Biophysical constraints of influenza neuraminidase evolution

项目摘要 季节性流感流行每年造成300万至500万人感染，25万至50万人死亡。而 季节性流感疫苗是可用的，并不断更新，其有效性往往受到阻碍， 流行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，预测流感病毒演变的能力差， 流感疫苗开发的挑战。因此，了解生物的进化轨迹 流感病毒正在形成，可以大大有利于公共卫生。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 传统上专注于靶向HA，NA作为一种有效的疫苗靶点， 近年NA的进化受到几种生物物理约束，包括蛋白质稳定性、表面张力、蛋白质结构、蛋白质结构和蛋白质结构。 表达和酶活性。这些生物物理约束不仅决定了 个体突变，以及这些适应性效应在其他突变存在下如何变化（即上位性）。 事实上，上位性是进化预测的主要障碍，因为上位性会导致相反的适应度 不同流感病毒株中相同突变的影响。这项研究将采用创新的高- 通量实验，以系统地探测所有可能的氨基酸突变对NA的适应性影响 并绘制NA自然进化中所涉及的上位相互作用。此外，分子 上位性的机制将通过生物化学和结构生物学方法来表征。统计 模型将进一步应用于量化NA和病毒的生物物理约束之间的关系， 健身研究结果将全面揭示控制突变适合度的生物物理学原理 影响和上位相互作用的流感NA，因此其在自然进化的进化轨迹。 因此，这项拟议的研究将促进建立一个统一的生物物理模型， 预测流感病毒的演变，从而促进下一代疫苗的开发。 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.