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: 10642891
• 负责人: Ahmad Samir Khalil
• 金额: $ 83.75万
• 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/10642891
• 关键词: Address; Aerobic; 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; Predisposition; Prevention strategy; Probiotics; Public Health; Research; Research Personnel; Resistance; Role; Sampling; Schedule; Scheme; Site; Source; System; Technology; Time; Work; atmospheric conditions; bacterial community; 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; 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.

项目总结/摘要 抗生素耐药微生物病原体是对公共卫生的严重和紧迫的威胁。随着吸毒率的上升- 随着耐药性感染和新抗生素治疗的不断减少，迫切需要 更好地了解、预测和预防抗菌素耐药性（AMR）的出现。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的发展路径。这 这种方法阐明了进化抗性的遗传途径，并可以确定可以利用的因素 以引导药物敏感状态并指导新的临床策略。然而，这一潜力 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，这需要以下关键能力：1）规模 在微生物、实验条件和抗生素的多样性中进化; 2）频繁的自动化 扰动和反馈在长的实验时间尺度; 3）控制，以再现的关键特征， 哺乳动物肠道环境，AMR在体内进化的主要场所。所有现有的工具在一个或多个 更多的这些能力。关键的是，实验室进化研究未能解释 细菌群落影响AMR的进化轨迹、动力学和结果。我们建议填补 通过开发一流的台式技术， 自动化和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 肠道环境耗氧（厌氧），并且目前的技术缺乏完全的氧控制， 我们将首先开发一个系统，用于单独控制微型生物反应器的大气条件， （atmostat）。我们将在eVOLVER平台上实现这一目标，eVOLVER平台是一个开源的微生物培养系统， 自动控制生长条件，易于适应新的控制功能， 可扩展的eVOLVER-atmostat的初步结果表明， 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AMR突变适合度景观的影响。大肠杆菌菌株。我们将实施一项 自动抗生素选择方案与氧气梯度的atmostat控制相结合，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。的 第二项研究将确定AMR如何在肠道微生物组的生态环境中出现，通过进化E. 大肠杆菌菌株，其肠道群落跨越多种抗生素。应用最先进的丰度量化技术 随着时间的推移和群体遗传学的方法，我们将定义生态和进化景观 大肠大肠杆菌在肠道社区。总的来说，这项工作将产生一种变革性的技术， 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AMR。

项目成果

Galectin-4 antimicrobial activity primarily occurs through its C-terminal domain.

Galectin-4 抗菌活性主要通过其 C 末端结构域发生。

• DOI: 10.1016/j.mcpro.2024.100747
• 发表时间: 2024
• 期刊: Molecular & cellular proteomics : MCP
• 作者: Jan,Hau-Ming;Wu,Shang-Chuen;Stowell,CarterJ;Vallecillo-Zúniga,MaryL;Paul,Anu;Patel,KashyapR;Muthusamy,Sasikala;Lin,Hsien-Ya;Ayona,Diyoly;Jajosky,RyanPhilip;Varadkar,SamataP;Nakahara,Hirotomo;Chan,Rita;Bhave,Devika;Lane,Wi
• 通讯作者: Lane,Wi

Vaginal microbiome-host interactions modeled in a human vagina-on-a-chip.

• DOI: 10.1186/s40168-022-01400-1
• 发表时间: 2022-11-26
• 期刊: Microbiome
• 影响因子: 15.5

Unlocking the magic in mycelium: Using synthetic biology to optimize filamentous fungi for biomanufacturing and sustainability.

• DOI: 10.1016/j.mtbio.2023.100560
• 发表时间: 2023-04
• 期刊: MATERIALS TODAY BIO
• 影响因子: 8.2
• 作者: Jo, Charles;Zhang, Jing;Tam, Jenny M.;Church, George M.;Khalil, Ahmad S.;Segre, Daniel;Tang, Tzu-Chieh
• 通讯作者: Tang, Tzu-Chieh