tetano
Editor, Senior Moderator
PLoS One. 2012;7(2):e30751. Epub 2012 Feb 17.
A Comparative Study of Human TLR 7/8 Stimulatory Trimer Compositions in Influenza A Viral Genomes.
Yang CW, Chen SM.
Source
Department of Microbiology, Soochow University, Shih-Lin, Taipei, Taiwan, Republic of China.
Abstract
BACKGROUND:
Variation in the genomes of single-stranded RNA viruses affects their infectivity and pathogenicity in two ways. First, viral genome sequence variations lead to changes in viral protein sequences and activities. Second, viral genome sequence variation produces diversity at the level of nucleotide composition and diversity in the interactions between viral RNAs and host toll-like receptors (TLRs). A viral genome-typing method based on this type of diversity has not yet been established.
METHODOLOGY/PRINCIPAL FINDINGS:
In this study, we propose a novel genomic trait called the "TLR stimulatory trimer composition" (TSTC) and two quantitative indicators, Score S and Score N, named "TLR stimulatory scores" (TSS). Using the complete genome sequences of 10,994 influenza A viruses (IAV) and 251 influenza B viruses, we show that TSTC analysis reveals the diversity of Score S and Score N among the IAVs isolated from various hosts. In addition, we show that low values of Score S are correlated with high pathogenicity and pandemic potential in IAVs. Finally, we use Score S and Score N to construct a logistic regression model to recognize IAV strains that are highly pathogenic or have high pandemic potential.
CONCLUSIONS/SIGNIFICANCE:
Results from the TSTC analysis indicate that there are large differences between human and avian IAV genomes (except for segment 3), as illustrated by Score S. Moreover, segments 1, 2, 3 and 4 may be major determinants of the stimulatory activity exerted on human TLRs 7 and 8. We also find that a low Score S value is associated with high pathogenicity and pandemic potential in IAV. The π value from the TSS-derived logistic regression model is useful for recognizing emerging IAVs that have high pathogenicity and pandemic potential.
PMID:
22363482
[PubMed - in process]
PMCID:
PMC3281872
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/22363482
A Comparative Study of Human TLR 7/8 Stimulatory Trimer Compositions in Influenza A Viral Genomes.
Yang CW, Chen SM.
Source
Department of Microbiology, Soochow University, Shih-Lin, Taipei, Taiwan, Republic of China.
Abstract
BACKGROUND:
Variation in the genomes of single-stranded RNA viruses affects their infectivity and pathogenicity in two ways. First, viral genome sequence variations lead to changes in viral protein sequences and activities. Second, viral genome sequence variation produces diversity at the level of nucleotide composition and diversity in the interactions between viral RNAs and host toll-like receptors (TLRs). A viral genome-typing method based on this type of diversity has not yet been established.
METHODOLOGY/PRINCIPAL FINDINGS:
In this study, we propose a novel genomic trait called the "TLR stimulatory trimer composition" (TSTC) and two quantitative indicators, Score S and Score N, named "TLR stimulatory scores" (TSS). Using the complete genome sequences of 10,994 influenza A viruses (IAV) and 251 influenza B viruses, we show that TSTC analysis reveals the diversity of Score S and Score N among the IAVs isolated from various hosts. In addition, we show that low values of Score S are correlated with high pathogenicity and pandemic potential in IAVs. Finally, we use Score S and Score N to construct a logistic regression model to recognize IAV strains that are highly pathogenic or have high pandemic potential.
CONCLUSIONS/SIGNIFICANCE:
Results from the TSTC analysis indicate that there are large differences between human and avian IAV genomes (except for segment 3), as illustrated by Score S. Moreover, segments 1, 2, 3 and 4 may be major determinants of the stimulatory activity exerted on human TLRs 7 and 8. We also find that a low Score S value is associated with high pathogenicity and pandemic potential in IAV. The π value from the TSS-derived logistic regression model is useful for recognizing emerging IAVs that have high pathogenicity and pandemic potential.
PMID:
22363482
[PubMed - in process]
PMCID:
PMC3281872
Free full text
http://www.ncbi.nlm.nih.gov/pubmed/22363482