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.

项目摘要/摘要 抗抗生素的微生物病原体是对公共卫生的严重和紧急威胁。随着药物率上升 抗性感染和新抗生素治疗的武器库减少，迫切需要 更好地理解，预测和防止抗菌耐药性（AMR）的出现的方法。到 实验进化方法，其中微生物在实验室中进化 用户定义的条件提供了一个强大的范式来定义AMR的进化路径。这 方法具有照明遗传途径来发展抗性，并且可以定义可以利用的因素 引导毒品敏感的状态并指导新的临床策略。但是，这种潜力 理解AMR进化的方法从根本上受到技术障碍的限制 进行连续培养和进化实验，这需要以下关键能力：1）规模 跨多种微生物，实验条件和抗生素发展； 2）频繁的自动化 在长时间的实验时间尺度上的扰动和反馈； 3）控制重现的关键特征 哺乳动物肠道环境，这是AMR体内进化的主要部位。所有现有工具都失败了 这些能力更多。至关重要的是，实验室进化研究无法说明内部的相互作用 细菌群落影响AMR的进化轨迹，动力学和结果。我们建议填补 通过开发一种一流的台式技术，用于可伸缩的技术和实验空隙 自动化和控制的微生物进化研究，并将其应用于AMR中的两个紧迫问题。因为 肠道环境耗尽了氧气（厌氧），而当前的技术缺乏完全控制的氧气控制， 我们将首先开发一个系统，以控制小型反应器的大气条件 （atmostat）。我们将在Evolver平台中实现这一目标，Evolver平台是一种开源微生物培养系统 对生长条件的自动控制很容易适应新的控制功能，并且非常适合 可扩展。最大发展的初步结果证明了连续的前所未有的量表 台式上严格的厌氧肠道微生物的培养和演变。第一项研究将确定 氧张力对大肠杆菌菌株中AMR突变适应性景观的影响。我们将实施 自动化抗生素选择方案与氧梯度的ATMOSTAT控制结合，并采用 宏基因组测序以绘制AMR中氧，抗生素和菌株背景的相互作用。这 第二项研究将通过不断发展的E来确定AMR如何在肠道微生物组的生态环境中出现。 大肠杆菌菌株具有多种抗生素的肠道群落。应用最先进的丰度量化 随着时间和人口遗传学的方法，我们将定义生态和进化格局 肠道社区中的大肠杆菌。总的来说，这项工作将产生一种变革性技术 全球研究人员，并开始揭示病原体如何在人类肠道生态系统中进化。