Molecular Biology of RV-C and its Asthma-related Receptor, CDHR3

2019年12月开始的新一轮冠状病毒疫情造成了全球公共卫生紧急状态。这 导致了一项密集的搜索，以确定导致疾病易感性和严重性的因素。我们 最近开发了一种阵列来识别鼻病毒的抗体结合表位。这些阵列中的数据可以 结合有关病毒蛋白结构的信息来识别呼吸道高免疫原性区域 病毒。我们建议将这个序列扩大到包括代表SARS-CoV-2和所有其他感染人类的常见冠状病毒(OC43、NL63等)的整个蛋白质组的线性表位。研究人群将 包括来自海岸、WISC和URECA出生队列研究的儿童，他们也参与了 英雄SARS-CoV-2监测研究。作为日常队列活动的一部分，这些儿童经历了一系列 血液和鼻腔分泌物的样本，我们可以使用阵列进行分析，以确定单个模式 抗病毒抗体表位识别。我们假设特异性抗体的模式和数量 常见冠状病毒的表位与SARS-CoV-2感染和疾病的易感性有关。我们 提出三个具体目标，以利用英雄前后从儿童那里获得的血清-确认 感染SARS-CoV-2。首先，在感染前获得的样本中，我们将使用阵列来识别模式 对常见儿童冠状病毒的抗体表位识别，评估与SARS-CoV-2的交叉反应， 并确定交叉反应是否与预防感染或疾病有关。在第二个 目的：我们将确定对常见呼吸道病毒的抗体反应的多样性是否与 减少感染或患病的风险。最后，在第三个目标中，我们将描述前面的抗体结合模式 并在已知新冠肺炎病例后确定具有免疫原性和中和作用的候选区域。至 为了实现这一目标，我们将进行微量中和分析(可在克里斯汀博士的BSL3实验室获得 Bernard，UW Madison)对出现症状的儿童的恢复期血清或鼻分泌物进行研究 感染。这些信息将与感染前和感染后的阵列数据一起使用计算机进行分析 识别中和表位的学习方法。识别交叉保护的血清学反应模式有助于识别人群中的易感个体，并指导疫苗设计 当前和未来的病毒。

The new coronavirus outbreak that begin in December 2019 has created a global public health emergency. This has led to an intense search to identify factors that contribute to the susceptibility and severity of illness. We recently developed an array to identify antibody-binding epitopes for rhinoviruses. Data from these arrays can be combined with information about viral protein structure to identify highly immunogenic regions for respiratory viruses. We propose to expand this array to include linear epitopes that represent the entire proteome of SARS-CoV-2 and all other common coronaviruses that infect humans (OC43, NL63, etc.). The study population will include children from the COAST, WISC and URECA birth cohort studies who are also participating in the HEROS SARS-CoV-2 surveillance study. As part of routine cohort activities, these children undergo serial sampling of blood and nasal secretions that we can analyze using the array to determine individual patterns of antiviral antibody epitope recognition. We hypothesize that the pattern and quantity of antibody specific for epitopes of common coronaviruses contributes to the susceptibility to SARS-CoV-2 infection and illness. We propose three specific aims that will utilize sera obtained from children before and after HEROS-confirmed infection with SARS-CoV-2. First, in specimens obtained pre-infection we will use the array to identify patterns of antibody epitope recognition to common childhood coronaviruses, assess cross-reactivity with SARS-CoV-2, and determine whether cross-reactivity is associated with protection against infection or illness. In the second aim, we will determine whether the diversity of antibody responses to common respiratory viruses is associated with a reduced risk of infection or illness. Finally, in the third aim we will describe antibody binding patterns before and after known COVID-19 cases to identify candidate regions that are immunogenic and neutralizing. To accomplish this aim, we will perform micro-neutralization assays (available in the BSL3 laboratory of Dr. Kristen Bernard, UW Madison) on convalescent sera or nasal secretions from children who developed symptomatic infection. This information will be analyzed together with pre- and post-infection array data using machine learning approaches to identify neutralizing epitopes. Identifying patterns of serologic responses that are crossprotective could help to identify susceptible individuals in the population and direct the design of vaccines to current and future viruses.