Cloud-enabled genomics resource for automated pathogen diagnostics in the field

描述(由申请人提供)：微生物病原体检测和特征的诊断改进将直接影响临床和公共卫生环境，特别是如果适用于现场的话。基于基因组测序的方法的优势包括提高了对分离株分型的分辨率，在某些情况下，可低至单核苷酸水平，全面的表型预测，例如毒力和/或抗生素耐药性，以及提供基因组数据库作为社区和公共卫生资源。然而，为了采用以基因组学为基础的诊断系统，需要新的标准化方案，理想情况下，这些方案不需要为典型的诊断实验室能力进行广泛的培训或扩大，并且可以在外地以最低限度的当地基础设施实施。为了解决这些问题，我们建议在项目的R21“概念验证”阶段，我们将论证建立自动诊断管道的可行性，以支持微生物分离株分型、毒力和抗菌素耐药性分析以及系统发生分类的基因组序列分析。我们预计，纳入的分析将影响个别患者的治疗过程，并将与公共卫生和感染控制有关。简要地说，我们将开发一个开放的数据库结构，用拟议分析的参考序列填充它，并将其记录下来，作为未来扩展的社区资源(目标1)。该数据库结构将与自动生物信息学分析管道相结合，以对照参考数据库从当前平台搜索原始序列数据，并创建一份可操作的诊断报告(目标2)。此分析管道将利用现有的 生物信息学软件基础设施(Clovr)，它使用易于使用的图形用户界面从本地桌面提供可移植性、再现性、平台独立性和在线云计算服务的利用。在该项目的R33阶段，将通过在模拟现场环境中部署带有诊断系统的新型测序技术来完成“向扩展开发的过渡”。在此阶段，我们将提供与传统方法的比较分析，以支持开发的诊断系统的实用性和准确性。我们将选择、实施和测试测序平台，该平台在成本、空间、工作量和数据生成方面是最实惠和适用于现场环境的，以及设置和操作培训(目标3)。测序平台和自动分析管道将在模拟和真实样本上进行测试，以验证诊断方案，改进报告结构，并确定置信度参数(目标4)。总体而言，这项研究计划的完成将导致开发和实施基因组测序和分析系统，该系统只需要电源、互联网连接和具有最低实验室技能的个人，即可将基因组测序作为一种诊断工具集成在任何医疗保健环境中，几乎具有无限的应用。 公共卫生相关性：本申请中提出的工作目标将是开发、实施和测试可现场部署的诊断资源，该资源将利用自动化序列分析管道与全基因组测序相结合，对人类细菌病原体进行鉴定、分型和表征。预计高通量测序所需的成本、时间和基础设施将减少，再加上使用云计算进行便携式分析，使这项变革性技术能够用作临床和公共卫生诊断工具，在该领域具有无限的未来应用。总体而言，拟议研究的完成将导致尽早采用一种创新的方法，并创建一种可用于世界各地临床环境的社区资源。

DESCRIPTION (provided by applicant): Diagnostic improvements for the detection and characterization of microbial pathogens will directly impact clinical and public health settings, especially if field-applicable. Advantages of genome sequencing-based approaches include increased resolution for isolate typing, in some cases, down to single nucleotide level, comprehensive phenotype prediction, e.g. for virulence and/or antibiotic resistance, and provisioning of genomic databases as community and public health resources. However, in order to adopt a genomics-based diagnostic system, new standardized protocols are needed which ideally would not require extensive training or scale up for typical diagnostic laboratory capacities, and could be implemented with minimal local infrastructure in the field. To address these issues we propose that in the R21, "proof-of-concept" phase of the project, we will demonstrate the feasibility of building an automated diagnostic pipeline to support genome sequence analysis for microbial isolate typing, virulence and antimicrobial resistance profiling and phylogenetic classification. We anticipate that the included analyses will impact the course of individual patient treatment and will be relevant to public health and infection control. Briefl, we will develop an open database structure, populate it with reference sequences for the proposed analysis, and document it to serve as a community resource for future expansions (Aim 1). This database structure will be integrated with an automated bioinformatics analysis pipeline to search raw sequence data from current platforms against the reference database and create an actionable diagnostic report (Aim 2). This analysis pipeline will utilize an existing bioinformatics software infrastructure (CloVR), which provides portability, reproducibility, platform- independence and utilization of online cloud computing services from the local desktop using an easy-to-use graphical user interface. In the R33 phase of the project, the "transition to expanded development" will be completed by deploying a novel sequencing technology with the diagnostic system in a simulated field setting. During this phase we will provide comparative analysis with traditional methods to support the utility and accuracy of the developed diagnostic system. We will select, implement and test the sequencing platform, which is most affordable and applicable to the field setting with respect to cost, space, effort, and data generation, as wel as training for setup and operation (Aim 3). Sequencing platform and automated analysis pipeline will be tested on mock and real-life samples to validate diagnostic protocols, refine report structures, and determine confidence parameters (Aim 4). Overall, completion of this research plan will result in the development and implementation of a genome sequencing and analysis system that will require little more than a power supply, internet connection and an individual with minimal laboratory skills to integrate genome sequencing as a diagnostic tool with virtually limitless applications in any healthcare setting. PUBLIC HEALTH RELEVANCE: The goal of the work proposed in this application will be to develop, implement and test a field-deployable diagnostic resource that will utilize automated sequence analysis pipelines in combination with whole-genome sequencing for the identification, typing and characterization of human bacterial pathogens. The predicted decrease in cost, time and infrastructure required for high-throughput sequencing coupled with portable analysis using cloud computing enables the use of this transformative technology as a clinical and public health diagnostic tool with limitless future applications in the field. Overall the completion of the proposed studies will result in early adoption of an innovative methodology and creation of a community resource that could be adapted for use in clinical settings around the world.