(P17-056-23) Development of “LibrAAry”, a Readily Available Database for Amino-Acid Profiles From Various Protein Sources. A Pilot Application on Wheat

Objectives: Knowing the amino acid (AA) profiles and their variability from various protein sources is crucial, as it allows to estimate the dietary intake of individuals, permits the design of diets based on specific requirements, and understanding some factors influencing protein quality. Since the current available reference values are becoming old (FAO from 1970 and USDA from 1989 for raw wheat), and don’t include informations on the various factors influencing the profile, therefore, there is a need to develop an AA database of proteins profile. Thus, the aim of this work was the creation of the AA database “LibrAAry” and the assessment of the relative variations based on the AA profile.

Methods: A systematic review of 2417 articles published between Jan 1970 and December 2022 from Pubmed, Food Science and Technology Abstract, and Web of Science, based on the AA composition of commonly consumed protein sources across the World, was done. 748 articles matching the title and access (full text available) were manually reviewed and compiled for further analysis. However, here we only present a pilot extraction of this work, focusing on wheat alone, derived from 34 published articles and resulting in 204 data points. Data were homogenized and converted into mg AA/g protein.Overall, we observed that 4 amino acids ((Asn, Gln, Trp, and Cys) were rarely quantified among the 20 proteinogenic amino acids, and were thus excluded from the analysis to avoid bias of sampling. Moreover, the non-essential AA were less reported (15% less) compared to the essential AA. Data were analyzed and visualized by Principal Component Analysis.

Results: The database ‘LibrAAry’ led to draw the amino acid profile of different food items, with related variability for each AA for wheat from 204 observations. The PC1 and PC2 demonstrated 35 and 14% of the variability with a clear distribution of different wheat types as well as for the method used for each observation. In addition, the database could also compare the low vs high content of specific AA among reported cultivars, such as Einkorn and Yumai 7036 for Lys, or Balcali 2000 and Kleiber for Thr.

Conclusions: The AA database can be used for understanding the AA profile of specific food items and for designing targeted AA intake-based diets taking into accounts a prespecified variability.

Funding Sources: Funded by INRAE and registered as the creation DI-RV-22-0130