A Droplet-based single cell platform for pathogen identification and AST
用于病原体识别和 AST 的基于 Droplet 的单细胞平台
基本信息
- 批准号:9038992
- 负责人:
- 金额:$ 118.49万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-04-01 至 2020-03-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAffectAgeAntibiotic susceptibilityAntibioticsArizonaBacterial InfectionsBiological AssayBypassCell Culture TechniquesCellsClinicalCulture MediaCytolysisDataDetectionDevelopment PlansDevice or Instrument DevelopmentDevicesDiagnosisDiagnosticDiffusionEncapsulatedEscherichia coliFutureGenerationsGoalsGrowthGuidelinesHealthHealthcareHourHumanIndividualInfectionInstitutesLaboratoriesLifeMeasurementMethodsMicrofluidic MicrochipsMicrofluidicsMinimum Inhibitory Concentration measurementMolecularMolecular DiagnosisMolecular ProbesNucleic AcidsOpticsPeptide Nucleic AcidsPredispositionProcessReagentReportingResearchResearch Project GrantsResearch SubjectsRibosomal RNASamplingSepsisSourceSpecificitySystemSystems IntegrationTechnologyTestingTimeTranslationsUniversitiesUrinary tractUrinary tract infectionUrineValidationVertebral columnbasecombinatorialcommunity-acquired UTIdesigneffective therapyevidence baseimprovedindustry partnerinnovationinstrumentmolecular diagnosticsmortalitymulti-drug resistant pathogenpathogenproduct developmentprospectivesample collectionurinaryvalidation studies
项目摘要
DESCRIPTION (provided by applicant): The ability for clinicians to provide effective treatments to bacterial infections with targeted antibiotics hinges on molecular diagnostics capable of identifying the pathogen and determining its susceptibility to antibiotics in a timely manner. Urinary tract infection (UTI) is a particularly representative infection because it one of the most common bacterial infections that affect all ages but is currently only diagnosed in centralized laboratories via bacterial culture, which typically takes 2-3 days for definitive diagnosis. The significant time delay between sample collection and result reporting contributes to widespread empiric use of broad-spectrum antibiotics, which has contributed towards emergence of multidrug-resistant pathogen. Toward addressing this important unmet need, our overall goal is to develop and validate an integrated diagnostic platform for bacterial pathogen identification (ID) and antibiotic susceptibility testing (AST) in a "sample-to-answer" manner in under 3 hours. Such rapid molecular diagnostics will transform the clinicians' ability to provide evidence-based diagnosis of bacterial infections, expedite treatments based on objective data, promote effective utilization of antibiotics. Specifically, we propose to develop an innovative droplet microfluidic network capable of combinatorially generating millions of picoliter (pL)-sized
droplets of different compositions, i.e. mixtures of samples and probes or antibiotics at varying concentration levels, as the backbone technology. The microfluidic chip enables a streamlined approach for sample-reagent mixing, compartmentalization of mixtures into a massive number of droplets, and serial dilutions to simultaneously carry out pathogen ID and AST. In the pathogen ID module, single bacterial cells are encapsulated in droplets, achieving an effective concentration equivalent to 108-109 cfu/ml and thereby enabling rapid identification via the hybridization of molecular beacon probes in an amplification-free approach. In the AST module, individual bacterial cells are encapsulated and cultured in droplets that enhance local culture condition for bacterial growth and enable direct measurements of single bacterial doublings, thereby facilitating direct phenotypic AST from urine samples. We have assembled an academic-industry partnership consisted of Johns Hopkins University (droplet microfluidics and diagnostics), Stanford University (UTI, molecular probes, validation studies), University of Arizona (microfluidic AST), and GE Global Research (manufacturing and system integration). We propose the following aims: 1) to achieve single cell, amplification-free pathogen ID in a droplet-based microfluidic chip using a panel of peptide nucleic acid molecular beacons that target bacterial 16S rRNA; 2) to develop a droplet-based single cell AST capable of determining the minimum inhibitory concentration (MIC) for commonly used antibiotics for UTI; 3) to perform system integration and instrument development through partnership with our industry partner; and 4) to perform analytical and clinical validation with the integrated device. To facilitate technology translation, a Product Development Plan for future clinical deployment is proposed.
项目成果
期刊论文数量(0)
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用于病原体识别和 AST 的基于 Droplet 的单细胞平台
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