Zika virus (ZIKV) is an emerging mosquito-borne flavivirus, first isolated in 1947 from the serum of a pyrexial rhesus monkey caged in the Zika Forest (Uganda/Africa) [1]. In 2007, ZIKV was reported linked to an outbreak of relatively mild disease, characterized by rash, arthralgia, and conjunctivitis on Yap Island, in the western Pacific Ocean [2]. In 2015, ZIKV circulated in the Americas, probably introduced through Easter Island (Chile) by French Polynesians [3], where concerns over its links with infant microcephaly have been raised. MicroRNAs (miRNAs) are small noncoding RNAs (sncRNAs) that regulate post-transcriptional gene expression by translational repression. It is estimated that more than 60% of human protein-coding genes are likely to be under the control of miRNAs [4]. Two hypotheses exist as to how miRNAs could influence ZIKV/human-host interaction. First, the virus could transcribe miRNAs that provide benefits associated with cellular and viral gene expression (e.g. Herpesvirus, Polyomavirus, Ascovirus, Baculovirus, Iridovirus, Adenovirus families) [5, 6]. RNA retrovirus miRNAs are transcribed through RNA polymerase III (pol III), instead of pol II. Virus-encoded miRNAs support persistent infections through subtle modulation of gene expression, leading to prevention of host cell death, evasion of the host immune system and regulation of the latent-lytic switch [7]. Second, retrovirus genomes may directly interact with cellular miRNAs to enhance viral replication potential [5]. By recruiting/exploiting cellular miRNAs, an RNA virus can disturb the regulation of host gene expression, which can trigger molecular disease. In order to provide a theoretical background for future experimental verification of these hypotheses, the ZIKV collaborative database (ZIKV-CDB) was assembled. This enables, (i) searching for predicted ZIKV miRNAs mimicking human miRNAs [searching criteria includes: “Gene name”, “Gene Symbol” or “Ensembl ID”] (hypothesis 1); and (ii) searching for human miRNAs with possible binding-sites to the ZIKV genomes (hypothesis 2).

The ZIKV-CDB comprises miRNAs predicted using HHMMiR [8] for all complete ZIKV genomes currently available at the GenBank (February, 2016—http://www.ncbi.nlm.nih.gov). Hairpin prediction was performed for all de novo miRNAs using previously predicted RNA secondary structure [9], and mature miRNAs were delineated with PHDcleav [10]. Potential human genome (Ensembl GRCh37) target sites for the predicted ZIKV miRNAs were detected with miRanda [11] using default parameters (minimum score = 140; minimum energy = 1). Also, all mature human miRNA sequences from miRBase Sequence Database (Release 21—http://www.mirbase.org) were retrieved and mapped against the available ZIKV genomes using miRanda [11] with default parameters, to keep only those miRNAs with a minimum complementarity to ZIKV genomes [at least with complementarity to the miRNA seed region (6–10 nt) of the miRNA]. The ZIKV-CDB is publicly available through a web interface at http://zikadb.cpqrr.fiocruz.br.

We introduce the ZIKV-CDB, a collaborative database encompassing both, predicted miRNAs encoded by ZIKV genomes that could potentially target the human genome, and cellular (human) miRNAs with sequence complementary to ZIKV genomes. This knowledgebase should facilitate researchers when exploring targets that may affect the expression of genes associated with microcephaly and other neurodevelopmental syndromes caused by ZIKV infection. The chosen method for predict ZIKV-encoded miRNAs was based on a previously published benchmark [13], which shows that among the evaluated tools, miRanda had the highest sensitivity for predicting miRNAs, providing more targets for validation. To increase the effectiveness of this strategy, further analysis using genome sequences of other viruses with experimentally validated virally encoded miRNAs should be explored as positive controls. In contrast to previous reports [14, 15], the miRNAs identified here are located in the ZIKV polyprotein coding region. Recently, a study using a similar approach identified miRNAs located in the CDS region of Ebola Virus [16].

Examples of genes predicted to be targeted by miRNAs and previously validated as having a potential link to neurological disorders include the peroxisomal biogenesis factor 26 gene (PEX26), the fibroblast growth factor 2 (FGF2), the SET binding factor 1 (SBF1), the hook microtubule-tethering protein 3 (Hook3), the pleckstrin homology domain, and the RhoGEF domain containing G4 (PLEKHG4) (Table 1). All these targets, when aligned to predicted miRNAs, met the minimum criteria of free energy (minimum energy = 1) and score (140). PLEKHG4 polymorphisms have been related to spinocerebellar ataxia [17], a progressive-degenerative genetic disease. Also, Hook3 has been reported to interact with Pericentriolar Material 1 (PCM1) during brain development, and an imbalance in the Hook3-PCM1 interaction can cause premature depletion of the neural progenitor pool in the developing neocortex [18]. Finally, defects in the PEX26 gene can lead to a failure of protein import into the peroxisomal membrane or matrix, being the cause of several neuronal disorders, including Zellweger syndrome (ZWS), and neonatal adrenoleukodystrophy (NALD) [19, 20]. It is important to highlight that none of the predicted miRNAs were associated with every analysed ZIKV genome, nor in all isolates from the recent outbreak in Brazil. Which suggests that these predicted miRNAs are not essential for virus replication, but may improve their replication success [5]. These differences between genomes also may be related to different phenotypes of ZIKV infection, such as microcephaly in infants, Guillain—Barré syndrome [21], other symptoms similar to those of dengue and chikungunya, or asymptomatic phenotype [22].

Interestingly, several human miRNAs known to exert an influence on the expression of genes with a known functional role in neuronal development were found to have sequence complementarity to regions in the ZIKV genome (Table 2). One of the human hsa-miR-34a miRNA targets, the Cyclin-Dependent Kinase 6 (CDK6) gene, for instance, was computationally predicted to interact with several ZIKV genomes. CDK6 is associated with the centrosome during mitosis, controlling the cell cycle division phases in neuron production [23]. Mutation in CDK6 can lead to a deficient centrosomes division, which in turns can cause autosomal recessive primary microcephaly (MCHP) [19]. There are seven well-know genes encoding centrosomal proteins that are involved in the autosomal recessive primary microcephaly (MCPH) [24], including the CDK5 Regulatory Subunit Associated Protein 2 (Cdk5rap2 or MCHP3) gene. We found a possible binding-site to the hsa-mir-324-3p, a cellular miRNA targeting Cdk5rap2 gene, in the ZIKV genomes. Equally, we found that ZIKV genomic regions can potentially bind the hsa-mir-615-3p and hsa-miR-193b-3p human miRNAs, which target the WD Repeat Domain 62 (WDR62 or MCHP2), also related to MCHP when mutated. Remarkably, a hsa-mir-21-5p miRNA complementary site was found in the genomes of ZIKV isolated from Brazil, Haiti, Martinique and French Polynesia, but not in those from Africa. This miRNA targets the MCHP4 gene, also linked to microcephaly cases. The geographic and hence historical accumulation of genomic differences may explain the recent rise of microcephaly, and this observation also corroborates the predicted pathway of transmission from Africa, through Oceania, and into Central and South America.

To further support this, phylogenetic analysis was performed for all complete ZIKV genomes (Fig 1), which identified a cluster of strains isolated in the Americas and Oceania (derived strains), and another with the African strains (ancient strains). A third group, including two Flavivirus genotypes closely related to ZIKV, which were added as an out-group. These differences were also supported by phylogenetic analysis of only the predicted miRNAs encoded by each ZIKV strain (S1 Fig). Nine predicted miRNA types were identified, with types 1–4 being shared exclusively by derived strains and 5–8 being exclusive to ancient strains. Type 9 was only found in the genomes of strains from the Central African Republic (Fig 2). The predicted miRNAs could target a total of 14,745 human genes; 9,106 are specific to miRNAs from ancient strains, 2,840 are specific to those from derived strains, and 2,789 are shared.

Recently, ZIKV was isolated from the brain tissue of a fetus diagnosed with microcephaly [25], and two laboratory studies have provided robust evidence that ZIKV infection may cause brain defects in infants by influencing brain cell development [26, 27]. However, the mechanism by which ZIKV alters neurophysiological development remains unknown, inhibiting the development of therapeutic interventions. Our results suggest a putative influence of miRNAs on the expression of human-genes associated with the symptoms of Congenital ZIKA Syndrome. The ZIKV-CDB provides a useful knowledge base to support research targeted at mitigating the impacts of this emerging health problem [28]. ZIKV-CDB is an open-source and collaboration-based forum for sharing and identifying potential targets. The database can guide experimental investigation to elucidate the possible association between ZIKV infection and neurobiological development in infants. The ZIKV-CDB is going to be further expanded to encompass information related to others sncRNAs, as predicted by other approaches. The database will also be continuously maintained and curated by the Genomics and Computational Biology Group, FIOCRUZ/CPqRR (http://www.cpqrr.fiocruz.br).