Zika virus (ZIKV) infection is implicated in severe fetal developmental disorders, including microcephaly. MicroRNAs (miRNAs) post-transcriptionally regulate numerous processes associated with viral infection and neurodegeneration, but their contribution to ZIKV pathogenesis is unclear. We analyzed the mRNA and miRNA transcriptomes of human neuronal stem cells (hNSCs) during infection with ZIKV MR766 and Paraiba strains. Integration of the miRNA and mRNA expression data into regulatory interaction networks showed that ZIKV infection resulted in miRNA-mediated repression of genes regulating the cell cycle, stem cell maintenance, and neurogenesis. Bioinformatics analysis of Argonaute-bound RNAs in ZIKV-infected hNSCs identified a number of miRNAs with predicted involvement in microcephaly, including miR-124-3p, which dysregulates NSC maintenance through repression of the transferrin receptor (TFRC). Consistent with this, ZIKV infection upregulated miR-124-3p and downregulated TFRC mRNA in ZIKV-infected hNSCs and mouse brain tissue. These data provide insights into the roles of miRNAs in ZIKV pathogenesis, particularly the microcephaly phenotype.

As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples. We term this approach leaderboard metagenome sequencing. To explore protocol optimization for leaderboard metagenomics in real samples, we introduce a benchmark of library prep and sequencing using internal references generated by synthetic long-read technology, allowing us to evaluate high-throughput library preparation methods against gold-standard reference genomes derived from the samples themselves. We introduce a low-cost protocol for high-throughput library preparation and sequencing.