Detection of Bioterrorism Agents with PM Technology

描述(由申请人提供)： 从事常规微生物学工作的实验室现在必须拥有能够识别和识别危险病原体的工具，这些病原体可能会出现在他们的正常工作流程中。他们需要这种能力来识别初期的生物恐怖主义袭击，通过快速诊断来拯救遭受袭击的人的生命，并防止实验室工作人员自己暴露在危险和不受控制的环境中。我们的建议为微生物学家目前面临的真正问题提供了新颖而实用的解决方案。Biolog将开发一种非常先进的细菌识别系统，任何临床微生物学实验室都可以使用该系统来识别800多种不同的细菌，包括可能用于攻击人类或美国农业的生物恐怖主义微生物。这一开发是由Biolog新开发的专有平台技术--表型微阵列(PM)实现的。PMS构成了一种新的基因组规模技术，它提供了关于活细胞特性的前所未有的详细信息，使科学家能够在名为OmniLog的专有记录仪器中同时测试2000种微生物细胞的特性。核心技术是一个图像分析系统，它可以检测在不同条件下生长的细胞呼吸的变化。因为测量了大量的参数，所以为每个细菌生成了信息丰富的比色图案，构成了该细菌的指纹。通过在自动化的高通量程序中测试广泛和具有代表性的细菌物种集合，我们将快速建立关于每个细菌物种共同的表型属性以及区分每个物种与其最近的近亲的属性的详细数据库。该数据库将用于生成能够在一次测试中识别800多种革兰氏阴性和革兰氏阳性细菌的测试板。这将大大提高细菌鉴定的简单性、速度和准确性，远远超过目前医学实验室可用的技术。我们还将开发新的、高选择性和特定的增菌和培养介质，使调查人员能够使用标准、廉价、低技术的琼脂平板监测环境中的生物恐怖主义微生物。

DESCRIPTION (provided by applicant): Laboratories doing routine microbiology now must have tools that allow them to recognize and identify dangerous pathogens that could appear as part of their normal workflow. They need this capability to identify incipient bioterrorism attacks, to save lives of stricken people by rapid diagnosis, and to prevent the laboratory workers themselves from dangerous and uncontrolled exposures. Our proposal provides novel yet practical solutions to the real problems faced by microbiologists right now. Biolog will develop a highly advanced, bacterial identification system that can be used by any clinical microbiology laboratory to identify over 800 different bacterial species including bioterrorism microorganisms that could be used in an attack against humans or U.S. agriculture. This development is enabled by Biolog's newly developed, proprietary platform technology, Phenotype MicroArrays (PMs). PMs constitute a new genomic scale technology that gives unprecedented detailed information about the properties of live cells allowing scientists to test 2000 properties of a microbial cell simultaneously in a proprietary recording instrument called the OmniLog. The core technology is an image analysis system that detects changes in respiration of cells grown under different conditions. Because a large number of parameters are measured, an information-rich colorimetric pattern is generated for each bacterium, constituting a fingerprint of that bacterium. By testing a broad and representative collection of bacterial species in an automated high-throughput program, we will rapidly build a detailed database on phenotypic properties common to each bacterial species as well as properties that distinguish each species from its closest relatives. The database will be used to generate test panels capable of identifying over 800 species of both gram-negative and gram-positive bacteria in a single test. This will improve the simplicity, speed, and accuracy of bacterial identification far beyond the technology available to medical labs at this time. We will also develop new, highly selective and specific enrichment and culture media that will allow investigators to monitor for bioterrorism microorganisms in the environment using standard, inexpensive, low tech agar plates.