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Mass-Spectrometric Analysis of Lipids (Lipidomics) 1. Identification 2. Quantification 3. Metabolism.

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Presentation on theme: "Mass-Spectrometric Analysis of Lipids (Lipidomics) 1. Identification 2. Quantification 3. Metabolism."— Presentation transcript:

1 Mass-Spectrometric Analysis of Lipids (Lipidomics) 1. Identification 2. Quantification 3. Metabolism

2 Why to do lipidomics? Biology: Functions of different lipids? Medicine: Diagnostics and Therapy Industry: Healthier food, Quality control

3 GlyceroPhospholipids >10 classes (PC, PE, PS, PI, PA etc) - Each class consists of numerous species with different fatty acid combinations (>20 different fatty acids) => Thousands of different molecular species possible Phosphatidylcholine (PC)

4 Neutral Glycerolipids - Triacylglycerols (TG) - Diacylglycerols (DG) - Monoacylglycerols (MG) -Each class consists of numerous species due to different fatty acid combinations => Hundreads of different molecular species TG DG

5 Lactosylceramide Ganglioside Sulfatide Sphingolipids - Ceramides - Neutral Glycosphingolipids - Acidic Glycosphingolipids -Each class consists of numerous species due to different fatty acid => Hundreads of different molecular species

6 The complete lipidome of no cell or tissue has ever been determined...because of technical limitations

7 Advantages of MS analysis  Sensitivity > 1000-fold higher than with conventional methods  Resolution - Allows quantification of hundreds of lipid species  Speed -100 times faster  Can be automated - High troughput possible

8 Ionization methods used in lipid MS Electrospray (ESI) –Does not cause fragmentation –Can be easily automated –Compatible with on-line LC Matrix-assisted laser desorption (MALDI) –Less used thus far –Suppression by PC/SM > All lipids not detected –On-line LC separation not feasible

9 Electrospray ionization Competition for charge => Suppression effects!

10 MS spectrum of cellular lipid extract = a Mess! Scanning MS1MS2 Collision cell Detector

11 How to improve selectivity? A. Lipid class -specific scanning (MS/MS) B. On-line chromatographic separation (LC-MS)

12 Lipid class -specific scanning Phospholipid class consist of species with the same polar head-group but different fatty acids Phospholipid classSpecific scan Phosphatidylcholines Precursors of +184 PhosphatidylinositolsPrecursors of -241 PhosphatidylethanolaminesNeutral-loss of 141 Phosphatidylserines Neutral-loss of 87

13 Precursor ion scanning  Requires a characteristic, charged product ion PC => Diglyceride + phosphocholine (+184) FragmentationScanningStatic (+184) MS1 MS2 Collision cell (Helium or Argon)

14 Precursors of +184 => PC + SM -Alkaline hydrolysis can be used to remove PCs SM-16:0

15 Neutral-loss scanning ScanningFragmentationScanning MS1 MS2 Collision cell (Helium or Argon) Mass interval = 141..when the characteristic fragment is uncharged PE => Diglyceride (+) + phosphoethanolamine (141)

16 Neutral-loss of 141 (= PE) MS-scan 700750800

17 MS analysis of Sphingolipids

18 Sphingosine Ceramide Lactosylceramide Ganglioside Sulfatide

19 Ceramide and Neutral Glycosphingolipids - Precursors of sphingosine (m/z +264) Ceramides Glucosylceramides 24:1

20 Sulfatides - Precursors of Sulfate (m/z -97)

21 Liquid chromatography-MS (LC-MS) Advantages - Increased sensitivity due to diminished suppression of minor species by - Major species - Impurities Disadvantages –Takes more time (not UPLC) –Data analysis more complex (?)

22 LC-MS analysis of mouse brain lipids Time Hermansson et al. (2005) Anal Chem.77:2166-75

23 Data analysis => software A. Processing of the data => Identification => Concentrations B. Bioinformatics => Biomarkers? =>Biological significance?

24 Quantification not simple Signal intensity depends on: Lipid head-group Acyl chain length Acyl chain unsaturation Ions present (adduct formation) Detergent and other impurities (suppression) Solvent composition and instrument settings => Internal standards necessary!

25 LIMSA Excel add-on for Quantitative Analysis of MS data (Haimi et al..2006. Anal Chem. 78:8324-31)  LIMSA does:  Peak picking and fitting  Peak overlap correction  Peak assignment (database of >3000 lipids)  Quantification with internal standards  Batch analysis

26 MS-imaging of Lipids by MALDI PI 38:4 Sulfatide 24:1 Hydroxy-Sulfatide 24:1

27 Analysis of Lipid Metabolism by MS  Adds another, dynamic dimension to lipidomics  Labeled lipids can be selectively detected! D 9 -PC => +193 (Unlabeled PC => +184) D 4 -PE => 145 (Unlabeled PE => 141) D 4 -PS => 90 (Unlabeled PS => 87) D 6 -PI => -247 (Unlabeled PI => -241) Precursors  Water soluble precursors (D 9 -choline etc)  Exogenous lipids

28 Phospholipid Remodeling: Exchange of acyl chains Glycerol Fatty acid Alcohol PO 4 Fatty acid Glycerol Fatty acid Alcohol PO 4 Fatty acid PLA 2 Glycerol Fatty acid Alcohol PO 4 OH Acyl transferase

29 Analysis of phospholipid remodeling using soluble precursor is problematic D 4 -ethanolamine => cells => D 4 -PE species Kinetics

30 Our approach: Use intact exogenous phospholipids with a deuterium-labeled head-group PROTOCOL Synthesize a phospholipid with a deuterium-labeled head group Make vesicles containing the labeled phospholipid Incubate cells with these vesicles and β-cyclodextrin (carrier) Extract and analyze lipids using MS/MS scans showing the labeled (or unlabeled) lipid only Determine the pathways and kinetics of remodeling

31 Unnatural 14:0/14:0-PE is remodeled very rapidly 14:0/14:0-D 4 -PE KINETICS

32 ”Natural” 18:1/18:1-PE is hardly remodeled

33 Positional isomers are remodeled with very different kinetics 14:0/18:1 18:1/14:0

34 Pathways of 14:0/14:0-PE remodeling Kainu et al. (2008) J Biol Chem. 283:3676-87

35 Studies with >50 phospholipid species (and PLA inhibitors) indicate that => Multiple acyl chain specific PLAs are involved in remodeling of phospholipids in mammalian cells BUT which PLAs?..and what determines their specificity?..and which acyltransferases are involved?

36 Conclusions  MS-based lipidomics is highly usefull in –Biology –Medicine –Food industry....but needs to be integrated with other “omics” and functional assays  Heavy isotope –labeling adds an important extra dimension to lipidomics

37 Contributors Martin Hermansson Ville Kainu Perttu Haimi


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