A Genomics Based Investigation of the Determinants of Polymicrobial Infectious Disease Outcomes

基于基因组学的多种微生物传染病结果决定因素的研究

• 批准号: 10375504
• 负责人: CLAIRE M. FRASER
• 金额: $ 342.87万
• 依托单位: UNIVERSITY OF MARYLAND BALTIMORE
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-04-15 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10375504
• 关键词: Acute; Address; Affect; Animals; Antifungal Agents; Antimalarials; Area; Bacteria; Bioinformatics; Biological; Biology; CRISPR/Cas technology; Cell Culture Techniques; Cells; Child; Childhood; Communicable Diseases; Complex; Development; Disease; Disease Outcome; Disease model; Drug resistance; Ecosystem; Enrollment; Enteral; Evolution; Feces; Female; Foundations; Gastrointestinal tract structure; Gender; Gene Expression; Gene Expression Profile; Genes; Genetic; Genome; Genomics; Gnotobiotic; Goals; Health; Human; Immune response; Immune system; Individual; Infection; Institutes; Integration Host Factors; Invaded; Investigation; Knowledge; Laboratories; Malaria; Maryland; Metagenomics; Microbe; Molecular; Nematoda; New York; Organism; Outcome; Parasites; Pathogenicity; Pathway interactions; Pharmaceutical Preparations; Plasmodium falciparum; Play; Primary Cell Cultures; Process; Published Comment; Research; Research Personnel; Research Project Grants; Respiratory System; Respiratory physiology; Role; Sampling; Scedosporium; Schistosoma haematobium; Sex Differences; Site; Sputum; Stimulus; Streptococcus pneumoniae; System; Technology; Testing; Toxic effect; Universities; Vaccines; Variant; Viral Genome; Viral Pathogenesis; Virulence; Virulence Factors; Virus; Virus Diseases; Work; antimicrobial; base; co-infection; commensal microbes; comparative; complex data; cross immunity; data integration; design; enteric pathogen; enteric virus infection; fungus; gene product; genome editing; genome sciences; high throughput technology; human subject; in vivo; influenzavirus; insight; male; medical schools; member; microbial genomics; microbiome analysis; microbiome components; microbiota; mouse model; multiple omics; new technology; new therapeutic target; nonhuman primate; normal microbiota; novel; pathogen; pathogenic bacteria; pathogenic fungus; pathogenic virus; priority pathogen; respiratory; single-cell RNA sequencing; stool sample; technology development; technology research and development; tool; transcriptomics; virome

The advent of high-throughput genomics and associated technologies have afforded the ability to begin to ask detailed questions about the biology of whole systems and the interactions of those parts, rather than examining parts of the system in isolation. This application contains studies that explore the dynamic interactions between pathogens, hosts, their microbiota and the immune system with the goal to provide a more comprehensive understanding of the determinants of infectious disease outcomes. Pathogens subvert host cells by using their gene products to manipulate cellular pathways for survival and replication; in turn, host cells respond to the invading pathogen through changes in gene expression. Deciphering these complex temporal and spatial dynamics to identify novel virulence factors or host response pathways is essential for complete understanding of the infectious disease process. However, even these approaches don't fully take into account the complexity of the interactions, given that the normal microbiota are also key players in these interactions. The majority of the members of the normal microbiota exist as mutualists that live in association with the host without causing disease. Yet, the interactions of a host, its microbiota, and a pathogen in the context of the host immune response, co-infections, anti-microbial therapies, or vaccines can greatly affect disease outcome. The integration of the high-throughput technology with the biological question highlights the evolution of genomics as an area of research from a strictly observational tool of only a few years ago, to being an integral part in the examination of the disease process and human health as a whole. The genomic viewpoint is becoming more complete, as we can begin to simultaneously characterize the interactions of host, pathogen and microbiota. The current application takes a systematic approach to the examination of not just a single pathogen, or the ecosystem that the pathogen is part of, but examines the impact of the other microbes and host factors on the infectious disease process. The integration of the data from these complex interactions is providing the foundation for a deeper understanding of health and disease. This proposal includes a highly collaborative group of investigators centered within the Institute for Genome Sciences at the University of Maryland and New York University who are experts in their respective areas of pathogen biology, but also are pioneers in the field of genomics. We expect that these studies will address major gaps in knowledge related to the molecular pathogenesis of viral, bacterial, fungal and parasitic pathogens.

高通量基因组学和相关技术的出现使我们有能力开始去问 关于整个系统的生物学和这些部分的相互作用的详细问题，而不是 孤立地检查系统的各个部分。此应用程序包含探索动态的研究 病原体，宿主，其微生物群和免疫系统之间的相互作用，目的是提供 更全面地了解传染病结果的决定因素。病原体颠覆 宿主细胞通过使用它们的基因产物来操纵细胞存活和复制的途径;反过来，宿主细胞 细胞通过基因表达的变化对入侵的病原体作出反应。解读这些复杂的 时间和空间动态，以确定新的毒力因子或宿主反应途径是必不可少的， 全面了解传染病的发病过程。然而，即使这些方法也不能完全 考虑到相互作用的复杂性，因为正常的微生物群也是这些相互作用的关键参与者。 交互.正常微生物群的大多数成员都是以共生的形式存在的 而不引起疾病。然而，宿主，其微生物群和病原体在体内的相互作用 宿主免疫应答的背景、合并感染、抗微生物疗法或疫苗可以极大地影响 疾病结果。高通量技术与生物学问题的结合突出了 基因组学作为一个研究领域的演变，从几年前的严格观察工具， 这是检查疾病过程和整个人类健康的一个组成部分。基因组 观点变得更加完整，因为我们可以开始同时描述宿主， 病原体和微生物群。本申请采用系统的方法来检查， 单一病原体，或病原体所在的生态系统，但检查其他微生物的影响 和宿主因素对传染病过程的影响。从这些复杂的互动中整合数据 为更深入地了解健康和疾病提供了基础。该提案包括一个高度 一个由研究人员组成的合作小组，以华盛顿大学基因组科学研究所为中心， 马里兰州和纽约大学谁是在各自领域的病原生物学专家，但也是 基因组学领域的先驱我们希望这些研究将解决知识相关的主要差距， 病毒、细菌、真菌和寄生虫病原体的分子发病机理。