Biophysical constraints of influenza neuraminidase evolution

项目总结 季节性流感疫情每年造成300-500万人感染，25万至50万人死亡。而当 季节性流感疫苗是可用的，并且不断更新，其有效性经常受到以下因素的阻碍 循环菌株的快速抗原漂移。因此，流感研究的一个主要目标是开发一种 更有效的疫苗。然而，对流感病毒演变的预测能力较差，构成了一个巨大的 流感疫苗研发中的挑战。因此，理解生物进化轨迹是如何 正在形成的流感病毒可以极大地造福公众健康。流感病毒有两个表面 抗原，即血凝素(HA)和神经氨酸酶(NA)。虽然流感疫苗的开发已经 传统上专注于针对HA的NA作为一种有效的疫苗靶点在 最近几年。NA的进化受到几个生物物理限制，包括蛋白质的稳定性，表面 表达和酶活性。这些生物物理限制不仅决定了 个体突变，以及在其他突变(即上位性)存在的情况下，这些适应度影响如何变化。 事实上，上位性一直是进化预测的主要障碍，因为上位性可能导致相反的适合度。 同一突变在不同流感病毒株中的影响。这项拟议的研究将使用创新的高 通过实验系统地探索所有可能的氨基酸突变对NA的适合度影响 并绘制了与NA自然进化有关的上位相互作用图。此外，分子 上位性的机制将通过生化和结构生物学的方法来表征。统计 将进一步应用建模来量化NA和病毒的生物物理约束之间的关系 健身。这些结果将全面揭示支配突变适应度的生物物理原理。 流感NA的影响和上位性相互作用，以及其在自然进化中的进化轨迹。 因此，这项拟议的研究将推动构建统一的生物物理模型，以准确地 预测流感病毒的演变，进而促进下一代的发展 流感疫苗。

PROJECT SUMMARY Seasonal influenza epidemic causes 3-5 million infections and 250,000 to 500,000 deaths every year. While seasonal influenza vaccine is available and being constantly updated, its effectiveness is often hampered by the rapid antigenic drift of circulating strains. As a result, a major goal of influenza research is to develop a more effective vaccine. Nevertheless, the poor ability to forecast the evolution of influenza virus poses a huge challenge in influenza vaccine development. Consequently, understanding how the evolutionary trajectories of influenza virus are being shaped can significantly benefit public health. Influenza virus has two surface antigens, namely hemagglutinin (HA) and neuraminidase (NA). While influenza vaccine development has traditionally focused on targeting the HA, NA has received increasing attention as an effective vaccine target in recent years. Evolution of NA is under several biophysical constraints including protein stability, surface expression, and enzymatic activity. These biophysical constraints determine not only the fitness effects of individual mutations, but also how these fitness effects vary in the presence of other mutations (i.e. epistasis). In fact, epistasis has been a main obstacle in evolution forecast since epistasis can lead to opposite fitness effects of the same mutation in different influenza strains. This proposed study will use innovative high- throughput experiments to systematically probe the fitness effects of all possible amino-acid mutations on NA and map epistatic interactions that are involved in the natural evolution of NA. In addition, the molecular mechanisms of epistasis will be characterized by biochemical and structural biology approaches. Statistical modeling will further be applied to quantify the relationships between biophysical constraints of NA and viral fitness. The results will comprehensively reveal the biophysical principles that govern the mutational fitness effects and epistatic interactions in influenza NA, and hence its evolutionary trajectories in natural evolution. This proposed study will therefore promote the construction of a unifying biophysical model to accurately forecast the evolution of influenza virus, which will in turn facilitate the development of next-generation influenza vaccines.