Defining humoral correlates of immunity against COVID-19
Defining humoral correlates of immunity against COVID-19
批准号:
10265799
负责人:
Galit Alter
金额:
$35.56万
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-04-10 至 2022-12-31
关键词:
AdenovirusesAnimal ModelAnimalsAntibodiesAntibody ResponseCOVID-19CoronavirusDNADevelopmentDiseaseFerretsFutureImmuneImmune responseImmunityImmunizeInfectionLeadLinkLung diseasesMacacaMacaca mulattaMachine LearningModelingMusPassive Transfer of ImmunityResolutionRoleSARS-CoV-2 immunitySARS-CoV-2 infectionSARS-CoV-2 spike proteinSamplingSerologySystemTranslatingVaccinationVaccine DesignVaccinesVirus DiseasesWorkimmunoregulationinsightnovel therapeuticspathogenpreventprotective efficacyvaccine development
中文摘要
自2002年以来,已经出现了几种能够导致严重呼吸道疾病的冠状病毒,但目前还没有疫苗可以防止这些迅速传播的病原体。由于我们缺乏对这些病原体的免疫相关性的了解,疫苗设计尤其滞后。细胞和体液免疫反应都与疾病的解决有关,但到目前为止,只有抗体的被动转移被证明对小鼠具有完全保护作用。有趣的是,“中和”抗体和非中和抗体的转移都显示出保护效果,突出了多种体液机制在限制病毒感染/传播中的作用。这些抗体对限制疾病具有最深远的影响,其确切的作用机制目前尚不清楚,但如果被阐明,可能为开发针对新冠肺炎和其他冠状病毒的有效疫苗提供关键见解。因此,在这里,我们的目标是采用一种系统的方法来解剖和定义抗体提供对新冠肺炎的保护的多克隆和单克隆机制。具体地说,来自脱氧核糖核酸和腺病毒26(AD26)-新冠肺炎钉蛋白(新冠肺炎)免疫的动物的样本,将受到新冠肺炎的挑战,将使用系统血清学进行全面的分析,以确定与保护小鼠、雪貂和猕猴免受感染/疾病相关的功能性体液免疫反应。机器学习建模将被用来辨别关键的免疫反应特征,这些特征在这些不同的动物环境中有效地翻译。这些研究不仅将定义疫苗和物种之间的免疫相关性,还将提供对抗体在未来疫苗背景下提供保护的精确机制的机械性见解。
英文摘要
Since 2002, several coronaviruses have emerged able to cause severe respiratory disease, however no vaccine is available to prevent these rapidly spreading pathogens. Vaccine design has specifically lagged due to our lack of understanding of the correlates of immunity against these pathogens. Both cellular and humoral immune responses have been implicated in resolution of disease, but to date only the passive transfer of antibodies has been shown to confer complete protection in mice. Interestingly, the transfer of both “neutralizing” and nonneutralizing antibodies have shown protective efficacy, highlighting the role of multiple humoral mechanisms in limiting viral infection/spread. The precise mechanism of action of these antibodies that have the most profound impact on limiting disease is currently unclear, but if elucidated could provide critical insights for the development of effective vaccines against COVID-19 and other coronaviruses. Thus, here we aim to take a systematic approach to dissect and define both the polyclonal and monoclonal mechanisms by which antibodies confer protection against COVID-19. Specifically, samples from DNA- and adenovirus 26 (Ad26)- COVID-19 Spike protein (S) immunized animals, that will be challenged with COVID-19, will be comprehensively profiled using Systems Serology, to define the functional humoral immune responses linked to protection from infection/disease in mice, ferrets, and macaques. Machine learning modeling will be employed to discern key immune response features that translate usefully across these diverse animal contexts. These studies will not only define correlates of immunity across vaccines and species, but also provide mechanistic insights into the precise mechanisms by which antibodies may confer protection in the context of future vaccines.
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