Scholarlink

<p>Influenza A virus (IAV) infections play a substantial role in human disease, hospitalization, and economic loss. In an effort to better understand the intracellular effects that IAV replication has on individual host cells, this study set out to analyze an existing single-cell RNA sequencing (scRNAseq) dataset to identify the different metabolic pathways disrupted in cells infected with IAV. Specifically, these analyses consisted of calculating differential expression, signaling pathway enrichment, and text mining methods on a publicly available dataset consisting of 2041 mammalian MDCK cells infected with H9N2 IAV to model cross-species spread of endemic avian influenza. Interestingly, this dataset detected cells that were infected by viruses that carried less than a full set of genome segments, allowing us to ascribe impacts on host gene expression to specific viral genes. The results from this analysis enabled us to observe (1) the differences in host cellular gene expression caused by individual IAV segments, (2) the effects of various segment combinations on the host response, and (3) the segment-specific disruptions in signaling pathways related to three categories: virus replication, host immune response, and cell cycle. Deeper examination of these trends will improve our understanding of the mechanistic effects of responses caused by IAV at the molecular level and improve the ongoing development of host-based anti-viral therapeutics.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Secondary analysis of influenza a virus-infected cells at single-cell resolution reveals host BANF1 response to individual and combinations of detected segments

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月20日

查看全文
  • Zach Fears,
  • Bradford K. Berges,
  • Miglena Manandhar,
  • Gene S. Tan,
  • Brett E. Pickett

摘要

Influenza A virus (IAV) infections play a substantial role in human disease, hospitalization, and economic loss. In an effort to better understand the intracellular effects that IAV replication has on individual host cells, this study set out to analyze an existing single-cell RNA sequencing (scRNAseq) dataset to identify the different metabolic pathways disrupted in cells infected with IAV. Specifically, these analyses consisted of calculating differential expression, signaling pathway enrichment, and text mining methods on a publicly available dataset consisting of 2041 mammalian MDCK cells infected with H9N2 IAV to model cross-species spread of endemic avian influenza. Interestingly, this dataset detected cells that were infected by viruses that carried less than a full set of genome segments, allowing us to ascribe impacts on host gene expression to specific viral genes. The results from this analysis enabled us to observe (1) the differences in host cellular gene expression caused by individual IAV segments, (2) the effects of various segment combinations on the host response, and (3) the segment-specific disruptions in signaling pathways related to three categories: virus replication, host immune response, and cell cycle. Deeper examination of these trends will improve our understanding of the mechanistic effects of responses caused by IAV at the molecular level and improve the ongoing development of host-based anti-viral therapeutics.