Gluten is a diverse class of proteins found in wheat, rye, barley and oats. Coeliac disease (CD) affects ~70 million people globally. When CD patients ingest gluten, it triggers an inappropriate auto-immune reaction resulting in intestinal inflammation and damage. The only current treatment for CD and gluten intolerants is lifelong avoidance of dietary gluten, however, such diets are costly and often low in fibre and high in calories, which in themselves are health risks. The worldwide market for gluten-free products is predicted to grow by ~25% over the next five years (to over US$7 billion). Gluten-free foods are commonplace, however, current methodologies (ELISA) do not accurately measure gluten as the antibodies are non-specific and show cross-reactivity.
We have developed a novel ultra-low gluten (ULG) barley variety in which the hordein (gluten) content was reduced to below 5 ppm. This was achieved using traditional breeding strategies to combine three recessive alleles, which act independently of each other to lower the hordein content in the parental varieties. We have employed advanced proteomics analysis to select the lines which showed the lowest gluten content and validate the low gluten content of the finished product.
Two LC-MS/MS approaches employing multiple reaction monitoring (MRM) and a data-independent acquisition strategy (SWATH) were used to quantify the complex protein mixtures present in nine barley varieties ranging from wild-type (gluten-containing) to ULG barley (gluten-free, < 20 ppm). Gluten-enriched and total protein fractions, extracted from flour using optimised protocols, was subjected to trypsin digestion by filter-aided sample preparation. The gluten peptide fragments were identified by high resolution LC-MS/MS with proteins identified from the Poaceae subset of proteins from Uniprot-KB. An MRM-based approach was explored for specific protein quantification and the results compared to those generated using variable window SWATH-MS.