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Human cytomegalovirus UL49 encodes an early, virion-associated protein essential for virus growth in human foreskin fibroblasts

Overview of attention for article published in Archives of Virology, February 2016
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Title
Human cytomegalovirus UL49 encodes an early, virion-associated protein essential for virus growth in human foreskin fibroblasts
Published in
Archives of Virology, February 2016
DOI 10.1007/s00705-016-2780-4
Pubmed ID
Authors

Feng Zhu, Jian Yuan, Hong-Jian Li, Zhi-Feng Zeng, Zhi-Wen Luo, Shi-Qian Li, Chi-Qiang He, Xue-Fang Jia, Xin Zhang, Hui Zuo, Yi-Min Liu, Martin Chang, Yue-Qin Li, Tian-Hong Zhou

Abstract

Despite recent results of deletion experiments showing that open reading frame (ORF) UL49 of human cytomegalovirus (HCMV) is essential, the expression, function and functional location of its encoded protein remain unknown. We generated an antibody specific for pUL49 to investigate the protein product encoded by the UL49 ORF and identified its function in HCMV-infected host foreskin fibroblasts. A bacterial artificial chromosome (BAC) of HCMV strain Towne (pRV-Towne) and the UL49-deleted mutant pRV-delUL49Towne were used to observe virus growth by plaque assay. Using a UL49-protein-binding antibody, we located pUL49 in the fibroblast cytoplasm. pUL49 exhibited expression kinetics resembling those of the class β-2 proteins and was detected in the virion tegument. Following deletion of UL49 ORF, the virus failed to replicate, but it could be recovered by addition of pUL49 from pCDNA3.1 (+)-UL49. Our findings indicate that UL49 ORF is essential for HCMV replication in host foreskin fibroblasts.

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Mendeley readers

The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 29%
Student > Ph. D. Student 3 21%
Researcher 3 21%
Student > Master 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 2 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 6 43%
Agricultural and Biological Sciences 2 14%
Computer Science 1 7%
Medicine and Dentistry 1 7%
Neuroscience 1 7%
Other 0 0%
Unknown 3 21%