Abstract Zika virus (ZIKV) infection affects early human brain development, but it is still not fully clear how different developmental cell lineages shape antiviral transcriptional responses. In this study, we carried out a secondary descriptive analysis using publicly available single-cell transcriptomic datasets from human fetal brain-derived neural tissue exposed ex vivo to Brazilian ZIKV-BR, the Cambodian 2010 Asian-lineage FSS13025 isolate, referred to here as ZIKV-FSS, or interferon-beta stimulation (IFNβ). Across neural lineages, radial glia-like cells enriched in progenitors and cycling NPC populations showed strong transcriptional IFN/ISG responsiveness and a higher number of genes that met exploratory differential expression criteria compared with several other cell types. Exploratory comparisons suggested strain-associated differences in response structure. In selected progenitor-focused and ISG-related summaries, the patterns linked to ZIKV-FSS showed more descriptive similarity to IFNβ-related profiles, while ZIKV-BR exposure was linked to broader and more varied gene expression changes. Sensitivity analyses showed that the transcriptional similarity between ZIKV and IFNβ depended on the gene universe used, was strongest among canonical interferon-stimulated genes (ISGs), and was more conservative across broader non-ISG and all-expressed gene sets. Contextual analyses of an independent human cerebral organoid bulk RNA-seq dataset and a Vero/moDC single-cell dataset supported the general presence of IFN/ISG-related transcriptional activation across ZIKV-exposed systems, but these were not interpreted as validation of fetal neural lineage-specific responses. Overall, these results provide an exploratory, lineage-resolved descriptive reference of antiviral transcriptional states in developing human neural tissue. Since the main fetal neural dataset included only one biological sample per condition, these findings should be interpreted as exploratory strain-associated patterns rather than definitive evidence for strain-dependent mechanisms.
Faraj et al. (2026) studied this question.