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A novel Bayesian method for detection of APOBEC3-mediated hypermutation and its application to zoonotic transmission of simian foamy viruses

Authors :
Xiaoxing Wang
Gregory A. Engel
Khanh Soliven
Christopher T Small
Mostafa M. Feeroz
M. Kamrul Hasan
Lisa Jones-Engel
Maxine L. Linial
Michael Emerman
Frederick A. Matsen
Karen L. Craig
Source :
PLoS Computational Biology, Vol 10, Iss 2, p e1003493 (2014), PLoS Computational Biology
Publication Year :
2014
Publisher :
Public Library of Science (PLoS), 2014.

Abstract

Simian Foamy Virus (SFV) can be transmitted from non-human primates (NHP) to humans. However, there are no documented cases of human to human transmission, and significant differences exist between infection in NHP and human hosts. The mechanism for these between-host differences is not completely understood. In this paper we develop a new Bayesian approach to the detection of APOBEC3-mediated hypermutation, and use it to compare SFV sequences from human and NHP hosts living in close proximity in Bangladesh. We find that human APOBEC3G can induce genetic changes that may prevent SFV replication in infected humans in vivo.<br />Author Summary Simian Foamy Virus (SFV) is a very common retrovirus in monkeys. When an infected monkey bites a human it can transmit the virus to the human; however, there are no documented cases of human to human transmission. There also appear to be significant differences between infection in monkey and human hosts. The reason for these differences in the two hosts is not completely understood. In this paper we show that a family of host defense enzymes called APOBEC3 may prevent replication of SFV in humans. They do this by changing the genome of the virus so that it cannot replicate. Although this same process also happens in monkeys, it appears to happen less than in humans, and the changes that the monkey APOBEC3 enzymes make are less likely to prevent the virus from replicating. We are able to make these inferences by seeing characteristic types of mutations in a collection of virus DNA sequences sampled in Bangladesh. We develop new statistical methodology to do this analysis.

Details

Language :
English
ISSN :
15537358
Volume :
10
Issue :
2
Database :
OpenAIRE
Journal :
PLoS Computational Biology
Accession number :
edsair.doi.dedup.....9a95643940b2954cb0fd17ec3f3d91a1