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Haemolymph removal by the parasite Varroa destructor can trigger the proliferation of the Deformed Wing Virus in mite infested bees (Apis mellifera), contributing to enhanced pathogen virulence

The association between the Deformed Wing Virus and the parasitic mite Varroa destructor has been identified as a major cause of worldwide honey bee colony losses. The mite acts as a vector of the viral pathogen and can trigger its replication in infected bees. However, the mechanistic details underlying this tripartite interaction are still poorly defined, and, in particular, the causes of viral proliferation in mite infested bees. Here we develop and test a novel hypothesis - grounded in ecological predator-prey theory - that mite feeding destabilizes viral immune control through the removal of both viral ‘prey’ and immune ‘predators’, triggering uncontrolled viral replication. Consistent with this hypothesis, we show that experimental removal of increasing volumes of haemolymph from individual bees results in increasing viral densities. In contrast, we find no support for alternative proposed mechanisms of viral expansion via mite immune-suppression or within-host viral evolution. Overall, these results provide a new model for the mechanisms driving pathogen-parasite interactions in bees, which ultimately underpin honey bee health decline and colony losses.


Background
Efficient pollination is vital for crop production (1) and the honey bee is the prevailing managed insect crop pollinator. Honey bees suffer from a range of adverse factors (2); in particular, the Deformed Wing Virus (DWV) is implicated in the substantial colony losses reported in many parts of the world (3). The parasitic mite Varroa destructor plays a key role in virus transmission and replication (4,5); however, there are still alternative and not fully resolved hypotheses about the major mechanisms underpinning the Varroa-DWV interaction.
The capacity of the Varroa mite to transfer DWV was proved by Ball (6) and later confirmed under field conditions (7); these authors also provided preliminary evidence for the replication of the virus within the mite, which was later confirmed (8). However, the mite does not act only as a vector of the virus, thus increasing the pathogen's prevalence, but can also trigger uncontrolled replication in infected bees, which undermines colony survival (9). Initially, increased replication was attributed to a direct immune suppressive action exerted by the mite (10) but this hypothesis was later questioned (11). It has been suggested that intense replication in infested bees, leading to the development of the characteristic symptom of an overt viral infection, represented by crippled wings at eclosion, is related to the active replication of the virus within the infesting mite (8). However, high DWV copy numbers are frequently detected in bees that are not mite-infested and a clear relationship between viral load within the mites and that in infested bees was not found in all cases (12). Based upon field experiments aiming at assessing the impact of Varroa infestation on bees, we showed that the immune challenge represented by the feeding mite amplifies existing viral infections through an escalating bee immunosuppression, perpetuated by the increasing DWV abundance (9). On the other hand, a study describing Varroa invasion into a previously mitefree area showed that this was associated with increased DWV prevalence and infection rates, as well as a rapid selection of a single virulent strain, adapted to mite transmission and associated with colony collapse events (13). This facilitation seems to take place also at the individual level when a mite infests a honey bee, where either parasitization or artificial injection favours the replication of a single quasi-clonal DWV strain within the bee (12).
In sum, in spite of the large body of evidence about the effect of mite infestation on the dynamics of viral infection in the honey bee and the importance of the Varroa-DWV association for honey bee health, there are still alternative and not fully resolved hypotheses on the major underpinning mechanisms. Actually, the available data can also support further and non-contrasting views on how mite feeding can influence the viral titer in bees. In particular, the significant increase in the viral titers of bees infested by three mites versus a single mite (9) and previous observations about the effects of multiple mite infestation on the proportion of symptomatic bees (14) suggests that feeding intensity may play a role. When more Varroa mites parasitize the same bee, they make a single wound into the bees' cuticle to access the haemolymph, and feed from the same opening (15,16). Thus, the immune response (in particular, melanisation pathways) will be similar for one versus three mites. However, three mites will extract a substantially higher volume of haemolymph from the bee than a single mite, and thus may impact the system by this process. The critical importance of haemolymph removal on DWV dynamics seems to be confirmed by the proliferation of DWV that can be observed after simple wounding with capillary needles and the resulting bleeding from the open wounds (11). Indeed, on a purely theoretical background, it is possible to hypothesize that the concurrent removal of virus particles and circulating antiviral immune effectors by the blood feeding mite can determine a dynamic response similar in principle to that observed when both preys and predators are constantly removed from a predator-prey system (17). Therefore, in order to clarify the causes of viral proliferation in mite infested bees, we carried out controlled lab experiments aiming at testing the existing hypotheses and, in particular, we used both a theoretical analysis and in vivo experiments to test the possibility that mite feeding destabilizes viral immune control through the removal of both viral 'prey' and immune 'predators', triggering uncontrolled viral replication.

Bees and mites used in this study
The biological material (honey bee worker larvae and Varroa destructor adult females) was obtained from an experimental apiary located in Udine (Northeastern Italy). Previous studies indicated that local colonies are hybrids between Apis mellifera ligustica Spinola and Apis mellifera carnica Pollman (18).

Artificial infestation of bees with V. destructor mites
The bee larvae and the mites were collected from brood cells capped 0-15 h previously.
Larvae obtained as above were transferred into gelatine capsules (Agar Scientific Ltd., 6.5 mm diameter), artificially infested with one mite or left uninfested, and maintained in an incubator (34 °C, 75% R.H., dark) until the adult emergence (19) (Fig. 1A). Newly emerged adult bees and the infesting mites were stored at -80 °C for subsequent molecular analyses.
Sixty bees per experimental group were prepared with this method, which, after removing dead bees and mites, resulted in 40 non parasitized honey bees (32 DWV positive) and 32 parasitized honey bees (30 DWV positive) together with 32 infesting mites (27 DWV positive), that were used in the analysis (Fig. 1B). To confirm the results on the distribution of viral infection levels in mite infested bees, another 58 infested bees, prepared as above, were analysed subsequently.
In order to test the relative importance of immunity on the increased viral titer normally observed in multiple infested bees, we artificially infested with no, one or three mites five last instar honey bee larvae obtained as described above ( Fig. 2A) and compared the expression of immune genes in those bees, as described below.

Study of the effects of an increasing haemolymph subtraction on viral replication
This experiment was designed to assess the effect of the removal of an increasing haemolymph volume, in absence of feeding mites, on the dynamics of DWV titer in naturally infected honey bees. Last instar bee larvae were collected from a brood comb as described above and maintained in an incubator (34 °C, 75% R.H., dark) until the white eyes stage, which occurred about 4 days after the collection from brood cells sealed in the preceding 15 hours. Then, 4 experimental groups, made of about 30 pupae each, were established. One group ("control") was left untreated, whereas all the other bees had the right antenna cut, at the level of the scapum, using fine scissors; pupae bleeding after cutting were discarded. Bees of one group ("wound") had the wound sealed with a cream containing Sulfathiazole (2%) and Neomycin sulfate (0.5%) to prevent secondary infections. Bees of the remaining two groups ("wound −1 µL" and "wound −2 µL") had the wound sealed as above, after removing either 1 or 2 µL of haemolypmh, with a microcapillary tube precisely graduated with 1 or 2 µL of ethanol, dispensed through a micropipette; untreated bees acted as further basal control.
By subtracting increasing amounts of blood, we tried to assess the effect of pure haemolymph subtraction, while minimizing the impact of wounding and the resulting immune reaction.
After treatment bees were kept into a Petri dish, lined with sterile filter paper, and maintained under dark, at 34 °C, 75% R.H., for 4 four days, before assessing the viral titer as described below. To account for the variability across colonies and genotypes, the experiment was repeated four times: on 2 colonies in Udine (Northern Italy) and 2 colonies in Napoli (Southern Italy).

Quantification of DWV concentration in the honey bee haemolymph
Haemolymph was collected from late instar honey bee larvae by puncturing with an entomological needle the dorsal vessel and collecting the bleeding fluid with a capillary tube.
Haemolymph was added to an Eppendorf tube containing the same quantity of anti-coagulant buffer (20), mixed and centrifuged at 1000 g for 10 min at 4 °C. Then, the supernatant containing the plasma was discarded and DWV quantified as described above.

Molecular analyses
Sequencing of DWV, quantitative DWV analysis, analysis of DWV mutant cloud, DWV Negative strand quantitative analysis and the transcriptomic study of bees were carried out using standard methods described in detail in SI Materials and Methods.

Statistical analysis of experimental data
The proportion of infected bees (Fig. S2) was compared by means of a Chi Square test; the confidence intervals reported in the figure were calculated with the formula: 1.96√(prop(1prop)/n). The skewness of the distribution of viral loads across samples was calculated after excluding samples were the virus had not been detected.
Since the normality of the distribution of data about viral infection in bees, as assessed by real time RT-PCR, is not warranted, non-parametric methods were preferred to standard parametric analysis. In particular, the correlation between viral load in mites and bees infested by those mites (Fig. S5) was tested by means of Spearman rank. Comparison between infection levels in bees belonging to different experimental groups was carried out by means of a Mann-Whitney U test ( Figures 1B, 1C, 1D) or Kruskal-Wallis ( Figures 2B, 3).
For the statistical analysis of transcriptomic data, see the respective section.

Theoretical analysis
In ref. 9 we presented a series of models capturing the coupled within-host dynamics of viral copy number (V) and a shared immune currency (I). The most parsimonious model analysed further in the current paper included an immuno-suppressive effect of high viral load, as described by the following ordinary differential equations These equations describe the within-host growth of a pathogen population V and its controlling immunological counterpart I. The maximal rate of pathogen replication is r, which is countervailed by a rate of immunological control cI. The dynamics of I are shaped by an intrinsic production rate a, a rate of decay u, and activation / suppression parameters b and s.
This model implementation ensures that the sign of the impact of virus on immune dynamic (immuno-stimulatory or immuno-suppressive) will depend on viral titre, V. Specifically, we assume that at low densities the pathogen is a net activator of immunological activity, whereas at high densities (whenever V > b/s) the pathogen becomes immuno-suppressive, with b/s controlling the threshold point between the two regimes.
To clarify presentation, we again work with a normalized version of equations (S1 in ref. 9) to reduce the parameter dimensions. Specifically, we rescale the units of time to the maximal growth rate of the virus (t = rt), the units of viral density to the density that halts immune proliferation (V = Vs/b) and the units of immune density to the density that halts viral proliferation (I = Ic/r). Applying these normalizations to equations (S1) lead to the following equations (dropping the bold font for clarity) Note that the full system (S1) can be recovered from (S2) by rescaling the units and replacing parameters as follows: For an equilibrium analysis of equations S2, see ref. 9.
In order to introduce a constant loss of both DWV particles and circulating immune effectors from the system, as caused by the mite feeding upon the bee's haemolymph, we introduce a rate of I and V loss m (scaled to growth rate r in this dimensionless form) such that the system In reference 9 we demonstrate for the m = 0 case that there is a lower stable and upper unstable equilibrium in V, which converge as y increases from zero (see figure 6 in ref. 9). In system (S3) the equilibria become In figure S8 we plot these equilibria as a function of increasing haemolymph removal rate m, and observe a decline in immune effectors and an increase in the lower stable equilibrium. To better understand the generality of this effect, we study !"#$!" * , and in the limit of small m, we find a tractable result, !" !" which is positive for reasonable parameter choices -specifically when y < 1 and x > y -z/4.

Viral infection in parasitized honey bees
To clarify the role of the mite in the dynamics of viral infection in honey bees, we evaluated the presence and abundance of DWV in adult bees that were artificially infested with one mite as mature larvae or were not infested with mites as controls (Fig. 1A); viral presence and titers were evaluated using quantitative real time PCR with sequence-specific DWV primers.
Furthermore, a subset of these bees (see Fig. 1B) was subjected to Next Generation Sequencing (NGS) which allowed us to confirm that the bees were infected with DWV and the sequences were >98% identical with a published sequence obtained from a sample We found that 80% of individuals not exposed to mite feeding (n=40) were DWV infected.
However, the prevalence of DWV in bees infested by a DWV-infected mite (n=27) was higher at 96% ( However, DWV infection levels showed even greater variability in mite-infested bees; in fact, most mite-infested bees showed infection levels falling within the same interval as that recorded in uninfested bees, but a few specimens largely exceeded the upper limit of this interval, reaching 10^10 viral genome copies per bee (Fig. 1B). Consequently, the distribution of viral loads was very skewed in mite-infested bees (skewness of the distribution of viral loads in mite infested bees (n=30)=5.48, skewness in uninfested bees (n=32)=2.50).
Individual bees sampled later in the field season, when the DWV prevalence and the basal infection rate are higher (9), and artificially infested with one mite, showed a similar skewed distribution of infection levels, with some individuals displaying very high DWV infection levels (skewness of the distribution of viral loads in mite infested bees (n=58)=5.66; Fig. S3).
Moreover, re-evaluation of previous data demonstrating the effect of single and multiple mite infestation on viral loads in bees (9) revealed a similar underlying distribution, with a higher median viral infection in mite-infested bees and the distribution of viral loads becoming increasingly sparse (Fig. S4). In sum, the DWV infection data show that the higher viral load observed, on average, in infested bees is due to a change in the distribution of individual viral levels, which is right skewed, due to the presence of a sub-population of highly infected bees as already observed using a different experimental setup (12).

Viral replication in mites
To study the vector role of Varroa, we evaluated the mites infesting the experimental bees above (Fig. 1A) and found that their infection levels were generally higher than those in the bees themselves (median viral load in mites (n=32)= 5.56E+11). A significant correlation was found between the mites' viral load and viral load of the bees they infested ( Fig. S5 Active replication of single stranded positive RNA viruses results in the synthesis of the complementary negative strand that is used as a template for the production of viral copies. Therefore, to assess the importance of viral replication within the mite on the level of bee infection, we assessed the presence of DWV negative strands in the mites used for the artificial infestation of bees (Fig. 1A). As expected, the mites containing DWV negative strands had a significantly higher infection level than those where no negative strands were found ( Fig. 1C; Mann-Whitney U=42, n 1 =9, n 2 =23, P=0.005). However, when we examined whether the viral replication in the parasite was related to the viral load in the host, we found that the infection level of bees infested by mites where an active viral replication was detected was not significantly different from that measured in bees infested by mites which did not apparently harbour an actively replicating virus ( Fig. 1D; Mann-Whitney U=80, n 1 =9, n 2 =23, P=0.157).

Composition of the viral mutant cloud
Short replication time and limited correction capability in RNA viruses favour rapid genetic changes, so that, even in a single host, a virus population normally consists of an ensemble of different genetic sequences (i.e. quasi-species). To study the composition of the viral mutant clouds in bees with different levels of viral infection, we amplified and sequenced by NGS the viral region encoding the virus RNA dependent RNA polymerase, by individually sequencing 5 highly infected bees and 5 bees with low infection levels (average DWV genome copies per bee of 1.41E+09 and 1.95E+03, respectively) that were obtained from the previous experiment (see Fig. 1B). From 74 to 559 different variants were reconstructed in each sample, based on a number of viral reads ranging from 40,107 to 160,842. We found no obvious common sequence in low vs high virus infected bees: the most represented sequence was present in six samples from both the low and highly infected groups, at prevalences ranging from 11 to 74% (Fig. 1E). Thus, a link between viral load and molecular diversity was not found (Fig. 1E, Fig. S6).

Effects of mite infestation and viral infection on the transcriptome of honey bees
To disentangle the effect of the Varroa mite parasitization from that of DWV infection on the immune response of bees, we studied the expression of immune genes in bees exposed to a different combination of stress factors (see confirmed that immune-suppression by the mites (10) does not play a major role.

Immune-virus 'predator-prey' dynamics within the host
In 2012, we proposed a series of mathematical models describing how within-host viral dynamics are controlled by immunological response, which in turn can be modified by the presence of the virus and other stress conditions, such as mite feeding or pesticide exposure (9,22). The simplest model consistent with the observation of divergent outcomes (lowcryptic or high-overt infection) required a threshold immune-suppressive effect of DWV.
Given this assumption, any factor that depletes the immune system (e.g. increasing mite load) will lead to a gradual increase in a stable DWV set-point until, for sufficiently large depletion, a critical transition to unbound viral replication will follow, leading to overt symptoms and ultimately host death. We hypothesized that, in case of mite infestation, immune depletion may result from the activation of competing immune reactions cross-modulated by shared networks of transcriptional control and, in particular, the melanisation and clotting reactions triggered at the mite's feeding site, which are under the control of a NF-kB transcription factor that is involved also in antiviral response (9, 23).
Here we mathematically explored the possibility that the concurrent removal of virus particles and circulating antiviral immune effectors by the blood feeding mite can determine a dynamic response similar in principle to that observed when both preys and predators are constantly removed from a predator-prey system (17), by adding to the existing models, which incorporate the depletion of the bee's immune resources related to the wounding by the parasitic mite (9), a constant rate of loss of both virus and immune effectors, resulting from the feeding of the blood sucking parasite. Indeed, according to this new model, increasing the simultaneous removal of both virus and immune effectors drops immunity and increases/destabilises the viral titre (Fig. S7).

Effects of the increasing haemolymph subtraction on viral proliferation
In order to verify this hypothesis, we carried out another lab experiment by artificially infesting mature bee larvae with one mite or three mites, using non-infested bees as controls, and by assessing both the viral infection level and immune response at eclosion (Fig. 2A). We In particular, the viral infection in bees to which 2 microliters of haemolymph were removed was about ten times higher than that observed in bees which had only 1 microliter of haemolymph removed from a single wound ( Fig. 3; Mann-Whitney U=377, n 1 =n 2 =40, P=0.00002), suggesting that blood subtraction alone can play a role, regardless of the immune reaction at the feeding site.

Discussion
The experimental and theoretical results, we conclude that the stress resulting from mite feeding has the potential of destabilizing the equilibrium between the pathogen and the bee's immune control (9) (Fig. S10D). Here we confirm our previous hypothesis, based on the depletion of a shared immune resource (9,23) and show that the intensity of mite feeding can affect the progression of viral infection through a dynamic process triggered by the concurrent removal of the virus and antiviral effectors, which is well described by models proposed for preypredators interaction (Fig. S10E). The removal of the virus by the feeding mite is a simple consequence of the presence of huge numbers of viral particles in the bee's haemolymph, as confirmed by the significant correlation between viral infection in bees and the mites which fed upon them, that could not be related to an enhanced within-mite replication. As for the possible presence of antiviral effectors in the bees' blood and thus the possibility that the mite can subtract significant amounts of them while feeding, it is worth noting that, despite our knowledge about antiviral defence in the honey bee is still incomplete, convincing evidence has been provided regarding the contribute of haemocytes to antiviral defence through phagocytosis in Drosophila (27) This is a conceptual hypothesis, under which different physiological mechanisms, largely unexplored at molecular level, can fit, and represents the most parsimonious interpretation of the mite role in the enhanced virulence of the virus, providing the logical framework for future experiments aiming to unravel the intimate molecular mechanisms involved.
To our knowledge, this "micro-ecological" perspective of the immune interactions has not been proposed so far for any other blood-feeding parasite and associated pathogens, likely because most species studied from this point of view do not perform a severe bleeding like Varroa mites, and, then, the impact on viral dynamics by blood removal is more limited.
Indeed, V. destructor can consume as much as 0.7 µL of bee haemolymph every 24 h (29), corresponding to the 0.6% of the bee pupa's haemolymph (30), which, according to our data, can contain up to 10^3-10^8 DWV particles per µL, according to the infection level.

Conclusions
We believe that this new information on the interactions within the bee-mite-virus network provides a new vision of the crucial role played by Varroa mite in the re-emergence of DWV, an endemic pathogen of honey bees that plays a key role in the current widespread crisis of the beekeeping industry. Moreover, the proposed "micro-ecological" perspective of the immune interactions has broader implications in the research area of animal parasitology.

Supplementary materials and methods
Sequencing of DWV. The de novo assembly of DWV was performed using CLC Genomics Workbench 9.0. Briefly, simple contig sequences were first created using the information from the read sequences using an assembly algorithm based on de Bruijn graphs -a compact representation based on short words (k-mers) that is ideal for high coverage, very short read (25-50 bp) data setsthen all reads were mapped using the simple contig sequence as a reference. A phylogenetic tree was constructed from two sequences obtained in this study (samples P11 and P31, Fig. 1B-1E)   Amplified products were run on a 1% agarose gel containing 0.5 µg/ml ethidium bromide and then visualized by UV transillumination. The specificity of the RT-PCR assay was confirmed by sequencing analysis. RT-PCR bands were excised from the agarose gel and purified using the Pure Link Quick Gel Extraction Kit (Invitrogen, Carlsbad, CA). The sequence data of the fragment were analysed using the BLAST server at the National Center for Biotechnology Information, NIH. For the RNAseq analysis, the same primer pairs described above were designed with a specific overhang (DWV\RdRp-Forward 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-3'; DWV\RdRp-Reverse 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-3'). All primer pairs were designed by using Primer Express Software (Applied Biosystems). Raw Illumina paired-end reads in forward and reverse orientation were merged using the PEAR software v0.9.8 (32), adaptor trimmed using cutadapt v1.9 (33) and quality filtered using the FASTX Toolkit's fastq_quality_filter program (34) requiring minimum quality of 20 in 95% bases or more. For the study of DWV variants we used a software designed for quasi-species reconstruction from next-generation sequencing data (35). Sequenced fragments were aligned against a reference genome and the reference genome was partitioned into a set of sliding windows, then a reconstruction algorithm based on combinations of multinomial distributions was applied. The selected reference genome was the one most closely related to the DWV samples sequenced in this study (i.e. NC_004830.2; Fig. S1). The analysis output is a collection of sequences with prevalences, which was used for a diversity analysis based on the Shannon index.
DWV Negative strand quantitative analysis. In order to quantify the DWV negative strand in infesting mites, a strand-specific Biotin/Streptavidin method was used. SYBR-Green real-time quantitative PCR (qPCR) as described above was preceded by a specific retrotranscription incorporated with biotinylated-primers (Biotin-DWV-Forward 5'-TCG ACA ATT TTC GGA CAT CA-3'; Biotin-DWV-Reverse 5'-ATC AGC GCT TAG TGG AGG AA-3') and magnetic bead purification by using the Dyna beads KilobaseBINDER Kit following the manufacturer's instructions (Applied Biosystems).
Transcriptomic study of bees. Samples were transferred into liquid nitrogen and the total RNA isolated using Tri-reagent (MRC Inc., USA) (Ambion Inc.). RNA sequencing libraries were generated by means of TruSeq Standard mRNA seq kit Illumina, according to the standard protocol indicated by the producer (Illumina, Inc., CA, USA) and starting from 1-2 micrograms of high quality RNA (RNA Integrity Number >7, Agilent Technologies Bioanalyzer, Agilent Technologies, USA). This protocol produced 25-30 million reads per sample that were 36 bases in length. The sequencing reads were trimmed using ERNE (36) in order to remove low quality reads and the adapters removed with Cutadapt (33). The remaining reads were aligned to the most recent honey bee genome build (Amel 4.5 (37)) with TopHAt2 (38) using default parameters and annotated with the newest official gene set (OGS 3.2). Reads were counted with Htseq count (39) using exons as accepted regions and cumulating the counts at whole gene level. The obtained data were uploaded into DEseq2 (40) to be elaborated by means of VST (Variance Stabilizing Transformation) algorithm and used for the cluster analysis. Five uninfested and 10 newly emerged infested bees, 5 with a high DWV infection level and 5 with a low infection level, were collected from the cages and processed as above (Fig. 1B). Also five newly emerged bees infested with no, one or three mites ( Fig. 2A) were processed as above.
To gain insight into the relative contribution of the Varroa mite and DWV in the alteration of the expression of genes belonging to the canonical immune pathways, we studied the transcriptome of bees exposed to a different combination of stress factors (Supplementary Data 1). In particular, to assess the influence of the mite, we compared the expression level of 191 immune genes, listed in ref.
12, in five uninfested bees bearing a low viral infection (average DWV infection=2.04E+03) and five mite infested bees bearing a similar, low viral infection level (average DWV infection=1.95E+03) (Fig. 1B); instead, to assess the influence of the combination Varroa-DWV we compared five uninfested bees bearing a low viral infection with five mite infested bees bearing a high viral infection level (average DWV infection=1.41E+09) (Fig. 1B). Note that 14 and 151 genes classified in ref. 12 as "immune related" and "immune system process" respectively, were not included in this analysis that concentrated on canonical immune pathways.
Due to the uncertainty about the distribution of data, the comparisons were carried out using the Mann-Whitney U test. Since the purpose of this research was not to gather data about single genes but rather to gain an indication about the involvement of different immune pathways, and keeping into account the moderate probability of type I errors, no correction for multiple comparisons was applied but rather differentially expressed genes were considered as such when probability was below 0.01. To verify the possible enrichment of each immune pathway, the proportion of differentially expressed genes belonging to that pathway out of the total number of DEGs in that contrast was compared with the proportion of genes belonging to that pathway out of the total number of genes considered here; Chi square test was used and, again, the level of probability was set to 0.01. In order to test the relative importance of immunity on the increased viral titer normally observed in multiple infested bees, we artificially infested with none, one or three mites five last instar honey bee larvae obtained as described above and compared the expression of immune genes in those bees, as described above (Supplementary data 2). The proportion of reads mapping onto the DWV genome provided an estimation of the viral infection level in bees whereas a cluster analysis of samples according to the expression of immune genes gave an indication of the effects of an increasing mite infestation on the bee's immunity. FPKM were used as gene expression data. The list of honey bee immune genes proposed by Ryabov et al. (12) was used.
To remove possible outlier samples from the analysis, the mean expression value across all samples for each gene was calculated as well as the standard deviation (note that here samples were considered as belonging to a single big group, in order not to introduce any bias in our preliminary filtering). Then expression values higher or lower than the mean expression value ±2 standard deviations were noted. Lastly the proportions of outlier genes in each sample were considered and samples having more than 25% of outlier genes were excluded (this procedure lead to the exclusion of one single sample out of 15, which appeared to have a number of outlier genes bigger by three fold than any other sample). Then we performed a cluster analysis using "Gene Cluster 3.0" (41) with the following options: centering genes around mean, similarity metrics: correlation (uncentered), clustering method: average linkage. The tree was displayed using "Treeview" (42). Figure S1. Phylogenetic relationship of the DWV infecting the bees used in this study (samples P11 and P31). The dendrogram is based on the complete genomes (nt sequences) of available sequences of DWV strains and related viruses.  Figure S2. DWV prevalence in bees parasitized or not by a DWV infected mite. Error bars represent the estimated confidence limits of the proportion.  frequency DWV genome copies Figure S4. Viral load in individual bees artificially infested at the L5 stage with one, three or no mites and sampled after 1, 6 and 12 days (eclosion). A further sample, parasitized by 3 mites and collected 1 day after eclosion, with infection level=1.22E+03, does not appear on this graph.  Figure S5. Infection level in infesting mites and infested bees. Note that zero values were transformed to 10.

Genes differentially expressed in each contrast
Toll TEP Serine prot. Scav. rec. PPO melan.
Lysozyme JNK cascade JAK-STAT Imd IG superfam. C-lectin dom. Antimicr. pept. RNAi Figure S9. Possible routes of infection of DWV. The bees are represented by squares of different colours according to the developmental stage, the virus is a yellow pentagon and the mite an orange hexagon. Both trans-ovarial (from queen to egg, 1) and trans-stadial (from egg to larva, 2, and from larva to adult, 3) as well as horizontal transmission between nurse bees and larvae (4) and from adult to adult (5) are possible among bees. The Varroa mite can transfer the virus from pupa to pupa (6), pupa to adult (7) and viceversa (8) and adult to adult (9). Note the possible infection routes of the bee larva (2,4), that are possible independently of the mite's presence. The contribution of the mite as a virus vector is highlighted by transmission routes 6, 7, 8, 9. bee egg bee larva/pupa adult bee