用于病原体发现和监测的自动化下一代测序生物信息学管道

M. Okomo-Adhiambo, E. Ramos, Reagan J. Kelly, Yatish Jain, R. Tatusov, A. Montmayeur, Gregory Doho, Rachel L. Marine, T. Ng, Adam C. Retchless, S. Oberste, P. Rota, X. Wang, Agha N. Khan
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引用次数: 0

摘要

新一代测序(NGS)已成为临床微生物学的重要工具,在传染病诊断、疫情调查和公共卫生监测方面有着广泛的应用。尽管NGS技术能够在相对较短的时间内以较低的成本进行全面的病原体检测,但所产生的大量基因组学数据为在临床相关的时间框架内有效组织、存档、分析和报告结果带来了重大挑战。自动化管道为标准化NGS数据处理和报告提供了第一步,从而消除了生物信息学分析中的常见瓶颈,并提供了快速周转。在这里,我们提出了用于病毒鉴定和全基因组组装的病毒NGS管道,以及用于脑膜炎病原体基因型表征的细菌性脑膜炎球菌基因组分析平台(BMGAP)。这些各自的管道已用于分析11,000多个临床样本和分离株。这些管道可部署在独立服务器和基于云的服务器上,使CDC内部用户以及外部合作伙伴(包括州公共卫生实验室和全球其他合作者)能够访问它们。这些自动化管道有可能有助于开发基于ngs的无偏见临床检测方法,用于需要快速周转时间的病原体检测,并有望在未来的传染病监测中发挥关键作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated Next Generation Sequencing Bioinformatics Pipelines for Pathogen Discovery and Surveillance
Next-generation sequencing (NGS) has become a vital tool in clinical microbiology, with numerous applications in infectious disease diagnostics, outbreak investigations, and public health surveillance. Although the NGS technology enables comprehensive pathogen detection in a relatively short time at a low cost, the enormous amount of genomics data generated creates a critical challenge of effectively organizing, archiving, analyzing, and reporting the results within a clinically relevant timeframe. Automated pipelines provide the first step in standardizing NGS data processing and reporting, thus eliminating the common bottlenecks in bioinformatics analyses, and providing rapid turnaround. Here, we present the Viral NGS Pipeline optimized for identification and whole genome assembly of viruses, and the Bacterial Meningococcus Genome Analysis Platform (BMGAP), designed for genotypic characterization of meningitis pathogens. These respective pipelines have been used to analyze more than 11,000 clinical samples and isolates. The pipelines are deployable on both standalone and cloud-based servers, enabling their accessibility to internal CDC users, as well as external partners, including state public health laboratories and other collaborators worldwide. These automated pipelines have the potential to contribute to the development of unbiased NGS-based clinical assays for pathogen detection that demand rapid turnaround times, and are expected to play a key role in infectious disease surveillance in the future.
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