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Food & Nutrition

Initial studies of the suitability of uniform stable- isotope labelling  (U-SIL) and mass spectrometry (MS) for compositional determination of classes of biomolecules in biomass have been conducted. Several preliminary MS experiments on biomasses from microbiological sources and their extracts were performed. As a follow-up, the innovation project has been considered with the aim to develop metabolomics quantification tool (MQT).  The expected  benefits could be summarized as following: 
  • Improvement of the comparability of studies due to the use of the MQT, as metabolite profiles obtained at different moments in time and/or in different labs can be compared. This is essential for the application of validated methods in industrial or clinical labs.
  • Time reduction of current data processing time. Due to the use of the MQT for quantification data processing will be improved as a wide range of labelled metabolites are available as internal standards for the quantification of metabolites. Currently, the same time is required for data processing as for data acquisition, and the first can be reduced by at least a factor of 2.
  • Reduction of number of experiments: due to the U-SIL technologies, MS method could save actual costs relative to the MS analysis allowing identification of metabolites in a few single experiments.
  • Reduction of labor costs.
  • Finally MQT will allow cost-effective screening of new metabolites in human fluids (such as plasma, blood, urine, saliva), relative quantification will be possible as in the wide range of labelled metabolites used as reference there will be always a suitable one, to be found via automated data processing, to be used as internal standard for the quantification of new metabolites.

Our ambition is to develop novel metabolomics and proteomics tools. This will be achieved via improvement of the comparability of studies obtained at different moments in time or in different labs. This is essential for the application of validated methods in industrial or clinical labs. Another benefit will be time reduction of current data processing time. Due to the use of novel tools for quantification, data processing will be improved as a wide range of stable-isotope labelled metabolites will become available as internal standards for the quantification of metabolites. Currently, the same time is required for data processing as for data acquisition, and the first can be reduced by at least a factor of two.  Finally, reduction of number of experiments could be achieved due to the uniform stable-isotope labelling technologies. MS method could save actual costs relative to the standard MS analysis allowing identification of metabolites in a few single experiments. In addition, cost-effective screening of new metabolites in human fluids (such as plasma, blood, urine, saliva) could be achieved.
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