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Kohonen Artificial Neural Network and Multivariate Analysis in the Identification of Proteome Changes during Early and Long Aging of Bovine Longissimus dorsi Muscle Using SWATH Mass Spectrometry

Authors :
Emilio Marengo
Jessica Brandi
Elisa Robotti
Enrico Novelli
Elettra Barberis
Daniela Cecconi
Marcello Manfredi
Source :
Journal of Agricultural and Food Chemistry
Publication Year :
2021
Publisher :
American Chemical Society (ACS), 2021.

Abstract

To study proteomic changes involved in tenderization of Longissimus dorsi, Charolais heifers and bulls muscles were sampled after early and long aging (12 or 26 days). Sensory evaluation and instrumental tenderness measurement were performed. Proteins were analyzed by gel-free proteomics. By pattern recognition (principal component analysis and Kohonen’s self-organizing maps) and classification (partial least squares-discriminant analysis) tools, 58 and 86 dysregulated proteins were detected after 12 and 26 days of aging, respectively. Tenderness was positively correlated mainly with metabolic enzymes (PYGM, PGAM2, TPI1, PGK1, and PFKM) and negatively with keratins. Downregulation in hemoglobin subunits and carbonic anhydrase 3 levels was relevant after 12 days of aging, while mimecan and collagen chains levels were reduced after 26 days of aging. Bioinformatics indicated that aging involves a prevalence of metabolic pathways after late and long periods. These findings provide a deeper understanding of changes involved in aging of beef and indicate a powerful method for future proteomics studies.

Details

ISSN :
15205118 and 00218561
Volume :
69
Database :
OpenAIRE
Journal :
Journal of Agricultural and Food Chemistry
Accession number :
edsair.doi.dedup.....ac1fd69f1060fa5ae612b90b698508a7