The Swedish Metabolomics Centre helps researchers to answer their questions by providing tailor-made metabolite and lipid analyses. SMC offers all analytical steps from sample preparation to data processing, for both untargeted and targeted analysis of low molecular weight compounds. To learn more about the Metabolomics service model, click here.
We offer four different products:
- untargeted methods
- targeted methods
- method development
- Open Access (i.e. you use our instruments to do the analysis yourself).
Together with you we choose which of these four that suits you. Feel free to contact us if you have questions about these or other methods. 
Untargeted methods
Untargeted methods are suitable when you want an overall picture of the metabolite profile in a set of samples. Metabolite differences between samples can be used for hypothesis generation (discovery) or confirmation (testing).
Targeted methods
Targeted methods are suitable if you want to analyze specific metabolites in a sample, when you want to dig deeper into specific metabolite pathways after an untargeted anysis, and for validation of metabolite data from untargeted analyses.
Method development
2-3 weeks full time method development for a specific research question where a standard analysis protocol currently does not exists. SMC also offers consulting for pilot studies, metabolite confirmation, identification of unknown, and other ad hoc projects.
Read more about some of our methods below.
The standard metabolomics analysis at SMC is performed using both GC-MS and LC-MS (positive and negative electrospray ionisation). The analysis is based on untargeted MS-analysis and is qualitative, i.e. the metabolite levels are expressed as normalised peak areas that can be compared between the analysed samples. The standard metabolomics analysis will result in a data table consisting of peak areas of identified metabolites and of detected putative non-identified metabolites. The number of identified metabolites is increasing, but still the majority of detected peaks are classified as unknowns. Major compound classes as amino acids, fatty acids, phenols, sugars, organic acids, sterols, lipids, flavonoids, oligolignols, and anthocyanins are all examples of classes that can be detected with the described approach.
GENERAL INFORMATION
NUMBER OF SAMPLES: 50-200 samples (analysis of fewer or more samples has to be discussed with SMC)
MATRICES: Plasma, Serum, CSF, Arabidopsis, Populus, bacteria, human tissues, cell cultures, and yeast (other matrices have to be communicated with SMC).
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published
INCLUDED IN STANDARD METABOLOMICS ANALYSIS
- Sample preparation for GC-MS and LC-MS (eg. methanol/water extraction)
- Analysis by both GC-MS and LC-MS (C18 using positive/negative ion mode ESI)
- Quality assurance of the analysis
- Generation of a compound list for GC-MS (~100 - depending on matrix) and LC-MS (~100 - depending on matrix)
- Generation of a table of relevant unknown integrated peak areas (annotated with retention time/index and mass)
- Initial statistical evaluation of the generated data according to the question asked in the project (multivariate and univariate data analysis)
- Initial identification of unknown compounds deemed relevant for the project (around 10-20 metabolites)
- Storage of a pooled sample for possible future extended identification (extended identification is not included)
- Report and feedback
- Archiving of raw data
Lipids are small molecules that can be divided into a number of different classes, e.g., fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, and sterol lipids (see Lipid Maps for classification and nomenclature). For lipid analysis an extraction protocol, such as Folch extraction, is used. Lipid analysis can be performed by LC-MS for all major classes of lipids and by GC-MS when fatty acid (FA) composition is of interest. Phosphatidylcholines (PC, 1-2 fatty acid chains), sphingomyelin (SM), and triacylglycerides (TG) are mainly detected in human plasma, serum and CSF. Other phospholipids might be present, but in lower concentrations. The analysis is based on MS-profiling and is qualitative, i.e. the metabolite data is expressed as normalised peak areas, and the values can be compared between the analysed samples. Targeted data processing using an in-house database can be applied to identify the total FA chain lengths and the total amount of double bonds.
Untargeted data processing of the obtained LC-MS chromatograms in both positive and negative ionization modes aiming for deeper identification of the lipid molecules is also possible to perform afterwards. Untargeted data processing and identification of the length of the FA:s for a specific lipid are not included in the standard lipid profiling.
See this example.
GENERAL INFORMATION
NUMBER OF SAMPLES: 50-140 samples (analysis of fewer or more samples has to be discussed with SMC)
MATRICES: Plasma, serum, CSF, tissue, and cells (other matrices have to be communicated with SMC)
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published.
INCLUDED IN STANDARD LIPID PROFILING
- Sample preparation for LC-MS (Folch extraction, with chloroform/methanol phase separation)
- Analysis by LC-MS (C18 column separation and QTOF MS detection using both positive and negative ion modes in ESI)
- Quality assurance of the analysis
- Targeted data processing, initially for five classes out of PC, SM, TG, DG, PE, PS, MGDG, DGDG and Cer in positive ion mode (~150 lipids, depending on matrix)
- Initial statistical evaluation of the generated data according to the question asked in the project (multivariate and univariate data analysis)
- Storage of a pooled sample for possible future extended identification (extended identification is not included in the price)
- Report and feedback
- Archiving of raw data
Plant hormones are highly bioactive signalling molecules with broad functions as chemical messengers that stimulate and regulate growth and development including flowering, seed germination, senescence and various stress responses. Plant hormones are large family of diverse compounds divided into several structurally different groups such as purine and indole derivatives, plant steroids, lipid-based substances and terpenoid carboxylic acids. The common characteristic of all hormones is that they are typically found in tissues in minute concentrations. Thus, direct quantification in complex plant extracts poses a difficult analytical task.
INTRODUCTION TO PHYTOHORMONE LC-MSMS METHODS
Cytokinin analysis – analysis of compounds from cytokinin metabolic pathway, including precursors (ribotides and ribosides), active bases (tZ, cZ, iP, DHZ) and various glycosylated forms (N7, N9, O and RO – glucosides)
Auxin analysis – analysis of main compounds in the auxin biosynthetic and metabolic pathway.
From tryptophane, tryptamine, anthranilic acid, indol-3-acedamide, indole-3-acetonitrile, and main auxin precursor, indole-3-pyruvic acid, through bioactive indole-3-acetic acid (auxin, IAA) to its oxidised form 2-oxoindole-3-acetic acid (oxIAA), the aminoacid conjugated forms (IAA- aspartate, glutamate, glycine, leucine, alanine, tryptophan, phenylalanine, valine) and glycosylated forms (IAA-Glc and oxIAA-Glc).
“Hormonomics“ – this approach encompasses the active compounds from several plant hormone classes (cytokinins, auxin, salicylic acid, abscisic adic, jasmonic acid, gibberellins and brassinosteroids), also some of their related compounds (precursors, metaboolites).
This method is perfect for the first plant hormone screening or in studies dealing with various stress conditions where the aim is to study the hormonal crosstalk.
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published
INCLUDED IN THE PLANT HORMONE ANALYSIS
- Sample preparation (e.g. extraction, purification, derivatization)
- Analysis by UHPLC-QqQ-MSMS
- Quality assurance of the analysis
- Quantification of targeted compounds
- Report and feedback
- Full access to raw data
Determination of fatty acid (FA) composition by GC-MS in biological matrices is performed after transmethylation (bound FA) and methylation (free FA) of the sample extract. Free FAs are found as single fatty acid chains, while bound FAs are attached, singly or several, to other molecules (e.g. phospholipids and triglycerides). Transmethylation and methylation are processes used to convert FAs in the samples to fatty acid methyl esters that are the products detected on the instrument. Our methods make it possible to detect 37 FAMEs - evenly numbered fatty acids found in eukaryotic cells, and 10 BAMEs - odd-numbered fatty acids found in bacteria. Quantification can be performed on FAMEs, whereas only relative values from calculated areas are reported for BAMEs.
GENERAL INFORMATION
NUMBER OF SAMPLES: 30-70 samples (analysis of fewer or more samples has to be discussed with SMC).
MATRICES: A wide variety of matrices can be used, communicate with SMC.
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published
INCLUDED IN THE FATTY ACIDS ANALYSIS
- Sample preparation (eg. Folch extraction with chloroform/methanol phase separation)
- Analysis by GC-MS TOF
- Quality assurance of the analysis
- Targeted data analysis of FAMEs and BAMEs
- Quantification of FAMEs
- Initial statistical evaluation of the generated data according to the question asked in the project (multivariate and univariate data analysis)
- Report and feedback
- Full access to raw data
Amino acids can be divided into six main groups on the basis of their structure and general chemical characteristics of their side chain groups, e.g. aliphatic, basic, acidic, and aromatic. All major amino acids can be quantified by LC (UHPLC)-UV or preferentially by UHPLC-QqQ-MSMS using AccQ•TagTM derivatization (Waters). SMC can provide quantification of 26 different amino acids; all proteinogenic amino acids included. In addition, we also offer analysis of free and bound amino acids.
GENERAL INFORMATION
NUMBER OF SAMPLES: 50-200 samples (analysis of fewer or more samples has to be discussed with SMC).
MATRICES: Plasma, serum, CSF, Arabidopsis, Populus, bacteria, cell cultures, and yeast (other matrices have to be communicated with SMC).
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published
INCLUDED IN THE AMINO ACIDS ANALYSIS
- Sample preparation (e.g. methanol/water extraction)
- Analysis by LC-QqQ-MSMS
- Quality assurance of the analysis
- Quantification of major amino acids
- Initial statistical evaluation of the generated data according to the question asked in the project (multivariate and univariate data analysis)
- Report and feedback
- Full access to raw data
Examples
Eicosanoids are bioactive lipids derived from arachidonic acid. Metabolites of other polyunsaturated fatty acids are, together with the eicosanoids, collectively known as oxylipins (including the pro-resolving mediators). They are produced mainly via three enzymatic pathways: cyclooxygenase (COX), lipoxygenase (LOX), and cytochrome P450 (CYP), as well as through auto-oxidation. Among the COX and LOX metabolites, prostaglandins and leukotriens are found. CYP metabolites include fatty acid epoxides and downstream diols. Other related fatty acid metabolites include endocannabinoids such as N-arachidonoylethanolamine (AEA or anandamide) and 2-arachidonoylglycerol (2-AG), as well as other fatty acid amides and glycerol esters.
GENERAL INFORMATION
NUMBER OF SAMPLES: 30-80 samples (analysis of fewer or more samples has to be discussed with SMC).
MATRICES: Plasma, serum, cell cultures (other matrices have to be communicated with SMC).
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published
INCLUDED IN THE EICOSANOID ANALYSIS
- Sample preparation (including solid phase extraction)
- Analysis by LC-QqQ-MSMS
- Quality assurance of the analysis
- Quantification of eicosanoids (extended panel of oxylipins, with or without endocannabinoids profiling can be discussed)
- Initial statistical evaluation of the generated data according to the question asked in the project (multivariate and univariate data analysis)
- Report and feedback
- Full access to raw data
REFERENCES
Gouveia-Figueira S, Späth J, Zivkovic AM, Nording ML. (2015) Profiling the oxylipin and endocannabinoid metabolome by UPLC-ESI-MS/MS in human plasma to monitor postprandial inflammation. PLoS ONE 10(7): e0132042.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4506044/
Gouveia-Figueira S, Nording ML. (2015) Validation of a tandem mass spectrometry method using combined extraction of 42 oxylipins and 15 endocannabinoid-related compounds including prostamides from biological matrices. Prostaglandins Other Lipid Mediat. 121:110-121.
http://www.sciencedirect.com/science/article/pii/S109888231500074X
Gouveia-Figueira S, Nording ML. (2014) Development and validation of a sensitive UPLC-ESI-MS/MS method for the simultaneous quantification of 15 endocannabinoids and related compounds in milk and other biofluids. Anal Chem 86(2):1186-1195.
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4109781/
Determination of sugars can be performed by several different strategies depending on the purpose of the analysis. For determination of soluble sugars in e.g. tissues or fluids methanol/water extraction combined with GC-MS is the most reliable method with which several classes of sugars, such as pentoses, hexoses, disaccharides, and trisaccharides can be detected. With application of this method a data table consisting of peak areas for identified sugars is obtained. The sugar levels are expressed as peak areas normalized to internal standard glucose or sucrose, which can be compared between the analyzed samples.
GENERAL INFORMATION
NUMBER OF SAMPLES: 50-100 samples (analysis of fewer or more samples has to be discussed with SMC).
MATRICES: Plasma, serum, CSF, Arabidopsis, Populus, bacteria, cell cultures, and yeast (other matrices have to be communicated with SMC).
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published
INCLUDED IN THE ANALYSIS
- Sample preparation (e.g. methanol/water extraction)
- Analysis by GC-MSTOF
- Quality assurance of the analysis
- Targeted data analysis for sugars (eg. pentoses, hexoses, disaccharides)
- Initial statistical evaluation of the generated data according to the question asked in the project (multivariate and univariate data analysis)
- Report and feedback
- Full access to raw data
TMAO is an amine oxide that can be quantified using UHPLC-QqQ-MSMS. Quantification of Choline and Betaine is included in the standard procedure as well.
See this example.
GENERAL INFORMATION
NUMBER OF SAMPLES: 50-200 samples (analysis of fewer or more samples has to be discussed with SMC).
MATRICES: Plasma, serum, CSF, and cell cultures (other matrices have to be communicated with SMC).
SMC is an independent partner and will be mentioned in the acknowledgements if the data is published.
INCLUDED IN THE TMAO ANALYSIS
- Sample preparation (e.g. methanol/water extraction)
- Analysis by LC-QqQ-MSMS
- Quality assurance of the analysis
- Quantification of TMAO
- Initial statistical evaluation of the generated data according to the question asked in the project (multivariate and univariate data analysis)
- Report and feedback
- Full access to raw data
SMC develops quantitative methods for metabolite analysis to be able to offer new targeted methods for future projects. We accept requests from researchers for specific metabolites with the aim to establish targeted methods. After discussing the client's project, we do a pilot study to determine if it is possible to analyze metabolites in the defined biological tissue (matrix) using either LC-MS or GC-MS. The purpose of the pilot study is to determine if it is possible to continue the method development or not. Then the method development is performed according to a number of analytical requirements. When the project is finished the outcome is compiled as an application note describing the result and is communicated to the customer.
See this example. (Cancer Res July 2016 DOI: 10.1158/0008-5472.CAN-15-291)
ANALYTICAL REQUIREMENTS
- The method must have a simple (preferably one step) and defined extraction procedure which can be used to generate an extract from the matrix suitable for metabolite analysis by mass spectrometry.
- The metabolites of interest must be stable in the extract until analysis by GC-MS or LC-MS.
- The metabolites must have a unique defined retention time (RT) on a chromatographic column, mass signal (molecular ion or eq.) in a full scan analysis and/or unique transition from a tandem mass analysis (e.g. MRM).
- Internal standards with similar chemical structure and chemical behavior must be available for quantification of the target metabolites.
- There should be a linear response at least in a magnitude order of 103 between the instrumental signal (MS detector) and each concentration of the target metabolites.
- The response of a metabolite must increase when the matrix extract is spiked with its corresponding standard.
- It must be possible to detect the metabolites within the linear concentration range
THE APPLICATION NOTE - documentation of the pilot method development
The outcome from the pilot method development is compiled as an application note used for future target analysis, and can be used as the basis in a publication. The documentation will include:
- A list of relevant references from the scientific literature
- Definition of the utilized matrix (e.g. cell lines or plasma)
- A protocol for sample preparation and extraction of the metabolites from the defined matrix
- A protocol describing instrumental parameters and the analytical procedure
- A chromatogram of standards and internal standards, both in organic solvent and in spiked matrix extract (high and low concentrations)
- Estimated detection limits of target metabolite standards
- Data showing the linear response of the target metabolites
- Data confirming that the metabolites are stable in the extract until the time of analysis
- Results showing the signal of the target metabolites in the defined matrix when they are spiked by a defined concentration of metabolite standards