Optimized identification of therapeutic bacterial strains in ulcerative colitis

溃疡性结肠炎治疗性菌株的优化鉴定

• 批准号: 10017191
• 负责人: Jose C Clemente
• 金额: $ 25.42万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10017191
• 关键词: Achievement; Address; Algorithms; Bacteria; Chronic; Clinical; Clinical Trials; Clostridium difficile; Colitis; Collection; Communities; Data; Data Analyses; Data Set; Development; Disease; Disease Progression; Disease remission; Environmental Risk Factor; Etiology; Future; Genetic; Genetic Predisposition to Disease; Gnotobiotic; Gold; Health; Immune response; Incidence; Infection; Inflammatory; Machine Learning; Mediating; Metagenomics; Methods; Modeling; Mus; Onset of illness; Outcome; Pathogenesis; Pathway Analysis; Patients; Positioning Attribute; Probiotics; Property; Research; Resources; Role; Sampling; Shotguns; Societies; Software Tools; T-Lymphocyte; Techniques; Testing; Therapeutic; Time; Ulcerative Colitis; United States; Voting; bacterial community; base; clinical remission; cohort; design; fecal transplantation; improved; in silico; learning network; learning strategy; metagenome; metagenomic sequencing; method development; microbial; microbiome; microbiota; mouse model; novel; novel strategies; outcome prediction; placebo group; potential biomarker; predicting response; predictive modeling; prevent; probiotic therapy; prophylactic; randomized trial; response; simulation; supervised learning; therapeutic target; tool

PROJECT SUMMARY Ulcerative colitis (UC) is a chronic gut inflammatory condition thought to be caused by a combination of genetic and environmental factors. Therapeutic options are only partially effective in inducing and maintaining remission, and there is currently no cure for UC. Recent studies have found the microbiome of UC patients is distinct compared to that of healthy controls, suggesting that the microbiome could be a promising therapeutic target. Fecal microbiota transplant (FMT) has been extremely successful in the treatment of colitis caused by Clostridium difficile infection, further demonstrating the potential for bacterial therapeutics. The recently completed FOCUS (Faecal Microbiota Transplantation in Ulcerative Colitis) trial has demonstrated that FMT from healthy donors can induce clinical remission in 27% of UC patients compared to only 8% in the placebo group. However, we still lack an understanding of the exact mechanisms by which FMT is able to modulate disease pathogenesis. The overarching hypothesis of this proposal is that UC remission after FMT is induced by specific bacteria, and that accurate identification of bacterial strains will be paramount to develop microbial therapeutics for UC. To test this hypothesis, we will first develop a novel ensemble method to identify bacterial species and strains from deep metagenomic data. This method combines software tools using a voting algorithm that is weighted based on the accuracy of each tool. The accuracy of this method will be tested using microbial culture collections from UC patients, in silico simulations, and a bacterial mock community as gold standards. We will then apply this approach to metagenomic data generated from the FOCUS study in order to identify bacterial strains that are associated with UC remission. This will be performed by using established supervised learning techniques, as well as through a novel method based on co- occurrence network analysis that identifies clusters of bacteria that act synergistically. Based on these results, we will finally validate our findings using a gnotobiotic model of colitis. The prophylactic and/or therapeutic potential of candidate bacteria will be tested by inoculating them to gnotobiotic mice colonized with the microbiota of UC patients and with colitis induced through the transfer of naïve T cells. Our proposal will be the first to address the question of how specific bacteria modulate disease progression in a randomized trial of FMT in UC through the development of more sensitive and accurate methods for strain characterization that can be experimentally validated. The rational design of our strategy to identify therapeutic bacteria will produce highly translational results that can be used to guide future clinical trials in UC.

项目概要 溃疡性结肠炎 (UC) 是一种慢性肠道炎症性疾病，被认为是由遗传因素共同引起的 和环境因素的治疗选择在诱导和维持方面仅部分有效。 最近的研究发现 UC 患者的微生物组是缓解的，目前尚无治愈方法。 与健康对照相比明显不同，表明微生物组可能是一种有前途的治疗方法 粪便微生物群移植（FMT）在治疗由肠道菌群引起的结肠炎方面取得了巨大成功。 最近，艰难梭菌感染进一步证明了细菌治疗的潜力。 已完成的 FOCUS（溃疡性结肠炎粪便微生物群移植）试验表明 FMT 来自健康捐赠者的捐赠可以使 27% 的 UC 患者出现临床缓解，而安慰剂组中只有 8% 的患者出现临床缓解 然而，我们仍然缺乏对 FMT 调节的确切机制的了解。 该提议的总体假设是 FMT 后 UC 缓解是 由特定细菌诱导，准确鉴定细菌菌株至关重要 开发治疗 UC 的微生物疗法 为了检验这一假设，我们将首先开发一种新的组合。 从深层宏基因组数据中识别细菌种类和菌株的方法该方法结合了软件。 使用投票算法的工具，该算法根据每个工具的准确性进行加权。 将使用来自 UC 患者的微生物培养物收集、计算机模拟和细菌模拟进行测试 然后，我们将这种方法应用于从社区生成的宏基因组数据。 将进行 FOCUS 研究，以确定与 UC 缓解相关的细菌菌株。 通过使用已建立的监督学习技术，以及通过基于合作的新颖方法 基于这些结果识别协同作用的细菌簇的发生网络分析， 我们最终将使用结肠炎的无菌模型来验证我们的发现。 候选细菌的潜力将通过将它们接种到定植有该细菌的无菌小鼠来测试 UC 患者的微生物群以及通过幼稚 T 细胞转移诱发的结肠炎。 首先在一项随机试验中解决特定细菌如何调节疾病进展的问题 通过开发更灵敏、更准确的菌株表征方法，在 UC 中进行 FMT 可以通过实验验证我们识别治疗性细菌的策略的合理设计。 高度转化的结果可用于指导未来的 UC 临床试验。