Implementing Metabolomics Analyses into Galaxy Workflows: Towards Genome-Metabolome Large-Scale Data Fusion

基因组和后基因组研究正在改变我们对生物-环境相互作用的机械论理解。虽然这一说法肯定是正确的，但它掩盖了过去十年中必须克服的许多重大挑战。今天，基因组学方法被来自NERC科学广度的研究人员广泛使用，利用成熟的(而且越来越便宜的)技术和分析管道，并提供影响较大的出版物。代谢组学还不能说同样的话，无论是在分析上还是在计算上，代谢组学都是一种相当不成熟的方法。代谢组学中的分析挑战限制了它对分析化学专家的使用，而计算挑战限制了可以从这些丰富的数据集中挖掘的知识。在这里，我们借鉴基因组学研究人员的智慧和经验，解决后一点。环境基因组学成功的原因之一是，生物学家在没有深入了解生物统计学和编程的情况下，能够使用标准化的工作流程构建和执行下一代测序(NGS)数据分析。银河(http://galaxyproject.org/))--标题为“面向所有人的在线生物信息学分析”--已成为新一代生物信息学数据分析的领先开源工作流程平台，拥有许多标准处理工具，可从其基于网络的用户界面访问。该工作流软件还成功地应用于蛋白质组学和化学信息学。我们在这一应用上的项目合作伙伴中国的北京基因组研究所的研究人员在Galaxy方面拥有丰富的专业知识，因为这个基于网络的数据分析和工作流系统构成了其数据分析平台的基础。他们还与Galaxy开发团队有着密切的联系。我们建议将Davidson博士从Viant教授的环境代谢组学实验室和伯明翰大学的NBAF-B跳槽到华大基因香港的一个计算实验室。在这里，他将获得Galaxy工作流程方面的专业知识，并将我们现有的代谢组学管道实施到Galaxy。这是朝着使代谢组学分析管道更有效(通过集成不断增长的代谢组学分析方法工具箱中的强大算法)、更标准化(能够更好地交叉比较不同研究的结果)以及更容易为生物学家所访问的方向迈出的极其重要的一步。我们的目标是使数据和分析工具都可以从一个软件平台访问，该软件平台提供了一个单一的、用户友好的界面，用于开发可由环境社区共享和重复使用的计算管道。最终，这将促进基因组和代谢数据集的整合，使我们能够对支撑我们环境中生物应激反应的机制进行新的研究。在这里，我们将重点分析水蚤的多组学数据集，以进一步研究环境毒物的分子响应。我们的国际研究团队提供独特的专业知识组合，涵盖环境代谢组学(Viant，Davidson)、环境基因组学(科尔本，周)和计算工作流(Li)，他们都被处理、分析和解释大规模组学数据集的共同兴趣和记录紧密地联系在一起。虽然科尔本、戴维森和维昂特在伯明翰大学生物科学学院工作，李和周住在中国的华大基因，但所有研究人员都是伯明翰新成立的华大基因-伯明翰环境与健康中心的一部分，该中心将为最先进的测序、代谢和生物信息学技术的整合提供世界级的学术、研究和培训环境。

"Genomic and post-genomic studies are transforming our mechanistic understanding of organism-environment interactions." While this statement is certainly true, it masks many of the major challenges that have had to be overcome during the last decade. Today, genomics approaches are widely used by researchers from across the breadth of NERC science, utilising established (and ever cheaper) technologies and analysis pipelines, and delivering high impact publications. The same cannot yet be said for metabolomics, which is a considerably less mature approach, both analytically and computationally. The analytical challenges in metabolomics have restricted its use to experts of analytical chemistry, while the computational challenges have restricted the knowledge that can be mined from these rich datasets. Here we address the latter point, drawing from the wisdom and experience of genomics researchers. One of the reasons for the success of environmental genomics is that biologists, without an in-depth knowledge of biostatistics and programming, have been able to construct and execute Next Gen Sequencing (NGS) data analyses using standardised workflows. Galaxy (http://galaxyproject.org/) - headlined as "Online bioinformatics analysis for everyone" - has emerged as the leading open-source workflow platform for NGS data analysis, with many standard processing tools accessible from its Web-based user interface. This workflow software is also being applied successfully to proteomics and chemo-informatics. Researchers at BGI (Beijing Genomics Institute) in China, our Project Partner on this application, have considerable expertise in Galaxy, since this web-based data analysis and workflow system forms the basis of its data analysis platform. They also have close links with the Galaxy development team. We propose to 'hop' Dr Davidson from Professor Viant's environmental metabolomics laboratory and NBAF-B at the University of Birmingham into a computational laboratory at BGI-Hong Kong. Here he will gain specialist expertise in Galaxy workflows and implement our existing metabolomics pipelines into Galaxy. This is an extremely important step towards making metabolomics analysis pipelines more effective (by integrating powerful algorithms from the ever growing toolbox of metabolomics analysis methods), more standardised (enabling greater cross comparison of results from different studies), and considerably more accessible to biologists. Our aim is for both data and analysis tools to be accessible from a software platform that provides a single, user-friendly interface for developing computational pipelines in a form that can be shared and reused by the environmental community. Ultimately this will facilitate the integration of genomic and metabolomic datasets, enabling novel studies of the mechanisms underpinning stress responses of organisms within our environment. Here we will focus on the analysis of multi-omics datasets of Daphnia spp., to further investigate the molecular responses to environmental toxicants. Our international team of investigators provides a unique combination of expertise spanning environmental metabolomics (Viant, Davidson), environmental genomics (Colbourne, Zhou) and computational workflows (Li), and are all strongly tied by a common interest and track record in the handling, analyses and interpretation of large-scale 'omics datasets. While Colbourne, Davidson and Viant are based in the School of Biosciences, University of Birmingham, and Li and Zhou reside at BGI in China, all investigators are part of the newly launched Joint BGI-Birmingham Environment and Health Centre at Birmingham that will provide a world-class academic, research and training environment for the integration of state-of-the-art sequencing, metabolomic and bioinformatics technologies.