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A complete map of potential pathogenicity markers of avian influenza virus subtype H5 predicted from 11 expressed proteins

Overview of attention for article published in BMC Microbiology, June 2015
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Title
A complete map of potential pathogenicity markers of avian influenza virus subtype H5 predicted from 11 expressed proteins
Published in
BMC Microbiology, June 2015
DOI 10.1186/s12866-015-0465-x
Pubmed ID
Authors

Zeeshan Khaliq, Mikael Leijon, Sándor Belák, Jan Komorowski

Abstract

Polybasic cleavage sites of the hemagglutinin (HA) proteins are considered to be the most important determinants indicating virulence of the avian influenza viruses (AIV). However, evidence is accumulating that these sites alone are not sufficient to establish high pathogenicity. There need to exist other sites located on the HA protein outside the cleavage site or on the other proteins expressed by AIV that contribute to the pathogenicity. We employed rule-based computational modeling to construct a map, with high statistical significance, of amino acid (AA) residues associated to pathogenicity in 11 proteins of the H5 type viruses. We found potential markers of pathogenicity in all of the 11 proteins expressed by the H5 type of AIV. AA mutations S-43(HA1)-D, D-83(HA1)-A in HA; S-269-D, E-41-H in NA; S-48-N, K-212-N in NS1; V-166-A in M1; G-14-E in M2; K-77-R, S-377-N in NP; and Q-48-P in PB1-F2 were identified as having a potential to shift the pathogenicity from low to high. Our results suggest that the low pathogenicity is common to most of the subtypes of the H5 AIV while the high pathogenicity is specific to each subtype. The models were developed using public data and validated on new, unseen sequences. Our models explicitly define a viral genetic background required for the virus to be highly pathogenic and thus confirm the hypothesis of the presence of pathogenicity markers beyond the cleavage site.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Unknown 28 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 28%
Student > Ph. D. Student 6 21%
Professor > Associate Professor 2 7%
Professor 2 7%
Lecturer > Senior Lecturer 1 3%
Other 3 10%
Unknown 7 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 28%
Biochemistry, Genetics and Molecular Biology 4 14%
Medicine and Dentistry 3 10%
Computer Science 3 10%
Environmental Science 1 3%
Other 2 7%
Unknown 8 28%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 June 2015.
All research outputs
#14,039,304
of 17,590,133 outputs
Outputs from BMC Microbiology
#1,825
of 2,673 outputs
Outputs of similar age
#165,991
of 238,497 outputs
Outputs of similar age from BMC Microbiology
#1
of 1 outputs
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