Systems Lipidomics tools and resources for biomedical research; LIPID MAPS.
Lead Research Organisation:
CARDIFF UNIVERSITY
Department Name: School of Medicine
Abstract
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.
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.
Technical Summary
Lipids are hydrophobic and amphipathic small molecules that account for a significant number of all known metabolites. Lipidomics refers to the analysis of lipids using mass spectrometry (MS), with or without liquid chromatography (LC). It describes the simultaneous measurement of up to thousands of species in a single sample, and is a technically specialist area requiring expert-curated databases, informatics tools and resources.
In 2003, the LIPID MAPS consortium began to systematically establish a database and nomenclature/classification system, that became the global industry standard in the field for lipid structure curation and categorization of molecules based on common structural motifs, and the work of the group continues today with input from lipid experts in the UK and abroad. However, the burgeoning area of Systems Lipidomics as applied to biomedical and clinical applications now requires a focus on providing the databases and tools that support data integration. This is a long term goal that starts with expansion of the lipid database into one that links structures, based on their biochemical transformations (reactions/metabolism), along with their respective enzymes/proteins/genes.
Databases are housed in a secure machine room at Babraham Institute. The backup server is mirrored to a secondary remote building on the campus. The website underwent full redesign/migration to a new web framework (Laravel) in 2019/20. Code is stored in a private github repository. BioPan is a lipidomics interrogation software in R and PHP, using HTML jQuery (v3.5.1) and Cytoscape.js library (v3.10.2). It uses PHP (v7.4.11) and R(v4.02) for request handing, data-processing and statistical analysis.
All curated data is housed and shared, without restriction, via the LIPID MAPS website (https://www.lipidmaps.org/), using the CC BY 4.0 license. The BioPAN software is available under the GPLv3+ license. LipidFinder code is available free on GitHub.
In 2003, the LIPID MAPS consortium began to systematically establish a database and nomenclature/classification system, that became the global industry standard in the field for lipid structure curation and categorization of molecules based on common structural motifs, and the work of the group continues today with input from lipid experts in the UK and abroad. However, the burgeoning area of Systems Lipidomics as applied to biomedical and clinical applications now requires a focus on providing the databases and tools that support data integration. This is a long term goal that starts with expansion of the lipid database into one that links structures, based on their biochemical transformations (reactions/metabolism), along with their respective enzymes/proteins/genes.
Databases are housed in a secure machine room at Babraham Institute. The backup server is mirrored to a secondary remote building on the campus. The website underwent full redesign/migration to a new web framework (Laravel) in 2019/20. Code is stored in a private github repository. BioPan is a lipidomics interrogation software in R and PHP, using HTML jQuery (v3.5.1) and Cytoscape.js library (v3.10.2). It uses PHP (v7.4.11) and R(v4.02) for request handing, data-processing and statistical analysis.
All curated data is housed and shared, without restriction, via the LIPID MAPS website (https://www.lipidmaps.org/), using the CC BY 4.0 license. The BioPAN software is available under the GPLv3+ license. LipidFinder code is available free on GitHub.
