Mass Spectrometry based Metabolomics, Lipidomics, and Fluxomics

Mass Spectrometry

  • The Metabolome is the collection of soluble low-molecular weight (50-1500 Da) organic molecules in a biological system.
  • Metabolomics is the systematic study of the Metabolome at a given time point of analysis.
  • Analysis of the metabolites gives an accurate picture of the physiological status of a cell/ tissue or biofluid, and is important in functional genomics, systems biology, biomarker identification, biomedicine, toxicology etc.
  • The two main technologies commonly used in Metabolomics are: Mass spectrometry (MS) and Magnetic Resonance (NMR).
  • The NT MS Lab comprises competence and infrastructure for both any type of MS based Metabolomics project, and we have also established method for MS based Lipidomics (i.e. the lipid composition in any sample) and Fluxomics (intracellular carbon flux distribution) research.

Mass spectrometry (MS) is a central technology in Metabolomics due to its very high sensitivity and selectivity. Combined with a separation step before the MS-detection (e.g. gas chromatography (GC), liquid chromatography (LC), convergence chromatography (UPC2), or capillary electrophoresis (CE)) it is a very powerful instrumentation for both quantitative and qualitative analyses of metabolites. There are several different types of mass spectrometers, some better suited for quantitative analyses (single and triple quadrupols) and others for qualitative analyses with requirements of high mass accuracy and high resolution (Time of Flight, Orbitrap, FT-ICR). The physico-chemical properties of metabolites are diverse, ranging from highly charged to hydrophobic species. The consequence is that there is no single GC/LC/UPC2/CE-MS method that completely covers all metabolites in a sample, and a comprehensive analysis of the Metabolome requires the same extract to be analyzed with different methods. Depending on the biological question that is to be answered, different methodological approaches can be used:

  • Metabolite Target Analysis: analysis restricted to metabolites of, for example, a particular enzyme system that would be directly affected by a biotic or abiotic perturbation
  • Metaboliic profiling: analysis focused on a group of metabolites, for example, a class of compounds such as carbohydrates, amino acids or those associated with a specific pathway
  • Metabolic fingerprinting: classification of samples on the basis of either biological relevance and origin
  • Metabolic footprinting: a strategy for analysing the properties of cells by looking in a high throughput manner at the metabolites that are excreted or taken up from the surroundings

Metabolomics methods at NT-MS lab

At the NT-MS lab we have established two core targeted and quantitative Metabolite Profiling methods (1 GC-MS/MS and 1 CapIC-MS/MS) that cover the major classes of metabolites (amino acids, organic acids, sugar and sugar alcohols, vitamines, sugar phosphates and other phospho-metabolites, nucleotides and nucleosides, in all  >150 metabolites are detected and quantitated if present in the sample)

Metabolites analyzed with the target GC-MS/MS method:  4-Methylvalerate, alpha-ketoglutarate, beta-Methylamino-L-alanine, Malonic acid, 2-Isopropylmalate, 2-oxobutyrate, Pyruvate, beta-hydroxypyruvate,  Cysteine, 3-Methyl-2-oxovalerate,  Hydroxylamine, Isocitrate, Fumarate, alpha-ketoadipate, Putrescine, Methylglyoxal, Leucine, beta-hydroxyaspartate, Succinate, Isoleucine, Phenylalanine, Lactate, gamma-aminobutyrate, Hippurate, Citraconate, Threonine, Phenylpyruvate, Itaconate, Malate, 2,4-Diaminobutyrate, Benzoate, Homoserine, 4-imidazoleacrylate, Citramalate, Proline, Cadaverine, β-3-hydroxybutyrate, OAA (Oxaloacetate), 4-Aminobenzoate, Alanine, Anthranilate, Histamine, Glycine, Aspatate, Coumarate, Methoxyamine, Citrate, Ornithine, Acetyl-L-Serine, 5-aminovalerate, Glycyl-Proline, Nicotinate, Glutamine, Lysine, Phenylacetate, Serine, Ferulate, 2-Aminobutyrate, Anthranilate, Histidine, Salicylate, Allantoin, Tyrosine, beta-Alanine, Glutamate, 2,6-diaminopimelate, m-Toluate, Methionine, Kynurenine, Adipate, N-Acetyl-L-Glutamate, Tryptophane, Valine,  Hydroxyproline, Serotonin

Metabolites analyzed with the target CapIC-MS/MS method:  2-deoxyglucose 6-phosphate, 3-phosphoglyceric acid, 5-phospho-D-ribose-1-diphosphate, 6-phospho gluconic acid, Acetyl CoA, ADP, AMP, ATP, cAMP, c-diAMP, c-diGMP, CDP, CTP, cGMP, CMP, CoA, dAMP, dATP, dCTP, dGTP, DHAP, dIMP, dTTP, dUMP, dUTP, Erythrose 4-phosphate, Farnesyl-pp, Fructose-1,6-DF, Fructose-1P, Fructose-6-phosphate, G-5DF-D-mannose, GDP, Geranyl-pp, Glucosamine 6-ph, Glucose-1-phosphate, Glucose-6-phosphate, Glyceraldehyde 3-P, Glycero-phosphate, GMP, GTP, IMP, Isopententyl-pp, ITP, Mannitol-1-P, Mannose-1-phosphate, Mannose-6-phosphate, NAD, NADH, NADP, NADPH, Phosphoenol pyruvate, Ribose 5-P, Ribulose 5-phosphate, Succinyl-CoA, TDP, TMP, Trehalose-6-phosphate, TTP, UDP, UMP, UTP, Xylulose 5-phosphate, 5-fluoro-2'deoxyuridine, 5-fluoro-2'deoxyuridine 5'monophosphate, 5-fluorouridine

Non-Target Metabolic Profiling

We have established 4 core 10min methods (HILIC and Reverse Phase chromatography with wither positive or negative ESI and MS scan, MS/MS or MSE data acquisition mode on the Synapt HDMS QTof MS) for non-target Metabolomics. Data processing is performed with the Transomics software form Nonlinear Dynamics/ Waters, and further statistical analysis/ multivariate data analysis is performed with EZInfo (Umetrics) and other available data analysis software. Final stage in the non-target MS Metabolomics work flow is potential identification through data base search (e.g. HMDB, Metlin) and interpretation of the results.

Lipidomics:

Lipid analysis is of interest in many biological studies, ranging from food applications to lipid status and profiling of healthy vs diseased individuals for a range of health conditions. Analysis of the lipidome by Mass Spectrometry in combination with efficient separation technologies ac LC, UPC2, GC is extremely promising due to high sensitivity and selectivity.

-    We have established a LC-QTOF MS method covering all major lipid classes (same lipid extract can be analysed in both positive and negative ESI modes)

-    At present we have a strong focus to develop both target and non-target methods for phospholipids and triglyceride lipid classes on the recently introduced separation platform Convergence Chromatography  UPC2.

Fluxomics:

Fluxomics is based on cultivation with 13C-labeled substrate, determination of incorporation of 13C-isotope in the different metabolites (i.e. mass isotopomer determination) by MS methodology, a stoichiometric model used for material and isotope balancing,   and estimation of intracellular metabolic flux patterns based on the experimental data and the stoichiometric model by using dedicated simulation software.

  • We have developed target GC-MS/MS and CapIC-MS/MS methods for mass isotopomer  determination of organic acids, amino acids, and phosphometabolites
  • And, we are using the 13CFLUX2 software (http://www.13cflux.net/13cflux2/) for the simulation tasks.

At the MS Metabolomics group at Department of Biotechnology we have been working with biological mass spectrometry for over ten years (see references below). We have focus on both developing new methods incl. sample processing as well as employing these methods on a variety of biological model systems (currently running Metabolome projects on bacteria, yeast, human cells, urine, and cancer tissue). 

Contact: Associate Professor Per Bruheim (Per.Bruheim@ntnu.no)

Reference list

1. Stafsnes MH, Dybwad M, Brunsvik A, Bruheim P (2013) Large scale MALDI-TOF MS based taxa identification to identify novel pigment producers in a marine bacterial culture collection. Antonie Van Leeuwenhoek International Journal of General and Molecular Microbiology 103 (3):603-615.

2. Lien SK, Sletta H, Ellingsen TE, Valla S, Correa E, Goodacre R, Vernstad K, Borgos SEF, Bruheim P (2013) Investigating alginate production and carbon utilization in Pseudomonas fluorescens SBW25 using mass spectrometry-based metabolic profiling. Metabolomics 9 (2):403-417.

3. Bruheim P, Kvitvang HFN, Villas-Boas SG (2013) Stable isotope coded derivatizing reagents as internal standards in metabolite profiling. Journal of Chromatography A 1296:196-203.

4. Tondervik A, Bruheim P, Berg L, Ellingsen TE, Kotlar HK, Valla S, Throne-Holst M (2012) Ralstonia sp U2 naphthalene dioxygenase and Comamonas sp JS765 nitrobenzene dioxygenase show differences in activity towards methylated naphthalenes. Journal of Bioscience and Bioengineering 113 (2):173-178.

5. Lien SK, Kvitvang HFN, Bruheim P (2012) Utilization of a deuterated derivatization agent to synthesize internal standards for gas chromatography-tandem mass spectrometry quantification of silylated metabolites. Journal of Chromatography A 1247:118-124.

6. Janeckova H, Hron K, Wojtowicz P, Hlidkova E, Baresova A, Friedecky D, Zidkova L, Hornik P, Behulova D, Prochazkova D, Vinohradska H, Peskova K, Bruheim P, Smolka V, St'astna S, Adam T (2012) Targeted metabolomic analysis of plasma samples for the diagnosis of inherited metabolic disorders. Journal of Chromatography A 1226:11-17.

7. Elde AC, Pettersen R, Bruheim P, Jarnegren J, Johnsen G (2012) Pigmentation and Spectral Absorbance Signatures in Deep-Water Corals from the Trondheimsfjord, Norway. Marine Drugs 10 (6):1400-1411.

8. Dybwad M, Granum PE, Bruheim P, Blatny JM (2012) Characterization of Airborne Bacteria at an Underground Subway Station. Applied and Environmental Microbiology 78 (6):1917-1929.

9. Vijayabharathi R, Bruheim P, Andreassen T, Raja DS, Devi PB, Sathyabama S, Priyadarisini VB (2011) Assessment of resistomycin, as an anticancer compound isolated and characterized from Streptomyces aurantiacus AAA5. Journal of Microbiology 49 (6):920-926. 10. Sletta H, Klinkenberg G, Winnberg A, Kvitvang HFN, Nilsen MB, Krokan HE, Otterlei M, Bruheim P (2011) A new high resolution screening method for study of phenotype stress responses of Saccharomyces cerevisae mutants. Journal of Microbiological Methods 87 (3):363-367.

11. Kvitvang HFN, Andreassen T, Adam T, Villas-Boas SG, Bruheim P (2011) Highly Sensitive GC/MS/MS Method for Quantitation of Amino and Nonamino Organic Acids. Analytical Chemistry 83 (7):2705-2711.

12. Klinkenberg G, Sletta H, Fjaervik E, Zahlsen K, Bruheim P (2011) Two-dimensional LC-MS fractioning and cross-matching of mass spectrometric data for rational identification of bioactive compounds in crude extracts. Journal of Separation Science 34 (23):3359-3363.

13. Stafsnes MH, Josefsen KD, Kildahl-Andersen G, Valla S, Ellingsen TE, Bruheim P (2010) Isolation and Characterization of Marine Pigmented Bacteria from Norwegian Coastal Waters and Screening for Carotenoids with UVA-Blue Light Absorbing Properties. Journal of Microbiology 48 (1):16-23.

14. Jorgensen H, Fjaervik E, Hakvag S, Bruheim P, Bredholt H, Klinkenberg G, Ellingsen TE, Zotchev SB (2009) Candicidin Biosynthesis Gene Cluster Is Widely Distributed among Streptomyces spp. Isolated from the Sediments and the Neuston Layer of the Trondheim Fjord, Norway. Applied and Environmental Microbiology 75 (10):3296-3303.

15. Jorgensen H, Degnes KF, Sletta H, Fjaervik E, Dikiy A, Herfindal L, Bruheim P, Klinkenberg G, Bredholt H, Nygard G, Doskeland SO, Ellingsen TE, Zotchev SB (2009) Biosynthesis of Macrolactam BE-14106 Involves Two Distinct PKS Systems and Amino Acid Processing Enzymes for Generation of the Aminoacyl Starter Unit. Chemistry & Biology 16 (10):1109-1121.

16. Villas-Boas SG, Bruheim P (2007) The potential of metabolomics tools in Bioremediation studies. Omics-a Journal of Integrative Biology 11 (3):305-313.

17. Villas-Boas SG, Bruheim P (2007) Cold glycerol-saline: The promising quenching solution for accurate intracellular metabolite analysis of microbial cells. Analytical Biochemistry 370 (1):87-97.

18. Bruheim P, Borgos SEF, Tsan P, Sletta H, Ellingsen TE, Lancelin JM, Zotchev SB (2004) Chemical diversity of polyene macrolides produced by Streptomyces noursei ATCC 11455 and recombinant strain ERD44 with genetically altered polyketide synthase NysC. Antimicrobial Agents and Chemotherapy 48 (11):4120-4129.

19. Robin J, Bruheim P, Nielsen ML, Noorman H, Nielsen J (2003) Continuous cultivations of a Penicillium chrysogenum strain expressing the expandase gene from Streptomyces clavuligerus: Kinetics of adipoyl-7-aminodeacetoxycephalosporanic acid and byproduct formations. Biotechnology and Bioengineering 83 (3):353-360.

20. Brautaset T, Bruheim P, Sletta H, Hagen L, Ellingsen TE, Strom AR, Valla S, Zotchev SB (2002) Hexaene derivatives of nystatin produced as a result of an induced rearrangement within the nysC polyketide synthase gene in S. noursei ATCC 11455. Chemistry & Biology 9 (3):367-373.