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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American Society for Microbiology
2018
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oai:doaj.org-article:1b8bf15e7dfe49ed9e788207cd3709232021-11-15T15:53:26ZTiming Is Everything10.1128/mBio.02140-172150-7511https://doaj.org/article/1b8bf15e7dfe49ed9e788207cd3709232018-03-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.02140-17https://doaj.org/toc/2150-7511ABSTRACT 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.Luis M. SchangAmerican Society for Microbiologyarticledynamic proteomicssingle-cell analysescell cyclegene expressionherpes simplex virusMicrobiologyQR1-502ENmBio, Vol 9, Iss 1 (2018) |
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dynamic proteomics single-cell analyses cell cycle gene expression herpes simplex virus Microbiology QR1-502 |
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dynamic proteomics single-cell analyses cell cycle gene expression herpes simplex virus Microbiology QR1-502 Luis M. Schang Timing Is Everything |
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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. |
format |
article |
author |
Luis M. Schang |
author_facet |
Luis M. Schang |
author_sort |
Luis M. Schang |
title |
Timing Is Everything |
title_short |
Timing Is Everything |
title_full |
Timing Is Everything |
title_fullStr |
Timing Is Everything |
title_full_unstemmed |
Timing Is Everything |
title_sort |
timing is everything |
publisher |
American Society for Microbiology |
publishDate |
2018 |
url |
https://doaj.org/article/1b8bf15e7dfe49ed9e788207cd370923 |
work_keys_str_mv |
AT luismschang timingiseverything |
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1718427258935312384 |