Dynamics of horizontal gene transfer in response to antibiotic treatment
Dynamics of horizontal gene transfer in response to antibiotic treatment
批准号:
9310629
负责人:
LINGCHONG YOU
金额:
$37.84万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-07-05 至 2021-06-30
关键词:
AddressAffectAntibiotic ResistanceAntibiotic TherapyAntibioticsBacteriaBacterial InfectionsBiological AssayClinicalCommunitiesDevelopmentDoseDrug resistanceElementsEngineeringEnvironmental Risk FactorExtended-spectrum β-lactamaseExtinction (Psychology)FoundationsGene ExchangesGenerationsGoalsGrowthHigh PrevalenceHorizontal Gene TransferInterventionInvadedKineticsLibrariesMeasurementMeasuresMediatingMethodologyMethodsMicrobial Drug ResistanceMicrofluidicsModelingOrganismOutcomePharmaceutical PreparationsPlasmidsPopulationPopulation DynamicsProcessProtocols documentationResearchResistanceSystemTestingTimeTreatment ProtocolsWorkacquired drug resistanceantibiotic designbacterial resistancebaseclinically relevantcombatexperimental studygut microbiomeinsightmicrobialmicrobial communitynovel therapeuticspathogenpathogenic bacteriaresistance generesponserisk minimizationtherapy designtreatment strategyusability
中文摘要
摘要
抗生素耐药性已经成为一种全球威胁。许多人辩称,我们已经
到了抗生素后时代,简单的细菌感染可能导致毁灭性的
后果。为了解决这一危机,需要作出广泛努力来制定战略。
除了开发新的抗生素外,更好地利用现有的抗生素。尤其是,它是
对于了解细菌种群对抗生素治疗的反应以及如何
抗生素治疗可以调节抗生素耐药性的产生和传播
细菌。抗生素耐药性快速传播的一个主要机制是水平基因
转移(HGT),尤指共轭。我们最近在广泛的范围内展示了
结合系统抗生素决定结合动力学主要是作为
挑剔的司机。特别是,抗生素可以促进和抑制HGT。
动态,取决于抗生素如何影响正在接受治疗的人口的增长率
共轭关系。基于这些结果,拟议研究的中心目标是
深入研究如何应用抗生素治疗以最大限度地减少肺炎的传播
抗生素耐药基因或迫使耐药性一旦被逆转
获得者。为了实现这一目标,我们将首先对细菌分离库中的HGT进行量化
表达超广谱β-内酰胺酶(ESBL S)。测量的参数将
允许我们将我们的模型扩展到临床相关的生物体。我们接下来将整合
用于确定抗生素剂量和组合的建模和定量实验
调节种群动态以最大限度减少耐药生物体比例的制度
并逆转抗生素耐药性。拟议的研究将产生
史无前例的定量测量抗生素和
其他环境因素。抗生素的剂量策略将有助于指导
抗生素在临床环境中的使用。
英文摘要
Abstract
Antibiotic resistance has emerged as a global threat. Many argue that we have
reached a post-antibiotic era, when simple bacterial infections could result in devastating
consequences. To address this crisis, extensive efforts are needed to develop strategies
to better use existing antibiotics, in addition to developing new ones. In particular, it is
critical to understand how bacterial populations respond to antibiotic treatment and how
antibiotic treatment can modulate the generation and spread of antibiotic-resistant
bacteria. A major mechanism of rapid spread of antibiotic resistance is horizontal gene
transfer (HGT), especially conjugation. We recently showed that in a broad range of
conjugative systems antibiotics determine conjugation dynamics primarily by serving as
a selective driver. In particular, antibiotics can both promote and suppress HGT
dynamics, depending on how antibiotics affect growth rates of populations undergoing
conjugation. Based on these results, the central goal of the proposed research is to
examine in depth how antibiotic treatment can be applied to minimize the spread of
antibiotic resistance genes or to force the reversal of the resistance once it was
acquired. To achieve this goal, we will first quantify HGT in a library of bacterial isolates
expressing extended spectrum ß-lactamases (ESBLs). The measured parameters will
allow us to expand our models to clinically relevant organisms. We next will integrate
modeling and quantitative experiments to define antibiotic dosing and combinations
regimes that modulate population dynamics to minimize fraction of resistant organisms
and to reverse antibiotic resistance. The proposed research will generate
unprecedented, quantitative measurements of modulation of HGT by antibiotics and
other environmental factors. The antibiotic dosing strategies will be useful for guiding the
use of antibiotics in the clinical setting.
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