Systems Lipidomics tools and resources for biomedical research; LIPID MAPS.

脂质（脂肪）代表人体组织中的大部分代谢物。它们是普遍存在的分子，在疾病以及疫苗开发、药物和营养等相关领域中发挥重要作用。它们通过酶/蛋白质进行代谢转化，进而由基因编码。脂质的动态变化反映了遗传和环境的影响，其准确分析对于临床诊断，生物标志物发现和精确医学具有重要意义。这是因为与基因不同，脂质会对环境、生活方式、疾病、感染、药物治疗和其他挑战做出反应。在生物医学研究中，使用质谱法对脂质进行大规模分析（脂质组学）正在迅速扩大。与此沿着的是，越来越需要结合来自其他组学领域（例如，转录组学和蛋白质组学）的复杂数据集来询问脂质组学。系统脂质组学的目的是汇集多维数据，以开发系统的整体视图。这种分析带来了巨大的挑战。具体而言，首先需要高度策划的数据库，其将脂质与其各自的反应/酶/蛋白质/基因结合在一起，并且在此之后，需要适当的信息学工具来严格利用从非靶向和靶向质谱法生成的大数据集，然后将其与多维组学数据联合收割机组合。系统脂质组学尚处于起步阶段，但如果没有高质量的专家策划的数据库，将产生低质量的数据，导致时间和资源的大量浪费。为了解决这个问题，我们将建立一个新的合作伙伴关系，重点是开发工具和资源，以支持这一新领域。将建立一个领导团队，其中包括基础和应用生物医学和生物化学研究人员和IT专家，总部设在卡迪夫大学，巴布拉罕研究所，斯旺西大学和爱丁堡大学。这将得到更广泛的全球合作者和行业项目合作伙伴Cayman Chemical的支持。该基础设施将托管在历史悠久的LIPID MAPS平台内，该平台自2003年以来一直在脂质命名和分类领域处于领先地位。有两个主要目标。(i)为脂质组学研究界提供系统生物学资源和新的数据库，以及（ii）扩大脂质结构管理、分类/命名、数据共享和培训活动。这些将通过重新配置我们的旗舰数据库LIPID MAPS结构数据库（LMSD）与来自其他合作资源（Rhea，Reactome）的数据以及最近与WikiPathways和ELIXIR发起的社区生物定位项目来实现。这将吸引反应，蛋白质和基因网络信息直接链接脂质结构条目，并由专家策展支持。新的工具将暴露数据库信息，用于数据分析/重用、访问途径和网络信息，以及稍后集成其他组学数据集（例如，转录组学）与脂质组学用于预测参与脂质代谢的基因/蛋白质调控网络。新的合作伙伴关系将直接支持新兴的系统脂质组学领域，应用于基础和应用生物医学和临床研究。LIPID MAPS是这个新伙伴关系的合适宿主，因为它在全球范围内被生物医学界使用，包括英国和世界各地的许多MRC资助的团体和大型计划。Google Analytics最近的数据显示，每年有超过72，000名用户和超过190万的页面浏览量，LMSD每年下载超过46，000次。LIPID MAPS于2020年成为ELIXIR-UK资源。

Lipids (fats) represent the majority of metabolites in human tissues. They are ubiquitous molecules that play essential roles in disease, as well in the related areas of vaccine development, pharmaceuticals and nutrition. They are metabolically transformed by enzymes/proteins, in turn encoded by genes. Dynamic changes in lipids reflect both genetic and environmental impacts and their accurate analysis is of major interest for clinical diagnostics, biomarker discovery and precision medicine. This is because unlike genes, lipids respond to environment, lifestyle, illness, infection, drug treatment and other challenges. The analysis of lipids at scale using mass spectrometry (lipidomics), is rapidly expanding in biomedical research. Along with this, there is a growing need to interrogate lipidomics in combination with complex datasets from other omic domains, for example, transcriptomics and proteomics. Termed Systems Lipidomics, the aim is to bring together multidimensional data to develop a holistic view of the system. This type of analysis brings enormous challenges. Specifically, there is first a need for highly-curated databases, that bring together lipids with their respective reactions/enzymes/proteins/genes, and following this, appropriate informatics tools are needed to rigorously exploit the large datasets generated from both untargeted and targeted mass spectrometry and then to combine it with multidimensional omic data. Systems Lipidomics is in its infancy, however without high quality expert curated databases, poor quality data will be generated, leading to significant wastage of time and resources.To address this, we will establish a new partnership, which will focus on generating tools and resources to support this new area. A leadership team will be established that includes basic and applied biomedical and biochemical researchers and IT specialists, based in Cardiff University, Babraham Institute, Swansea University, and University of Edinburgh. This will be supported by a wider group of global collaborators, and an industry project partner, Cayman Chemical. The infrastructure will be hosted within the long established LIPID MAPS platform, which has led the field in lipid nomenclature and classification since 2003. There are two primary objectives. (i) Provide systems biology resources and new databases for the lipidomics research community, and (ii) Expand lipid structure curation, classification/nomenclature, data sharing and training activities. These will be achieved through re-configuring our flagship database LIPID MAPS Structure Database (LMSD) with data from other collaborating resources (Rhea, Reactome) and a community biocuration project that has recently been initiated with WikiPathways and ELIXIR. This will draw in reaction, protein, and gene network information to directly link lipid structure entries, backed up by expert curation. New tools will expose the database information for data analysis/reuse, access to pathway and network information, and later, integration of other omics datasets (e.g., transcriptomics) with lipidomics for prediction of gene/protein regulatory networks involved in lipid metabolism. The new partnership will directly support the emerging area of Systems Lipidomics as applied to both fundamental and applied biomedical and clinical research. LIPID MAPS is the appropriate host for this new partnership, since it is globally used by the biomedical community, including by many MRC-funded groups and large scale initiatives, in the UK and worldwide. Recent data from Google Analytics shows >72K users and >1.9M pageviews annually, with LMSD downloaded >4.6K times per year. LIPID MAPS became an ELIXIR-UK resource in 2020.