Does growth efficiency determine the inoculum effect?
Does growth efficiency determine the inoculum effect?
批准号:
10359939
负责人:
Robert P Smith
金额:
$46.25万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-12-17 至 2024-11-30
关键词:
AddressAdjuvantAdjuvant TherapyAffectAmericanAntibiotic TherapyAntibioticsAttenuatedBacteriaBacterial Antibiotic ResistanceBacterial InfectionsBiochemical PathwayBioinformaticsBiomassCase StudyCell DensityCessation of lifeClinicClinicalComputer SimulationCoupledDataDevelopmentDoseESKAPE pathogensEnvironmentEquilibriumEscherichia coliEvolutionFoodGenerationsGenesGoalsGrowthHospital CostsIn VitroInfectionInterdisciplinary StudyKlebsiella pneumoniaeKnock-outLeadMeasuresMetabolic PathwayMetabolismMinimum Inhibitory Concentration measurementModelingMolecularPathway interactionsPatient-Focused OutcomesPatientsPharmaceutical PreparationsPhasePopulationPopulation DensityPredispositionProtocols documentationPseudomonas aeruginosaPublic HealthResearchResistanceRiskRoleSourceStaphylococcus aureusTestingTreatment ProtocolsWorkantibiotic tolerancebacterial metabolismclinically relevantdensityeffectiveness evaluationexhaustexperienceexperimental studygraduate studentimprovedin vivointerestmathematical modelmetabolic ratemortalitynew therapeutic targetnovelnovel therapeuticspathogensuccessundergraduate student
中文摘要
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英文摘要
Project Summary/Abstract
2.8 million Americans are infected with antibiotic resistant bacteria annually. This leads to increased deaths and
hospital costs. Moreover, there are few new antibiotics being developed. There is a dire need to extend the
usefulness of existing antibiotics by understanding how bacteria tolerate antibiotic treatment. One way that
bacteria tolerate antibiotics is the inoculum effect (IE), where the initial density of a bacterial population
determines the concentration of antibiotic required to kill the population: a population of bacteria with a higher
density will require more antibiotics to kill. IE has been observed in nearly all bacteria and antibiotics, and in the
clinical setting. Surprisingly, we currently do not have treatment approaches that reduce IE, which would increase
the ability to treat infections. It has been recently discovered that bacterial metabolic rate can determine the
effectiveness of antibiotics. A higher metabolic rate reduces the amount of antibiotic required to kill a population
of bacteria. This finding is particularly relevant in the context of IE, as bacterial density, metabolism, and growth
are interrelated. Highly dense populations have a short period of growth before they exhaust their food source.
This small window of growth leads to an overall low metabolic rate. Lower density populations have a longer
period of growth before exhausting their food source. This long period of growth leads to an overall high metabolic
rate. Thus, due its overall higher metabolic rate, the population with low density would require less antibiotic to
kill relative to the high density population. This relationship between growth rate and metabolism can be
described as growth efficiency. It is possible that changes in growth efficiency can determine IE, but we have
not yet studied this. This is an important question to address as there is growing interest in using metabolite
adjuvants with antibiotic treatment to increase antibiotic efficacy. However, without knowing how metabolism, or
growth efficiency, affect IE, we risk enhancing the ability of bacteria tolerate antibiotics, which will complicate
infections. The goal of this research is to investigate how growth efficiency determines IE. This will help us
achieve our long term goal of altering bacterial metabolism to make bacteria easier to kill using antibiotics. To
address our goal, we will first examine how growth efficiency determines IE in Pseudomonas aeruginosa and
Staphylococcus aureus with a goal of determining growth conditions that can reduce, or even eliminate, IE. Next,
we will discover what genes and biochemical pathways determine growth efficiency and IE towards developing
a molecular mechanism. Our work may lead to the development of new antibiotics that reduce, or eliminate, IE.
We will use a combination of experiments that measure growth, metabolism and the ability of antibiotics to kill
bacteria. We will couple these experiments with mathematical modeling, computer simulations and
bioinformatics. The proposed work will involve graduate and undergraduate students in interdisciplinary research
with a focus on understanding antibiotic tolerance.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1128/spectrum.03241-23
发表时间:
2024-01-16
期刊:
MICROBIOLOGY SPECTRUM
影响因子:
3.7
作者:
[Aduru,Sai Varun, Szenkiel,Karolina, Lopatkin,Allison J.]
通讯作者:
Lopatkin,Allison J.
海外基金