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
基本信息
- 批准号:10642891
- 负责人:
- 金额:$ 83.75万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AddressAerobicAntibiotic ResistanceAntibiotic TherapyAntibioticsAntimicrobial ResistanceAtmosphereAutomationAutomobile DrivingBioreactorsClinicalCommunitiesComplexDrug resistanceEcologyEcosystemEnvironmentEscherichia coliEvolutionFeedbackGasesGeneticGrowthHumanHuman MicrobiomeIndividualInfectionLaboratoriesLifeMapsMicrobeMicrobial Antibiotic ResistanceMutationNatureOrganismOutcomeOxygenPathogenicityPathway interactionsPharmaceutical PreparationsPopulationPopulation GeneticsPredispositionPrevention strategyProbioticsPublic HealthResearchResearch PersonnelResistanceRoleSamplingScheduleSchemeSiteSourceSystemTechnologyTimeWorkatmospheric conditionsbacterial communitycostcost effectiveemerging antibiotic resistanceemerging antimicrobial resistanceexperimental studyfitnessgenetic approachgenetic elementglobal healthgut microbesgut microbiomegut microbiotahigh throughput technologyin vivoinstrumentmembermetagenomic sequencingmicrobialmicrobiome researchmulti-drug resistant pathogennovelopen sourcepathogenpathogenic bacteriapathogenic microbepreventresistance mutationsuccesstooltreatment strategy
项目摘要
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
期刊论文数量(3)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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:
- 影响因子:0
- 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:
- 影响因子:15.5
- 作者:
- 通讯作者:
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:
- 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
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Ahmad Samir Khalil其他文献
Ahmad Samir Khalil的其他文献
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{{ truncateString('Ahmad Samir Khalil', 18)}}的其他基金
2023 Synthetic Biology Gordon Research Conference and Gordon Research Seminar
2023年合成生物学戈登研究大会暨戈登研究研讨会
- 批准号:
10753604 - 财政年份:2023
- 资助金额:
$ 83.75万 - 项目类别:
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 - 财政年份:2022
- 资助金额:
$ 83.75万 - 项目类别:
Synthetic toolkit for precision gene expression control and signal processing in mammalian cells
用于哺乳动物细胞中精确基因表达控制和信号处理的合成工具包
- 批准号:
10380832 - 财政年份:2020
- 资助金额:
$ 83.75万 - 项目类别:
Synthetic toolkit for precision gene expression control and signal processing in mammalian cells
用于哺乳动物细胞中精确基因表达控制和信号处理的合成工具包
- 批准号:
10584605 - 财政年份:2020
- 资助金额:
$ 83.75万 - 项目类别:
Synthetic toolkit for precision gene expression control and signal processing in mammalian cells
用于哺乳动物细胞中精确基因表达控制和信号处理的合成工具包
- 批准号:
10153781 - 财政年份:2020
- 资助金额:
$ 83.75万 - 项目类别:
ePACE: an automated system for high-throughput, closed-loop control of continuous molecular evolution to enable novel therapeutics
ePACE:一种自动化系统,用于高通量、闭环控制连续分子进化,以实现新型疗法
- 批准号:
9925776 - 财政年份:2019
- 资助金额:
$ 83.75万 - 项目类别:
ePACE: automation platforms for adaptable and scalable continuous evolution of biomolecules with therapeutic potential
ePACE:自动化平台,用于具有治疗潜力的生物分子的适应性和可扩展的持续进化
- 批准号:
10734591 - 财政年份:2019
- 资助金额:
$ 83.75万 - 项目类别:
ePACE: an automated system for high-throughput, closed-loop control of continuous molecular evolution to enable novel therapeutics
ePACE:一种自动化系统,用于高通量、闭环控制连续分子进化,以实现新型疗法
- 批准号:
10113365 - 财政年份:2019
- 资助金额:
$ 83.75万 - 项目类别:
ePACE: an automated system for high-throughput, closed-loop control of continuous molecular evolution to enable novel therapeutics
ePACE:一种自动化系统,用于高通量、闭环控制连续分子进化,以实现新型疗法
- 批准号:
10391333 - 财政年份:2019
- 资助金额:
$ 83.75万 - 项目类别:
Combatting antibiotic resistance with synthetic biology technologies
利用合成生物学技术对抗抗生素耐药性
- 批准号:
9167953 - 财政年份:2016
- 资助金额:
$ 83.75万 - 项目类别:
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