Understanding Etiology: Mapping Clostridium difficile Spatial Distribution and Mi

了解病因：绘制艰难梭菌空间分布和 Mi

• 批准号: 8497402
• 负责人: William E Holben
• 金额: $ 35.38万
• 依托单位: UNIVERSITY OF MONTANA
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2016-09-14
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8497402
• 关键词: Address; Affect; Aftercare; Antibiotic Therapy; Antibiotics; Area; Bacteria; Carrier State; Chronic; Chronically Ill; Clinical Treatment; Clostridium difficile; Colitis; Communicable Diseases; Communities; Contracts; Development; Diarrhea; Disease; Disease Outbreaks; Disease Progression; Doctor of Philosophy; Ecology; Ecosystem; Environment; Epithelial; Etiology; Event; Faculty; Fellowship; Fluorescent in Situ Hybridization; Gastrointestinal tract structure; Goals; Health; Hospitals; Human; Immune; Incidence; Individual; Infection; Inflammation; Inflammatory Bowel Diseases; Intestinal Diseases; Intestines; Invaded; Knowledge; Language; Lead; Link; Location; Maps; Medical; Mentors; Metagenomics; Mission; Modeling; Molecular; Monitor; Mus; National Institute of Allergy and Infectious Disease; Organism; Patients; Pattern; Population; Predisposition; Prevalence; Prevention; Probiotics; Process; Prophylactic treatment; Recurrence; Recurrent disease; Research; Research Personnel; Research Project Grants; Research Technics; Research Training; Role; Sampling; Sequence Analysis; Spatial Distribution; Structure; Students; Taxon; Techniques; Testing; United States National Institutes of Health; Veterinarians; Work; base; community living; deep sequencing; design; graduate student; insight; member; microbial; microbial community; microbiome; microorganism interaction; mouse model; novel; novel strategies; pathogen; prebiotics; public health relevance; rRNA Genes; response; symposium; theories; tool; undergraduate student

DESCRIPTION (provided by applicant): One barrier that all disease-causing organisms must overcome in order to affect their host is that of microbial communities that live on and within the host (the host microbiome). Yet most studies of infectious disease fail to examine associations between pathogens and the microbiome. Here, we propose using Clostridium difficile as a model for examining how an opportunistic pathogen either causes or takes advantage of changes in the intestinal microbiome to infect the host and cause disease. C. difficile causes serious intestinal disease associated with diarrhea and colitis. C. difficile associated disease (CDAD) is linked with antibiotic treatment regimes and is increasing in incidence, with many hospital associated (nosocomial) outbreaks and continued sequelae. Current theory implies that clinical treatment with antibiotics for other infections disturbs the normal intestinal flora, alloing C. difficile to become established as an invader. While there is evidence to support this etiology, the details of how bacterial overgrowth happens, why many patients do not recover fully after treatment and why, in some patients, CDAD recurs, is still unknown. It is important to examine in detail the changes to the intestinal microbiome that contribute to disease caused by opportunistic pathogens such as C. difficile, as well as to elucidate potential interactions between the intestinal microbiome and pathogens. The language used to describe C. difficile overgrowth in the intestine is similar to that used by invasion ecologists to describe invasion events in large ecosystems. By considering the intestinal microbiome as an ecosystem and combining techniques commonly used in microbial ecology with sampling and analysis techniques from invasion and landscape ecology, a better understanding of how opportunistic pathogens invade and cause disease can be achieved. Use of a recently developed mouse model combined with deep sequencing analysis of different intestinal compartments will determine if C. difficile is distributed non- randomly with regard to location and bacterial taxa i the GI tract, and whether these bacterial associations affect where C. difficile is active which of its various disease states is manifested. In addition, fluorescence in situ hybridization (FISH) wil be used to perform a detailed analysis of the spatial organization of C. difficile with respect to specific microbiome taxa during disease progression and treatment. Aim 1: Comparison using deep sequencing and metagenomic analysis of bacterial communities in five different areas of the intestine, during antibiotic therapy, during the different states of CDAD and in normal controls. Aim 2: Spatial mapping of bacterial populations within the intestine using FISH with a special emphasis on individual species that have positive and negative associations with C. difficile. Aim 3: Advancing the NIAID AREA mission will be accomplished by uniting a molecular microbial ecologist, a bioinformatician and a veterinarian (also a Ph.D. candidate), all of whom are new NIH Investigators, in this small-scale, health-related research project which will develop and implement novel research approaches to study fundamental aspects of infectious disease.

描述（由申请人提供）：所有致病生物体为了影响其宿主而必须克服的一个障碍是生活在宿主体内和宿主体内的微生物群落。 宿主（宿主微生物组）。然而，大多数传染病研究未能检验病原体与微生物组之间的关联。在这里，我们建议使用艰难梭菌作为模型来研究机会性病原体如何引起或利用肠道微生物组的变化来感染宿主并引起疾病。艰难梭菌会引起与腹泻和结肠炎相关的严重肠道疾病。艰难梭菌相关疾病 (CDAD) 与抗生素治疗方案有关，并且发病率不断增加，许多医院相关（院内）爆发并持续出现后遗症。目前的理论表明，使用抗生素治疗其他感染的临床治疗会扰乱正常的肠道菌群，使艰难梭菌成为入侵者。虽然有证据支持这一病因， 细菌过度生长是如何发生的、为什么许多患者在治疗后没有完全康复以及为什么在某些患者中 CDAD 复发的细节仍然未知。重要的是详细检查肠道微生物组的变化，这些变化导致艰难梭菌等机会性病原体引起的疾病，并阐明肠道微生物组和病原体之间的潜在相互作用。用于描述艰难梭菌在肠道中过度生长的语言与入侵生态学家用于描述大型生态系统中入侵事件的语言类似。通过将肠道微生物组视为一个生态系统，并将微生物生态学中常用的技术与入侵和景观生态学的采样和分析技术相结合，可以更好地了解机会性病原体如何入侵并导致疾病。使用最近开发的小鼠模型结合不同肠道区室的深度测序分析将确定艰难梭菌在胃肠道中的位置和细菌分类群方面是否非随机分布，以及这些细菌关联是否影响艰难梭菌的分布位置活跃其中的 其各种疾病状态均有体现。此外，荧光原位杂交（FISH）将用于在疾病进展和治疗期间对艰难梭菌相对于特定微生物组分类群的空间组织进行详细分析。目标 1：在抗生素治疗期间、CDAD 不同状态期间和正常对照中，对肠道五个不同区域的细菌群落进行深度测序和宏基因组分析进行比较。目标 2：使用 FISH 对肠道内细菌种群进行空间绘图，特别强调与艰难梭菌有正相关和负相关的单个物种。目标 3：推进 NIAID AREA 的使命将通过联合一名分子微生物生态学家、一名生物信息学家和一名兽医（也是一名博士候选人）来完成，他们都是 NIH 新研究人员，在这个小规模的、与健康相关的领域研究项目将开发和实施新的研究方法来研究传染病的基本方面。