A型H3N2流行性感冒病毒之基因演化與抗原性演化之關聯性研究

Abstract

流行性感冒病毒經常對人類造成大規模的感染與死亡。發生在病毒表面紅血球凝集素(hemagglutinin簡稱為HA)上的胺基酸突變在逐漸累積之後會產生不同抗原特性的病毒株(稱為抗原性變異株)，並且造成抗原性漂變(antigenic drift)，此時疫苗常常需要在下一波疫情來臨前重新設計以提供足夠的保護力。目前人們對於流感病毒的基因演化(genetic evolution)與抗原性演化(antigenic evolution)間之關聯性尚未十分清楚，探究它們的關聯性對於公共衛生與疫苗發展是一個重要且有高度急迫性的議題。 在流感病毒中，A型(H3N2)對人有高的致死率，且演化快速。本論文提供三個構面來研究A型(H3N2)流感病毒之基因演化與抗原性演化之關聯性。在第一構面中，針對HA的抗原性變異株提出一個以決策規則為主的方法用以挑選關鍵的胺基酸位置、建立規則並研究共同改變的胺基酸位置。做法是使用資訊獲得量(information gain，IG)與亂度(entropy)來量度一個胺基酸位置用於區分抗原性變異株與相似株的鑑別力高低。該規則根據紅血球凝集素的胺基酸突變來描述一株流行病毒株是否能被疫苗株產生之抗體所抑制，而共同改變的胺基酸位置常與逃脫抗體辨識以及抗原性漂變相關。 在第二構面中，本研究加入抗原與抗體交互作用的概念，並且發展了一套抗原決定位(epitope)為主的方法以鑑別抗原性漂變。首先定義一個「變異的抗原決定位」是一個具有累積構形改變且逃脫抗體辨識的抗原決定位。實驗結果顯示，兩個關鍵胺基酸位置的改變可以引起一個抗原決定位的構形改變。除此之外，鄰近受體結合區(receptor-binding site)的兩個抗原決定位(A與B)在逃脫抗體辨識上扮演重要的角色。通常兩個改變的抗原決定位可以造成抗原性漂變。 在第三構面中，本研究探討胺基酸位置是否具有相同抗原性影響力，並且發展了一套以貝式理論為基礎的方法用以鑑別抗原性漂變。做法是利用概率比(likelihood ratio，LR)量度每個胺基酸位置所造成的抗原性變化大小。根據單純貝式網路與概率比，此方法定義ADLR用於量度一對紅血球凝集素序列間的抗原性距離(antigenic distance)。實驗結果顯示，位於抗原決定位與空間上鄰近受體結合區的位置對於抗原性漂變有決定性的影響。除此之外，ADLR與血球凝集抑制試驗(hemagglutination inhibition，HI)之血清測試值有高度的相關性，且可以解釋自西元1968年至2008的A型(H3N2)疫苗株選擇。 整體而言，此論文顯示了上述模型對於描述基因演化與抗原性演化之關聯性具有可行性與穩健度。根據HI之血清測試值、紅血球凝集素與抗體之結晶結構，此研究發現A型(H3N2)流感病毒抗原性變異株的關鍵胺基酸位置、共同演化位置、胺基酸位置規則與抗原決定位規則；更重要的是這些模型可以有效反映流感疫苗株的選擇、預測抗原性變異株及對於抗原性漂變提供具有生物意義的新洞察角度。我們相信此研究有助於未來流感疫苗的發展與了解流感病毒的演化，並能指引如何快速研發更有效的流感疫苗。未來可能的研究方向包括研究季節性H1N1流行性感冒病毒以及抗原與抗體間的交互作用。

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.