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Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses

Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts...

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Autores principales: Eng, Christine L. P., Tong, Joo Chuan, Tan, Tin Wee
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4767729/
https://www.ncbi.nlm.nih.gov/pubmed/26915079
http://dx.doi.org/10.1371/journal.pone.0150173
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author Eng, Christine L. P.
Tong, Joo Chuan
Tan, Tin Wee
author_facet Eng, Christine L. P.
Tong, Joo Chuan
Tan, Tin Wee
author_sort Eng, Christine L. P.
collection PubMed
description Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak.
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spelling pubmed-47677292016-03-09 Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses Eng, Christine L. P. Tong, Joo Chuan Tan, Tin Wee PLoS One Research Article Zoonotic influenza A viruses constantly pose a health threat to humans as novel strains occasionally emerge from the avian population to cause human infections. Many past epidemic as well as pandemic strains have originated from avian species. While most viruses are restricted to their primary hosts, zoonotic strains can sometimes arise from mutations or reassortment, leading them to acquire the capability to escape host species barrier and successfully infect a new host. Phylogenetic analyses and genetic markers are useful in tracing the origins of zoonotic infections, but there are still no effective means to identify high risk strains prior to an outbreak. Here we show that distinct host tropism protein signatures can be used to identify possible zoonotic strains in avian species which have the potential to cause human infections. We have discovered that influenza A viruses can now be classified into avian, human, or zoonotic strains based on their host tropism protein signatures. Analysis of all influenza A viruses with complete proteome using the host tropism prediction system, based on machine learning classifications of avian and human viral proteins has uncovered distinct signatures of zoonotic strains as mosaics of avian and human viral proteins. This is in contrast with typical avian or human strains where they show mostly avian or human viral proteins in their signatures respectively. Moreover, we have found that zoonotic strains from the same influenza outbreaks carry similar host tropism protein signatures characteristic of a common ancestry. Our results demonstrate that the distinct host tropism protein signature in zoonotic strains may prove useful in influenza surveillance to rapidly identify potential high risk strains circulating in avian species, which may grant us the foresight in anticipating an impending influenza outbreak. Public Library of Science 2016-02-25 /pmc/articles/PMC4767729/ /pubmed/26915079 http://dx.doi.org/10.1371/journal.pone.0150173 Text en © 2016 Eng et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Eng, Christine L. P.
Tong, Joo Chuan
Tan, Tin Wee
Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses
title Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses
title_full Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses
title_fullStr Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses
title_full_unstemmed Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses
title_short Distinct Host Tropism Protein Signatures to Identify Possible Zoonotic Influenza A Viruses
title_sort distinct host tropism protein signatures to identify possible zoonotic influenza a viruses
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4767729/
https://www.ncbi.nlm.nih.gov/pubmed/26915079
http://dx.doi.org/10.1371/journal.pone.0150173
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