Metabolomic profile of phenolic compounds in sorghum during grain growth

International audience

anglais. Sorghum grains have gained prominence, since it represents a non-allergenic alternative to gluten and due to the health benefits of its bioactive compounds. However, these bioactive compounds may complex with sorghum proteins, limiting proteolysis and reducing digestibility up to 50%. This work aimed to investigate the phenolic profile of sorghum (Sorghum bicolor L., caudatum) in six different stages (S1-S6) of grain growth. Grains were freeze-dried and cryogenically ground. Free (FPC) and bound (BPC) phenolic compounds were extracted and the total phenolic content was determined by Folin–Ciocalteau method adapted to microplates. Phenolic profile was analyzed by UPLC-ESI-QTOF-MSE in negative mode. Data were processed with Progenesis QI using a customized database based on PubChem and Phenol explorer applying: mass error (<10ppm), isotope similarity (>80%) and reproducibility (3/3). FPC ranged between 101.24 to 443.84 mg GAE/100g (db), being the highest values in immature stages (S2-S4); while BPC varied from 125.48 to 306.12 mg GAE/100g (db), where the highest values were found in mature grains (S8, S10, mature). S6 represents the grain filling stage; in this point sorghum grains showed the same content of FPC and BPC. When represented per grain, the total phenolic content increased until S6 and remained constant until maturity. Globally, 118 FPC and 197 BPC were tentatively identified. Phenolic acids and flavonoids were the most abundant classes (68%). Immature grains (S2-S6) showed a distinguished phenolic profile presenting higher abundance than matures. It was still possible to identify tannins directly related to the reduction of protein digestibility, mainly the condensables (93% of total identified) until trimers. The abundance of these PC progressively increased until S6 and then reduced. This work seems to be the first one to reveal the phenolic profile based on metabolomic approach during sorghum grain growth. These data will be hereafter correlated with proteomic analysis.