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Gigapixel digital PCR in Giant Unilamellar Vesicles

Gigapixel digital PCR in Giant Unilamellar Vesicles
巨型单层囊泡中的十亿像素数字 PCR
批准号:
10197925
负责人:
Adam R. Abate
金额:
$62.1万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-09-30 至 2023-03-31

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中文摘要
翻译
摘要 传染病仍然是全球发病率的主要原因。成功的医疗干预 需要准确的诊断,这可能是具有挑战性的,因为感染之间有共同的症状。此外, 耐药性的增加使得识别和表征致病微生物并选择 及时有效的治疗。在这一竞争更新中,我们将扩展在 我们之前的R01能够实现快速、灵敏和信息丰富的传染病诊断。我们的新产品 我们称之为Gigapixel NGS的技术将我们的Gigapixel Digital PCR(DPCR)技术从 之前的R01通过整合强大的下一代测序功能而实现。的核心创新之处 Giapixel dPCR是在双乳泡中进行dPCR分析,而不是传统的水在... 商用dPCR仪器(Bio-Rad、RainDance)使用的油滴。小泡不再需要 专门的液滴分析仪,并允许使用普通的流式细胞仪进行定量。流式细胞仪 在研究和临床实验室中无处不在,具有卓越的分析能力(即速度、灵敏度和 多路传输)与专门的液滴分析仪进行比较。这使得Gigapixel dPCR可以增加 可分析的隔室数量超过1亿个,灵敏度提高100倍 量化的结果。此外,流式细胞仪可以分选出聚合酶链式反应检测到DNA靶标的囊泡。 现有液滴分析仪没有的功能。 在这一竞争更新中,我们将利用Gigapixel NGS的能力来检测、分离和排序 直接从患者样本中提取感染性病原体基因组。建议的工作流程将提高效率 以及病原体测序的敏感性,以低得多的成本产生更高质量的草稿基因组。在协作中 与加州大学旧金山分校的传染病内科医生Charles Chiu博士合作,专门从事临床样本测序 病原体检测,我们将开发生物信息学工具来询问恢复的基因组,以便相关 生物标记物序列,如毒力因子和耐药基因。通过进一步与 流畅的生物科学,我们将使Gigapixel NGS适应他们的商业平台,允许协议 由研究和临床实验室作为商业可用试剂盒实施。 我们建议的具体目标是: 1)将Gigapixel PCR扩展到临床相关平台,以Gigapixel NGS的形式出现。 2)展示细菌感染的综合量化和准确的基因组测序 脑膜炎。 3)将该技术应用于黄病毒感染的电子鉴定和诊断。 血浆和脑脊液等样本。
英文摘要
ABSTRACT Infectious disease remains a major cause of morbidity across the globe. Successful medical intervention requires accurate diagnosis, which can be challenging due to symptoms shared among infections. Moreover, increasing drug resistance makes it important to identify and characterize pathogenic microbes and choose effective treatments in a timely manner. In this competing renewal, we will extend technology developed under our previous R01 to enable rapid, sensitive, and information-rich infectious disease diagnosis. Our new technology, which we dub Gigapixel NGS, extends our Gigapixel digital PCR (dPCR) technology from the previous R01 by incorporating a powerful next-generation sequencing capability. The core innovation of Gigapixel dPCR was to perform dPCR assays in double emulsion vesicles, rather than conventional water-in- oil droplets utilized by commercial dPCR instruments (Bio-Rad, RainDance). Vesicles obviate the need for specialized droplet analyzers and allow common flow cytometers to be used for quantification. Flow cytometers are ubiquitous in research and clinical labs, with superior analysis capabilities (i.e. speed, sensitivity, and multiplexing) in comparison to specialized droplet analyzers. This allows Gigapixel dPCR to increase the number of compartments that can be analyzed to over 100 million, providing a 100-fold increase in sensitivity of quantification. Moreover, flow cytometers can sort out vesicles in which PCR has detected a DNA target, a functionality not found in existing droplet analyzers. In this competing renewal, we will leverage the capability of Gigapixel NGS to detect, isolate and sequence infectious pathogen genomes directly from patient samples. The proposed workflow will increase the efficiency and sensitivity of pathogen sequencing, yielding higher-quality draft genomes at far lower cost. In collaboration with Dr. Charles Chiu, an infectious disease physician at UCSF specializing in clinical sample sequencing for pathogen detection, we will develop bioinformatic tools to interrogate the recovered genomes for relevant biomarker sequences, such as virulence factors and drug resistance genes. Through further collaboration with Fluent Biosciences, we will adapt Gigapixel NGS to their commercial platform, allowing the protocol to be implemented by research and clinical labs as a commercially available kit. The Specific Aims of our proposal are to: 1) Extend Gigapixel PCR into a clinically relevant platform, in the form of Gigapixel NGS. 2) Demonstrate integrated quantification and accurate genome sequencing of bacterial infections in meningitis. 3) Apply the technology for in silico identification and diagnosis of flavivirus infections from (liquid) biopsy samples such as plasma and cerebrospinal fluid.
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Next Generation Infectious Disease Diagnostics: Microfluidic-Free Gigapixel PCR with Self-Assembled Partitioning
Sorting and Sequencing Latent Reservoirs in HIV+ Opioid Users
  • 批准号:
    10789790
  • 项目类别:
  • 资助金额:
    $163.09万
  • 财政年份:
    2023
  • 负责人:
    Adam R. Abate
  • 依托单位:
A non-invasive metabolic sensor for improving success in IVF
Identification of regulatory mechanisms operating in rare pathogenic astrocyte subsets in multiple sclerosis with a novel genomic technology
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