Wang Rui, Chen Jiahui, Hozumi Yuta, Yin Changchuan, Wei Guo-Wei
Department of Mathematics, Michigan State University, East Lansing, Michigan 48824, United States.
Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, Chicago, Illinois 60607, United States.
ACS Infect Dis. 2022 Mar 11;8(3):546-556. doi: 10.1021/acsinfecdis.1c00557. Epub 2022 Feb 8.
The surge of COVID-19 infections has been fueled by new SARS-CoV-2 variants, namely Alpha, Beta, Gamma, Delta, and so forth. The molecular mechanism underlying such surge is elusive due to the existence of 28 554 unique mutations, including 4 653 non-degenerate mutations on the spike protein. Understanding the molecular mechanism of SARS-CoV-2 transmission and evolution is a prerequisite to foresee the trend of emerging vaccine-breakthrough variants and the design of mutation-proof vaccines and monoclonal antibodies. We integrate the genotyping of 1 489 884 SARS-CoV-2 genomes, a library of 130 human antibodies, tens of thousands of mutational data, topological data analysis, and deep learning to reveal SARS-CoV-2 evolution mechanism and forecast emerging vaccine-breakthrough variants. We show that prevailing variants can be quantitatively explained by infectivity-strengthening and vaccine-escape (co-)mutations on the spike protein RBD due to natural selection and/or vaccination-induced evolutionary pressure. We illustrate that infectivity strengthening mutations were the main mechanism for viral evolution, while vaccine-escape mutations become a dominating viral evolutionary mechanism among highly vaccinated populations. We demonstrate that Lambda is as infectious as Delta but is more vaccine-resistant. We analyze emerging vaccine-breakthrough comutations in highly vaccinated countries, including the United Kingdom, the United States, Denmark, and so forth. Finally, we identify sets of comutations that have a high likelihood of massive growth: [A411S, L452R, T478K], [L452R, T478K, N501Y], [V401L, L452R, T478K], [K417N, L452R, T478K], [L452R, T478K, E484K, N501Y], and [P384L, K417N, E484K, N501Y]. We predict they can escape existing vaccines. We foresee an urgent need to develop new virus combating strategies.
新冠病毒感染的激增是由新的严重急性呼吸综合征冠状病毒2（SARS-CoV-2）变体引发的，即阿尔法、贝塔、伽马、德尔塔等等。由于存在28554个独特突变，包括刺突蛋白上的4653个非同义突变，这种激增背后的分子机制难以捉摸。了解SARS-CoV-2传播和进化的分子机制是预见新出现的疫苗突破性变体趋势以及设计抗突变疫苗和单克隆抗体的先决条件。我们整合了1489884个SARS-CoV-2基因组的基因分型、一个包含130种人类抗体的文库、数万个突变数据、拓扑数据分析和深度学习，以揭示SARS-CoV-2进化机制并预测新出现的疫苗突破性变体。我们表明，由于自然选择和/或疫苗诱导的进化压力，流行变体可以通过刺突蛋白受体结合域（RBD）上的感染性增强和疫苗逃逸（共）突变来定量解释。我们说明感染性增强突变是病毒进化的主要机制，而疫苗逃逸突变在高疫苗接种人群中成为主要的病毒进化机制。我们证明拉姆达变体的传染性与德尔塔变体相当，但对疫苗更具抗性。我们分析了高疫苗接种国家（包括英国、美国、丹麦等）新出现的疫苗突破性共突变。最后，我们确定了具有大量增长高可能性的共突变集：[A411S，L452R，T478K]、[L452R，T478K，N501Y]、[V401L，L452R，T478K]、[K417N，L452R，T478K]、[L452R，T478K，E484K，N501Y]和[P384L，K417N，E484K，N501Y]。我们预测它们能够逃避现有疫苗。我们预见到迫切需要制定新的病毒对抗策略。
