Metabolomics Core Facility

• To understand the link between diet and gut microbiome and the interaction between metabolites from the microbes digestion on the human physiology.
  (see Microbiome group.)
• To identify biomarkers of food intake to cover common dietary habits and to explore metabolites associated with health outcomes in nutrition studies.
  (see Dietary Biomarkers)
• To elucidate mechanisms of diseases and to identify  biomarkers of disease susceptibility and risk.  
  (see  DNA-adductomics).
• To set up new targeted and untargeted methods using liquid chromatography coupled with high resolution mass spectrometry
• To collaborate broadly with external partners by providing efficient metabolic profiling and biomarker identification in all biological sample types.

We analyse most biological matrices including urine, blood plasma/serum, fecal extracts, tissue extracts. We work mainly with human samples or samples from experimental animals, but we can also profile cultured cells, bacteria, or the growth media.

We are specialized in both targeted and untargeted methods:

Untargeted metabolomics

The technique is highly useful for explorative studies as a basis for generating new hypotheses. We perform the whole metabolomics untargeted workflow from study design, sample collection, data acquisition, data preprocessing, statistical analysis, and metabolite identification.

Untargeted DNA adductomics

The technique uses the same principles as untargeted metabolomics but applied to chemical modification on DNA, i.e. DNA adducts.

Fine annotation of unknown compounds

We annotate compounds by MS/MS spectra interpretation and confirmation with reference standard (we have more than 600 synthesized or bought reference standards).

Microbial metabolites

A multi-targeted method including more than 100 microbial metabolites, analysed in feces and blood.

Food intake biomarkers

A multi-targeted method including more than 60 food intake biomarkers, analysed in urine.

Short chain fatty acids (SCFA)

A quantitative method including more than 10 SCFA, analyzed in feces, blood, and urine.

Bile acids

A quantitative method including more than 20 bile acids, analyzed in feces and blood.

D- and L- aromatic lactic acids

A quantitative chiral method including 6 enantiomers analyzed in feces and blood.

Carotenoids

A quantitative method in serum.

Alcohol intake biomarkers

A quantitative method in urine, blood, and hair.

D- and L- aminoacids

A semi quantitative chiral method including enantiomers of aminoacids analyzed in urine.

Phenols and polyphenols

A semiquantitative method, in feces.

Saturated and unsaturated fatty acids

A semiquantitative method, In plasma/serum.

• UHPLC H-Class + Vion High Resolution Mass Spectrometer (Waters, Milfold, MA, USA)
• Vanquish + Orbitrap Exploris 120 High Resolution Mass Spectrometer (Thermo, Waltham, MA, USA)
• UHPLC Classic + photodiode array detector (PDA) (Waters, Milfold, MA, USA)
• UHPLC + fraction collector (Waters, Milfold, MA, USA)
• Calorimetric bomb
• Vacuum and nitrogen evaporators

Metabolite profiling in untargeted metabolomics results in large complex datasets that need to be processed to be interpretable.

Following essential steps such as pre-processing and statistical analysis, we are selecting sets of metabolites that are associated with health or disease.

The identification of these features is a major bottleneck in metabolomics.

In order to facilitate this work, we are constantly developing new tools to facilitate data preprocessing and annotation.

Among them:

• QC4Metabolomics: A tool for real time LC-MS analysis monitoring and quality control assessment.
• MScurate: A tool for curating spectral libraries.
• XCMS Annotator: An R package for compound annotation.
• PredRet: A tool for retention time prediction.
• xcmxVisGUI: A tool for browsing and automatically annotation raw data.
• decomposemz: A tool to decompose a mass to a molecular formula.
• and others (see below squidr)