RAPID: Immunogenicity of SARS-CoV2 to Human T Cells

自古以来，由传染性病原体引起的流行病就一直困扰着人类。由SARS-CoV-2病毒引起的2019冠状病毒病（COVID-19）目前正在包括美国在内的世界范围内迅速蔓延，对健康和经济产生了重大不利影响。SARSCoV-2的爆发导致了几项紧急努力，以开发可能提供对这种病毒的保护的疫苗。目前尚不清楚目前所采用的方法是否会在人类中引起保护性免疫反应。虽然疫苗对许多病原体非常有效，但两个多世纪前巴斯德和詹纳开创的疫苗开发经验方法未能生产出对抗人类免疫缺陷病毒、疟疾、结核病和许多其他病原体的有效疫苗。因此，基于对相关病毒学和免疫学的机制理解，正在进行合理的疫苗设计，这些努力包括植根于统计物理学的工作。SARSCoV-2在系统发育上与SARS-CoV最相似。该项目将使用机器学习方法来了解SARS-CoV-2病毒如何与免疫T细胞相互作用。这项工作将直接影响SARS-CoV-2疫苗的设计以及未来针对地方性致病性病原体的疫苗。对从SARS-CoV中康复的患者的分析表明，抗体反应在几年后并不普遍，但记忆T细胞反应是持久的，可能提供长期保护。本项目解决的主要问题是：1。在SARS-CoV-2中发生突变的人类T细胞靶向的SARS-CoV肽是否仍会引起人类T细胞反应，即它们是否具有免疫原性？2：仅通过宿主主要组织相容性分子结合试验鉴定出的102种肽是否具有SARS-CoV和SARS-CoV-2在人类中的共同免疫原性？如果没有，从疫苗设计的角度来看，它们是无关紧要的。这里提出的工作目标是采用基于物理的机器学习方法来确定SARS-CoV-2蛋白对人类T细胞反应的免疫原性。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Pandemics caused by infectious pathogens have plagued humanity since antiquity. The Coronavirus Disease 2019 (COVID-19) caused by the SARS-CoV-2 virus is currently spreading across the world rapidly, including in the United States, with major adverse impact on health and the economy. The SARSCoV-2 outbreak has led to several urgent efforts to develop vaccines that may offer protection against this virus. It is unknown as to whether the current approaches being pursued will elicit protective immune responses in humans. While vaccines have been very effective against many pathogens, the empirical methods for vaccine development pioneered by Pasteur and Jenner over two centuries ago have failed to produce effective vaccines against Human Immune Deficiency Virus, Malaria, Tuberculosis, and many other pathogens. Therefore, rational design of vaccines based on a mechanistic understanding of the pertinent virology and immunology is being pursued, and these efforts include work that is rooted in statistical physics. SARSCoV-2 is phylogenetically most similar to SARS-CoV. This project will use a machine learning approach to understand how the SARS-CoV-2 virus interacts with the immune T cells. This work will directly impact the design of SARS-CoV-2 vaccines and vaccines against future endemic-causing pathogens.Analyses of patients who have recovered from SARS-CoV shows that antibody responses are not prevalent a few years later, but memory T cell responses are durable and may offer long-term protection. The main questions addressed by this project are 1. Will the SARS-CoV peptides targeted by human T cells that are mutated in SARS-CoV-2 still elicit human T cell responses - i.e. are they immunogenic? 2: Are the 102 peptides identified by host major histocompatibility molecules binding assays alone that are common between SARS-CoV and SARS-CoV-2 immunogenic in humans? If not, they are irrelevant from vaccine design perspective. The goal of the work proposed here is to take a physics-based machine learning approach to determine the immunogenicity of SARS-CoV-2 proteins to human T cell responses.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.