Isolation of Kallithea virus

We identified KV-infected flies through a PCR screen for previously published D. melanogaster viruses in 80 previously untested wild-caught flies (see [31] for primers and cycling conditions). We homogenised each fly in 0.1 mL of Ringer's solution, transferred half of the homogenate to Trizol for nucleic acid extraction, and performed RT PCR assays on the resulting RNA for all D. melanogaster viruses reported by Webster et al [31]. We selected a KV-positive sample from Thika, Kenya (Collected by John Pool in 2009; subsequently stored at -80C), removed debris from the remaining fly homogenate by centrifugation for 10 minutes at 1000 × g, and microinjected 50 nL of the supernatant into Dicer-2^L811fsX flies, which lack a robust antiviral immune response [38]. After one week, we homogenised 100 KV-injected Dicer-2 ^L811fsX flies in 10 uL Ringer’s solution per fly, cleared the solution by centrifugation as above, and re-injected this homogenate into further Dicer-2^L811fsX flies. This process was then repeated twice more with the aim of increasing viral titres. In the final round of serial passage, we injected 2000 Dicer-2 ^L811fsX flies, which were homogenised in 5 mL 10 mM Tris-HCl. We cleared the homogenate by centrifuging at 1000 × g for 10 minutes, filtering through cheese cloth, centrifuging twice more at 6000 × g for 10 minutes, and finally filtering through a Millex 0.45 µm polyvinylidene fluoride syringe filter. The resulting crude virus preparation was used as input for gradient ultracentrifugation.

We screened the crude preparation by RT-PCR for other published Drosophila virus sequences, and identified the presence of DAV, Nora virus, DCV, and La Jolla virus. To separate KV from these viruses, we used equilibrium buoyant density centrifugation in iodixanol (“OptiPrep”, Sigma-Aldrich) as enveloped viruses are expected to have lower buoyant densities than most unenveloped viruses. Iodixanol is biologically inert, and gradient fractions can be used directly for downstream infection experiments (avoiding dialysis, which we found greatly reduces KV titres). We concentrated virus particles by centrifuging crude virus solution through a 1 mL 10% iodixanol layer onto a 2 mL 30% iodixanol cushion at 230,000 × g for 4 hours in a Beckman SW40 rotor. Virus particles were taken from the 30%-10% interphase, and layered onto a 40%-10% iodixanol step gradient, with 2% step changes, and centrifuged for 48 hours at 160,000 × g. We fractionated the gradient at 0.5 mL intervals, phenol-chloroform extracted total nucleic acid from aliquots of each fraction, and measured virus concentration by quantitative PCR (qPCR). We pooled all Kallithea-positive, RNA virus-negative fractions and calculated the infectious dose 50 (ID50) by injecting 3 vials of 10 flies with each of a series of 10-fold dilutions and performing qPCR after 5 days. We simultaneously performed the above isolation protocol with uninfected Dicer-2^L811fsX flies and extracted the equivalent fractions for use as an injection control solution (hereafter referred to as “gradient control”).

Transmission electron microscopy

A droplet of viral suspension was allowed to settle on a Formvar/Carbon 200 mesh Copper grid for 10 minutes. We removed excess solution and applied a drop of 1% aqueous uranyl acetate for 1 minute before removing the excess by touching the grid edge with filter paper. The grids were then air dried. Samples were viewed using a JEOL JEM-1400 Plus transmission electron microscope, and representative images were collected on a GATAN OneView camera.

Measurement and analysis of viral titre

Flies were reared on a standard cornmeal diet until infection, after which they were transferred to a solid sucrose-agar medium. We infected flies by abdominal injection of 50 nL of 10⁵ ID50 KV using a Nanoject II (Drummond Scientific), and these flies were then used to assay changes in viral titre, mortality, fecundity, or daily movement. To test whether the change in viral titre over time was influenced by sex or the presence of Wolbachia endosymbionts, we injected 25 vials of 10 male or female Oregon R flies with KV, with or without Wolbachia (totalling 1000 flies). We phenol-chloroform extracted total nucleic acid at 5 time-points: directly after injection and 3, 5, 10, and 15 days post-infection. We used qPCR to measure viral titre relative to copies of the fly genome with the following (PCR primers: kallithea_126072F CATCAATATCGCGCCATGCC, kallithea_126177R GACCGAGTTAGCGTCAATGC, rpl32_465F CTAAGCTGTCGGTGAGTGCC, rpl32_571R: TGTTGTCGATACCCTTGGGC). We analysed the log-transformed relative expression levels of Kallithea virus as a Gaussian response variable in a linear mixed model using the Bayesian generalised mixed modelling R package MCMCglmm (V2.24; [39]). R code and raw data used to fit all models in this paper is provided on figshare (doi: 10.6084/m9.figshare.c.3936037.v1).

The fixed effects portion of the model included an intercept term and coefficients for the number of days post-inoculation (DPI), sex, and DPI by sex interaction. We estimated random effects for each qPCR plate and assumed random effects and residuals were normally distributed. We initially fitted the model with Wolbachia infection status included as a fixed effect, however this term was not significant and was excluded from the final model.

We also attempted to infect flies with KV by feeding. We anesthetised flies in an agar vial and sprayed 50 uL of 5x10³ ID50 KV onto the flies and food. We then collected flies immediately (for the zero time-point) and at 7 DPI and used the primers above to calculate relative KV titre.

Mortality following KV infection

We performed mortality assays to test the effect of KV infection on longevity, and to test whether this was affected by sex or Wolbachia infection status. We injected a total of 1200 Oregon R flies with control gradient or KV for each sex with or without Wolbachia (Wolbachia had previously been cleared by 3 generations of Ampicillin treatment and its absence was confirmed by PCR). We maintained flies for each treatment in 10 vials of 10 flies, and recorded mortality daily for three weeks. Mortality that occurred in the first day after infection was assumed to be due to the injection procedure and excluded from further analysis. We analysed mortality using an event-analysis framework as a generalised linear mixed model using MCMCglmm, with per-day mortality in each vial as a binomial response variable. We included fixed effects for DPI, DPI² (used to capture nonlinear mortality curves), KV infection status, the two-way interaction between DPI and KV infection status, the two-way interaction between DPI and sex, and the three-way interaction between DPI, KV infection status, and sex. We fitted vial as a random effect to account for non-independence among flies within vials, assuming these follow a normal distribution. As in the model for viral titre, we found no evidence for differences associated with Wolbachia infection, and Wolbachia terms were excluded from the final model. The higher rate of male mortality we observed was also confirmed in a second independent experiment using an outbred population derived from the Drosophila Genetic Reference Panel (DGRP; see below).

Fecundity following KV infection

We measured fecundity during early (1 and 2 DPI) and late (7 and 8 DPI) Kallithea virus infection. Virgin female flies from an outbred population derived from the DGRP ([37]; created from 113 DGRP lines and maintained at a low larval density with non-overlapping generations) were injected with either KV, or with chloroform-inactivated KV as a control, and individually transferred to standard cornmeal vials. The following day we introduced a single male fly into the vial with the virgin female. We transferred the pair to new vials each day and recorded the number of eggs laid. Per-day fecundity was analysed in MCMCglmm as a Poisson response variable using a hurdle model, which models the probability of zeroes in the data and the Poisson process as separate variables. We included fixed effects associated with KV infection status, infection stage (early or late), the interaction between KV infection and infection stage, and random effects associated with each fly pair (vial).

We analysed ovary morphology to examine whether changes in fecundity were detectable in ovaries. Flies were injected with either control virus solution or KV and kept on solid sucrose-agar medium vials. After 8 DPI, flies were transferred to vials with standard cornmeal medium supplemented with yeast. Two days later, we dissected ovaries in phosphate-buffered saline solution, fixed ovaries in 4% paraformaldehyde, and stained nuclei with DAPI. Ovaries were analysed under a Leica fluorescence microscope, and we recorded whether each ovariole within an ovary included egg chambers past stage 8 (i.e. had begun vitellogenesis), and whether any egg chambers within an ovariole exhibited apoptotic nurse cells. The probability of an ovariole containing a post-vitellogenic egg chamber was analysed using a logistic regression in MCMCglmm, with KV infection status as a fixed effect and the ovary from which the ovariole derived as a random effect. We analysed whether apoptotic nurse cells are associated with KV virus-infected ovary in the same way.

Daily movement following KV infection

We used a Drosophila Activity Monitor (DAM, TriKinetics; [40]) to measure per-day total movement of individual flies. The DAM is composed of multiple hubs, each with 32 tubes containing a single fly, and movement is recorded on each occasion the fly breaks a light beam. We injected 96 female flies from an outbred DGRP population with either chloroform-inactivated KV or KV, randomly assigned these flies within and across 3 hubs, and measured total movement for one week. Movement was binned for each day and this per-day total movement was analysed in a linear mixed model as a Poisson response variable using MCMCglmm. We completely excluded flies that failed to move for a whole day or longer, assuming them to be dead. As before, we included fixed effects associated with DPI, KV infection status, and the interaction between KV and DPI. We included random effects associated with each fly (repeated measures) and each of the DAM hubs, and assumed each of these take values from a normal distribution.

Quantitative genetic analysis

The DGRP is a collection of highly inbred fly lines derived from a D. melanogaster population collected in Raleigh, North Carolina [37], and is widely used to estimate and dissect genetic variation in complex traits in Drosophila. We measured KV titre in females and mortality following KV infection in both sexes for 125 DGRP lines, and estimated genetic (line) variances and covariances among these traits. To measure viral titre in the DGRP, we infected 5 vials of 10 flies for each line across 5 days, with a vial from each line being represented each day. After 8 DPI, living flies were killed and homogenised in Trizol for nucleic acid extraction and qPCR. To measure mortality following KV infection in the DGRP, we injected 3 vials of 10 flies of each sex and recorded mortality on alternate days until half the flies in the vial were dead (i.e. median survival time). Flies were transferred to fresh agar vials every 10 days. Mortality occurring in the first 3 DPI was assumed to be caused by the injection procedure and was removed from the analysis.

We fitted a multi-response linear mixed model in MCMCglmm to estimate heritability and genetic covariances among lines [1] where is the log-transformed relative viral titre or the duration until median mortality (LT50). We only estimated sex-specific fixed effects () for LT50, because we did not measure titre in both sexes. The first part of the random effects model accounts for block effects due to date of injection () and qPCR plate (). We assumed a 2x2 identity matrix as the covariance structure for , with effects associated with each trait from independent normal distributions. Effects for the plate were assumed to be normally distributed. The second part of the random effects model () estimates the variance in each trait across lines and was allowed to vary by sex. We estimated all variance-covariance components of the 3x3 G matrix associated with . Finally, we fitted separate error variances for each trait in each sex (, where residuals were associated with independent normal distributions.

The diagonal elements of the covariance matrix represent posterior distributions of genetic variances for viral titre in females, LT50 in females, and LT50 in males (, ). We calculated broad-sense heritability (i.e. line effects) for each trait as , where is the residual variance associated with each trait, estimated in the model as . However, heritabilities cannot readily be compared because of their dependence on the residual variance, which can be vastly different for different phenotypes [41]. Therefore, we also calculated the coefficient of genetic variation (CV_G) as , where V_G is standardised by the phenotypic mean () and is more appropriate for comparisons across phenotypes. All confidence intervals reported are 95% highest posterior density intervals.

Genome-wide association studies

We used measurements of viral titre and mortality following KV infection in the DGRP lines to perform a series of genome-wide association studies (GWAS). Although our power to detect small-effect genetic variants with only 125 lines is very low, past studies have demonstrated genetic variation in natural viral resistance in Drosophila is often dominated by few large effect variants ([12,14–16]; but for caveats see [42]). We performed a GWAS on each phenotype separately by fitting an individual linear model for each variant in the genome using the full data. For the titre GWAS, we included focal SNP, qPCR plate, and date of injection as linear predictors. For the mortality GWAS, we included focal SNP, sex, and a sex-by-SNP interaction as linear predictors. Models were fitted using the base R linear model function ‘lm()’. We tested the significance of the SNP and SNP-by-sex predictors with a t-test, and we obtained significance thresholds for each GWAS by permuting genotypes across phenotypes 1000 times and recording the lowest p-value for each pseudo-dataset.

Confirmation of GWAS hits

We chose 19 genes identified near significant GWAS hits to further test their involvement in KV infection. For each gene, we crossed a transgenic line containing a homologous foldback hairpin under the control of the Upstream Activating Sequence (UAS) to two GAL4 lines: w*; P{UAS-3xFLAG.dCas9.VPR}attP40, P{tubP-GAL80^ts}10; P{tubP-GAL4}LL7/TM6B, Tb¹ (Bloomington line #67065; hereafter referred to as tub-GAL4) and w*; P{GawB}Myo31DF^NP0001/CyO; P{UAS-3xFLAG.dCas9.VPR}attP2, P{tubP-GAL80^ts}2 (Bloomington line #67067; hereafter referred to as myo31DF-GAL4). These lines drive GAL4 expression in the entire fly and in the gut, respectively, and contain a temperature-sensitive Gal80, which is able to inhibit GAL4 at the permissive temperature (18 degrees). RNAi lines included the following genes (BDSC numbers): Pkcdelta (28355), btd (29453), dos (31766), tll (34329), Atg10 (40859), Dgk (41944), Cip4 (53321), hppy (53884), LpR2 (54461), CG5002 (55359), sev (55866), eya (57314), Gprk2 (57316), Sox21b (60120), CG11570 (65014), ATPCL (65175), Pdcd4 (66341), CG7248 (67231), and yin (67334). As a control, we crossed the genetic background of the RNAi lines (Bloomington line #36304) to the two GAL4 lines. All crosses were made at 18 degrees. After eclosion, offspring were transferred to agar vials (10 flies per vial) at the non-permissive temperature (29 degrees) for two days to facilitate silencing of candidate genes, then injected with KV. We measured titre at 5 DPI for 5 vials of each KV-infected genotype for each GAL4 driver. We used a linear mixed model to analyse log-transformed viral titre in each knockdown relative to the genetic background controls, with GAL4 driver as a fixed effect, gene knockdown as a random effect, and with separate error variances for each GAL4 driver. If the random effect associated with a candidate gene was significantly different from zero, we concluded this gene played a role in determining the outcome of infection by KV. The specification of gene as a ‘random effect’ allows comparison of each knockdown to all other knockdowns, accounting for any possible overall effect of overexpressing a dsRNA hairpin. As a proof of principle, we confirmed knock-down of the largest-effect gene (Cip4) using the DRSC FlyPrimerBank qPCR primers Cip4_PP33370F (ATTGCGGGAGTGACGCTTC) and Cip4_PP33370R (CTGTGTGGTGAGGTTCTGCTG). We did not assess knockdown efficiency for the other crosses, and any negative findings should be treated with caution.

Sample preparation for RNA-sequencing

We next aimed to characterise the host expression response to KV infection, and whether this differed between males and females. We injected 6 vials of 10 flies for each sex with either the control gradient solution or with KV. After 3 DPI, we homogenised flies in Trizol, extracted total nucleic acid, and enriched the sample for mRNA through DNAse treatment and poly-A selection. We used the NEB Next Ultra Directional RNA Library Prep Kit to make strand-specific paired-end libraries for each sample, following manufacturer’s instructions. Libraries were pooled and sequenced by Edinburgh Genomics (Edinburgh, UK) using three lanes of an Illumina HiSeq 4000 platform with strand-specific 75 nucleotide paired end reads. We subsequently identified a low level of Drosophila A Virus (DAV) contamination in both KV treated and untreated flies, reflecting the widespread occurrence of this virus in fly stocks and cell cultures. All reads have been submitted to the European Nucleotide Archive under project accession ERP023609.

We used SPAdes genome assembler (v3.11.1; [43]) to assemble the KV genome from RNA-sequencing reads, using the previously published genome (NC_033829.1) as an ‘untrusted contig’ (File S1).

Differential expression analysis

We removed known sequence contaminants (primer and adapter sequences) from the paired end reads with cutadapt (V1.8.1; [44]) and mapped remaining reads to the D. melanogaster genome (FlyBase release r6.15) and to all known Drosophila virus genomes using STAR (V2.5.3a; [45]), with a maximum intron size of 100 KB, but otherwise default settings. We counted the number of reads mapping to each gene using the featurecounts command in the subread package (V1.5.2; [46]) and used these raw count data as input to DESeq2 (V1.16.0; [47]) for differential expression analysis. DESeq2 fits a generalised linear model for each gene, where read counts are modelled as a negative binomially distributed variable [47,48] and includes a sample-specific size factor and a dispersion parameter that depends on the shared variance of read counts for genes expressed at similar levels [47,48]. Our design matrix included sex, KV infection status, and the interaction between the two, allowing us to test for expression changes following KV infection and how these changes differ between the sexes. To account for the unintended presence of DAV, and differences in the level of DAV within and between the treatments, we also include the relative titre of DAV as a continuous predictor. Using this model, we calculated log₂ fold changes in DESeq2, and tested for significance using Wald tests. We used the ‘plotPCA’ function implemented in DESeq2 to perform principal component analysis of the rlog-transformed read count data [47].

GO term and network analysis

We performed five independent gene ontology (GO) term enrichment analysis, using: (1) genes with significant SNPs in the GWAS for titre; (2) genes with significant SNPs in the GWAS for mortality, (3) genes upregulated in either sex (p < 0.001); (4) genes downregulated in either sex (p < 0.001); and (5), genes significantly different between males and females (p < 0.05). For each of these gene lists, we tested for GO term enrichment using the ‘goseq’ R package (V1.26.0; [49]), which accounts for the difference in power for detecting differential expression caused by gene length, and tests for significant over-representation of genes in a GO term.

We performed a network analysis on genes identified in GWAS or RNA-sequencing studies at a liberal significance threshold (p < 0.10) to infer broadly acting pathways involved in KV infection that may have been overlooked in individual gene analyses. We used the PPI-spider tool [50] available on the bioprofiling webserver [51], which uses the IntAct database to find enriched subpathways within a provided gene list, allowing one gene absent from the provided list to mediate an interaction. Enriched pathways in the given gene list are then compared to random gene lists of the same length to assess significance.

Isolation of Kallithea virus

We isolated Kallithea Virus (KV) by gradient centrifugation following 4 rounds of serial passage in flies. Many laboratory fly stocks and cell culture lines are persistently infected with RNA viruses [17; 31], and following serial passage we identified co-infections of DAV, Nora Virus, and Drosophila C Virus (DCV) by PCR. The high prevalence of these viruses in laboratory stocks presents a substantial hurdle in the isolation of new Drosophila viruses, requiring the separation of the new viruses of interest. Although this can be relatively simple (e.g. separating enveloped from non-enveloped viruses), most of the recently identified Drosophila viruses [31,52,53] are from ssRNA virus families with buoyant densities similar to common laboratory infections. To exclude these from our isolate, we concentrated KV using a 1.18 g/mL cushion, retaining KV at the interphase, but excluding most of the contaminating RNA viruses. Subsequent equilibrium density gradient centrifugation produced a KV band at 1.17 g/mL, and with some DAV contamination at approximately 1.20 g/mL (Fig 1A). Although nudiviruses have not previously been prepared using an iodixanol gradient, the equilibrium buoyant density was consistent with the lower buoyant densities of enveloped particles [54] and similar to other enveloped dsDNA viruses (e.g. Herpesviruses: 1.15 g/mL). KV was estimated to be an approximately 650-fold higher concentration than DAV at 1.17 g/mL, and we were unable to identify intact DAV particles by electron microscopy (KV shown in Fig 1B). KV is morphologically similar to Oryctes rhinoceros nudivirus [55], with an enveloped rod-shaped virion approximately 200 nm long and 50 nm wide.

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Fig 1. Isolation of KV and growth in flies.

(A) Density gradient and virus titre: Kallithea virus (purple) was effectively separated from DAV (green) at 1.18 g/mL (dotted line) in fractions 15 and 16 of an iodixanol gradient. (B) Transmission electron micrograph of KV-positive fractions showed KV to be a rod-shaped enveloped particle, as has been described previously for other nudiviruses [55]. We did not observe unenveloped KV particles, bacteria, or RNA viruses in the isolate. (C) Relative viral titres normalised by the number of fly genomic copies and virus levels at time zero in each sex. Each point represents a vial of 10 flies. Viral titres peaked at 10 days post-infection, and were generally higher in females (red) than males (blue) late in infection. (D) We were able to infect adult flies orally by applying the viral isolate to Drosophila medium, although relative copy number of the virus was very low and infection was inefficient, with only 2 of 16 vials (each of 10 flies) having increased titre after one week, indicating an infectious rate lower bound of ~1% at 5x10³ ID50.

https://doi.org/10.1371/journal.ppat.1007050.g001

Kallithea virus growth in flies

We injected the KV isolate into Drosophila Oregon R males and females, with and without Wolbachia, and measured viral titre at four time-points by qPCR. In females, KV increased approximately 45,000-fold by day 10, and then began to decrease (Fig 1C). In males, the KV growth pattern was altered, growing more slowly (or possibly peaking at an earlier un-sampled time point), resulting in a 7-fold lower titre than in females after 10–15 days, (nominal MCMC p-value derived from posterior samples, MCMCp = 0.002). Wolbachia did not affect virus growth rate in either sex (MCMCp = 0.552, S1 Fig), reaffirming previous findings that Wolbachia do not offer the same protection against DNA viruses in Drosophila as they do against RNA viruses [56].

Nudiviruses have previously been reported to spread through sexual and faecal-oral transmission routes. The Drosophila innubila Nudivirus (DiNV), a close relative of KV, is thought to spread faecal-orally, so we tested whether KV can spread through infected food. We found that although oral transmission occurred, it was relatively inefficient (Fig 1D). However, the concentration of DiNV found in D. innubila faeces is broadly similar to our KV isolate after gradient centrifugation ([19]; Fig 1D), but the administered suspension had been diluted 50-fold and may consequently provide a lower dose than flies encounter naturally. To explore the potential for transovarial vertical transmission or gonad-specific infections following sexual transmission (as reported for Helicoverpa nudivirus 2; [57]), we also performed qPCR on dissected ovaries and the remaining carcasses at 3 DPI (S2 Fig). We found that KV was highly enriched in the carcass relative to the ovaries. Although intra-abdominal injection could influence KV tissue-specificity, there were still substantial levels of KV in the ovaries, indicating there is not a complete barrier to infection. These results imply that KV is likely transmitted faecal-orally, as are closely related nudiviruses, but explicit tests for transovarial or sexual transmission are required.

Sex-specific mortality, lethargy, and altered fecundity patterns following KV infection

Drosophila innubila infected with DiNV suffer fitness costs including increased mortality and decreased fecundity [19]. We investigated KV-induced mortality in D. melanogaster by injecting males and females, with and without Wolbachia, with either control gradient solution or KV. We found that KV caused slightly, but significantly, increased mortality in females compared with controls (21% dead by day 20, vs. 11% in controls, MCMCp = 0.001), but caused a dramatically increased mortality in males compared to females (63% dead by day 20, vs. 14% in controls, sex:virus interaction MCMCp < 0.0001; Fig 2A). Therefore, males appear less tolerant of infection by KV, displaying increased mortality and a lower titre than females. We confirmed the KV-induced male death was not caused by DAV or other unknown small unenveloped RNA viruses present in our initial isolate, as chloroform treatment of the KV isolate eliminated treatment associated mortality (S3 Fig). Male-specific costs of infection are widespread across animal hosts and their pathogens (e.g. [58]), and reduced male tolerance has been found in flies infected with DCV [59]. We found that Wolbachia infection had no detectable effect on KV-induced mortality in males or females, and thus does not affect tolerance (MCMCp = 0.20; S1 Fig). This is consistent with previous studies showing that Wolbachia infection affects resistance and tolerance to RNA viruses but not a DNA virus [56].

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Fig 2. KV causes male-biased mortality, increased lethargy, and decreased fecundity.

(A) Injection of KV virus into OreR flies led to sex-specific mortality. Infected females (red dotted line) experienced a small but significant increase in mortality, but males (blue dotted line) experienced a significantly larger rate of mortality after day 10. Flies injected with control gradient solution were unaffected (solid lines). Each point is the mean and standard error for the proportion of flies alive in each vial (10 vials of 10 flies). (B) Although females remained alive for longer, they were more lethargic. We assessed daily movement of flies injected with either chloroform-inactivated KV (green) or active KV (purple). KV-infected flies moved less from days 3–7 post-infection. (C) Females also displayed altered egg laying behaviour. Thirty pairs of flies were injected with inactive chloroform treated KV (green) or active KV (purple). KV-infected flies laid a slightly, but not significantly, higher number of eggs during early infection (1 and 2 DPI) but laid significantly fewer eggs in late infection (7 and 8 DPI). This reduction in egg laying is due to a shutdown of oogenesis before vitellogenesis (D, E), and ovaries from KV-infected flies house a lower proportion of ovarioles that include late-stage and mature egg chambers (F) and a higher proportion which contain apoptotic nurse cells (G). Ovaries were analysed 10 DPI, and error bars (F,G) show the standard error.

https://doi.org/10.1371/journal.ppat.1007050.g002

We next tested whether female flies suffer sub-lethal fitness costs, by monitoring fly movement for a week following infection. KV-infected female flies showed similar movement patterns to chloroform-treated KV-injected flies for two days post-infection, but from three days post-infection moved significantly less (~70% reduction relative to controls; MCMCp < 0.001; Fig 2B). We conclude that females suffer from increased lethargy resulting from KV infection. In a natural setting, this could translate into fitness costs associated with increased predation, and reduced egg dispersal, mating, and foraging.

Finally, we tested whether KV infection resulted in decreased fecundity by monitoring the number of eggs laid for 8 days post-infection. We found that infected females exhibited markedly different egg laying patterns (MCMCp < 0.001; Fig 2), with KV-infected flies consistently laying fewer eggs between 7 and 8 days post-inoculation. This reduction in egg-laying during late infection could be due to a behavioural response or a cessation of oogenesis. To differentiate between these possibilities, we dissected ovaries, and determined the proportion of ovarioles that contained mature egg chambers. We found that ovaries from KV-infected flies halt oogenesis around stage 8 (MCMCp < 0.001), before vitellogenesis, and house an increased number of apoptotic egg chambers (MCMCp < 0.001) (Fig 2). This phenotype is similar to that seen upon starvation [60], and could be the manifestation of a trade-off to reroute resources to fighting infection, or of sickness-induced anorexia (e.g. [61]). Alternatively, this could be a direct consequence of viral infection, consistent with the gonadal atrophy reported for HzNV-2 [57]. Future studies should address whether this phenotype is a direct or indirect consequence of infection, and if the latter, whether it is orchestrated by the host or the virus.

Variation in titre and mortality following KV infection

The DGRP [37] have previously been used to dissect genetic variation underlying resistance and tolerance to bacterial, fungal, and viral pathogens [12,13,62,63]. We infected 125 DGRP lines with KV and estimated broad-sense heritabilities (H²: the proportion of phenotypic variance attributable to genetic line) and coefficients of genetic variation (CV_G: a mean-standardised measure of genetic variation) in viral titre and LT50 values in females, and LT50 values in males (Table 1). Our estimates of H² and CV_G fall within the range found for resistance to other pathogens in the DGRP, although direct comparison is difficult as studies are inconsistent in the statistics used to report genetic variation. H² in survival following infection with an opportunistic bacterium or fungus was similar to our estimate for survival following KV infection (Pseudomonas aeruginosa: H² in males = 0.47, H² in females = 0.38; Metarhizium anisopliae: H² in males = 0.23, H² in females = 0.27; 13), although comparing heritability can be easily confounded by differences in environmental (residual) variance [41]. Genetic variation in resistance has also been measured in response to two non-native D. melanogaster viruses (Flock House Virus and Drosophila affinis Sigma Virus) and two native viruses (DCV and DmelSV) in females of the DGRP. Of these, the lowest heritabilities are those associated with resistance to non-native fly viruses (FHV: narrow sense heritability h² = 0.07, CV_G = 7; D. affinis sigma virus: h² = 0.13), and the highest are associated with native fly viruses (DCV: h² = 0.34, CV_G = 20; DmelSV: h² = 0.29). Although Magwire et al [12] inferred h² as half V_G and accounted for the homozygosity of inbred lines when inferring CV_G, it is clear that V_G for resistance to KV is closer to the V_G for resistance to other native fly viruses than to non-native ones, at least for survival. It is also notable that CV_G estimates for survival are higher than estimates for titre, consistent with the observation that traits more closely related to fitness are expected to have higher CV_G values [41].

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Table 1. Trait means, genetic variance (V_G), total phenotypic variance (V_P), heritability (H²), and coefficient of genetic variation (CV_G) in titre and mortality following KV infection in the DGRP.

https://doi.org/10.1371/journal.ppat.1007050.t001

We calculated genetic correlations between male and female mortality, and between viral titre and mortality in females (Fig 3). Note that we found no correlation between survival time following KV infection and published estimates of longevity in the absence of infection, nor to resistance to any other RNA viruses [12,64]. We found a strong positive correlation between males and females in median survival time following KV infection (0.57 [0.34–0.78]; MCMCp <0.001), such that lines in which infected males die quickly are also lines in which infected females die quickly, suggesting a shared genetic basis for early lethality following infection. We also surprisingly find a positive genetic correlation between viral titre and LT50 values (r = 0.32 [0.05–0.59], MCMCp = 0.017), such that fly lines that achieved higher titres on day 8 tended to live slightly longer. However, the effect size is small (a doubling of viral titre led to a half-day increase in median survival time) and the result is only marginally significant. The absence of a negative correlation is counter-intuitive, and contrasts with infection of the DGRP with Providencia rettgeri and Metarhizium anisopliae, and infection across Drosophila species with DCV, where fly lines or species with higher parasite loads suffer increased mortality [13,63,65]. This apparent decoupling of titre and mortality could result from inherent costs associated with the induction of an immune response, whereby flies that raise a more potent immune response keep KV at lower titres but induce greater tissue damage.

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Fig 3. Genetic variation in resistance to KV.

(A) We measured LT50 in both sexes, and titre in females, following KV injection in the DGRP. For titre, each bar represents the mean (and standard error) titre relative to fly genome copy-number, as assessed by qPCR for 5 vials of 10 flies for each of 125 DGRP lines. For LT50, each bar represents the mean time until half the flies (in a vial of 10) were dead, for three vials per line, per sex. (B, C) We used a multi-response linear mixed model to calculate genetic correlation between the traits. Shown are the raw data (left), and the estimated line effects (right) after accounting for any injection date and qPCR plate effects, and for the estimated variance among lines. Each point is a DGRP line measured for both phenotypes. We find a strong positive correlation between male and female LT50 values (B). We also observe a weak positive correlation between titre and LT50 (C).

https://doi.org/10.1371/journal.ppat.1007050.g003

Identification of candidate genes underlying host variation in KV titre

Using the phenotypes in the DGRP lines measured above, we performed a genome-wide association study to identify candidate genes underlying variation in titre, LT50, and differences in LT50 between the sexes. We found 10 SNPs (9 near genes) that were significantly associated with viral titre (p_rand < 0.05, based on 1000 random permutations of phenotypes across lines; Fig 4). The SNP with the smallest p-value appeared in Lipophorin receptor 2 (LpR2), which encodes a low-density lipoprotein receptor, previously found to be broadly required for flavivirus and rhabdovirus cell entry (e.g. [66–68]).

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Fig 4. Genome-wide association of polymorphism in the DGRP with KV-induced titre and mortality.

Manhattan plots showing the p-value for the effect of each polymorphism on viral titre (purple) and mortality (green). The top SNPs for each phenotype are shown in expanded inset panels, including surrounding genes. For clarity “CG” is omitted from gene identifiers. Horizontal lines show significance thresholds obtained through randomisation (p_rand = 0.05 in blue; p_rand = 0.01 in red).

https://doi.org/10.1371/journal.ppat.1007050.g004

We tested whether these candidate polymorphisms were enriched in any molecular, biological, or cellular processes using a GO enrichment analysis, and found the top hit to be the torso signalling pathway with 2 genes of 34 in the category (p = 0.0004), tailless and daughter of sevenless (dos). Torso signalling is upstream of extracellular-signal-regulated kinase (ERK) pathway activation in some tissues, and human orthologues of dos (GAB1/GAB2/GAB4) are cleaved by an enterovirus-encoded protease, thereby activating ERK signalling and promoting viral replication [69,70]. ERK signalling is also an important regulator of virus replication in the fly midgut, where it couples nutrient availability with antiviral activity [71,72]. See S1 Table for a list of all nominally significant SNPs with associated locations, mutation types (e.g. intronic, synonymous coding, etc), nearby genes, p-values, effect sizes, and GO terms.

Identification of candidate genes underlying host variation in KV-induced mortality

We found 86 SNPs (65 near genes) that were significantly associated with LT50 following KV infection in the DGRP (p_rand < 0.05; Fig 4 and S1 Table), none of which were identified in the GWAS for viral titre. We performed a GO enrichment analysis, and found genes associated with these SNPs were enriched for hydrolase activity (top molecular function GO term, p = 0.0004), stem cell fate determination (top biological process GO term, p = 0.002), and in the plasma membrane (top cell component GO term, p = 0.004), among others (S2 Table). Of these 86 SNPs, we found 34 (26 near genes) that were highly significant, and selected these for further analysis and confirmation (p_rand < 0.01; see S1 Table for all significant SNPs). The polymorphism with the most confident association was located in Cdc42-interacting protein 4 (Cip4), a gene involved in membrane remodelling and endocytosis [73,74]. This SNP is intronic in the majority of Cip4 transcripts, but represents a nonsynonymous polymorphism segregating leucine and proline in the first exon of Cip4-PB and Cip4-PD isoforms, perhaps indicating spliceform-specific effects on KV-induced mortality. Of particular interest from the remaining 33 highly significant SNPs was a synonymous SNP in the receptor tyrosine kinase, sevenless, known to interact with dos (above), and seven genes (Dgk, Atg10, ATPCL, Hppy, Pkcdelta, Gprk2, Pdcd4) previously implicated in viral pathogenesis or general immune processes. Of these, three (Gprk4, hppy, Pkcdelta) are involved in NF-κB signalling [75–77]. ATPCL was identified in an RNAi screen for factors regulating Chikungunya virus replication in humans [78] and is involved in the late replication complexes of Semliki Forest Virus [79]. Finally, Atg10 and Pdcd4 are involved in autophagy and apoptosis, respectively, both broadly antiviral cellular functions known to have a role in antiviral immunity in Drosophila [80,81]. We found no SNPs significantly associated with sex-specific KV-induced mortality (S4 Fig).

Confirmation of GWAS hits

We chose 18 GWAS-candidate genes with available UAS-driven RNAi constructs to verify their involvement in KV infection. We found that knockdown of Cip4 and CG12821 caused significantly increased viral titre, and knockdown of sev and dos resulted in significantly decreased viral titre, relative to other knockdown lines (Figs 5 and S5). We confirmed tub-GAL4>Cip4^IR flies had reduced (26% of wild-type) Cip4 RNA levels and a concomitant increase in viral titre relative to the genetic background control (3.4-fold increase, 95% C.I. 1.3–9.6 fold) (Fig 5). This strongly suggests that Cip4 is a KV restriction factor that likely segregates for functional polymorphism affecting survival following KV infection (Fig 5). It is known that baculovirus budded virions enter cells through clathrin-mediated endocytosis or micropinocytosis [82,83], and gain their envelope at the cell membrane upon exit [84]. Cip4 could therefore plausibly enact an antiviral effect by limiting KV cell entry or spread, perhaps through its known function in cell membrane remodelling and trafficking.

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Fig 5. Confirmation of antiviral genes identified in GWAS.

KV titre was measured in flies expressing a foldback hairpin targeting 18 genes identified in the GWAS, using GAL4 lines that knock each down in either the whole fly or specifically in the gut. (A) The data were used to estimate random effects associated with each gene knock down, plotted with 95% highest posterior density intervals. (B) Knock-down of the most confident association in the GWAS, Cip4, caused reduced Cip4 RNA levels and (C) increased viral titre. (D) The associated variant (3L_4363810_SNP), was polymorphic (G/A), representing a nonsynonymous polymorphism in some splice variants, and survival following KV infection was significantly increased in fly lines with the “A” genotype, especially in females. Each point in comparison of survival in the two genotypes is a line mean. (*MCMCp < 0.05).

https://doi.org/10.1371/journal.ppat.1007050.g005

Differential expression following KV infection

Previous transcriptional profiling in response to RNA virus infection has shown upregulation of heatshock proteins, JAK-STAT, JNK, and Imd pathways [4,28,85,86]. However, the D. melanogaster expression response to a DNA virus has not previously been investigated. We separately injected male and female flies with control gradient solution or KV and extracted mRNA for sequencing 3 days post-infection. KV gene expression increased dramatically 3 days post-inoculation, consistent with our qPCR analysis of genome copy-number (Figs 1 and S10). Although not previously detectable by PCR, RNAseq read mapping identified a low level of DAV in both control and KV-infected flies, with an overall higher level in KV-infected flies. To account for this potentially confounding contaminant, we fitted the number of DAV-mapped reads as a covariate in the differential expression analysis, and used a stringent Benjamini–Hochberg adjusted significance threshold of p < 0.001 to infer nominal significance. We found 54 genes upregulated and 79 genes downregulated in response to KV in either males or females (Fig 6 and S3 Table). There was no enrichment for GWAS hits among the KV-responsive genes (S6 Fig). Principal components analysis on depth-normalised read counts separated males and females along PC1 and partially separated KV-infected and control-injected libraries along PC3 (S7 Fig). GO term analysis identified ‘defense response to virus’ (p = 3.1x10^-4), ‘serine peptidase activity’ (p = 1.2x10^-7, identified in part due to downregulation of Jonah family serine proteases), and ‘chorion’ (p < 1x10^-8) as the most highly enriched biological process, molecular function, and cellular component, respectively (Fig 6 and S4 Table). Subsequent network analysis identified a large pathway of interactions enriched for genes either differentially expressed or associated with variation in KV infection, including known defense response genes (S8 Fig).

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Fig 6. KV induces differential regulation of chorion, virus defense, and serine endopeptidase genes.

(A) Volcano plots showing fold changes and p-values from Wald tests for differential expression of D. melanogaster genes following KV infection for females (left), males (center), those different between the sexes (right), with DAV read count fit as a covariate and nominal significance threshold of p < 0.001. In each panel, the genes with the smallest p-values are labelled. All of the genes that were significantly differentially regulated between the sexes are highly significant in females. (B) Highly induced genes are mostly functionally unannotated, but include some with known roles in viral pathogenesis. (C) The male response is correlated with females, but muted, with few genes identified as significantly differentially expressed in males. Genes with weak evidence of differential expression in either sex (p < 0.05) are plotted, where the dotted line represents a perfect correlation, and red points are genes identified as significantly differentially expressed. (D) The top GO enrichment terms for each GO class (Molecular Function, Biological Process, Cellular Component) were genes involved the chorion, virus defense, and serine peptidase activity. For each plot, estimated fold changes and their associated standard errors are plotted for every gene matching the GO term, regardless of the significance of the Wald test. Generally, chorion genes were downregulated, virus defense genes were upregulated, and serine peptidases were downregulated.

https://doi.org/10.1371/journal.ppat.1007050.g006

There are few described induced antiviral immune effectors in Drosophila (e.g. [81]). In line with this we observe 57% of differentially expressed genes have not yet been named (i.e. “CG” genes), significantly greater than the genome-wide rate of 41% (p = 3x10^-4), and the most highly induced genes have not been implicated in viral pathogenesis. The cytochrome P450 family gene Cyp304a1 was most highly upregulated, concomitant with the upregulation of four other genes in this family (Cyp309a1, Cyp309a2, Cyp4p3, and Cyp6a20). The next most highly induced genes include the hemocyanin Larval serum protein 2, the cytidine deaminase CG8353, four genes without functional annotation or recognisable domains (CG33926, CG31955, CG32368, CG13641), and an additional six genes without functional annotation (CG43064, CG42825, Gagr, CG10211, CG17264, and CG17224 –the last two of which are adjacent on chromosome arm 2L). We also note the striking but variable upregulation of 11 of the 24 Tweedle genes (S9 Fig) in some (but not all) of the infected samples. These are secreted, insect-specific cuticle proteins that regulate body shape [87], and are also upregulated in response to Sindbis virus infection in cell culture [88], perhaps suggesting a general role in viral pathogenesis.

Genes with known involvement in viral pathogenesis were also found to be induced following KV infection. The RNAi effector AGO2 was upregulated, consistent with the previous results that DNA viruses are a target of the RNAi pathway [21,28,29]. Vago, an antiviral factor downstream of Dicer-2 [89], was upregulated and was also adjacent to a SNP found in the mortality GWAS (dos; Figs 4 and 6), as were pastrel and ref(2)P, identified in previous genome wide association analyses for resistance to DCV and DMelSV, respectively. Finally, we found that KV induced expression of CG1667, the Drosophila homologue of STING. The vertebrate cGAS-STING pathway is involved in cytosolic DNA sensing and activation of immune factors in response to DNA virus infection [90]. This upregulation of CG1667 may suggest that this is another pathway conserved between Drosophila and vertebrates.

As we had observed male and female differences in KV-induced mortality and titre (Figs 1 and 2), we tested for sex-specific transcriptional regulation in response to KV infection. We found that females and males had similar patterns of differential expression following KV infection (spearman rank correlation coefficient, ρ = 0.57, p = 2.2x10^-16), although the male response was often less potent (Fig 6). Nine genes were significantly differentially expressed (p < 0.05) between the sexes specifically in response to KV (S3 Table), and these were all downregulated in females and highly enriched for genes associated with the chorion (Fig 6 and S4 Table). Strikingly, all but three genes classified with the GO term ‘chorion’ were downregulated in females (Fig 6), consistent with the observed reduction in mature ovarioles and eggs during late infection, and implying a substantial reorganization of oogenesis (Fig 2). We did not identify any previously described immune genes with significant sex-specific regulation during KV infection.