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Introduction

Human malaria infects up to 500 million people per year and causes almost 3 million deaths annually (Hay et al., 2004). Traditional control strategies that target the mosquito vector (such as insecticides) are becoming less effective due to the emergence of resistance (Enayati & Hemingway, 2010). Therefore, there is a concerted effort to develop novel strategies to combat arthropod-borne diseases. One such strategy is to use microbes to manipulate components of host vector competence. While some microbes can either directly or indirectly affect Plasmodium development in the host (Cirimotich et al., 2011; Ricci et al., 2011; Hughes et al., 2011a; Hughes et al., 2014), the genetic modification of mosquito symbiotic microorganisms with effector molecules which inhibit pathogens (paratransgenesis) has been proposed as one novel method to control malaria (Favia et al., 2007; Wang et al., 2012). To be a microbial candidate for paratransgenic malaria control, the microorganism should not significantly compromise the host fitness and must be manipulatable to produce effector molecules of interest (Beard, Cordon-Rosales & Durvasula, 2002; Durvasula et al., 2003).

Densonucleosis viruses (or densoviruses (DNVs)) are icosahedral, non-enveloped parvoviruses that have been identified from many invertebrate taxa, including multiple mosquito species (Boublik, Jousset & Bergoin, 1994; Jousset, Baquerizo & Bergoin, 2000; Ledermann et al., 2004; Carlson, Suchman & Buchatsky, 2006; Ren, Hoiczyk & Rasgon, 2008; Zhai et al., 2008; Ng et al., 2011). DNVs are easily to manipulate and are candidate agents for paratransgenic control of vector-borne diseases by expression of toxins or anti-pathogen effector molecules (Ren, Hoiczyk & Rasgon, 2008; Suzuki et al., 2014). Mosquito DNVs are generally lethal to young larvae but are tolerated by older larvae, which develop into infected adults that complete the pathogen life cycle by inoculating virus into the aquatic larval environment (Carlson, Suchman & Buchatsky, 2006). Unlike the Aedes aegypti densovirus (AeDNV), which is generally lethal to young larvae and virulent to adults in a dose-dependent manner (Ledermann et al., 2004), the An. gambiae densovirus (AgDNV) has minimal pathogenic effects in larvae (Ren, Hoiczyk & Rasgon, 2008). In contrast to AeDNV, AgDNV does not replicate substantially in the immature or early adult life stages of An. gambiae, perhaps explaining minimal larval virulence. Instead, AgDNV replicates preferentially in adult mosquitoes (Ren & Rasgon, 2010).

To further evaluate the suitability of AgDNV for use in a paratransgenic malaria control strategy we studied the effect of infection on adult An. gambiae mosquitoes. By examining life history traits and the transcriptomic response of Anopheles mosquitoes to AgDNV infection we found minimal impact of AgDNV upon the mosquito host at the molecular level or upon adult fitness. Taken together, these data suggest that AgDNV could be a useful agent for paratransgenesis in An. gambiae mosquitoes as there is minimal fitness or transcriptome impact on the host after infection.

Materials and Methods

Cell culture, mosquito infection and rearing conditions

Sua5B cells, which are naturally infected with AgDNV (Ren, Hoiczyk & Rasgon, 2008), were passaged weekly in Schneider’s media with 10% FBS. AgDNV was obtained from the infected cell line Sua5B and first-instar mosquito larvae infected by exposure to purified virus as previously described (Ren, Hoiczyk & Rasgon, 2008). Control mosquitoes were mock infected with Schneider’s medium. After infection, mosquitoes were reared in 2L pans according to a standard feeding protocol as described (Ren & Rasgon, 2010).

Life-table analysis

At the pupal stage, cups of emerging pupae were placed in cages and removed 12 h later ensuring that adults were of similar ages. Mosquitoes were allowed access to 10% sucrose but were not blood fed. Mortality was accessed daily at the same time ±1 h. There were 3–4 cages per treatment (approximately 50 mosquitoes per cage), and the entire experiment was replicated three times (total = 740 AgDNV-infected mosquitoes, 860 control mosquitoes). For AgDNV treatments, collected dead mosquitoes were assayed for AgDNV infection by PCR amplification of a ∼300 bp fragment of the AgDNV capsid gene as described (Ren, Hoiczyk & Rasgon, 2008); infection rates per cage ranged from 87% to 100%. The experiment included both males and females, but mosquitoes were not sexed for analysis. Data were analyzed by the Gehan–Breslow–Wilcoxon test using GraphPad Prism 5.

RNA extraction and microarrays

Affymetrix GeneChip microarrays were used to assess the effect of AgDNV infection on An. gambiae gene transcription. First instar larvae were infected or mock infected as described above and reared to adulthood. At 10 days post-emergence when AgDNV titers are at their highest (Ren & Rasgon, 2010) mosquitoes were processed for analysis. For each biological replicate, pools of 20 adult mosquitoes were processed (mosquitoes were not sexed). There were three replicates per treatment. 20 randomly selected mosquitoes per replicate were tested by PCR (Ren, Hoiczyk & Rasgon, 2008) to confirm AgDNV infection; 100% of mosquitoes treated with virus as larvae were positive for infection by PCR compared to 0% of control mosquitoes. Mosquitoes were homogenized and lysed with Lysing Matrix D (MP bio) in 1 ml of Trizol reagent (Invitrogen) by rapid agitation in a FastPrep 120 Instrument (MP Biomedicals, Solon, OH) for 45 s at speed setting 6 and placed on ice for 2 min. Homogenization and ice incubation was repeated twice or until the samples were completely homogenized. After homogenization, RNA was extracted, purified and quantified as previously described (Hughes et al., 2011b). For each array 100 ng total RNA was hybridized to the Affymetrix Plasmodium/Anopheles microarray using the Affymetrix 3′ IVT express kit, according to manufacturer’s recommended protocol. Hybridization cocktails were prepared as recommended for arrays of Standard format using reagents in the Affymetrix Hybridization, Wash, and Stain kit. Hybridization was performed at 45 °C for 16 h at 60 rpm in the Affymetrix rotisserie hybridization oven. The signal amplification protocol for washing and staining of eukaryotic targets was performed in an automated fluidics station (Affymetrix FS450) using Affymetrix protocol FS450_0004. Arrays were transferred to a GCS3000 laser scanner with autoloader and 3G upgrade (Affymetrix) and scanned at an emission wavelength of 570 nm at 2.5 µm resolution. Quality assessment of hybridizations and scans was performed with Expression Console software. Detailed analyses were performed using Partek Genomics Suite version 6.4. GC-RMA algorithm defaults were used for background correction, normalization and summarization of probesets. Analysis of variance (AVOVA) was performed with linear contrasts for each densovirus treatment vs. control. Gene lists were developed based on 1.75 or 2.0 fold change (FC) or greater gene expression using a false discovery rate of P < 0.05. Raw Affymetrix CEL files are available as Supplemental data at http://rasgonlab.files.wordpress.com/2014/08/renetalrawaffymetrixdata.zip (controls: W1.CEL, W2.CEL, W3.CEL; treatment: AgDNV1.CEL, AgDNV2.CEL, AgDNV3.CEL).

qPCR validation of microarray analysis

qPCR analysis was completed as previously described (Hughes et al., 2011b). Briefly, RNA was extracted from pools of ten mosquitoes either infected with densovirus or uninfected using an RNeasy mini kit (Qiagen). Five biological replicates were completed for each treatment. RNA was DNase treated (Ambion) and cDNA synthesized using superscript III (Invitrogen) following manufactures guidelines. qPCR was completed using a Rotor gene Q (Qiagen) using Rotor gene SYBR green PCR kit (Qiagen) according to manufactures guidelines. To validate microarray results we assayed five genes selected both from genes affected and not affected in the microarray analysis (AMMECR1, Rel1, Rel2, cactus and caspar; primers in Table 1). Expression of each target gene was normalizing to expression of the ribosomal protein S7 gene (Table 1). All qPCRs were performed in triplicate. Melt curve analysis was completed on all PCRs. Determinations of relative expression were calculated using qGENE (Joehanes & Nelson, 2008).

Table 1:
PCR and qPCR primer sequences.
Primers used for qPCR validation of microarray results and detection of AgDNV.
Gene name AGAP/GenBank ID# Primers (5′–3′)
Rel1 AGAP009515 Forward: TCAACAGATGCCAAAAGAGGAAAT
Reverse: CTGGTTGGAGGGATTGTG
Caspar AGAP006473 Forward: TCCACACATGCAACCTGTTT
Reverse: CTCGCTGCAGCACAGCGGTA
Rel2 AGAP006747 Forward: CGGTGCTCCTCGTAATGACT
Reverse: GTATCGTTGCGTCGGATTG
Cactus AGAP007938 Forward: GAACGGCTGCGCTTTAACA
Reverse: TCGTTCAAGTTCTGTGCAAGTGT
AMMECR1 AGAP000328 Forward: AAGAGACTCCCGTTTCTCGCCAAT
Reverse: TCGAGCCACGCTCATTGTAGAACT
S7 AGAP010592 Forward: CATTCTGCCCAAACCGATG
Reverse: AACGCGGTCTCTTCTGCTTG
AgDNV capsid gene EU233812 Forward: CAGAAGGATCAGGTGCAG
Reverse: GTTACTCCAAGAGCTACTC
DOI: 10.7717/peerj.584/table-1

Results and Discussion

Life table analysis

We used life table analysis to assess the fitness effects of AgDNV infection on adult An. gambiae (Keele strain) mosquitoes. For replicates 1 and 2, survival trajectories of AgDNV infected and uninfected mosquitoes were not significantly different (Table 2, Figs. 1A and 1B). For replicate 3, mosquitoes in both treatments had significantly elevated mortality compared to replicates 1 and 2, and AgDNV-infected mosquitoes had a slight, but statistically significant reduction in lifespan (P = 0.003) (Table 2, Fig. 1C). We do not know why results from replicate 3 differed from replicates 1 and 2, but the significant reduction (greater than 50%) in lifespan for both treatments in replicate 3 suggests other confounding factors besides AgDNV infection are at play.

Survival of AgDNV infected or uninfected adult Anopheles gambiae.

Figure 1: Survival of AgDNV infected or uninfected adult Anopheles gambiae.

Mosquitoes infected at the larvae stage with AgDNV purified from Sua5B cells (or mock infection as control; WT) were assessed for adult survivorship every 24 h until all the mosquitoes had perished. (A), (B) and (C) refer to replicates 1, 2 and 3 respectively.
Table 2:
Survival statistics for individual experimental replicates.
Replicate Treatment N Mean lifespan (days) Chi-square P value
1 WT 344 24 0.047 0.828
AgDNV 289 25
2 WT 298 23 2.51 0.113
AgDNV 199 22
3 WT 218 11 8.92 0.003
AgDNV 252 9
DOI: 10.7717/peerj.584/table-2

Microarray analysis

To evaluate the effect of AgDNV infection on host gene expression, we completed microarray analysis comparing infected versus uninfected adult mosquitoes. AgDNV infection had very limited effect on An. gambiae gene expression with global expression analysis identifying only 4 genes modestly differentially up-regulated (fold-change (FC) ≥ 2, P < 0.05) in response to infection, and no genes significantly down-regulated (Table 3). qPCR of selected genes showed similar results (R2 = 0.84, P = 0.03; Fig. 2). These results are in stark contrast to the effect of the human pathogen O’Nyong-nyong virus in An. gambiae, where infection resulted in the regulation of 253 genes (152 up-regulated, 102 down-regulated), including many genes involved in anti-viral and innate immune pathways (Waldock, Olson & Christophides, 2012). However, our results are similar to other studies examining gene expression in response to DNV infection in other insects. Minimal effects on host gene expression were seen in the moth Spodoptera frugiperda with the up-regulation of only 8 genes after injection of DNV into fat body tissue (Barat-Houari et al., 2006). Using subtractive hybridization to identify differentially expressed genes in Bombyx mori in response to virus infection, only 28 genes were found in a moth line resistant to DNV, while infection in susceptible line lead to differential expression of 23 genes (Bao et al., 2008). While infection with other microbes profoundly affects gene expression in An. gambiae (Abrantes et al., 2008), AgDNV (and DNVs in general) seem to neither strongly elicit nor suppress global gene expression patterns. Further studies are required to ascertain whether the virus employs mechanism(s) to avoid modulating the host transcriptome.

qPCR validation of microarray data.

Figure 2: qPCR validation of microarray data.

Validation of microarray data in DNV-infected adult An. gambiae mosquitoes. Log2 fold change values for both microarray and qPCR methods were compared for 5 selected An. gambiae genes (AMMECR1, Rel1, Rel2, cactus and caspar). P = 0.03.
Table 3:
Significantly regulated (P < 0.05, FC >1.75) genes in AgDNV-infected An. gambiae mosquitoes identified by microarray analysis.
Affymetrix probe AGAP number Gene Function P value Fold-change
Ag.3R.866.0.CDS_at AGAP008277 TRYPSINOGEN 2 Peptide bond hydrolysis 0.0148 2.40
Ag.X.430.0_CDS_at AGAP000328 AMME SYNDROME CANDIDATE GENE 1 Unknown 0.0093 2.21
Ag.X.341_CDS_a_at AGAP001039 CYTOCHROME P450 Redox 0.0327 2.20
Ag.3R.900.4_s_at AGAP009368 PLUGIN Mating plug 0.0400 2.00
Ag.2L.2922.0_a_at AGAP007116 CONSERVED HYPOTHETICAL PROTEIN Unknown 0.0399 1.99
Ag.2L.1432.0_CDS_a_at AGAP006418 VENOM ALLERGIN Secreted 0.0439 1.80
Ag.3R.292.0_CDS_a_at AGAP009036 SODIUM/HYDROGEN EXCHANGER CELLULAR
RETINALDEHYDE BINDING
Ion transport 0.0171 1.75
Ag.3R.1298.0_CDS_s_at AGAP009365 CRALBP Binding 0.0431 1.66
Ag.3L.707.0_UTR_at AGAP010732 ZINC FINGER PROTEIN Binding 0.0414 1.66
Ag.2R.861.0_CDS_at AGAP001281, AGAP001282 INWARD RECTIFIER POTASSIUM
CHANNEL SPECTRIN REPEAT SYNAPTIC NUCLEAR
Ion transport 0.0384 −1.63
Ag.UNKN.1513.0_CDS_s_at AGAP009554 ENVELOPE SERINE/THREONINE-PROTEIN Actin binding 0.0228 −1.65
Ag.2R.3544.0_CDS_at AGAP004096 PHOSPHATASE 2A SUBUNIT EPSILON Binding 0.0432 −1.72
Ag.UNKN.2468.0_s_at ? Unknown Unknown 0.0012 −1.73
Ag.UNKN.2158.0_CDS_at ? Unknown
GLUCOSE DEHYDROGENASE
Unknown 0.0290 −1.78
Ag.2R.613.1_CDS_s_at AGAP003785 [ACCEPTOR} PRECURSOR Dehydrogenase activity 0.0049 −1.79
DOI: 10.7717/peerj.584/table-3

Of the 4 genes marginally up-regulated by AgDNV infection, two are putatively associated with stress response (cytochrome P450 (CYP450) and AMME syndrome candidate gene 1 (AMMECR1)). In mosquitoes, CYP450s are detoxification enzymes expressed when the insect is under oxidative stress (Feyereisen, 1999) and are known to be expressed when the mosquito is infected by pathogens (Abrantes et al., 2008). No functional studies have been conducted on AMMERCR1 in insects. The other two identified significantly regulated genes are trypsinogen 2 and plugin. Trypsinogen is the precursor of trypsin, which is involved in hydrolysis of peptide bonds during bloodmeal digestion (Noriega et al., 1996) while plugin is one of the major components of the mating plug (Le et al., 2013).

When we applied a less stringent FC criteria (1.75 FC), 15 genes were differently regulated in response to DNV virus infection (Table 3) with 9 genes up-regulated and 6 down-regulated. Besides functionally unknown genes, the rest of the genes are classified to transport-, metabolism- or binding-related transcripts (Table 3).

Paratransgenesis is an approach that attempts to modulate vector competence of the vector by manipulation of microorganisms within the host (Beard, Cordon-Rosales & Durvasula, 2002; Riehle & Jacobs-Lorena, 2005). Malaria researchers have focused on paratransgenesis as a novel alternative to traditional transgenic strategies (Favia et al., 2007). Our results suggest that AgDNV infection has minimal impact on survival or gene expression of its mosquito host making it a potentially attractive agent for paratransgenesis in An. gambiae. It should be noted that survival is only one component of the complex amalgam of traits that, collectively make up “fitness” and that further studies need to be performed to assess the effect of AgDNV infection on other fitness components (such as development time, fecundity, and mating behavior).