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）：为了影响其宿主，所有引起疾病的生物必须克服的障碍是生活在和内部和内部的微生物群落的障碍 主机（主机微生物组）。然而，大多数关于传染病的研究未能检查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研究机会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的模型。艰难梭菌会引起与腹泻和结肠炎有关的严重肠道疾病。艰难梭菌相关疾病（CDAD）与抗生素治疗方案有关，发病率正在增加，许多医院相关（医院）暴发和持续后遗症。当前的理论暗示，用抗生素治疗其他感染的临床治疗会扰乱正常的肠菌群，分配了艰难梭菌作为入侵者建立。尽管有证据支持这种病因，但 细菌过度生长如何发生的细节，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复发仍然未知。重要的是要详细检查肠道微生物组的变化，这些变化导致了艰难梭菌等机会性病原体引起的疾病，并阐明了肠道微生物组和病原体之间的潜在相互作用。用来描述肠道梭菌过度生长的语言类似于入侵生态学家用来描述大型生态系统中入侵事件的语言。通过将肠道微生物组视为生态系统，并将在微生物生态学中通常使用的技术与入侵和景观生态学的抽样和分析技术相结合，可以更好地理解机会性病原体如何入侵和导致疾病。使用最近开发的小鼠模型与不同肠室的深层测序分析相结合，将确定艰难梭菌在位置和细菌分类群中是否非随机分布，gi段，以及这些细菌的关联是否会影响艰难梭菌的活性。 它的各种疾病状态被表现出来。此外，将使用荧光原位杂交（FISH）来对艰难梭菌在疾病进展和治疗过程中相对于特定微生物组的空间组织进行详细分析。 AIM 1：在CDAD的不同状态和正常对照中，使用肠道五个不同区域的细菌群落的深层测序和宏基因组分析进行比较。 AIM 2：使用鱼类在肠内的细菌种群的空间映射，特别着重于与艰难梭菌具有正相关和负相关的个体物种。 AIM 3：推进NIAID区域任务将通过团结一个分子微生物生态学家，生物信息学家和兽医（也是博士学位候选人），所有这些都是新的NIH研究人员，在这项小规模，健康相关的研究项目中，将开发和实施新的研究方法，以研究和实施研究基本疾病的新型研究方法。