Scouting for Naturally Low-Toxicity Wheat Genotypes by a Multidisciplinary Approach.
Rosa PilolliAgata GadaletaGianfranco MamoneDomenica NigroElisabetta De AngelisNicola MontemurroLinda MonaciPublished in: Scientific reports (2019)
Over the last years, great efforts have been devoted to develop effective gluten detoxification strategies with a consequent detrimental alteration of the technological properties as well. Obtaining low-gluten products without affecting the rheological properties of wheat could still be considered a new challenge to face. In this investigation, we presented a comprehensive characterization of durum wheat genotypes aimed at identifying low gluten ones, which combine the potential lower toxicity/immunogenicity with conserved yield and rheological properties to encompass the perspective usability for bread or pasta making. A preliminary profiling of gluten proteins was accomplished by immunoassay-based quantification and liquid chromatography coupled to UV detection, focusing on the gliadin fraction as main responsible for immunoreactivity in celiac disease patients. In addition, data on grain protein content, grain yield per spike, dry gluten and gluten index were collected in order to provide complementary information about productivity-related traits and quali-quantitative characteristics related to wheat nutritional value and its technological properties. The whole pool of data was statistically evaluated driving to the selection of a preferred list of candidate low-toxicity genotypes that were subjected to in-vitro simulated gastroduodenal digestion and untargeted HR-MS/MS peptide identification. Finally, an in-silico risk assessment of potential toxicity for celiac disease patients was performed according to the most recent guidance provided by EFSA.
Keyphrases
- celiac disease
- end stage renal disease
- risk assessment
- newly diagnosed
- ejection fraction
- electronic health record
- ms ms
- oxidative stress
- chronic kidney disease
- liquid chromatography
- mass spectrometry
- human health
- climate change
- machine learning
- prognostic factors
- transcription factor
- gene expression
- quality improvement
- big data
- patient reported outcomes
- tandem mass spectrometry
- genome wide
- liquid chromatography tandem mass spectrometry
- binding protein
- oxide nanoparticles
- artificial intelligence
- small molecule
- molecular dynamics simulations
- solid phase extraction
- gas chromatography mass spectrometry