Systems Biology of Microbiome-mediated Resilience to Antibiotic-resistant Pathogens

微生物组介导的对抗生素耐药病原体的恢复力的系统生物学

• 批准号: 9234463
• 负责人: Eric G. Pamer
• 金额: $ 169.71万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-03-01 至 2021-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9234463
• 关键词: Allogenic; Antibiotic Resistance; Antibiotic Therapy; Antibiotics; Bacteria; Bacterial Antibiotic Resistance; Bacterial Infections; Categories; Clinical; Clinical Treatment; Clostridium difficile; Collection; Computer Simulation; Data; Databases; Deposition; Development; Diagnostic radiologic examination; Diet; Dietary intake; Enrollment; Event; Feces; Gastrointestinal tract structure; Germ-Free; Gnotobiotic; Goals; Growth; Hematopoietic Stem Cell Transplantation; Hospitalization; Hospitals; Human; Immune; Immunocompromised Host; Infection; Integration Host Factors; Intestinal Content; Intestines; Klebsiella pneumonia bacterium; Laboratories; Lead; Machine Learning; Measurable; Mediating; Medical Records; Memorial Sloan-Kettering Cancer Center; Metabolic; Metabolic Pathway; Metagenomics; Modeling; Modification; Molecular; Mus; Patient risk; Patients; Pharmaceutical Preparations; Pharmacy facility; Population; Predisposition; Resistance; Resistance to infection; Risk; Sampling; Symbiosis; Symptoms; Systems Biology; Testing; Toxic effect; Transplantation; Uncertainty; Vancomycin Resistance; Vancomycin resistant enterococcus; antimicrobial drug; bacterial resistance; clinically relevant; commensal microbes; computer studies; design; experimental study; falls; gut microbiota; immune activation; mathematical model; member; metabolome; metabolomics; metagenome; metagenomic sequencing; microbiome; microbiota; microorganism interaction; mouse model; network models; novel; novel strategies; parallel computer; pathogen; patient population; prevent; public health relevance; rRNA Genes; resilience; resistance mechanism; text searching; transcriptome; transcriptome sequencing; transcriptomics

 DESCRIPTION (provided by applicant): Infections caused by antibiotic-resistant bacterial pathogens are exceedingly common in immunocompromised hosts. Patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) are particularly susceptible to these infections and are the patient population our studies will focus upon. Our goal is to extend and further develop systems biology approaches that our group has pioneered to identify mechanisms by which the intestinal microbiota confers resistance to infection by Vancomycin-resistant Enterococcus (VRE), antibiotic-resistant Klebsiella pneumoniae (arKp) and Clostridium difficile (C. diff). Aim 1 of our project is to establish a clinical database from the hospital recrds of allo-HSCT patients during their initial hospitalization that will include all laboratory values,vital signs, pharmacy data, dietary data, symptoms and physical exam findings. Aim 2 will expand our fecal bank by collecting fecal samples from approximately 160 allo-HSCT patients per year and determining the presence/absence of VRE, arKp and C. diff by culture and PCR. We will use NGS of 16S rRNA genes to determine microbiota composition on each sample, will perform metagenomic and RNA sequencing to determine the bacterial transcriptome and perform metabolomic analyses on a selected subset of fecal samples. Aim 3 is to extend our mathematical modeling to identify specific members of the microbiota, metabolic pathways and metabolic products that correlate with resistance to VRE or arKp expansion in the GI tract or are associated with resistance to C. diff infection. The clinical database will be used to establish correlations between clinical treatments or events and changes in the intestinal microbiota or the expression of bacterial metabolic pathways. Ultimately, the computational platforms developed in aim 3 will identify bacterial species or consortia that are associated with resistance to infection and Aim 4 will test these associations in germ-free mouse models. We will culture bacterial species associated with resistance, colonize mice with these protective bacteria and test for resistance against VRE, arKp and C. diff. Samples obtained from these experimental studies will be subjected to metagenomic and metabolomic analyses to further refine, in an iterative fashion, computational models developed in aim 3. Our proposed studies will develop new and extend existing computational models to identify bacterial species and molecular mechanisms that confer resistance to antibiotic-resistant bacterial infections.

 描述（由适用提供）：在免疫功能低下的宿主中，由抗生素耐药细菌病原体引起的感染非常普遍。接受同种异体造血干细胞移植（Allo-HSCT）的患者特别容易受到这些感染的影响，并且是我们的研究将重点关注的患者人群。我们的目标是扩展和进一步开发系统生物学方法，我们的小组率先确定肠道微生物群赋予抗性万古霉素耐药肠球菌（VRE），抗生素抗生素 - 抗生素kleblebsiella kleumoniae（ARKP）和梭菌（ARKP）和梭状芽胞杆菌（C. C. diff）的机制。我们项目的目标1是在初始住院期间从医院新兵中建立一个临床数据库，其中包括所有实验室价值，生命体征，药物数据，饮食数据，症状和身体检查结果。 AIM 2每年从约160名Allo-HSCT患者中收集粪便样品，并确定VRE，ARKP和C. diff通过培养和PCR确定存在/不存在。我们将使用16S rRNA基因的NGS确定每个样品上的微生物群组成，将执行元基因组和RNA测序，以确定细菌转录组并对选定的粪便子集进行代谢组分分析。 AIM 3是扩展我们的数学建模，以识别与抗GI区域中对VRE或ARKP膨胀的抗性相关的微生物群，代谢途径和代谢产物的特定成员，或与C. diff C. diff感染的抗性相关。临床数据库将用于在临床治疗或事件之间建立相关性，以及肠道菌群的变化或细菌代谢途径的表达。最终，AIM 3中开发的计算平台将识别与抗药性相关的细菌物种或宪法 感染和AIM 4将在无细菌小鼠模型中测试这些关联。我们将培养与耐药性相关的细菌物种，将小鼠与这些受保护的细菌定殖，并测试抗VRE，ARKP和C. diff的耐药性。从这些实验研究中获得的样品将进行宏基因组和代谢组学分析，以迭代的方式进一步完善AIM 3中开发的计算模型。我们提出的研究将开发新的和扩展现有的计算模型，以鉴定细菌物种和分子机制，从而赋予抗生素抗性细菌感染。