An Emory University-led team takes a look at transcriptome patterns found in human neural progenitor cells infected with various strains of Zika virus. Using RNA sequencing and other analyses, the researchers analyzed transcripts found in forebrain-specific human neural progenitor cells infected with Asian Zika virus, African Zika virus, or the dengue virus, a related flavivirus. Though infection with either viral species seemed to dial down expression of genes from cell cycle, DNA replication, and DNA repair pathways, they report, the DNA replication and repair pathways appeared to be more specifically altered in the Zika virus-infected cells compared to the broader transcriptional shifts detected in dengue-infected cells.
Researchers from Portugal report on a resource designed for analyzing and predicting regulatory features in pathogenic yeast species. The "Pathogenic Yeast Search for Transcriptional Regulators and Consensus Tracking," or PathoYeastract database brings together information for tens of thousands of regulatory associations involving transcription factors, target genes, DNA binding sites, and the like in the pathogenic yeast species Candida albicans and C. glabrata, the authors note. "The PathoYeastract database has been developed to provide researchers and clinicians working in the field of fungal infections with a tool to obtain a more complete understanding of the complex regulatory control that underlies the biology, pathogenicity, and drug resistance capability of Candida species," they write.
Finally, a team from North Carolina State University and the Mount Desert Island Biological Laboratory present an updated version of the Comparative Toxicogenomics Database — an online resource designed to consider chemical, disease, gene, and protein interactions. The researchers note that the current version of the core CTD currently contains tens of millions of toxicogenomic connections and roughly one-third more data than a 2015 iteration of the database. The CTD also contains new information on gene ontology-based functions and potential disease connections, along with a science module relating toxicogenomic data from the lab to chemical information in real world settings.