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Keywords:

  • innate immunity;
  • antiviral defence;
  • mosquito;
  • arbovirus;
  • small RNA

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information

To define microRNA (miRNA) involvement during arbovirus infection of Aedes aegypti, we mined deep sequencing libraries of Dengue type 2 (DENV2)-exposed mosquitoes. Three biological replicates for each timepoint [2, 4 and 9 days post-exposure (dpe)] and treatment group allowed us to remove the outliers associated with sample-to-sample variability. Using edgeR (R Bioconductor), designed for use with replicate deep sequencing data, we determined the log fold-change (logFC) of miRNA levels [18–23 nucleotides (nt)]. The number of significantly modulated miRNAs increased from ≤5 at 2 and 4 dpe to 23 unique miRNAs by 9 dpe. Putative miRNA targets were predicted by aligning miRNAs to the transcriptome, and the list was reduced to include the intersection of hits found using the Miranda, PITA, and TargetScan algorithms. To further reduce false-positives, putative targets were validated by cross-checking them with mRNAs reported in recent DENV2 host response transcriptome reports; 4076 targets were identified. Of these, 464 gene targets have predicted miRNA-binding sites in 3′ untranslated regions. Context-specific target functional groups include proteins involved in transport, transcriptional regulation, mitochondrial function, chromatin modification and signal transduction processes known to be required for viral replication and dissemination. The miRNA response is placed in context with other vector host response studies by comparing the predicted targets with those of transcriptome studies. Together, these data are consistent with the hypothesis that profound and persistent changes to gene expression occur in DENV2-exposed mosquitoes.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information

By definition, arbovirus transmission cycles require alternating replication in vector arthropods and vertebrate hosts. Mosquitoes mount a multipronged antiviral response to arboviruses (Xi et al., 2008; Sanchez-Vargas et al., 2009; Colpitts et al., 2011; Chauhan et al., 2012; Ocampo et al., 2013). One avenue of the innate immune response relies on toll receptors, the JAK-STAT pathway, apoptosis and other factors (Sanders et al., 2005; Xi et al., 2008; Souza-Neto et al., 2009; Bartholomay et al., 2010; Ramirez & Dimopoulos, 2012; Rodriguez-Andres et al., 2012). Another avenue uses a small RNA regulatory pathway specific for short interfering RNAs (siRNAs) to cleave viral targets via an Argonaute-2/Dicer-2 dependent RNA interference (RNAi) mechanism. A closely related RNAi pathway (miRNAi) uses microRNAs [miRNAs; ∼18–23 nucleotides (nt)] to modulate gene expression of housekeeping and developmental cellular processes in an Argonaute-1/Dicer-1 dependent manner. There are at least 88 unique miRNA genes in Aedes aegypti (MirBase.org; MirBase release 19). Moreover, miRNAs control gene expression of at least 15% of the Drosophila genome (Grun et al., 2005).

A variety of studies indicate that vector competence is a complex multigenic trait (Keene et al., 2004; Franz et al., 2006; Campbell et al., 2008; Sanchez-Vargas et al., 2009; Behura et al., 2011). Quantitative genetic analysis has shown that ∼40% of variation in vector competence is attributable to traits present at several loci (Bosio et al., 2000; Gomez-Machorro et al., 2004; Bennett et al., 2005). Included in these phenotypes are barriers that prevent the virus from infecting midguts or salivary glands, or, for example, escaping the midgut, as happens with the midgut escape barrier (MEB) (Bosio et al., 2000; Bennett et al., 2005). Importantly, Dicer-1 may be part of the MEB in wild mosquito populations (Bernhardt et al., 2012). Our earlier work showed evidence of the production of viRNAs in DENV2-infected Ae. aegypti at 2, 4 and 9 days post-exposure (dpe) (Hess et al., 2011). The recently identified association of Dicer-1 to the MEB in mosquitoes led us to investigate possible roles played by miRNAi in DENV2 infection. Importantly, the limits of antiviral defence in vector mosquitoes and the complexity of these converging pathways are poorly understood, but may be critical to the biology of host–virus interactions.

Recent transcriptome studies of DENV2-infected Ae. aegypti provide a contextual framework for the study of miRNA pathway involvement in virus infection (Guo et al., 2010; Behura et al., 2011; Colpitts et al., 2011; Bonizzoni et al., 2012; Sim et al., 2012). Using these data to cross-validate predicted miRNA targets would reduce false-positives and allow us to move toward converging the existing small RNA regulatory pathway data in virus-infected arthropods; however, there is limited concordance between differentially expressed mRNAs among recent transcriptome dataset publications (Fig. S1). This variation may be attributable to differences in mosquito host or virus strains, inoculation routes, length of extrinsic incubation period or a natural heterogeneity in the overall mosquito response. By characterizing modulated miRNAs during DENV2 infection and placing them in the context of mosquito transcriptional responses to DENV infection, we hope to define the common features of gene expression control that underpin host defence mechanisms. Moreover, miRNA target prediction allows us to identify coordinated miRNA responses that could work together to alter infection outcomes. A challenge to the use of deep sequencing data is the variability associated with biological replicates. In the present study, we used a method developed specifically for analysis of deep sequencing data with biological replicates, edgeR (R, Bioconductor). We follow up with miRNA target prediction and conclude with a discussion of the implications for the mosquito host response to DENV2 infection.

Results and discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information

miRNA modulation

Eighteen sRNA libraries representing three biological replicates of pooled DENV2-exposed and un-exposed control mosquitoes were mined to identify significantly modulated miRNAs (Hess et al., 2011). sRNAs were aligned to miRBase hairpin release 17 (Griffiths-Jones, 2006; Kozomara & Griffiths-Jones, 2011). Mapped reads in the miRNA size range (18–23 nt) showed a marked predominance of forward strand reads, whereas reads <18 nt showed a more balanced representation of both forward and reverse strands (data not shown). This evidence supports the current understanding of miRNA biogenesis mechanisms, wherein the guide strand is retained and the complementary strand is degraded. In miRNA biogenesis, this process occurs via a two-step RISC-loading process, wherein the partial complementarity of the double-stranded precursor is sensed by the RISC, one strand is nicked by Argonaute-2, and the guide strand is loaded into a second RISC, with concomitant loss of the passenger strand and subsequent cleavage of target mRNAs (Preall & Sontheimer, 2005; O'Toole et al., 2006; Diederichs & Haber, 2007), In contrast, siRNA biogenesis relies on a single cleavage-dependent RISC loading event of dsRNA precursors that presumably results in either strand serving as guide strand.

DENV2-exposed Ae. aegypti sRNA libraries showed modulation of miRNA profiles compared with un-exposed controls at 2, 4 and 9 dpe. Age-matched DENV2-fed and unexposed controls were analysed for each timepoint. Only those miRNAs homologous to previously reported mature −5p and −3p miRNAs, previously termed miRNAs and *miRNAs, respectively, were analysed further (MirBase.org)(Griffiths-Jones, 2006). Conserved miRNAs from 31 miRNA genes showed significant modulation (edgeR, P < 0.05) (Fig. 1, Table 1). Of these, 26 unique miRNAs have orthologues in insects, and 24 have been reported for Ae. aegypti (Mirbase.org).

figure

Figure 1. Significantly modulated miRNAs and indicated LogFC at each timepoint, relative to unexposed controls (P < 0.05).

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Table 1. MicroRNA LogFC. Table lists miRNA sequence, length and edgeR output, log fold-change, and P value
miRNASequencent #Control*DENV2*Total countlogFCP
  1. *Counts are totalled across sequencing libraries.

mir-iab(2d)ACGUAUACUGAAUGUAUCCUGAG23714124359576−1.090.024
bantam-3p(9d)GAGAUCAUUUUGAAAGCUGAUUU23524961822970725−1.840.014
let-7(9d)UGAGGUAGUUGGUUGUAUAG2010298419314491−1.610.025
mir-1000-5p(9d)AUAUUGUCCUGUCACAGCAGU21313214154547−1.460.015
mir-1175-3p(9d)GAGAUUCUACUUCUCCGACUUAA238961189910860−2.550.001
mir-124-5p(9d)UAAGGCACGCGGUGAAUGCC20642529129337−1.460.025
mir-1890-5p(9d)GAAAUCUUUGAUUAGGUCUGG219044141318−1.440.030
mir-210-5p(9d)UUGUGCGUGUGACAACGG1814233711794−2.250.006
mir-276-5p(9d)AGCGAGGUAUAGAGUUCCUAU21733423749708−1.940.017
mir-281a-3p(9d)UGUCAUGGAAUUGCUCUCUUUAC2311068466615734−1.560.026
mir-281a-5p(9d)AAGAGAGCUAUCCGUCGACAGUA23578473844996296−0.910.038
mir-281b-3p(9d)UGUCAUGGAAUUGCUCUCUUGAU23492619406866−1.660.012
mir-281c-5p(2d)AGAGAGCUAUCCGUCGACAGUAU2315153625021403−0.810.049
mir-2945-5p(4d)UGACUAGAGGCAGACUCG18419331750−1.350.037
mir-2945-5p(9d)GACUAGAGGCAGACUCGUUUAGG239068204611114−2.460.004
mir-2b-5p(9d)AUCACAGCCAGCUUUGUA1816558142469−1.340.046
mir-305-5p(9d)AUUGUACUUCAUCAGGUG1823838573240−1.790.015
mir-308-3p(9d)AUCACAGGAGUAUACUGUGA2032078398−2.350.021
mir-317-5p(9d)GAACACAGCUGGUGGUAUCUUG2210870491915789−1.460.046
mir-33-5p(9d)GUGCAUUGUAGUUGCAUUGC2013274551782−1.860.015
mir-3368-5p(4d)UCAGUCUUUUAGAGAAGAAG2023364297−2.60.001
mir-34-3p(9d)AACCACUAUCCGCCCUGCCGCC22683825628324661.590.027
mir-3722-5p(2d)CGAUUCGAGGUGgCGGUUUC2015116−3.190.047
mir-4275-5p(2d)CCAAUUACCACUucUUUUU1948873561−2.270.020
mir-5108-5p(4d)GGUAGAGCACUGGAUGGUU1926982351−1.910.031
mir-5119-5p(2d)CAUCUCAUCCUGGGGCUG181046562.6320.008
mir-79a-3p(9d)AUAAAGCUAGAUUACCAAAGCAU2324365913027−2.360.001
mir-79b-3p(9d)UAAAGCUAGAUUACCAAAGCAUA23573166739−2.10.010
mir-79c-3p(9d)UAAAGCUAGAUUACCAAAGCAUG2315949208−2.010.006
mir-8-5p(9d)AAUACUGUCAGGUAAAGAUGUCU238602836245122273−1.560.023
mir-87-5p(9d)UGAGCAANNUUUCAGGUGUGCG22426219226182.0470.002
mir-932-5p(9d)UCAAUUCCGUAGUGCAUUGCAG2231798924071−2.150.001
mir-988-5p(9d)CCCCUUGUUGCAAACCUCACGC22783193121393904581.6790.026
mir-999-5p(9d)GUUAACUGUAAGACUGUGUCUCG2310152581273−2.290.009
mir-9c-5p(9d)UCUUUGGUAUUCUAGCUGUAGA2215058122317−1.210.041

Over the course of infection, out of a total of 35 modulated miRNAs, the number of unique modulated miRNAs increased from 5 and 3 at 2 dpe and 4 dpe, respectively, to 23 by 9 dpe (Fig. 1, Table 1). At all timepoints, DENV2 viral small RNAs (viRNAs) were detectable in DENV-exposed pools (Hess et al., 2011). Importantly, the libraries were constructed from whole mosquitoes that had received a virus-laden bloodmeal, and 50% of the mosquitoes sampled did not retain detectable virus by plaque titration at 9 dpe (Hess et al., 2011). The retention of significantly modulated miRNAs at 9 dpe is remarkable, considering that 50% of any given pool would have no detectable virus by plaque titration. In our previous work, we found that significant differences in overall host sRNA profiles were largely abrogated by 9 dpe, probably because of the mixed infection status. Persistent changes to the miRNA pathway have implications for lifelong alteration of mosquito metabolism. Hypotheses with similar implications have been tested previously to assess behavioural changes in DENV-infected aedines, but this is the first evidence of a regulatory response at the global level (Platt et al., 1997; Sim et al., 2012).

Target prediction

Although 3′ untranslated regions (UTRs) were originally identified as being the key sites of miRNA-target interactions, recent target prediction studies set a precedent for probing full transcriptomes rather than merely 3′ UTRs (Hafner et al., 2010; Fang & Rajewsky, 2011); this approach seems especially suitable for an organism whose genome is not extensively annotated, such as Ae. aegypti. Putative miRNA targets were identified from transcriptome release 1.3 (Vectorbase.org) using the Miranda, PITA and TargetScan prediction methods (Enright et al., 2003; Lewis et al., 2005; Kertesz et al., 2007). miRNA targets are commonly identified by comparing the base complementarity of a portion of the miRNA to that of a given target sequence. In animals, miRNAs show partial rather than complete complementarity to targets (Brennecke et al., 2005). This partial complementarity is most important at the 5′ end of the miRNA and typically spans nt positions 2–8, thus defining the miRNA seed regions that are used in target prediction algorithms. The Targetscan prediction algorithm relies on base complementarity of seed region positions 2–8, whereas PITA also considers the free-energy of association between the miRNA and target along the length of the seed (Enright et al., 2003; Lewis et al., 2005; Kertesz et al., 2007). Miranda, one of the earliest prediction methods, considers free energy of association along the entire length of the miRNA-target region (Enright et al., 2003; Lewis et al., 2005; Kertesz et al., 2007). Putative targets were cross-validated with genes previously reported to be associated with DENV2 infection in Ae. aegypti (Guo et al., 2010; Behura et al., 2011; Colpitts et al., 2011; Bonizzoni et al., 2012; Sim et al., 2012). Only those targets contained within the intersection of the three target prediction methods and cross-validated by RNA-Seq reports were analysed further.

The 35 modulated miRNAs share 4076 in silico-validated transcriptome targets among all three prediction methods (Fig. 2A). PITA and TargetScan identified many more sites per target than Miranda. The Miranda prediction algorithm with stringent cut-off criteria produced the most inclusive target set of all approaches used (see Experimental procedures).

figure

Figure 2. Context-specific canonical miRNAs common to the target prediction methods PITA, Miranda, and TargetScan. (A) Context-specific targets for each prediction method. (B) Context-specific targets identified in 3′ UTR and coding sequences (CDS) using the Miranda package.

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Target sites in both the 3′UTR and the coding sequence (CDS) have been suggested to be synergistic for miRNA regulation (Fang & Rajewsky, 2011). Upon interrogation of 3′ UTRs alone, we found 464 unique gene targets (Fig. 2B). Of these, 365 targets contain miRNA-binding sites in both the CDS and the 3′ UTR, further strengthening their predicted significance as targets.

To characterize miRNA target biological attributes over the course of infection, 4076 targets common to the three target prediction methods were graphed according to miRNA and functional group (Table S2). Targets were classified by processes known to be associated with viral replication (Le Breton et al., 2011; Perera et al., 2012). The functional groups chosen account for ≥85% of all targets (data not shown). The processes involving transport, transcription/translation and cytoskeletal/structural components are required for successful DENV2 replication and dissemination. Transport, signal transduction, cytoskeletal/structural and metabolism make up the four most abundant target functional groups (Table S2). It is important to acknowledge the limitations inherent to studies of miRNA expression analysis. Any post-transcriptional or post-translational modifications of predicted targets would not be detected.

Implications for viral replication

The DENV2 miRNAi response could be a manifestation of several possible host responses. The following hypotheses are founded upon a variety of vector host response studies (Xi et al., 2008; Behura et al., 2011; Colpitts et al., 2011; Bonizzoni et al., 2012; Chauhan et al., 2012; Ocampo et al., 2013). For example, modulation of miRNA activity could regulate cell autonomous responses, such as those that occur within infected cells, or be indicative of signal transduction events that influence processes in distal tissues. Alternatively, modulation of miRNA levels could be evidence of viral exploitation of cellular processes. Some proteins, such as Loquacious, interact with proteins involved in both the miRNAi and siRNAi pathways (Fukunaga et al., 2012; Martinez & Gregory, 2013).

Importantly, because of the mixed infection status by 9 dpe, another possibility is that the significantly changed miRNAs at this timepoint represent responses to repair mechanisms in uninfected mosquitoes. To explore the possibilities, we compared our results with other host response studies. We used data from two recent reports describing the comparison of gene expression responses in DENV2-resistant and -susceptible Ae. aegypti strains (Chauhan et al., 2012; Ocampo et al., 2013). For example, Chauhan et al. (2012) reported that expressed genes representing glycolysis, gluconeogenesis, and the Wingless (Wnt) signalling functions are enriched in resistant strains, while transcripts with functions related to ER protein processing, nucleotide excision repair, the pentose phosphate pathway and the proteasome, are enriched in susceptible mosquitoes. In another study, Ocampo et al. (2013) described increased caspase expression in DENV2-infected tissues of resistant mosquitoes. To determine whether the predicted targets in the present work are supportive of resistant or susceptible phenotypes described by these two studies, we looked at the number of targets listed in Table S1 in each of these categories, There are 43 targets associated with ER protein processing and 84 associated with proteasome function. There are 11 targets associated with glycolysis/gluconeogenesis and two for Wnt signalling genes. The caspases Caspase-16, Dronc, and Dredd were not present on the target list. Of the 35 miRNAs modulated, four are enriched and the remaining 31 are depleted. Upon miRNA depletion, given that the predicted target mRNAs would be expected to be retained rather than degraded, and therefore expected to subsequently produce more protein, we speculate that our results are consistent with a susceptible rather than a resistant phenotype.

Modulation of miRNAi at early timepoints in DENV2 infection suggests that upstream regulatory processes are altered early during infection and raises the important question of whether the miRNAi host response is a defence response or a result of viral exploitation. Alternative explanations for changes to miRNA levels could include the removal or repair of infected cells containing these noncoding RNAs. To explore the possible implications of modulation to miRNA levels, targets orthologous to human flavivirus host response proteins were identified among the predicted targets. A subset of the targets is orthologous to a group of human proteins that physically interact with flavivirus non-structural proteins NS3 and NS5 (Le Breton et al., 2011). Human chromatin structural modification proteins also directly interact with flavivirus NS3 and S5 (Le Breton et al., 2011). In the present study, we identified 141 putative targets in the chromatin structure and dynamics functional category. DENV2 NS3 and NS5 are essential for successful flavivirus replication in endoplasmic reticulum-associated replication vesicles (Luo et al., 2008; Welsch et al., 2009). Importantly, 50 predicted miRNA targets are identical to a subset of human proteins that physically interact with flavivirus NS3 and NS5 (Table S1) (Le Breton et al., 2011). Fifteen of these are targets of miRNAs modulated at 2 dpe. Moreover, we found 33 unique targets with innate immunity or defence descriptors (Table S1). As discussed above, because 31 of the 35 miRNAs are depleted rather than enriched, any such mRNA targets would be expected to be retained rather than depleted. These results suggest that suppression of the innate immune response in vectors, should it occur, may be mediated through other response mechanisms. Clearly, these preliminary indications require closer investigation to clarify possible gene-for-gene interactions between viral proteins and the host response.

Mitochondrial function is essential for cellular energy production and often associated with DENV2 infection (El-Bacha et al., 2007; Sessions et al., 2009; Perera et al., 2012). We found 235 mitochondrial protein targets within the common target set (Tables S1 and S2). The most likely explanation for these target effects is that mitochondrial function increases to accommodate increased demand for cellular energy needs. A major component of dipteran mitochondrial membranes, phosphatidylethanolamine, is significantly altered during DENV2 infection of mosquito cells (Chan, 1970; Perera et al., 2012). It is tempting to speculate that the predicted mosquito host response produces changes to mitochondrial membrane composition, as well, although this hypothesis remains to be validated experimentally.

The presence of modulated miRNAs in DENV2-exposed mosquitoes suggests that miRNA pathway activity is altered during infection, although the causal factors remain unknown. The characteristics of that involvement must rely on characterization of miRNA activity on a gene-by-gene level in future studies. The importance of this is illustrated in a recent work, wherein it was demonstrated that a bloodmeal-induced miRNA, miR-375, stimulates enrichment of one mRNA and depletion of another (Hussain et al., 2012). In our dataset, alteration of mIR-375 was depleted in DENV2-exposed mosquitoes at 9 dpe, but the change was not significant (−1.6 LogFC, P = 0.08, edgeR).

Conclusion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information

This work describes the characterization of miRNA levels for a mixed population of mosquitoes that showed a 50% infection rate by 9 dpe (Hess et al., 2011). This mixed population, tested as three biological replicates, showed a pattern of miRNA modulation that was most marked at 9 dpe. This result supports the hypothesis that persistent metabolic changes occur in DENV2-fed mosquitoes, regardless of resistant or susceptible infection status and begs the question of whether there may be some unknown fitness benefit for DENV2-exposed mosquitoes.

These data provide the foundation for future studies to determine whether modulation of the miRNA pathway during DENV2 infection is a host defence response attempting to clear the virus or evidence of viral hijacking of host cellular processes.

Experimental procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information

Mosquito infections and library preparation

Infection conditions were reported previously (Hess et al., 2011). Briefly, three independent cohorts of RexD colony mosquitoes [originally collected from Rexville, San Juan, Puerto Rico (Miller & Mitchell, 1991)] were fed either meals containing mosquito cell culture-derived DENV2 virus, strain Jamaica 1409, or conditioned cell culture medium mixed 1:1 with defibrinated sheep's blood. The DENV meal titres ranged from 6.7 to 7.8 log plaque-forming units per ml. Pools of 20 whole mosquitoes were harvested at 2, 4 or 9 dpe from both DENV2-fed and unexposed controls. Infection rates, as determined by plaque assay, were 50% at 9 dpe. After RNA extraction, small RNAs were isolated using the FLASHPAGE system (Applied Biosystems, Foster City, CA, USA), and small RNA libraries were prepared using the SOLiD small RNA library preparation kit (Applied Biosystems). A total of 18 libraries, three each from unexposed and exposed mosquitoes at each timepoint, were sequenced on a SOLiD 3 platform. Sequences are archived at the National Center for Biotechnology Information Sequence Read archive, with a study accession number of SRP026241. The exposure status of all pooled samples was confirmed by the detection of viral sRNAs (Hess et al., 2011).

Fold-change analysis

Small RNAs 18–23 nt in length were aligned to the miRBase hairpin database (Release 17; mIRBase.org) using the NextGene suite (Softgenetics, LLC) and the parameters reported previously (Hess et al., 2011). On a preliminary screen of the miRNA hairpins, differentially expressed miRNA candidates were identified among all libraries. Peak calls of miRNA read data were performed using the R statistical package (Gentleman et al., 2004). Peaks, representing mature miRNAs, were identified along each hairpin and classified in the following manner: conserved (or −5p, previously reported miRNA), *miRNA (or −3p, complementary to miRNA), or unclassified. Final cut-off values for confirmed mature miRNAs required ≥10 reads across all libraries. In compliance with changes to miRNA naming conventions, all complementary miRNAs identified in the present study have been named according to the −5p/-3p nomenclature. miRNA naming conventions were confirmed with updates presented in miRBase Release 19 (http://www.mirbase.org/). miRNA read counts were analysed by edgeR as previously described, using total mapped reads for each library for scaling (Hess et al., 2011). edgeR uses a negative binomial distribution and employs an empirical Bayes strategy to calculate changes to relative gene expression levels; in addition, it is designed specifically for biological replicate data (Robinson et al., 2010). Only those miRNAs showing a LogFC P value of < 0.05 are reported.

miRNA target prediction and analyses

Differentially expressed miRNAs were analysed for complementarity to the Ae. aegypti transcriptome release (1.3) using three widely used algorithms; an intersection of targets identified by all three methods was used for analyses. Miranda was used with the following stringent parameters: energy value ≤−20 kcal/mol, Score ≥ 140 (Enright et al., 2003). PITA was implemented using high stringency parameters for seeds of 7–8, and excluded six-seed matches (Enright et al., 2003; Kertesz et al., 2007) (http://genie.weizmann.ac.il/pubs/mir07/mir07_exe.html). Excluding 6-nt seed matches in the PITA output has been shown to significantly reduce false-positive target identification (Fang & Rajewsky, 2011). Targetscan was used with default parameters (Lewis et al., 2005). Analysis of 3′ UTR vs coding sequence miRNA-binding sites relied on Miranda targets.

Predicted miRNA targets were annotated using Gene Ontology terms and SwissProt functional annotation data from AegyXcel (http://exon.niaid.nih.gov/transcriptome.html#aegyxcel). Data analysis scripts were implemented in Java and Python. Targets were validated in silico by cross-checking with transcriptome reports (Guo et al., 2010; Behura et al., 2011; Colpitts et al., 2011; Bonizzoni et al., 2012; Sim et al., 2012). Only those targets that were present in the aforementioned RNA-Seq reports were analysed further. Venn diagrams were generated using Venny (http://bioinfogp.cnb.csic.es/tools/venny/index.html). Other graphs were prepared using Prism Graphpad, or Microsoft Excel.

Acknowledgements

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information

We thank Mariangela Bonizzoni for providing RNA-Seq data. We also thank the reviewers for their insightful suggestions. TH was supported by NIH-R01 AI067380.

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  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information
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Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Results and discussion
  5. Conclusion
  6. Experimental procedures
  7. Acknowledgements
  8. References
  9. Supporting Information
FilenameFormatSizeDescription
imb12070-sup-0001-fig_s1.tif534K

Figure S1. Intersection of genes common to RNA-Seq datasets and predicted protein interaction network. (A) Venn diagram shows genes common to three recent transcriptome reports of DENV2-infected Aedes (Behura et al. 2011; Colpitts et al. 2011; Bonizzoni et al. 2012). (B) Genes common to transcriptome reports shown in 1A and protein interaction prediction network of Guo et al. (2010).

imb12070-sup-0002-table_s1.xlsx731K

Table S1. Predicted miRNA targets.

imb12070-sup-0003-table_s2.xlsx687K

Table S2. Targets from the intersection of three target prediction methods were categorized by functional group. Functional categories: transport (TRP) (ie. receptor transport and secretory pathway); defence (DEF); lipid metabolism (LIP); signal transduction (SigT); apoptosis (APOP); mitochondrial function (MIT); chromatin structure and dynamics (CSD); DNA replication and repair; protease (PRO), including protein turnover; oxidation/reduction (REDOX); cytoskeletal or structural functions (CYT/STR); transcriptional activation or repression (TF/TR), transcription/translation (TT), unknown (UNK), metabolism (MET), or diverse functions (DIV).

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