| Summary: | 博士 === 國立交通大學 === 生物資訊及系統生物研究所 === 99 === Influenza viruses often cause significant human morbidity and mortality. Gradually accumulated mutations on the glycoprotein hemagglutinin (HA) occur immunologically distinct strains (named as antigenic variants), which lead to the antigenic drift. The emergence and spread of antigenic variants often require a new vaccine strain to be formulated before each annual epidemic. The relationship between the genetic and antigenic evolution remains unclear and to understand the relationship is an emergent issue to public health and vaccine development.
Among the influenza viruses, the influenza A (H3N2) subtype causes high mortality rates and evolves rapidly. In this thesis, we study the relationship between the genetic and antigenic evolution of influenza A (H3N2) viruses focusing on the following three dimensions. In the first dimension, we proposed a rule-based method for identifying critical amino acid positions, rules, and co-mutated positions for antigenic variants. The information gain (IG) and the entropy are used to measure the score of an amino acid position on HA for discriminating between antigenic variants and similar viruses. Based on the IG, we identified the rules describing when one (e.g. circulating) strain will not be recognized by antibodies against another (e.g. vaccine) strain. In addition, our experimental results reveal that the co-mutated positions are often related to antibody recognition and the antigenic drift.
In the second dimension, we incorporated the concept of antigen-antibody interactions and developed an epitope-based method to identify the antigenic drift of influenza A utilizing the conformation changes on antigenic sites (epitopes). A changed epitope, an antigenic site on HA with accumulated conformation changes to escape from neutralizing antibody, can be considered as a "key feature" for representing the antigenic drift. Our experimental results show that two critical position mutations can induce the conformation change of an epitope. The epitopes (A and B), which are near the receptor-binding site of HA, play key role for neutralizing antibodies. Two changed epitopes often drive the antigenic drift.
In the third dimension, we addressed the issue of whether the amino acid positions are antigenically equivalent and developed a Bayesian method to identify the antigenic drift of influenza A by quantifying the antigenic effect of each amino acid position on HA. We utilized the likelihood ratio (LR) to quantify the antigenic distance of an amino acid position. Based on naïve Bayesian network and LR, we developed an index, ADLR, to quantify the antigenic distance of a given pair of HA sequences. Our experimental results show that the positions locating on the epitopes and near the receptor-binding site are crucial to the antigenic drift. In addition, the ADLR values are highly correlated to the hemagglutination inhibition (HI) assays and can explain WHO vaccine strain selection from 1968 to 2008.
In summary, this thesis demonstrates that our models are feasible and robust to describe the relationship between the genetic and antigenic evolution. According to the HI assays and HA/antibody complex structures, we statistically derived the critical amino acid positions, co-evolution positions, residue-based rules and epitope-based rules of the antigenic variants for influenza A (H3N2) viruses. More importantly, our models can reflect the WHO vaccine strain selection, predict antigenic variants and provide biological insights for the antigenic drift. We believe that our models are useful for the vaccine development and understanding the evolution of influenza A viruses. The future work includes the study of seasonal H1N1 viruses and antigen-antibody interactions.
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