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Search Results: 1 - 10 of 50909 matches for " WEI "
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Receptor binding specificity and origin of 2009 H1N1 pandemic influenza virus  [PDF]
Wei Hu
Natural Science (NS) , 2011, DOI: 10.4236/ns.2011.33030
Abstract: Recently, a genetic variant of 2009 H1N1 has become the predominant virus circulating in the southern hemisphere, particularly Australia and New Zealand, and in Singapore during the winter of 2010. It was associated with several vaccine breakthroughs and fatal cases. We analyzed three reported mutations D94N, N125D, and V250A in the HA protein of this genetic variant. It appeared that the reason for D94N and V250A to occur in pairs was to maintain the HA binding to human type receptor, so the virus could replicate in humans efficiently. Guided by this interpretation, we discovered a new mutation V30A that could compensate for N125D as V250A did for D94N. We demonstrated that the presence of amino acids 30A and 125N in HA enhanced the binding to human type receptor, while 30V and 125D favored the receptors of avian type and of A/South Carolina/1/18 (H1N1). Furthermore, a combination of 94D, 125D, and 250V made the primary binding preference similar to that of A/South Carolina/1/18 (H1N1) and a combination of 94N, 125D, and 250A resulted in the primary binding affinity for avian type receptor, which clearly differed from that of A/California/07/2009 (H1N1), a strain used in the vaccine for 2009 H1N1. We also re-examined the origin of 2009 H1N1 to refine our knowledge of this important issue. Although the NP, PA, PB1, and PB2 of 2009 H1N1 were closest to North American swine H3N2 in sequence identity, their interaction patterns were closest to swine H1N1 in North America.
Highly conserved domains in hemagglutinin of influenza viruses characterizing dual receptor binding  [PDF]
Wei Hu
Natural Science (NS) , 2010, DOI: 10.4236/ns.2010.29123
Abstract: The hemagglutinin (HA) of influenza viruses in itiates virus infection by binding receptors on host cells. Human influenza viruses preferenti ally bind to receptors with α2,6 linkages to gala ctose, avian viruses prefer receptors with α2,3 linkages to galactose, and swine viruses favor both types of receptors. The pandemic H1N1 2009 remains a global health concern in 2010. The novel 2009 H1N1 influenza virus has its ge netic components from avian, human, and sw ine viruses. Its pandemic nature is characterized clearly by its dual binding to the α2,3 as well as α2,6 receptors, because the seasonal human H1N1 virus only binds to the α2,6 receptor. In pr evious studies, the informational spectrum me thod (ISM), a bioinformatics method, was appli ed to uncover highly conserved regions in the HA protein associated with the primary receptor binding preference in various subtypes. In the present study, we extended the previous work by discovering multiple domains in HA associa ted with the secondary receptor binding prefer ence in various subtypes, thus characterizing the distinct dual binding nature of these viruses. The domains discovered in the HA proteins were mapped to the 3D homology model of HA, which could be utilized as therapeutic and diag nostic targets for the prevention and treatment of influenza infection.
Subtle differences in receptor binding specificity and gene sequences of the 2009 pandemic H1N1 influenza virus  [PDF]
Wei Hu
Advances in Bioscience and Biotechnology (ABB) , 2010, DOI: 10.4236/abb.2010.14040
Abstract: A recent phylogenetic inference indicated that the 2009 pandemic H1N1 strains circulating from March 2009 to September 2009 could be divided into two closely related but distinct clusters. Cluster one contained most strains from Mexico, Texas, and California, and cluster two had most strains from New York, both of which were reported to co-circulate in all continents. The same study further revealed nine nucleotide changes in six gene segments of the new virus specific for the two clusters. In the current study, the informational spectrum method (ISM), a bioinformatics technique, was employed to study the receptor binding patterns of the two clusters. It discovered that while both groups shared the same primary human binding affinity, their secondary binding preferences were different. Cluster one favored swine binding as its secondary binding pattern, whereas cluster two mostly exhibited the binding specificity of A/South Carolina/1/18 (H1N1) (one of the 1918 flu pandemic strains) as its secondary binding pattern. Besides all the nine nucleotide changes found in the previous study, Random Forests were applied to uncover several new nucleotide polymorphisms in 10 genes of the strains between the two clusters, and several amino acid changes in the HA protein that might be accountable for the discrepancy of the secondary receptor binding patterns of the two clusters. Finally, entropy analysis was conducted to present a global view of gene sequence variations between the two clusters, which illustrated that cluster one had much higher genetic divergence than cluster two. Furthermore, it suggested a significant overall correspondence between the nucleotide positions of high importance in differentiating the two clusters and nucleotide positions of high entropy in cluster one.
Correlated mutations in the four influenza proteins essential for viral RNA synthesis, host adaptation, and virulence: NP, PA, PB1, and PB2  [PDF]
Wei Hu
Natural Science (NS) , 2010, DOI: 10.4236/ns.2010.210141
Abstract: The NP, PA, PB1, and PB2 proteins of influenza viruses together are responsible for the transcription and replication of viral RNA, and the latter three proteins comprise the viral polymerase. Two recent reports indicated that the mutation at site 627 of PB2 plays a key role in host range and increased virulence of influenza viruses, and could be compensated by multiple mutations at other sites of PB2, suggesting the association of this mutation with those at other sites. The objective of this study was to analyze the co-mutated sites within and between these important proteins of influenza. With mutual information, a set of statistically significant co- mutated position pairs (P value = 0) in NP, PA, PB1, and PB2 of avian, human, pandemic 2009 H1N1, and swine influenza were identified, based on which several highly connected networks of correlated sites in NP, PA, PB1, and PB2 were discovered. These correlation networks further illustrated the inner functional dependence of the four proteins that are critical for host adaptation and pathogenicity. Mutual information was also applied to quantify the correlation of sites within each individual protein and between proteins. In general, the inter protein correlation of the four proteins was stronger than the intra protein correlation. Finally, the correlation patterns of the four proteins of pandemic 2009 H1N1 were found to be closer to those of avian and human than to swine influenza, thus rendering a novel insight into the interaction of the four proteins of the pandemic 2009 H1N1 virus when compared to avian, human, and swine influenza and how the origin of these four proteins might affect the correlation patterns uncovered in this analysis.
New mutational trends in the HA protein of 2009 H1N1 pandemic influenza virus from May 2010 to February 2011  [PDF]
Wei Hu
Natural Science (NS) , 2011, DOI: 10.4236/ns.2011.35051
Abstract: As we enter the year of 2011, the 2009 H1N1 pandemic influenza virus is in the news again. At least 20 people have died of this virus in China since the beginning of 2011 and it is now the predominant flu strain in the country. Although this novel virus was quite stable during its run in the flu season of 2009-2010, a genetic variant of this virus was found in Singapore in early 2010, and then in Australia and New Zealand during their 2010 winter influenza season. Several critical mutations in the HA protein of this variant were uncovered in the strains collected from January 2010 to April 2010. Moreover, a structural homology model of HA from the A/Brisbane/10/2010(H1N1) strain was made based on the structure of A/California/04/2009 (H1N1). The purpose of this study was to investigate mutations in the HA protein of 2009 H1N1 from sequence data collected worldwide from May 2010 to February 2011. A fundamental problem in bioinformatics and biology is to find the similar gene sequences for a given gene sequence of interest. Here we proposed the inverse problem, i.e., finding the exemplars from a group of related gene sequences. With a clustering algorithm affinity propagation, six exemplars of the HA sequences were identified to represent six clusters. One of the clusters contained strain A/Brisbane/12/2010(H1N1) that only differed from A/Brisbane/10/2010 in the HA sequence at position 449. Based on the sequence identity of the six exemplars, nine mutations in HA were located that could be used to distinguish these six clusters. Finally, we discovered the change of correlation patterns for the HA and NA of 2009 H1N1 as a result of the HA receptor binding specificity switch, revealing the balanced interplay between these two surface proteins of the virus.
Host markers and correlated mutations in the overlapping genes of influenza viruses: M1, M2; NS1, NS2; and PB1, PB1-F2  [PDF]
Wei Hu
Natural Science (NS) , 2010, DOI: 10.4236/ns.2010.211150
Abstract: The influenza A viruses have three gene segments, M, NS, and PB1, which code for more than one protein. The overlapping genes from the same segment entail their interdependence, which could be reflected in the evolutionary constraints, host distinction, and co-mutations of influenza. Most previous studies of overlapping genes focused on their unique evolutionary constraints, and very little was achieved to assess the potential impact of the overlap on other biological aspects of influenza. In this study, our aim was to explore the mutual dependence in host differentiation and co-mutations in M, NS, and PB1 of avian, human, 2009 H1N1, and swine viruses, with Random Forests, information entropy, and mutual information. The host markers and highly co-mutated individual sites and site pairs (P values < 0.035) in the three gene segments were identified with their relative significance between the overlapping genes calculated. Further, Random Forests predicted that among the three stop codons in the current PB1-F2 gene of 2009 H1N1, the significance of a mutation at these sites for host differentiation was, in order from most to least, that at 12, 58, and 88, i.e., the closer to the start of the gene the more important the mutation was. Finally, our sequence analysis surprisingly revealed that the full-length PB1-F2, if the three stop codons were all mutated, would function more as a swine protein than a human protein, although the PB1 of 2009 H1N1 was derived from human H3N2.
Analysis of correlated mutations, stalk motifs, and phylogenetic relationship of the 2009 influenza A virus neuraminidase sequences  [PDF]
Wei Hu
Journal of Biomedical Science and Engineering (JBiSE) , 2009, DOI: 10.4236/jbise.2009.27080
Abstract: The 2009 H1N1 influenza pandemic has attracted worldwide attention. The new virus first emerged in Mexico in April, 2009 was identified as a unique combination of a triple- reassortant swine influenza A virus, composed of genetic information from pigs, hu- mans, birds, and a Eurasian swine influenza virus. Several recent studies on the 2009 H1N1 virus util-ized small datasets to conduct analysis. With new sequences available up to date, we were able to extend the previous research in three areas. The first was finding two networks of co-mutations that may po-tentially affect the current flu-drug binding sites on neuraminidase (NA), one of the two surface proteins of flu virus. The second was discovering a special stalk motif, which was dominant in the H5N1 strains in the past, in the 2009 H1N1 strains for the first time. Due to the high virulence of this motif, the second finding is significant in our current research on 2009 H1N1. The third was updating the phylogenetic an- alysis of current NA sequences of 2009 H1N1 and H5N1, which demonstrated that, in clear contrast to previous findings, the N1 sequences in 2009 are di-verse enough to cover different major branches of the phylogenetic tree of those in previous years. As the novel influenza A H1N1 virus continues to spread globally, our results highlighted the importance of performing timely analysis on the 2009 H1N1 virus.
The interaction between the 2009 H1N1 influenza A hemagglutinin and neuraminidase: mutations, co-mutations, and the NA stalk motifs  [PDF]
Wei Hu
Journal of Biomedical Science and Engineering (JBiSE) , 2010, DOI: 10.4236/jbise.2010.31001
Abstract: As the world is closely watching the current 2009 H1N1 pandemic unfold, there is a great interest and need in understanding its origin, genetic structures, virulence, and pathogenicity. The two surface proteins, hemagglutinin (HA) and neuraminidase (NA), of the influenza virus have been the focus of most flu research due to their crucial biological functions. In our previous study on 2009 H1N1, three aspects of NA were investigated: the mutations and co-mutations, the stalk motifs, and the phylogenetic analysis. In this study, we turned our attention to HA and the interaction between HA and NA. The 118 mutations of 2009 H1N1 HA were found and mapped to the 3D homology model of H1, and the mutations on the five epitope regions on H1 were identified. This information is essential for developing new drugs and vaccine. The distinct response patterns of HA to the changes of NA stalk motifs were discovered, illustrating the functional dependence between HA and NA. With help from our previous results, two co-mutation networks were uncovered, one in HA and one in NA, where each mutation in one network co-mutates with the mutations in the other network across the two proteins HA and NA. These two networks residing in HA and NA separately may provide a functional linkage between the mutations that can impact the drug binding sites in NA and those that can affect the host immune response or vaccine efficacy in HA. Our findings demonstrated the value of conducting timely analysis on the 2009 H1N1 virus and of the integrated approach to studying both surface proteins HA and NA together to reveal their interdependence, which could not be accomplished by studying them individually.
Identification of Small and Discriminative Gene Signatures for Chemosensitivity Prediction in Breast Cancer  [PDF]
Wei Hu
Journal of Cancer Therapy (JCT) , 2011, DOI: 10.4236/jct.2011.22025
Abstract: Various gene signatures of chemosensitivity in breast cancer have been discovered. One previous study employed t-test to find a signature of 31 probe sets (27 genes) from a group of patients who received weekly preoperative chemotherapy. Based on this signature, a 30-probe set diagonal linear discriminant analysis (DLDA-30) classifier of pathologic complete response (pCR) was constructed. In this study, we sought to uncover a signature that is much smaller than the 31 probe sets and yet has enhanced predictive performance. A signature of this nature could inform us what genes are essential in response prediction. Genetic algorithms (GAs) and sparse logistic regression (SLR) were employed to identify two such small signatures. The first had 13 probe sets (10 genes) selected from the 31 probe sets and was used to build a SLR predictor of pCR (SLR-13), and the second had 14 probe sets (14 genes) selected from the genes involved in Notch signaling pathway and was used to develop another SLR predictor of pCR (SLR-Notch-14). The SLR-13 and SLR-Notch-14 had a higher accuracy and a higher positive predictive value than the DLDA-30 with much lower P values, suggesting that our two signatures had their own discriminative power with high statistical significance. The SLR prediction model also suggested the dual role of gene RNUX1 in promoting residual disease (RD) or pCR in breast cancer. Our results demonstrated that the multivariable techniques such as GAs and SLR are effective in finding significant genes in chemosensitivity prediction. They have the advantage of revealing the interacting genes, which might be missed by single variable techniques such as t-test.
Cryptanalysis of TEA Using Quantum-Inspired Genetic Algorithms  [PDF]
Wei Hu
Journal of Software Engineering and Applications (JSEA) , 2010, DOI: 10.4236/jsea.2010.31006
Abstract: The Tiny Encryption Algorithm (TEA) is a Feistel block cipher well known for its simple implementation, small memory footprint, and fast execution speed. In two previous studies, genetic algorithms (GAs) were employed to investigate the randomness of TEA output, based on which distinguishers for TEA could be designed. In this study, we used quan-tum-inspired genetic algorithms (QGAs) in the cryptanalysis of TEA. Quantum chromosomes in QGAs have the advan-tage of containing more information than the binary counterpart of the same length in GAs, and therefore generate a more diverse solution pool. We showed that QGAs could discover distinguishers for reduced cycle TEA that are more efficient than those found by classical GAs in two earlier studies. Furthermore, we applied QGAs to break four-cycle and five-cycle TEAs, a considerably harder problem, which the prior GA approach failed to solve.
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