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

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.
 描述(申请人提供):临床医生是否有能力为细菌感染提供有效的靶向抗生素治疗,取决于能够识别病原体并及时确定其对抗生素敏感性的分子诊断。尿路感染(UTI)是一种特别具有代表性的感染,因为它是影响所有年龄段的最常见的细菌感染之一,但目前只能在集中式实验室通过细菌培养进行诊断,通常需要2-3天才能确诊。样本收集和结果报告之间的显著时间延迟导致广谱抗生素的广泛经验性使用,这导致了多重耐药病原体的出现。为了解决这一重要的未得到满足的需求,我们的总体目标是开发和验证一个集成的诊断平台,用于细菌病原体鉴定(ID)和抗生素敏感性测试(AST),在3小时内以“样本到答案”的方式进行。这种快速的分子诊断将改变临床医生提供细菌感染循证诊断的能力,加快基于客观数据的治疗,促进抗生素的有效利用。具体地说,我们建议开发一种创新的液滴微流控网络,能够组合产生数百万皮升(Pl)大小的液滴 不同成分的液滴,即样品和探针的混合物或不同浓度水平的抗生素,作为骨干技术。微流控芯片实现了一种简化的方法,用于样品-试剂混合,将混合物分隔成大量液滴,并进行连续稀释,以同时进行病原体ID和AST。在病原体ID模块中,单个细菌细胞被包裹在液滴中,达到相当于108-109 cfu/ml的有效浓度,从而能够通过分子信标探针以无扩增的方法进行快速鉴定。在AST模块中,单个细菌细胞被包裹并在液滴中培养,这些液滴增强了细菌生长的本地培养条件,并能够直接测量单个细菌的加倍,从而便于从尿样中直接检测表型AST。我们与约翰霍普金斯大学(液滴微流体和诊断)、斯坦福大学(UTI、分子探针、验证研究)、亚利桑那大学(微流体AST)和GE Global Research(制造和系统集成)组成了学术-行业合作伙伴关系。我们提出了以下目标:1)使用一组针对细菌16S rRNA的肽核酸分子信标,在基于液滴的微流控芯片中实现单细胞、无扩增病原体ID;2)开发基于液滴的单细胞AST,能够确定常用抗生素对UTI的最低抑菌浓度(MIC);3)通过与我们的行业合作伙伴合作进行系统集成和仪器开发;以及4)使用集成设备进行分析和临床验证。为了促进技术转换,提出了未来临床部署的产品开发计划。

项目成果

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JOSEPH C LIAO其他文献

JOSEPH C LIAO的其他文献

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{{ truncateString('JOSEPH C LIAO', 18)}}的其他基金

Intraoperative integration of artificial intelligence during cystoscopic surgery
膀胱镜手术中人工智能的术中整合
  • 批准号:
    10365872
  • 财政年份:
    2022
  • 资助金额:
    $ 118.49万
  • 项目类别:
Intraoperative integration of artificial intelligence during cystoscopic surgery
膀胱镜手术中人工智能的术中整合
  • 批准号:
    10544344
  • 财政年份:
    2022
  • 资助金额:
    $ 118.49万
  • 项目类别:
BCCMA: Basic and Translational Mechanisms of Cancer Initiation of the Urothelium in Veterans Exposed to Carcinogens: Leveraging Artificial Neural Networks to Enhance Detection of Carcinoma in situ
BCCMA:暴露于致癌物的退伍军人尿路上皮癌症发生的基本和转化机制:利用人工神经网络增强原位癌的检测
  • 批准号:
    10260145
  • 财政年份:
    2021
  • 资助金额:
    $ 118.49万
  • 项目类别:
MagSToNE - a magnetic system for kidney stone fragment elimination
MagSToNE - 用于消除肾结石碎片的磁性系统
  • 批准号:
    10354258
  • 财政年份:
    2021
  • 资助金额:
    $ 118.49万
  • 项目类别:
MagSToNE - a magnetic system for kidney stone fragment elimination
MagSToNE - 用于消除肾结石碎片的磁性系统
  • 批准号:
    10491338
  • 财政年份:
    2021
  • 资助金额:
    $ 118.49万
  • 项目类别:
BCCMA: Basic and Translational Mechanisms of Cancer Initiation of the Urothelium in Veterans Exposed to Carcinogens: Leveraging Artificial Neural Networks to Enhance Detection of Carcinoma in situ
BCCMA:暴露于致癌物的退伍军人尿路上皮癌症发生的基本和转化机制:利用人工神经网络增强原位癌的检测
  • 批准号:
    10513315
  • 财政年份:
    2021
  • 资助金额:
    $ 118.49万
  • 项目类别:
Personalized assessment of bladder cancer treatment response using urinary molecular biomarkers
使用尿液分子生物标志物对膀胱癌治疗反应进行个性化评估
  • 批准号:
    10514572
  • 财政年份:
    2020
  • 资助金额:
    $ 118.49万
  • 项目类别:
Personalized assessment of bladder cancer treatment response using urinary molecular biomarkers
使用尿液分子生物标志物对膀胱癌治疗反应进行个性化评估
  • 批准号:
    10293596
  • 财政年份:
    2020
  • 资助金额:
    $ 118.49万
  • 项目类别:
Personalized assessment of bladder cancer treatment response using urinary molecular biomarkers
使用尿液分子生物标志物对膀胱癌治疗反应进行个性化评估
  • 批准号:
    10015540
  • 财政年份:
    2020
  • 资助金额:
    $ 118.49万
  • 项目类别:
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
  • 批准号:
    8875827
  • 财政年份:
    2015
  • 资助金额:
    $ 118.49万
  • 项目类别:

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