Programmable benchtop bioreactors for scalable eco-evolutionary dynamics of the human microbiome

用于人类微生物组可扩展生态进化动力学的可编程台式生物反应器

• 批准号: 10503736
• 负责人: Ahmad Samir Khalil
• 金额: $ 86.76万
• 依托单位: BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-10 至 2027-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10503736
• 关键词: Address; Aerobic; Anaerobic Bacteria; Antibiotic Resistance; Antibiotic Therapy; Antibiotics; Antimicrobial Resistance; Atmosphere; Automation; Automobile Driving; Bioreactors; Clinical; Communities; Complex; Drug resistance; Ecology; Ecosystem; Environment; Escherichia coli; Evolution; Feedback; Gases; Genetic; Growth; Human; Human Microbiome; Individual; Infection; Laboratories; Life; Maps; Microbe; Microbial Antibiotic Resistance; Mutation; Nature; Organism; Outcome; Oxygen; Pathogenicity; Pathway interactions; Pharmaceutical Preparations; Population; Population Genetics; Prevention strategy; Probiotics; Public Health; Research; Research Personnel; Resistance; Role; Sampling; Schedule; Scheme; Site; Source; System; Technology; Time; Work; atmospheric conditions; bacterial community; base; cost; cost effective; emerging antibiotic resistance; emerging antimicrobial resistance; experimental study; fitness; genetic approach; genetic element; global health; gut microbes; gut microbiome; gut microbiota; high throughput technology; in vivo; instrument; member; metagenomic sequencing; microbial; microbiome research; multi-drug resistant pathogen; novel; open source; pathogen; pathogenic bacteria; pathogenic microbe; prevent; programs; resistance mutation; success; tool; treatment strategy

PROJECT SUMMARY/ABSTRACT Antibiotic-resistant microbial pathogens are a grave and urgent threat to public health. With rising rates of drug- resistant infections and a diminishing arsenal of new antibiotic treatments, there is pressing need for approaches to better understand, predict, and prevent the emergence of antimicrobial resistance (AMR). To this end, experimental evolution approaches, in which microbial organisms are evolved in the laboratory in user-defined conditions, provide a powerful paradigm to define the evolutionary paths toward AMR. This approach has illuminated genetic pathways to evolving resistance, and can define factors that can be exploited to steer toward drug-susceptible states and guide new clinical strategies. However, the potential of this approach for understanding AMR evolution is fundamentally constrained by technological barriers in conducting continuous culture and evolution experiments, which requires the following key capacities: 1) Scale to evolve across a diversity of microbes, experimental conditions, and antibiotics; 2) Automation for frequent perturbations and feedback over long experimental time scales; 3) Control to reproduce key features of the mammalian gut environment, a primary site for the evolution of AMR in vivo. All existing tools fail in one or more of these capacities. And critically, laboratory evolution studies fail to account for how interactions within bacterial communities impact the evolutionary trajectory, dynamics, and outcomes of AMR. We propose to fill this technological and experimental void by developing a first-in-class, benchtop technology for scalable, automated, and controlled microbial evolution studies, and apply it to two pressing problems in AMR. Because the gut environment is depleted of oxygen (anaerobic), and current technology lacks complete oxygen control, we will first develop a system for individual control of atmospheric conditions across mini-bioreactors (atmostat). We will achieve this in the eVOLVER platform, an open-source microbial culture system for automated control of growth conditions that is easily adapted to new control features, and is exceedingly scalable. Preliminary results of eVOLVER-atmostat demonstrate unprecedented scale for continuous culture and evolution of strict anaerobic gut microbes on the benchtop. The first study will determine the effects of oxygen tension on the mutational fitness landscapes of AMR in E. coli strains. We will implement an automated antibiotic selection regime in combination with atmostat control of oxygen gradients, and employ metagenomic sequencing to map the interactions of oxygen, antibiotics, and strains backgrounds in AMR. The second study will determine how AMR emerges in the ecological context of the gut microbiome, by evolving E. coli strains with a gut community across multiple antibiotics. Applying state-of-the-art abundance quantification over time and population genetics approaches, we will define both the ecological and evolutionary landscape of E. coli in the gut community. Collectively, this work will produce a transformative technology to be used by researchers worldwide, and begin to reveal how pathogens evolve AMR in the human gut ecosystem.

项目概要/摘要 耐抗生素微生物病原体对公众健康构成严重而紧迫的威胁。随着吸毒率的上升 由于耐药性感染和新抗生素治疗方法的不断减少，迫切需要 更好地了解、预测和预防抗菌素耐药性 (AMR) 出现的方法。到 为此，实验进化方法，其中微生物有机体在实验室中进化 用户定义的条件，提供了一个强大的范例来定义 AMR 的进化路径。这 该方法阐明了耐药性进化的遗传途径，并且可以定义可以利用的因素 引导药物敏感状态并指导新的临床策略。然而，这种潜力 理解 AMR 演变的方法从根本上受到技术障碍的限制 进行连续的培养和进化实验，需要以下关键能力：1）规模 在多种微生物、实验条件和抗生素中进化； 2) 频繁的自动化 长时间实验时间范围内的扰动和反馈； 3) 控制重现关键特征 哺乳动物肠道环境是体内 AMR 进化的主要场所。所有现有工具都会在一个或多个方面失败 更多这些能力。至关重要的是，实验室进化研究未能解释内部相互作用如何 细菌群落影响抗菌素耐药性的进化轨迹、动态和结果。我们建议填写 通过开发一流的、可扩展的台式技术来弥补这种技术和实验空白， 自动化、受控的微生物进化研究，并将其应用于 AMR 中的两个紧迫问题。因为 肠道环境缺氧（厌氧），而目前的技术缺乏完全的氧气控制， 我们将首先开发一个单独控制微型生物反应器大气条件的系统 （自动调节器）。我们将在 eVOLVER 平台中实现这一目标，这是一个开源微生物培养系统，用于 生长条件的自动控制，很容易适应新的控制功能，并且非常有效 可扩展。 eVOLVER-atmostat 的初步结果展示了前所未有的连续规模 在台式严格厌氧肠道微生物的培养和进化。第一项研究将确定 氧张力对大肠杆菌菌株 AMR 突变适应性的影响。我们将实施一个 自动抗生素选择方案与氧气梯度的恒温器控制相结合，并采用 宏基因组测序可绘制 AMR 中氧气、抗生素和菌株背景的相互作用。这 第二项研究将通过进化大肠杆菌来确定 AMR 在肠道微生物群的生态环境中是如何出现的。 具有跨多种抗生素的肠道群落的大肠杆菌菌株。应用最先进的丰度定量 随着时间的推移和群体遗传学方法的发展，我们将定义生态和进化景观 肠道群落中的大肠杆菌。总的来说，这项工作将产生一种变革性的技术，供 世界各地的研究人员开始揭示病原体如何在人类肠道生态系统中进化出 AMR。