Using a comparative One Health approach to investigate the structural basis of antigenic variation among human and avian influenza viruses

据估计，人类流感病毒每年在全球造成300万至500万例严重疾病，造成25万至50万人死亡。禽流感病毒（AIVs）通过人畜共患感染和重组病毒的大流行潜力对全球家禽生产和人类健康构成威胁。世卫组织的全球流感监测和应对系统进行了半个多世纪的病毒学监测，负责对流行的流感病毒进行遗传和抗原鉴定，并支持选择流感病毒用于人类流感疫苗的生产。在许多国家，家禽疫苗接种已成为控制地方病的主要做法之一，人接种疫苗将是大流行情况下应对措施的重要组成部分。现有预防人类和禽流感病毒的疫苗的有效性受到抗原变异出现的威胁。由于抗原漂移导致的疫苗匹配不理想可导致疫苗失败，给人类和动物健康造成负担，造成重大经济损失，并威胁粮食安全。流感疫苗的效力高度依赖于疫苗种子与流行毒株的抗原匹配，流感毒株的特点是抗原随时间漂移，b细胞表位的结构变化有助于摆脱预先存在的免疫。因此，迫切需要更好地了解主要流感抗原血凝素抗原性的分子基础。对于艾滋病病毒来说尤其如此，因为它们通常受到的关注较少，因此对它们的了解也较少。同时，在人类季节性流感病毒，特别是甲型H1N1流感和H3N2流感的抗原特征方面投入了大量资源，以指导关于人类季节性流感疫苗组成的决定。关于人类病毒的广泛知识和数据可以为更严格和更了解生物学的模型提供信息，以适用于艾滋病病毒感染者，在这种情况下，使用“同一个健康”比较方法有机会取得重大进展。基于这些人类和禽类病原体抗原蛋白的结构和氨基酸序列，将建立一个具有生物物理信息的免疫反应性和受体结合亲和力的结构模型。这将用于确定影响病毒交叉反应性的潜在因素，从而确定疫苗效力。该模型将通过对三维蛋白质结构和决定抗体-抗原相互作用的生物物理学信息的更大整合来扩展先前的工作。已经产生的关于人类甲型流感病毒的大量数据将被整理并用于改进这一模型。然后，这个改进的模型将应用于AIV，将医学领域的知识转移到兽医领域。实验室工作将用于实验验证血凝素表型变异的结构模型。对aiv的研究将提供更好地了解受体结合亲和度变化对交叉反应性的影响，这反过来有利于医学领域，因为这对于人类甲型H3N2流感病毒来说已经变得非常难以测量。然后，我们将利用这些结果来预测新出现病毒的交叉反应性，从而预测疫苗逃逸的可能性，并提出最有可能有效控制新型AIV威胁的疫苗种子株，从而使兽医疫苗学受益。对透明质酸表型变异结构基础的进一步了解也将有利于预测流感病毒进化轨迹的现有方法，帮助决策者关注人类流感病毒的选择。此外，生物物理模型将允许预测以前未观察到的病毒蛋白质的变化。

Human influenza viruses are estimated to cause 3-5 million cases of severe illness globally each year resulting in 250,000 to 500,000 deaths. Avian influenza viruses (AIVs) represent a threat to global poultry production and to human health through both zoonotic infection and the pandemic potential of reassortant viruses. The WHO's Global Influenza Surveillance and Response System has conducted virological surveillance for over half a century, is responsible for genetic and antigenic characterisation of circulating, and supports the selection of influenza viruses for human influenza vaccine production. Vaccination of poultry has become one of the principal practices for control of the endemic disease in many countries and human vaccination would be a vital component of the response in a pandemic situation. The effectiveness of vaccines that exist to protect against human and avian influenza viruses are threatened by the emergence of antigenic variants. Suboptimal vaccine matching due to antigenic drift can result in vaccine failure burdening human and animal health, causing significant economic losses, and threatening food security. Influenza vaccine efficacy is highly dependent on antigenic matching of vaccine seed to circulating strains, and influenza strains are characterized by antigenic drift over time, structural changes in B-cell epitopes facilitate escape from pre-existing immunity. There is, therefore, a pressing need to better understand the molecular basis of antigenicity of the major influenza antigen, haemagglutinin. This is particularly true for AIVs which typically have received less attention and consequently about which less is known. Meanwhile, extensive resources have been invested in the antigenic characterisation of human seasonal influenza viruses, in particular influenza A H1N1 and H3N2, to guide decisions on human seasonal influenza vaccine composition. The extensive knowledge and data from human viruses can inform more rigorous and biologically informed models to apply to AIVs where there is an opportunity for significant advances to be made using a comparative One Health approach. A biophysically-informed structural model of the immunological reactivity and receptor binding avidity of these human and avian pathogens based on the structures and amino-acid sequences of their antigenic proteins will be built. This will be used to identify the underlying factors that affect virus cross-reactivity, and hence vaccine efficacy. This model will extend previous work through greater integration of information on 3-D protein structures and the biophysics determining antibody-antigen interactions. The extensive data already generated for human influenza A viruses will be collated and used to refine this model. This refined model will then be applied to AIV, transferring knowledge from the medical field to the veterinary field. Laboratory work will be used to experimentally validate the structural model of HA phenotypic variation. Studies of AIVs will offer a provide a better understanding of the influence of changes in receptor-binding avidity on cross-reactivity, which can in turn benefit the medical field, since this has become very difficult to measure for human influenza A H3N2 viruses.We will then use these results to predict cross-reactivity for newly emerging viruses and thereby the likelihood of vaccine escape, and to propose vaccine seed strains most likely to be effective for control of novel AIV threats benefitting veterinary vaccinology. The improved knowledge of the structural basis of variation in HA phenotype will also benefit existing methods used to predict evolutionary trajectories of influenza viruses, aiding decision makers concerned with the selection of human influenza viruses. Additionally, the biophysical model will allow predictions of previously unobserved changes to viral proteins to be made.