Unifying metabolome and proteome informatics

统一代谢组和蛋白质组信息学

• 批准号: BB/L018616/2
• 负责人: Andrew Dowsey
• 金额: $ 10.1万
• 依托单位: University of Liverpool
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2015
• 资助国家: 英国
• 起止时间: 2015 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FL018616%2F2
• 关键词: Unifying; metabolome; proteome; informatics

Biologists are increasing wishing to understand the complex interactions between the building blocks of genes, metabolites and proteins that control the function of every living organism. The field of systems biology has emerged to overcome the deficiencies of the traditional reductionist approach, which has identified the building blocks themselves and many of the individual interactions but has not been able to deduce how systems of these blocks act and react in unison. The application of systems biology is widespread, as it promises to revolutionise our understanding of healthy processes in plants, animals and humans, as well as how they break down under disease and how this breakdown can be averted.Often the systems biology approach starts with a 'snapshot' of a particular biological sample. Mass spectrometry is a pervasive technique for gaining a snapshot of a sample, and it does this by ionising the sample and then measuring each constituent compound's mass and quantity based on the resulting charge. This is often not enough to separate out the sample fully and therefore a preceding phase of liquid or gas chromatography is used to provide an initial separation. Classes of protein and metabolite require different sample preparation, ionisation and chromatography approaches. These all add different kinds of biases and variation which make it extremely challenging to infer links between compounds, especially if the compounds are from different classes. To make matters worse, many snapshots are needed to capture different 'angles' of the biological process under investigation, and the instrumental conditions themselves are not entirely reproducible over time. All this has led systems biology to become a progressively computational discipline.The academic disciplines for studying global patterns of proteins ('proteomics') and metabolites ('metabolites') have broadly originated from different fields, and therefore there is little synergy between the two. This is also the case for the computational aspect, despite the fact both are applied to mass spectrometry data. Cross-fertilisation of methodology and ideas therefore has the prospect of seeding novel, effective new approaches of analysis. The project team is involved in the development of the prominent mzMatch and ProteoSuite informatics packages for metabolomics and proteomics respectively. They are the most actively developed academic metabolome and proteome informatics packages in the UK. Therefore there is a timely opportunity to lead a concerted effort bringing together the informatics community, methodology and software for metabolomics and proteomics to: (a) Establish a new, powerful unified informatics workflow 'borrowing strength' in methodology advancements across both fields, greater than the sum of its parts and with coherent statistical properties enabling optimal integration into systems biology research; (b) Underpin cross-disciplinary collaborations, new understanding and mobility between metabolomics and proteomics fields; and (c) Support development of joint data exchange and reporting standards for optimal integration of metabolomics and proteomics data. To achieve this, we will first integrate mzMatch into ProteoSuite with unified data exchange and reporting. This will then enable the development of the novel unified informatics pipeline. The key is to use the same underlying statistical methodology for both types of omics, with analysis differing only in biological models utilised, thus underpinning coherent delivery to downstream systems biology modelling. We will also spearhead a programme of community involvement to encourage long-term community participation in the unified informatics approach. This will include an international one-day workshop drawing in leading groups from both metabolome and proteome informatics disciplines for the first time, in order to foster a shared mind-set towards unifying the two fields.

生物学家越来越多地希望了解控制每个生物体功能的基因，代谢产物和蛋白质的构成区块之间的复杂相互作用。系统生物学领域已经出现了，以克服传统还原主义方法的缺陷，该方法已经确定了构件本身和许多个体相互作用，但无法推断这些块的系统如何在统一性上采取行动和反应。系统生物学的应用是广泛的，因为它有望彻底改变我们对植物，动物和人类健康过程的理解，以及它们如何在疾病下分解以及如何避免这种分解。通常，系统生物学方法始于特定生物学样本的“快照”。质谱是一种普遍存在的技术，用于获得样品的快照，它通过将样品电离，然后根据所得电荷来测量样品，然后测量每个组成型化合物的质量和数量。这通常不足以完全分离样品，因此使用液态或气相色谱法的先前阶段来提供初始分离。蛋白质和代谢产物的类别需要不同的样品制备，电离和色谱方法。这些都增加了不同种类的偏见和变化，这使得在化合物之间推断联系极为具有挑战性，尤其是在化合物来自不同类别的情况下。更糟糕的是，需要许多快照来捕获所研究的生物过程的不同“角度”，并且随着时间的流逝，工具性条件本身并不完全可重现。所有这些使系统生物学成为逐步的计算学科。研究全球蛋白质模式（“蛋白质组学”）和代谢产物（“代谢产物”）的学术学科广泛地来自不同的领域，因此两者之间几乎没有协同作用。尽管事实将两者都应用于质谱数据，但计算方面也是如此。因此，方法论和思想的交叉剥夺具有播种新颖，有效的新分析方法。该项目团队分别参与了代谢组学和蛋白质组学的著名MZMATCH和蛋白能仪信息软件包的开发。它们是英国最积极发达的学术代谢组和蛋白质组信息套件。因此，有及时的机会进行一致的努力，将信息组和蛋白质组学的信息学界，方法论和软件汇总到：（a）建立一个新的，强大的统一的统一信息学工作流程“借用借用力量”在两个领域的方法中的“借用力量”，比其各个部分的成分和更大的零件统计属性更大，并具有一致的统计属性，以实现最佳的统计属性。 （b）基础跨学科合作，代谢组学和蛋白质组学领域之间的新理解和流动性； （c）支持开发联合数据交换和报告标准，以最佳的代谢组学和蛋白质组学数据的最佳整合。为了实现这一目标，我们将首先将MZMatch与统一的数据交换和报告集成为ProteoSuite。然后，这将使新型统一信息学管道的发展。关键是要对两种类型的OMICS使用相同的基本统计方法，分析仅在使用的生物学模型中有所不同，从而使连贯的交付给下​​游系统生物学建模。我们还将率领社区参与计划，以鼓励长期社区参与统一信息学方法。这将包括首次代谢组和蛋白质信息组信息学学科的领先小组中的国际一日研讨会绘图，以促进共同的思维方式来统一这两个领域。

项目成果

Incorporating peak grouping information for alignment of multiple liquid chromatography-mass spectrometry datasets.

• DOI: 10.1093/bioinformatics/btv072
• 发表时间: 2015-06-15
• 期刊: Bioinformatics (Oxford, England)
• 作者: Wandy J;Daly R;Breitling R;Rogers S
• 通讯作者: Rogers S

Unsupervised Discovery and Comparison of Structural Families Across Multiple Samples in Untargeted Metabolomics.

• DOI: 10.1021/acs.analchem.7b01391
• 发表时间: 2017-07-18
• 期刊: Analytical chemistry
• 影响因子: 7.4
• 作者: van der Hooft JJJ;Wandy J;Young F;Padmanabhan S;Gerasimidis K;Burgess KEV;Barrett MP;Rogers S
• 通讯作者: Rogers S