PDF(Pubmed)
Abstract：
Influenza neuraminidase (NA) has received increasing attention as an effective vaccine target. However, its mutational tolerance is not well characterized. Here, the fitness effects of >6,000 mutations in human H3N2 NA are probed using deep mutational scanning. Our result shows that while its antigenic regions have high mutational tolerance, there are solvent-exposed regions with low mutational tolerance. We also find that protein stability is a major determinant of NA mutational fitness. The deep mutational scanning result correlates well with mutational fitness inferred from natural sequences using a protein language model, substantiating the relevance of our findings to the natural evolution of circulating strains. Additional analysis further suggests that human H3N2 NA is far from running out of mutations despite already evolving for >50 years. Overall, this study advances our understanding of the evolutionary potential of NA and the underlying biophysical constraints, which in turn provide insights into NA-based vaccine design.
摘要：
流感神经氨酸酶(NA)作为一种有效的疫苗靶标受到越来越多的关注。然而,其突变耐受性没有得到很好的表征。这里,使用深度突变扫描探测人类H3N2NA中>6,000个突变的适应性效应。我们的结果表明，尽管其抗原区域具有较高的突变耐受性，有低突变耐受性的溶剂暴露区域。我们还发现蛋白质稳定性是NA突变适合度的主要决定因素。深度突变扫描结果与使用蛋白质语言模型从自然序列推断的突变适合度很好地相关。证实了我们的发现与循环菌株的自然进化的相关性。另外的分析进一步表明,尽管已经进化了>50年,人类H3N2NA还远未耗尽突变。总的来说,这项研究提高了我们对NA的进化潜力和潜在的生物物理约束的理解，这反过来提供了对基于NA的疫苗设计的见解。
