivity (HS) Kit (Thermo Fisher Scientific Inc.). Quality was assessed using the Bioanalyzer 2100 instrument with an RNA Nano 6000 Kit (Agilent), followed by depletion of ribosomal rRNA with the NEBNext rRNA Depletion Kit v2 (Human/Mouse/Rat) (New England Biolabs) and Agencourt RNAClean XP beads (Beckman Coulter). Library preparation was performed according to the manufacturer’s protocol by using NEBNext Ultra II Directional RNA Library Prep Kit for Illumina. To barcode the libraries and therefore facilitate multiplex sequencing, Multiplex Oligos for Illumina (96 Unique Dual Index Primer Pairs) (New England Biolabs) were used. Libraries were further purified with Agencourt AMPure XP Reagent (Beckman Coulter), and quality and quantity of the amplified cDNA were assessed with a DNA High Sensitivity Kit (Agilent). After pooling, denaturing, and diluting the libraries, 150 bp long paired-end reads were sequenced on the NovaSeq system (Illumina).
The generated sequence reads were basecalled, and demultiplexed prior to analysis. All sequence reads obtained were filtered by mapping against their respective virus genome (DENV 2 (NC_001474.2); TBEV (NC_001672.1); WNV isolate NY99 (MZ605381.2); YFV-17D/Tiantan (FJ654700.1); ZIKV strain PRVABC59 (KU501215.1)), before aligning them to the human genome sequence GRCh38.p14 (RefSeq GCF_000001405.40) using STAR68. Aligned sequence reads were sorted by position using SAMtools69, and sequence read counts per gene or transcript were calculated for each library using the subread function featureCounts70. Differential gene expression analyses were performed with the R-package DESeq271. Data were normalized per regularized log transformation and shrunk using the adaptive shrinkage estimator for the ashr package72. Genes were considered differentially expressed when the adjusted p value was below 0.05 and the log2 fold change was above 1 or below −1.
Lentivirus production and transduction
Lentiviral particles were produced as previously described73. Briefly, 293T cells were co-transfected with the pSicoR-MS1 shRNA constructs, a packaging construct (pCMVΔR8.91), and a construct expressing the glycoprotein of vesicular stomatitis virus (VSV-G) (pMD.G). Pseudotyped lentiviral particles were concentrated using ultracentrifugation. Lentiviral transductions were carried out in the presence of 4 µg/ml polybrene (Sigma). Lentiviral stocks were titrated on Huh7 cells using flow cytometry (Guava easyCyte HT Cytometer) or microscopy.
CPE assay
Huh7 cells were either transduced with constructs for shRNA targets or treated with inhibitors. Four days post transduction (shRNAs) or 2 d post treatment (inhibitors) cells were infected with the different orthoflaviviruses. Cells were fixed 3 dpi and stained with crystal violet to visualize CPE. Plates were scanned on a ChemiDoc imaging system (BioRad) and CPE quantified using ImageJ.
Immunoblot analysis
Cells were lysed in RIPA buffer (150 mM NaCl, 50 mM Tris-HCl pH 7.6, 1% NP-40, 0.5% sodium deoxycholate, 5 mM EDTA, protease inhibitor cocktail (Sigma), PMSF (AppliChem)) for 1 h on ice. Clarified lysates or culture supernatants were subjected to SDS–PAGE followed by blotting onto a nitrocellulose membrane (Amersham Protran, Cytiva). Following staining with antibodies, protein bands were detected by chemiluminescence using Lumi-Light substrate (Roche) or SuperSignal West Femto (Thermo Fisher) on a ChemiDoc imaging system (BioRad). Band signal intensities were quantified using the quantification function of Image Lab (BioRad).
RNA isolation and quantitative RT-PCR
vRNA from the cultures supernatant was isolated using NucleoSpin RNA Virus Kit (Machery Nagel) according to the manufacturer’s protocol. Total cellular RNA isolation was performed with TriReagent (Sigma-Aldrich). Cellular DNA was digested with rDNaseI using the TURBO DNA-free DNase kit (Ambion). RNA was transcribed into cDNA using random hexamers (Qiagen), SuperScript III reverse transcriptase (Thermo Fisher), and RNaseOut (Thermo Fisher). cDNA was subjected to qPCR using the Luna Universal qPCR master mix (New England Biolabs). For quantitative PCR, we used the primers listed in Supplementary Data 3 and Luna Universal qPCR master mix (New England Biolabs) on a StepOnePlus Real Time—qPCR Thermal Cycler (Applied Biosystems).
Immunofluorescence microscopy
For immunofluorescence microscopy, cells seeded on coverslips were infected and fixed at different time points in 4% paraformaldehyde. After permeabilization for 5 min in 0.1% Triton X-100 in PBS and incubation in blocking solution (5% BSA, 1% fish skin gelatin, 50 mM Tris in PBS), cells were stained overnight with primary antibodies, followed by Alexa Fluor-conjugated secondary antibodies. LDs were stained with BODIPY493/503, nuclei with Hoechst, and coverslips were embedded in Mowiol mounting media. Microscopy was performed on a Leica TCS SP5 II confocal laser scanning microscope or Leica Thunder DMI8 widefield microscope. For the quantification of LDs, we used cells that expressed a cell-based orthoflavivirus reporter74,75 to monitor infection. LDs were quantified using the particle analyzer function of Fiji76.
Virus entry assay
Viral entry efficacy was determined as described77 with minor modifications: Huh7 cells were transduced with lentiviral particles and seeded at 4 dpt. At 5 dpt, the media was changed to DMEM supplemented with 3% FCS and the cultures were pre-cooled for 10 min at 4 °C prior to infection with ZIKV (MOI 2), WNV (MOI 5), DENV (MOI 2), TBEV (MOI 10), and YFV-17D (MOI 5). The inoculum was removed after 1 h, cells were washed with cold DMEM containing 10% FCS and shifted to 37 °C. Four hours post infection, the cells were washed 1× with DMEM and 1× with PBS. Following incubation with pre-warmed trypsin for 2 min at RT the cells were washed again with DMEM and PBS prior to lysis with TriReagent (Sigma-Aldrich). RNA Isolation and RT-qPCR were performed as described above.
Transduction, differentiation, and flow cytometry of THP-1 cells
THP-1 were spin-infected in 24-well plates in RPMI supplemented with polybrene with lentiviral particles by centrifugation at 500 × g for 1 h followed by incubation with the inoculum o/n. At 4 dpt cells were seeded and IL-4 and PMA were added to initiate differentiation as described33 (final concentration: IL-4 (20 ng/ml), PMA (20 ng/ml)). After 4 days, the presence of the receptor DC-SIGN/CD209 was confirmed by flow cytometry and cells were used for infection experiments with YFV-17D and DENV. For flow cytometry, cells were trypsinized and fixed with 4% paraformaldehyde, washed twice with PBS/glycine, blocked with 5% BSA, 1% fish skin gelatin, 50 mM Tris in PBS, and stained with FITC-conjugated CD209 antibody (Thermo Fisher) for 1 h at 4 °C while rotating. Analysis was performed on a Guava easyCyte HT flow cytometer and data was analyzed using FlowJo.
Quantification and statistical analysis
R78 and RStudio79 were used to visualize data and for statistical analysis. Statistical analysis was performed using unpaired two-tailed Welch’s unequal variances t-test, Mann–Whitney U test, or, in case of normalized data, one sample Student’s t-test, and adjusted for multiple comparison with the false discovery rate (FDR) as indicated in the figure legends. Sample sizes (n) represent independent experiments, if not stated otherwise. The data were analyzed and visualized using several packages available for R, namely, gdata (version 3.0.0), dplyr (version 1.1.4)80, tidyr (version 1.3.0)81, factoextra (version 1.0.7)82, ggplot2 (version 3.4.4)83, pheatmap (version 1.0.12)84, cowplot (version 1.1.1)85, ggrepel (version 0.9.4)86, purrr (version 1.0.2)87, coin (version 1.4-3)88, ggsignif (version 0.6.4)89, ggbeeswarm (version 0.7.2)90, as well as BioPan (https://www.lipidmaps.org/biopan/)28, LipidLynxX91, and LION (http://www.lipidontology.com)27 with missing data imputed with MetImp 1.2 (https://metabolomics.cc.hawaii.edu/software/MetImp/)92 using MCAR/MAR method RF.
Data availability
All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. The lipidomics data generated in this study are provided in Supplementary Data 1 and 2 and the raw data are available under accession number MTBLS11030 via MetaboLights [https://www.ebi.ac.uk/metabolights/editor/MTBLS11030]. The lipidomic data processing pipeline including LipidXplorer import settings, MFQL-queries, and post-processing parameters is available via LipidCompass under accession number LCE00000015. The transcriptome data generated in this study have been deposited in the Gene Expression Omnibus database under accession code GSE264306. All unique/stable reagents generated in this study are available with a completed materials transfer agreement. Source data are provided with this paper.
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Acknowledgements
We thank Ralf Bartenschlager (University of Heidelberg, Germany) for the DENV-2 construct and Huh7 cells, Charles M. Rice (Rockefeller University, NY) for the YFV-17D construct, Claire Huang (CDC, GA) for the WNV NY99 construct, Melanie Ott, Sakshi Tomar (Gladstone Institutes, CA) and Gregory Ebel (Colorado State University) for the ZIKV PRVABC59 construct, Karin Stiasny (Medical University of Vienna, Austria) for the TBEV Neudoerfl construct, Alexander Slowik (RWTH Aachen) for HMC3 cells, and Matt Spindler (Gladstone Institutes, CA) for pSicoR-MS1. We like to thank Nils Hoffmann (CeBiTec, Universität Bielefeld) for support in data management of the lipidome data. This study was supported by funds from the Deutsche Forschungsgemeinschaft [DFG project IDs 416701689, 517270163, 517270083, 197785619 (CRC 2021 project B10) to E.H., 197785619 (CRC 2021 project Z02) to T.H.,] and the LOEWE Center DRUID (Novel Drug Targets against Poverty-related and Neglected Tropical Infectious Diseases, E.H.). This study was further supported by funds of the Lipidomics Informatics for Life Sciences (LIFS) project within the German Network for Bioinformatics Infrastructure (de.NBI) to D.S.
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Conceptualization: J.H., L.S., D.S., and E.H.; methodology: J.H., L.S., T.H., D.S., and E.H.; investigation: J.H., L.S., A.W., B.O., and K.C.T.V.; writing—original draft: J.H., L.S., and E.H.; writing—review and editing: B.O., K.C.T.V., A.S., T.H., and D.S.; funding acquisition: D.S. and E.H.; resources: A.S.; supervision: T.H., D.S., and E.H.
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Hehner, J., Schneider, L., Woitalla, A. et al. Glycerophospholipid remodeling is critical for orthoflavivirus infection. Nat Commun 15, 8683 (2024). https://doi.org/10.1038/s41467-024-52979-y
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DOI: https://doi.org/10.1038/s41467-024-52979-y
