We’ve rebranded some of our products, learn more ›

CODEX is now PhenoCycler
Phenoptics is now Phenolmager

Quantification of Viral and Host Biomarkers in the Liver of Rhesus Macaques

Authors: Greenberg, Alexandra Rachel; Huber, Bertrand Russel; Liu, David Xianhong; Logue, James Patrick; Woolsey Hischak, Amanda Marie; Hart, Randy John; Abbott, Maureen; Isic, Nejra; Hisada, Yohei Michael; Mackman, Nigel; Bennett, Richard S.; Hensley, Lisa E.; Connor, John Hazard; Crossland, Nicholas Alexander

Online: https://linkinghub.elsevier.com/retrieve/pii/S0002944020301383

Issue: Am J Pathol. 2020 Jul;190(7):1449-1460.


Zaire ebolavirus (EBOV) causes Ebola virus disease (EVD), which carries a fatality rate between 25% and 90% in humans. Liver pathology is a hallmark of terminal EVD; however, little is known about temporal disease progression. We used multiplexed fluorescent immunohistochemistry and in situ hybridization in combination with whole slide imaging and image analysis (IA) to quantitatively characterize temporospatial signatures of viral and host factors as related to EBOV pathogenesis. Eighteen rhesus monkeys euthanized between 3 and 8 days post-infection, and 3 uninfected controls were enrolled in this study. Compared with semiquantitative histomorphologic ordinal scoring, quantitative IA detected subtle and progressive features of early and terminal EVD that was not feasible with routine approaches. Sinusoidal macrophages were the earliest cells to respond to infection, expressing proinflammatory cytokine interleukin 6 (IL6) mRNA, which was subsequently also observed in fibrovascular compartments. The mRNA of interferon-stimulated gene-15 (ISG-15), also known as ISG15 ubiquitin like modifier (ISG15), was observed early, with a progressive and ubiquitous hybridization signature involving mesenchymal and epithelial compartments. ISG-15 mRNA was prominent near infected cells, but not in infected cells, supporting the hypothesis that bystander cells produce a robust interferon gene response. This study contributes to our current understanding of early EVD progression and illustrates the value that digital pathology and quantitative IA serve in infectious disease research.