Bioinformatics Core: Core C

生物信息学核心：核心 C

基本信息

批准号：
10224804
负责人：
Rafick Pierre Sekaly
金额：
$ 19.32万
依托单位：
DREXEL UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-08-10 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10224804
关键词：
AIDS/HIV problem Acquired Immunodeficiency Syndrome Algorithms Anaerobic Bacteria Animals Antibodies Antigens Archaea Autophagocytosis Bacteria Bacterial Genes Bioinformatics CD8-Positive T-Lymphocytes Cells Characteristics Clinical Cohort Studies Collection Communities Computer Models DNA DNA Sequence Data Data Analyses Descriptor Development Diet Research Disease Enteral Enterobacteriaceae Food Generations Genes Grant HIV-1 Helminths Herpesviridae Infections Human Human Genetics Immune Immune response Immune system Individual Inflammatory Inflammatory Bowel Diseases Influenza Interleukin-10 Intestines Lead Libraries Link Macaca Mammals Measures Metadata Metagenomics Methods Molecular Molecular Profiling Mus Parasites Parasitic infection Phenotype Physiological Physiology Preparation Process Productivity Regulatory T-Lymphocyte Reproducibility Research Research Personnel Ribosomal RNA Role SIV Sampling Sampling Studies Services Shotguns Source Statistical Data Interpretation T cell response Testing Time Toll-like receptors Vaccination Vaccines Variant Viral Virus bacteriome co-infection computational pipelines computerized tools digital fecal microbiome fungus gut microbiome helminth infection host-associated microbial communities human disease immunogenic immunogenicity microbiome microbiome analysis microbiome signature mycobiome novel strategies novel vaccines predictive signature programs vaccination outcome vaccine efficacy vaccine response virome

项目摘要

Abstract: The microbiome is a key contributor to many physiologic parameters and diseases in mammals, but the effects on vaccine responses are less well defined. The microbiome has co-evolved with mammals over millions of years to include an estimated 100 trillion bacteria and perhaps 10-fold more viruses. We have recently found that anaerobic bacteria have profound effects on the generation of IL10-expressing CD4 Treg cells through autophagy gene-dependent mechanisms in both mice and humans. Importantly, it has been shown that preexisting antibodies to enteric bacteria can skew vaccine responses to cross-reacting HIV-1 antigen, arguably rendering a vaccine less protective and that enteric bacterial components regulate the vaccine response to influenza in mice through activation of Toll-like receptors. Helminth infections also have profound effects on host immune response. Limited study in human suggests that helminth infection may alter bacterial microbiome61. Helminths are documented to lower the efficacy of vaccination. The role of Core C is to provide centralized computational and technologic expertise, sequencing, and algorithms to generate an in depth analysis of the microbiome in subjects within the study cohorts that will be critical to understand both difference in the microbiome between subjects with and without helminth infection and the relationship between these descriptors and vaccine responses. Integrated analysis linking variations in the microbiome to study cohort metadata including measures of immune responses and other '-omic' signatures may lead to identification of digital and molecular signatures within the microbiome and host baseline immune characteristics that may be predictive of vaccine efficacy. Should the hypothesis of the U19 grant be validated (that the microbiome correlates with changes in basal immune parameters and vaccine responses), we will identify computational models that can be used as a component of analyses of new vaccines; these will be made accessible to the broader research community.

抽象的：微生物组是哺乳动物许多生理参数和疾病的关键因素，但其影响关于疫苗反应的定义尚不明确。微生物组与哺乳动物共同进化了数百万年估计需要数年时间才能包括 100 万亿个细菌以及可能多出 10 倍的病毒。我们最近发现厌氧菌通过以下方式对表达 IL10 的 CD4 Treg 细胞的产生产生深远影响：小鼠和人类的自噬基因依赖性机制。重要的是，已经表明预先存在的肠道细菌抗体可能会影响疫苗对交叉反应 HIV-1 抗原的反应，可以说使疫苗的保护作用减弱，并且肠道细菌成分调节疫苗通过激活 Toll 样受体对小鼠流感做出反应。蠕虫感染也有对宿主免疫反应产生深远影响。有限的人类研究表明蠕虫感染可能会改变细菌微生物组61。据记录，蠕虫会降低疫苗接种的效果。 Core C 的作用是提供集中的计算和技术专业知识、排序和对研究队列中受试者的微生物组进行深入分析的算法对于理解接受和不接受受试者之间微生物组的差异至关重要蠕虫感染以及这些描述符与疫苗反应之间的关系。融合的将微生物组的变化与研究队列元数据（包括免疫测量）联系起来的分析响应和其他“-omic”签名可能会导致识别数字和分子签名微生物组和宿主基线免疫特征可预测疫苗功效。应该 U19 的假设得到验证（微生物组与基础免疫的变化相关）参数和疫苗反应），我们将确定可用作组成部分的计算模型新疫苗的分析；这些将向更广泛的研究界开放。