Evolutionarily smart vaccine strain selection for proactive vaccinology

对于像SARS-CoV-2这样的病毒，它们可以随着时间的推移而改变以逃避免疫，保持疫苗的最新状态，并有效地对抗当前的变种是一项重大挑战。流行的病毒在不断变化，因此是一个移动的目标，这很容易使疫苗中的变异落在后面。在SARS-CoV-2之前，唯一定期更新疫苗变体以跟踪病毒演变的疫苗是流感病毒疫苗。就流感而言，经过数十年的研究和实践，世卫组织的评估和毒株推荐系统运行良好，但仍有很大改进空间。与SARS-CoV-2流感疫苗株选择相当的系统仍处于起步阶段。我们的联盟将直接利用合作伙伴在流感和SARS-CoV-2方面的专业知识，优化SARS-CoV-2疫苗株选择过程，以最好地保护处于风险中的英国人群，并将继续接种COVID疫苗。该项目以我们向英国政府SAGE委员会提交的题为“为SARS-CoV-2建立中长期疫苗株选择和免疫管理”的咨询文件中概述的疫苗接种战略为基础。为了实现我们的目标，有必要能够准确地确定SARS-CoV-2变体之间的“抗原”差异。抗原差异是指病毒的变化，导致早期接种疫苗或感染所提高的免疫力得以逃脱。我们将测试来自英国和世界各地的SARS-CoV-2变体，以生成并在整个项目中保持最新的“抗原图”，以高分辨率确定SARS-CoV-2变体之间的抗原关系。此外，我们将结合三种方法进行横向扫描并积极探索病毒如何进一步进化。1. 与英国卫生安全局项目合作伙伴以及包括美国疾病控制中心和美国国立卫生研究院在内的世界范围内参与监测的同事合作，监测英国和全球变异。通过分析全球序列监测数据中的平行进化模式，确定揭示有利早期迹象的病毒遗传变化。3. 在实验室中生成病毒（不是活病毒）刺突蛋白的变体，我们用它来实验测试当前进化之前的抗原性和氨基酸取代特性。与病毒学监测相结合，我们还将进行“血清学监测”，跟踪800人队列中的抗体免疫情况，我们从大流行开始就有高度可靠的疫苗接种和感染史，并将在本项目期间继续跟踪。这种血清学监测将使我们能够测量病毒逃避免疫的选择压力，并估计人群对可能进化的新变体的免疫力，从而确定当前人群对哪些变体的免疫力最低，从而确定哪些变体的风险最大。然后，我们将测试备选疫苗株选择选择，以找到那些在最需要它的抗原空间部分最好地建立免疫力的疫苗株。这里可以进行大量优化，因为这种疫苗接种是在先前对早期变体免疫的情况下进行的。因此，我们将结合使用计算模型、动物模型和最后阶段的人体实验药物来选择和测试疫苗株。这项工作将与相关的欧洲、美国和世卫组织全球疫苗株选择过程紧密结合，并对其作出重大贡献。

For viruses, such as SARS-CoV-2, that can change over time to escape immunity, keeping a vaccine up to date, and effective against current variants is a substantial challenge. Circulating viruses are constantly changing and are thus a moving target, that is easy for the variants in the vaccine to fall behind. Before SARS-CoV-2, the only vaccine for which the variants in the vaccine are routinely updated to track the evolution of the virus is the influenza virus vaccine. For influenza, decades of research and practice have resulted in a WHO assessment and strain recommendation system that functions well, but can still be substantially improved. The equivalent system to influenza vaccine strain selection for SARS-CoV-2 is still in its infancy. Our consortium will build directly on the partners' expertise in both influenza and SARS-CoV-2 to optimize the SARS-CoV-2 vaccine strain selection process to best protect the UK population that is at risk and will continue to be vaccinated against COVID. This project builds on the vaccination strategy outlined in our advisory paper to the UK Government SAGE committee titled 'Setting up medium-and long-term vaccine strain selection and immunity management for SARS-CoV-2'.To achieve our goals it is necessary to be able to accurately determine 'antigenic' differences among SARS-CoV-2 variants. Antigenic differences are the changes in the virus that result in escape from immunity raised by earlier vaccination or infection. We will test SARS-CoV-2 variants from the UK and around the world to generate, and keep current throughout the project, 'antigenic maps' to determine, at high resolution, the antigenic relationships among SARS-CoV-2 variants. Further, we will horizon-scan and proactively explore how the virus might further evolve using a combination of three methods. 1. Surveillance of UK and global variation in collaboration with the UK Health Security Agency project partner and colleagues world-wide involved in surveillance including the US Centers for Disease Control and US National Institutes of Health. 2. Identifying genetic changes in the virus that reveal early signs of being advantageous by analyzing patterns of parallel evolution in the global sequence surveillance data. 3. Generating in the laboratory variants of the spike protein of the virus (not live virus) with which we experimentally test the antigenic and characteristics of amino acid substitutions ahead of the current evolution. In combination with this virological surveillance we will also do 'serological surveillance' in which we track the antibody immunity in a cohort of 800 individuals for which we have highly reliable vaccination and infection history from the start of the pandemic and will continue to track during this project. This serological surveillance will allow us to both measure the selection pressure on the virus to escape immunity, and to estimate the population immunity to new variants that might evolve, and thus determine which variants the current population has least immunity to, and thus to which it is most at-risk.We will then test alternate vaccine strain selection choices to find those that best build immunity in the part of antigenic space that most needs it. There is substantial optimization that can be done here because such vaccination is being done in the context of prior immunity to earlier variants. We will thus select and test vaccine strains using a combination computational models, animal models, and in final stages experimental medicine in humans. This work will be tightly integrated with, and contribute substantially to, the related european, US, and WHO global vaccine strain selection processes.