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Research facilities

BioMedical Metabolomics Facility Leiden

The BioMedical Metabolomics Facility Leiden (BMFL) offers a highly structured environment for advanced metabolomics studies. BMFL builds on fully validated, state-of-the-art platforms that each cover a part of the human metabolism and together span the complete human metabolome.
BMFL is particularly geared towards biomarker discovery of human disease and health. BMFL works according to ISO17025 guidelines and employs rigorous quality standards, working with well validated methods and using our quality control pipeline which provides correction for analytical variation, data monitoring by means of quality control reports and data standardization. This ensures robust data that enables truly comparative studies.
Amy Harms

BMFL is the core facility of Leiden University and the Netherlands Metabolomics Centre (NMC) and its users include internal as well as external academic collaborators and pharmaceutical and industrial clients from all over the world, measuring over 15,000 profiles annually. BMFL does not only perform routine measurements, but operates at the frontier of metabolomics developments and opportunities. The BMFL team covers the complete track from involvement in experimental design, study set-up and sample collection to the actual measurements, data analysis, identification of unknown compounds and comprehensive feedback on the results. In close collaboration with partners, BMFL defines a tailor-made approach that offers the best fit between your biological question and optimal use of the potential of our highly advanced facilities.

Currently available BMFL platforms:

  total number of metabolites identified metabolites  absolute quantification volume plasma/serum required for analysis     metabolite classes covered
Untargeted profiling platforms     
Apolar lipids [2] 800 250 10 10 µl phospholipids, cholesterol esters, di/triglycerides
Polar lipids [2] 150 150 40 20 µl free fatty acids, phospholipids
Global medium polar [4] 250 120 40 50 µl primary metabolites, sugars, organic acids, amines
Bile acids 15 15 15 50 µl bile acids

Targeted platforms
Oxylipins [3] 120 120 80 250 µl hydroxylated fatty acids, prostaglandins, thromboxanes
Biogenic amines [1] 100 100 70 5 µl amino acids, catecholamines, polyamines
Acylcarnitines 50 50 20 10 µl acylcarnitines, TMAO, choline, betaine
Research platforms        
Global apolar 400 150 40 50 µl peptides, hormones, cofactors
Central carbon/energy metabolism 300 220 100 10 µl sugar phosphates, nucleotides

nitrosylated stress

60 60 60 250 µl isoprostanes, sphinganine, sphingosine phosphate
Endocannabinoids 20 20 10 100 µl fatty acid amines
Folic acids 6 6 6   folate pathway metabolites

Being embedded in the university ensures that new technological opportunities are quickly recognized and further developed into new platforms. The BMFL portfolio is therefore continuously improved and expanded. Major research efforts in miniaturizing methods, increasing sensitivity and coupling to organ-on-a-chip are currently being done jointly with researchers in the division of Analytical Biosciences.

Together with the Metabolomics Research lab of the Division of Analytical Sciences, led by prof. Thomas Hankemeier, the facility hosts more than 15 mass spectrometers, comprising ion-trap hybrids with FT-ICR and FT-Orbitrap, Q-ToF, Q-ion mobility-ToF, Triple quadrupole.

[1] Amine method Noga, M.J., et al. Metabolomics of cerebrospinal fluid reveals changes in the central nervous system metabolism in a rat model of multiple sclerosis. Metabolomics 2012; 8: 253-263. 

[2] Lipid method
Chunxiu Hu et al., RPLC-Ion-Trap-FTMS Method for Lipid Profiling of Plasma: Method Validation and Application to p53 Mutant Mouse Model. J. Proteome Res., 2008, 7 (11), pp  4982–4991.
doi: 10.1021/pr800373m.

[3] Oxylipin method
Strassburg et al., Quantitative profiling of oxylipins through comprehensive LC-MS/MS analysis: application in cardiac surgery. ANALYTICAL AND BIOANALYTICAL CHEMISTRY 2012; 5:1413-1426
doi: 10.1007/s00216-012-6226-x.

[4] GC (optimized version based on a method developed)
Koek MM, van der Kloet FM, Kleemann R, Kooistra T, Verheij ER, Hankemeier T. Semi-automated non-target processing in GC × GC–MS metabolomics analysis: applicability for biomedical studies. Metabolomics. 2011;7(1):1-14.

[5] QC correction method
Van der Kloet, F.M. et al., Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping. , J. Proteome Res., 2009, 8 (11), pp 5132–5141
doi: 10.1021/pr900499r.


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