P17-056-23 Development of “LibrAAry,” a Readily Available Database for Amino-Acid Profiles From Various Protein Sources. A Pilot Application on Wheat
Résumé
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, herewe only present a pilot extraction
of this work, focusing on wheat alone, derived from 34 published
articles and resulting in 204 data points. Datawere 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, andwere thus excluded
from the analysis to avoid bias of sampling. Moreover, the nonessential
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.
Domaines
Alimentation et Nutrition
Origine : Fichiers produits par l'(les) auteur(s)