In our labs is a place only for the best of them


Gas Chromatography
    Time of Flight
        Mass Spectrometry

With helium gas as the mobile phase, GC is ideal for separating low-molecular-weight, volatile compounds. Compounds of limited volatility can be rendered volatile of derivatization.

Our GC–TOF–MS facilitates the identification of ~200 analytes, mostly primary metabolites: amino acids, sugars, components of glycolysis and the TCA cycle; to name but a few.


Reversed Phase
    Ultra-Performance Liquid Chromatography
        Fourier Transform
            Mass Spectrometry

This device combines the best of available separation and detection techniques. Each of its components gives it a different edge, be it metabolite diversity (RP), separation power (UPLC), or accurate mass determination (FT).

Our particular FT–MS is of the Orbitrap type and enables both the detection of larger, semi-polar, mostly secondary metabolites and natural products that are precluded from GC–MS analysis; as well as simple and complex lipids. More than 1500 compounds of each category can be detected.

For unknown compounds of particular interest, partial structure elucidation by tandem mass spectrometry (MS/MS) is possible.


Reversed Phase
    Ultra-Performance Liquid Chromatography
        Quadrupole Ion Trap
            Mass Spectrometry

When it comes to high-sensitivity, absolute metabolite quantification, our QTrap–MS cannot be matched.

On a standard basis we quantify mainly primary metabolites; upon special request the quantification of other classes can be conducted too.


We're particularly proud of our metabolite database







Meticulous, systematic recording of thousands of natural metabolites (as standard references) allowed us to construct a unique, world-class metabolite database.

Our on-growing database currently comprises over 8000 entries and is composed of the major and essential molecular building blocks of any living organisms from the plant, animal, and fungi kingdoms: amino acids, carbohydrates, organic acids, alkaloids, flavonoids, complex lipids, and many more.

Mathematical Modeling

Generating big data is only half the story


Our analysts are experts in reading between the lines of large amounts of data. Metabolite levels—the main type of data we produce—can be used to predict traits: biomass, growth rate, resistance to biotic and abiotic stress, taste, appearance; to name but a few.

metaSysX uses special algorithms, developed in-house, to define metabolic biomarkers and predict traits. Aside from unraveling biological mechanisms in basic research, such modeling can be extremely useful from a commercial point of view. It may lead to increased yield and resistance in crops, for instance.

For companies that provide foodstuff mixtures (coffee, tea, tobacco, seasoning, condiments, spices), we have rich experience in devising blending schemes based on modeling the single components that comprise the mix.


Genomic, transcriptomic, proteomic, and phenomic studies generate immense amounts of data. At metaSysX we know precisely how to integrate your various datasets in a meaningful way. Metabolite levels can be regarded as quantitative traits.

By associating metabolite levels with genetic makeup, novel genes that control metabolite levels can be detected.

Two common methodologies for that are quantitative trait locus (QTL) mapping and genome-wide association studies (GWAS); we have vast experience in both. Our systems biologists develop custom-tailored solutions for each scientific question.

The deep knowledge of our experts in network, graph theories and machine learning allows us to carry out profound analysis of metabolomic data and transcripts for a given experiment.