Bilateral NSF/BIO-BBSRC: Collaborative Research: ABI Development: A Metagenomic Exchange - enriching metagenomics analysis by synergistic harmonisation of MG-RAST and the EBI Metag

微生物几乎存在于所有的环境中。当一个群落内存在不平衡时，可能会导致严重的影响，例如人类肠道疾病或植物无法在土壤中有效生长。了解社区内部的组成和相互作用使我们能够潜在地操纵它们。宏基因组学是对这些不同微生物群落的研究，它是通过从环境样本（例如水、土壤、动物粪便）中的生物体中分离DNA，对DNA进行测序，然后进行计算分析，以解码存在哪些生物体及其可能执行的功能来实现的。这种计算是复杂的：1)有大量的数据；2)序列数据是来自不同生物的片段的混杂；3)解码DNA是困难的——通常一个样本中90%的生物体都没有很好地表征。本提案汇集了宏基因组学数据存档和分析领域的三个主要资源。这项提议和相关资源的产出的最直接受益者将是全世界从事宏基因组学研究的科学家。这个多样化，广泛和不断扩大的社区包括（但不限于）对理解微生物群落结构和相互作用感兴趣的微生物学家，旨在发现具有功能应用的新蛋白质的生化学家，以及寻求调查和调节与健康或疾病状态相关的微生物群落的临床医生。欧洲核苷酸档案（ENA）是DNA序列数据的存储库。重要的是，ENA还捕获宏基因组上下文数据，例如采样的地点和时间，DNA是如何提取和测序的。EBI宏基因组门户网站（EMG，英国）和MG-RAST （MGR，美国）是两个宏基因组序列分析平台。该项目的目的是启动EMG和MGR平台之间的长期合作，以建立和运营一个全面的数据交换系统，即宏基因组学交换（ME）。该资源将确保宏基因组序列读取、衍生数据和相关元数据被永久保存，并可供未来最广泛的使用。至关重要的是，它将确保这些科学家能够发现和挖掘预处理数据集，并在不同的平台上比较他们的分析。将不再需要耗时的详尽搜索ENA， MG-RAST （MGR）和EBI宏基因组学（EMG）来发现数据，也不需要同时提交MGR和EMG-交叉提交将自动发生。此外，由于做了MG-RAST和EMG？S管道可互操作，科学家将能够利用一组通用参数进行增强分析，并允许混合和匹配管道组件，以适应正在处理的数据，改进和丰富他们的分析结果。这也将减少由非生物人为因素引起的差异，使结果更加清晰。通过结果接口的统一，标准用户和高级用户将受益，MGR和EMG结果可以通过彼此的网站访问，这有助于前一组用户，并能够为后一组用户提供跨多个数据集的挖掘能力。

Micro-organisms are found in virtually all environments. When there is an imbalance within a community, this can lead to severe effects, such as disease in the human gut or the inability for plants to grow efficiently in soil. An understanding of the composition and interplay within the communities allows us to potentially manipulate them. Metagenomics is the study of these different micro-organism communities, which is achieved by isolating the DNA from the organisms within an environmental sample (e.g. water, soil, animal stool), sequencing the DNA, followed by the computational analysis to decode which organisms are present and the functions they might be performing. This computation is complicated: 1) there is a huge amount of data; 2) The sequence data is a jumbled mix of fragments from different organisms; 3) Decoding the DNA is hard - typically 90% of organisms within a sample are not well characterized. This proposal brings together three major resources within the field of metagenomics data archiving and analysis. The most immediate beneficiaries of the outputs from this proposal and associated resources will be the scientists worldwide who are involved in metagenomics research. This diverse, extensive and expanding community includes (but is not limited to) microbiologists interested in understanding microbial community structure and interactions, biochemists aiming to discover new proteins with functional applications, and clinicians seeking to investigate and modulate the microbial communities associated with healthy or diseased states. The European Nucleotide Archive (ENA) is a repository of DNA sequence data. Importantly, ENA also captures metagenomic contextual data, such as where and when the sample was taken, how the DNA was extracted and sequenced. The EBI metagenomics portal (EMG,UK) and MG-RAST (MGR,US) are 2 metagenomics sequence analysis platforms. The aim of this project is to initiate a long-term collaboration between the EMG and MGR platforms to build and operate a comprehensive data exchange system, the Metagenomics Exchange (ME). This resource will ensure that metagenomic sequence reads, derived data and associated metadata are permanently preserved and made available for the broadest future use. Crucially, it will ensure that these scientists can discover and mine pre-processed datasets and compare their analysis across varying platforms. There will no longer be the time consuming need for exhaustive searching of ENA, MG-RAST (MGR) and EBI metagenomics (EMG) to discover data, nor will there be the need to submit to both MGR and EMG-the cross submission will simply happen automatically. Furthermore, as a result of the work to make MG-RAST and EMG?s pipelines interoperable, scientists will have access to enhanced analyses that utilize a common set of parameters and allow mixing and matching of pipeline components to suit the data that is being processed, improving and enriching their analysis results. This will also reduce differences that are caused by non-biological artifacts, enabling greater clarity of results. Through the unification of result interfaces, standard users and power users will benefit, with MGR and EMG results accessible via each other's websites, helping the former set of user, and the ability to mine across multiple datasets offered for the latter user set.