The core Metabolomics and Lipidomics Laboratory (cMaLL) is a technology ‘hub’, working on technological advances in metabolomics and lipidomics measurement and analysis that will contribute to biomedical innovation in diseases where metabolism is perturbed.
cMaLL works collaboratively to identify and validate metabolic markers that can be used in diagnosis and prognosis of disease and treatment, providing the complete pipeline from experimental design, sample preparation, analysis, data processing and bioinformatics.
cMaLL provides comprehensive and targeted analytical pipelines to study lipid and small molecule metabolism. It is supported by funding from the IMS-MRL and NIHR BRC NOME. We have a wide experience in metabolomics and lipidomics and all work will be collaborative and expected to be on cost recovery basis, with different costing levels depending on the staff and equipment contribution. In all cases we are keen to discuss how you can use metabolomic and lipidomics in your research and how our methods can help you to answer relevant questions. We have experience with biofluids, cells, tissues, model systems and can help to design the most relevant/appropriate experiments or metabolomic or lipidomics work. All applications for analysis need to be done by completing an analysis request form, and prioritisation will be decided by the cMaLL Scientific Advisory Board.
Please contact Albert Koulman before completing the application form or for further details.
Combined lipidomics training and sample analysis: WATCH OUR VIDEO
Methods
Type of methods and approaches that are provide by cMaLL. Full terms and conditions are available. We aim to provide quantitative data on specific metabolites and lipids.
1: time: this is the expected timeline is for internal users, depending on other demand, for external users it will be dependent on other projects and can be changed if internal priority work is demanded. Time lines will be discussed and set when samples are received in the lab.
2: costs per sample is based on a minimum of 80 samples or multiple thereof. Projects that consist of smaller sample sets need to be combined with other smaller experiments and thus are difficult to prioritise. It is possible to prioritise small sample sets when the costs of a full run (80 sample) are covered.
3: Costs per sample for commercial partners is on request.
4: fully untargeted profiling is possible but will only give relative concentration and tentative identifications, which will require additional work. We do not encourage the use of fully untargeted data for publications. Identification and quantification are required for publication and will require further work. Data will be processed. and initial data analysis will be provided as well as guidance on the data analysis.
Results
In all cases the results will be in the form of spreadsheet with the concentration of each lipid/metabolite per sample. The data format will be ready to be used on in on-line data analysis tools like Metaboanalyst. Preliminary data analysis is possible depending on the level of metadata available. Also we can provide advice and directions on the data analysis. When in depth interpretation of the data is expected than the collaborator needs to makes this clear at the start of the project so that time can included for this.
Training
We can also provide bespoke hands-on training that will allow you to do your own sample preparation and data processing. Training is typically one week in the lab followed by data processing training. At the end of the training, you will have publication ready data. The full cost of the training is £1000 based on sample set of 80 samples for team members in of the IMS MRL or BRC NOME themes. £1500 for team members in of CIMR or the Medical School and £2000 for academic scientists from outside. We can also provide training for non-academic and commercial partners and the costs for this are on request.
Publications
All data produced will be a publication level standards. The analysis, peak picking and quantitation are require expert knowledge and scientific judgement. When cMaLL data is used for the a publication we expect that head of the lab and the lab members involved will included as co-authors of the manuscript and that the manuscript will be shared with the cMaLL team before submission.
