Timing Is Everything
ABSTRACT N. Drayman et al. in their recent article (mBio 8:e01612-17, 2017, https://doi.org/10.1128/mBio.01612-17) have used dynamic proteomics and machine learning to show that the cell cycle state of any individual cell affects the outcome of a productive herpes simplex virus 1 (HSV-1) infection....
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| Formato: | article |
| Lenguaje: | EN |
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American Society for Microbiology
2018
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| Acceso en línea: | https://doaj.org/article/1b8bf15e7dfe49ed9e788207cd370923 |
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| Sumario: | ABSTRACT N. Drayman et al. in their recent article (mBio 8:e01612-17, 2017, https://doi.org/10.1128/mBio.01612-17) have used dynamic proteomics and machine learning to show that the cell cycle state of any individual cell affects the outcome of a productive herpes simplex virus 1 (HSV-1) infection. Cells infected from early G1 through S were most permissive for expression of genes from the HSV-1 genome, whereas cells infected in late G2 to mitosis were much less so. Most of the infected cells that underwent mitosis became permanently nonpermissive for HSV-1 gene expression afterward. The cell cycle stage accounted for 60% of the success of infection, and cell density and motility accounted for most of the rest. To successfully reactivate, HSV-1 must express its genes in neurons and cells of the spinosum and granulosum epidermis strata. These cells are permanently in the cell cycle stages most permissive for HSV-1 gene expression, and none reenters mitosis, thus maximizing the efficiency of a successful HSV-1 reactivation before the adaptive immunity can control it. |
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