Biophysical constraints of influenza neuraminidase evolution

流感神经氨酸酶进化的生物物理限制

• 批准号: 10522548
• 负责人: Nicholas C. Wu
• 金额: $ 51.23万
• 依托单位: UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-28 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10522548
• 关键词: Amino Acid Substitution; Amino Acids; Antibodies; Attention; Biochemical; Biological Assay; Biology; Biophysical Process; Biophysics; Cessation of life; Data; Development; Effectiveness; Evolution; Genetic; Genetic Epistasis; Glycoproteins; Goals; Hemagglutinin; Human; Immunity; Individual; Infection; Influenza; Influenza A Virus, H1N1 Subtype; Influenza A Virus, H3N2 Subtype; Influenza A virus; Influenza Hemagglutinin; Knowledge; Lead; Light; Maps; Measures; Molecular; Mutation; Neuraminidase; Pathway interactions; Play; Population; Proteins; Public Health; Research; Role; Shapes; Statistical Models; Surface; Surface Antigens; Update; Vaccines; Viral; Viral Proteins; Virus Replication; biophysical model; experimental study; fitness; global health; influenza epidemic; influenza virus strain; influenza virus vaccine; influenzavirus; innovation; insight; interdisciplinary approach; interest; mutant; mutation screening; next generation; porcine model; seasonal influenza; structural biology; transmission process; vaccine development; viral fitness; virus development

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.

项目概要 季节性流感流行每年造成3-500万人感染和25万至50万人死亡。尽管 季节性流感疫苗已经可用并不断更新，其有效性往往受到以下因素的影响： 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，预测流感病毒进化的能力差给我们带来了巨大的影响。 流感疫苗开发面临的挑战。因此，了解进化轨迹如何 正在塑造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）。虽然流感疫苗的研发已经 传统上主要针对 HA，NA 作为有效的疫苗靶点受到越来越多的关注 近年来。 NA 的进化受到多种生物物理限制，包括蛋白质稳定性、表面 表达和酶活性。这些生物物理限制不仅决定了健身效果 个体突变，以及这些适应度效应在其他突变存在时如何变化（即上位性）。 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应度 相同突变对不同流感病毒株的影响。这项拟议的研究将使用创新的高 通量实验系统地探讨所有可能的氨基酸突变对 NA 的适应性影响 并绘制了参与 NA 自然进化的上位相互作用。此外，分子 上位机制将通过生化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 健康。结果将全面揭示控制突变适应性的生物物理原理 流感 NA 的影响和上位相互作用，以及其在自然进化中的进化轨迹。 因此，这项研究将促进统一生物物理模型的构建，以准确地 预测流感病毒的进化，从而促进下一代流感病毒的开发 流感疫苗。