SBIR Phase II: Rapid Pathogen Diagnostics and Biosurveillance using Multiplexed High-throughput Sequencing

这个小企业创新研究（SBIR）二期项目的更广泛影响/商业潜力是提高我们对抗传染病的能力，这些传染病对农业产量产生负面影响，降低全球粮食生产和分配系统的效率。通过利用高通量测序和生物信息学的力量，这一创新将加强科学和技术的理解，提供一种病原体鉴定和监测工具，证明其对已知和未知感染因子的有效性。该平台快速、灵敏、成本效益高，可用于任何动物样本检测几乎所有可能的微生物，甚至是以前从未被表征过的微生物。可以快速筛选数百个样品，而无需依赖已知的微生物遗传/基因组数据。预计2012 - 2017年全球分子诊断市场复合年增长率（CAGR）将超过14%，其中传染病检测是领先的应用，占26%的份额，因此该项目的商业机会是巨大的。拟议的项目是在诊断平台（SBIR一期）验证的基础上进行的，并深入研究改进病毒检测和基因数据生成。此外，本提案旨在开发一个基础信息学基础设施，连同样品制备的改进将有助于对多个样品进行可扩展的高通量分析。目前的诊断方法依赖于已知的目标微生物遗传学，并且以已知目标序列的存在/缺失的形式提供有限的信息。SBIR一期有助于降低基于DNA测序和贝叶斯统计的高通量无偏病原体检测平台相关的技术风险。为了标准化和验证我们的宏基因组病原体鉴定平台，本项目建议：1)提高病毒检测能力和准确性，2)开发新的功能，3)将第一阶段和第二阶段的进展纳入一个集成的内部网络可访问界面。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve our ability to fight infectious diseases that negatively impact agricultural yields and reduce the efficiency of global food production and distribution systems. This innovation will enhance scientific and technological understanding by leveraging the power of high-throughput sequencing and bioinformatics to provide a pathogen identification and surveillance tool with demonstrated efficacy against known and unknown infectious agents. This platform is fast, sensitive, and cost-effective, and can be used for any animal sample to detect virtually all possible microbes even microbes that have never before been characterized. Hundreds of samples can be rapidly screened without relying upon known genetic/genomic data of microbes. The global molecular diagnostics market is expected to grow at a compound annual growth rate (CAGR) of over 14% from 2012 to 2017, with infectious disease testing being the leading application at 26% share, therefore the commercial opportunity of this project is vast.The proposed project follows up on the validation of the diagnostic platform (SBIR Phase I) and delves deeper into improving virus detection and genetic data generation. In addition, this proposal seeks to develop a basal informatics infrastructure that together with sample preparation improvements will be conducive of scalable, high-throughput analysis of several samples. Current diagnostic methods rely on what is already known about target microbe genetics, and provide limited information in the form of presence/absence of a known target sequence. The SBIR Phase I was instrumental to lowering the technical risks associated with a high-throughput unbiased pathogen detection platform based on DNA sequencing and Bayesian statistics. In the pursue of standardizing and validating our metagenomics pathogen identification platform, this project proposes to: 1) improve viral detection capabilities and accuracy, 2) develop new functionalities, and 3) incorporate Phase I and Phase II advances into an integrated in-house web-accessible interface.