Sensoproteomics: Ein neuer Ansatz zur Identifizierung geschmackaktiver Peptide in fermentierten Lebensmitteln. [06.11.18]
In einer aktuellen Studie der TUM unter Mitwirkung des Hohenheimer Professors Jörg Hinrichs wurde ein neuer Ansatz entwickelt, um geschmacksgebende Verbindungen in Lebensmitteln rasch und eindeutig zu identifizieren. Dieses als „Sensoproteomics“ bezeichnete Verfahren kann im Hochdurchsatzverfahren genutzt werden und so Produktionsprozesse optimieren.
Foto: Journal of Agricultural and Food Chemistry 66
Originalpublikation
Sebald, Karin; Dunkel, Andreas; Schäfer, Johannes; Hinrichs, Jörg; Hofmann, Thomas (2018): Sensoproteomics: A New Approach for the Identification of Taste-Active Peptides in Fermented Foods. In: Journal of Agricultural and Food Chemistry 66 (42), S. 11092–11104. DOI: 10.1021/acs.jafc.8b04479.
Author information:
1 Department of Food Chemistry and Molecular Sensory Science, Technical University of Munich, Lise-Meitner-Strasse 34, Freising, D-85354, Germany
2 Leibniz-Institute for Food Systems Biology, Technical University of Munich, Lise-Meitner-Strasse 34, Freising, D-85354, Germany
3 Institute of Food Science and Biotechnology, Department of Soft Matter Science and Dairy Technology, University of Hohenheim, Garbenstrasse 21, Stuttgart, D-70599, Germany
4 Bavarian Center for Biomolecular Mass Spectrometry, Technical University of Munich, Gregor-Mendel-Strasse 4, Freising, D-85354, Germany
Abstract
Aiming at the identification of the key bitter peptides in fermented foods, a new approach, coined "sensoproteomics", was developed and applied to fresh cheese samples differing in bitter taste intensity. By means of MPLC fractionation of the water-soluble cheese extracts in combination with taste dilution analysis, complex fractions with intense bitter taste were located and then screened by UPLC-MS/MS for the entire repertoire of ∼1600 candidate peptides, extracted from a literature meta-analysis on dairy products, by using a total of 120 selected reaction monitoring methods computed in silico. A total of 340 out of the 1600 peptides were found in the cheese samples, among which 17 peptides were identified as candidate bitter peptides by considering only peptides that were located in the bitter-tasting MPLC fractions (signal-to-noise ratio: ≥10) with a fold-change of ≥3 when comparing the less bitter to the more bitter cheese sample and that were validated by comparison with the synthetic reference peptides. While EIVPNS[phos]VEQK (αs1-CN70-78) and INTIASGEPT (κ-CN122-131) did not exhibit any bitter taste up to 2000 μmol/L, 15 of the 17 target peptides showed bitter taste thresholds ranging from 30 (ARHPHPHLSFM, κ-CN96-106) to 690 μmol/L (IQKEDVPS, αs1-CN81-88). Finally, quantitative peptide analysis followed by calculation of dose-overthreshold factors revealed a primary contribution of MAPKHKEMPFPKYPVEPF (β-CN102-119) and ARHPHPHLSFM (κ-CN96-106) to the perceived bitter taste of the fresh cheese samples. Finally, the evolution of the bitter peptides throughout two different fresh cheese manufacturing processes was quantitatively recorded. Copyright © 2018 American Chemical Society.
