Massively Multiplexed dsDNA Invasion Arrays

项目总结 由侵袭性微生物血流感染(BSI)引起的败血症是一种重大的医疗负担， 仅在美国，每年就有超过170万起病例。以高死亡率(~20%)为特征，预后 对于败血症患者，在缺乏适当治疗的情况下，病情每小时恶化一次。及时准确的病原体 识别是使治疗与感染相匹配的关键。不幸的是，目前的诊断方法 BSI依赖血液培养，这是缓慢的(1-3天)，并且在存在先前的抗菌剂时不可靠 治疗。与此同时，医生必须依靠广谱治疗，这往往会漏掉感染， 导致并发症，并导致抗菌素耐药性。需要新的诊断方法，可以 直接从血液中快速检测和鉴定感染源，无需培养 为了解决这一未得到满足的需求，HelixBind开发了一个样本到答案流程，该流程可以识别 细菌和真菌在3小时内直接从血液中提取出来。利用专有检测方法，利用 人工合成，双链DNA入侵，核酸，该分析提供了物种水平的详细信息，以单CFU/ml 敏感度。基于dsDNA侵袭的检测(而不是单链DNA杂交)提供了单BP特异性和 能够可靠地区分密切相关的物种，并减少由于随机原因而产生的假阳性 污染物。然而，到目前为止，入侵从未以一种适合大规模 并行检测。在这项提议中，HelixBind将首次开发一种DNA入侵阵列，它可以 同时检测和识别数百种病原体。这个数组将被合并到一个样本到- 在台式仪器上操作的Answer流体卡带。由此产生的测试将为临床医生提供 全面覆盖与BSI相关的几乎所有病原体，并明确识别 在病人出现后几个小时内感染，使早期应用适当的抗菌剂成为可能， 改善护理，拯救无数生命。 HelixBind之前已经建立了基于液体的侵袭能力来从临床中识别BSI 样本，在本应用程序中，我们提供了基于固相阵列的入侵的初步数据，允许 大规模多路传输检测。在本提案中，我们将解决与以下相关的生物物理挑战 创建高度多路复用的dsDNA入侵阵列以及与集成该阵列相关的技术障碍 阵列进入样品到答案的流控装置。具体的目标，每个目标都有可量化的交付成果，用来解决 发展过程中的主要风险和渐进步骤。在这项第二期工程完成后，我们 将拥有一种功能齐全的检测方法和一种适合生产放大和临床测试的产品。我们 还将开发一种新的、高度多元化的分析格式，具有单一BP分辨率，可以 适用于广泛的应用，需要在密切相关的 目标。

PROJECT SUMMARY Septicemia, induced by an invasive microbial bloodstream infection (BSI), is a significant healthcare burden, accounting for over 1.7M cases annually just in the US. Characterized by high mortality rates (~20%), prognosis for septic patients deteriorates hourly in the absence of appropriate treatment. Timely and accurate pathogen identification is critical to match treatment to the infection. Unfortunately, current diagnostic approaches for BSIs rely on blood culture, which is slow (1-3 days) and unreliable in the presence of prior antimicrobial treatment. In the meantime, physicians must rely on broad-spectrum treatment, which often misses the infection, leads to complications, and drives antimicrobial resistance. New diagnostic approaches are needed which can quickly detect and identify the infectious agent directly from blood, without cultures To address this unmet need, HelixBind has developed a sample to answer process which can identify bacterial and fungal BSIs directly from blood in 3 hours. Utilizing a proprietary detection approach leveraging synthetic, duplex DNA invading, nucleic acids, the assay provides species level detail at single CFUs/ml sensitivity. dsDNA invasion-based detection (rather than ssDNA hybridization) affords single-bp specificity and the ability to reliably differentiate between closely related species and reduce false-positives due to random contaminations. To date, though, invasion has never been demonstrated in a format appropriate for massively parallel detection. In this proposal, HelixBind will develop, for the first time, a DNA invasion array which can detect and identify hundreds of pathogens simultaneously. This array will be incorporated into a sample-to- answer fluidic cassette operated on a benchtop instrument. The resulting test will provide clinicians with comprehensive coverage of essentially all pathogens associated with BSIs and unequivocal identification of an infection within hours of patient presentation, enabling early application of appropriate antimicrobials, improving care and saving countless lives. HelixBind has previously established the capability of fluid-based invasion to identify BSIs from clinical samples and in this application, we present preliminary data for solid-phase array-based invasion, allowing massively multiplexed detection. In this proposal we will address the biophysical challenges associated with creating a highly multiplexed dsDNA invasion array and the technical hurdles associated with integrating this array into a sample-to-answer fluidic device. Specific Aims, each with quantifiable deliverables, serve to address the key risks and progressive steps in the development process. Upon completion of this Phase II project, we will have a fully functional assay and a product appropriate for manufacturing scale up and clinical testing. We will also have developed a new, highly multiplexed assay format, with single-bp resolution, which can be adapted for a wide range of applications requiring sensitive and specific differentiation among closely related targets.