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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
- 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.
- Subjects :
- Male
Proteomics
Meat
Multivariate analysis
Proteome
Biology
PLS-DA
Article
Mass Spectrometry
Andrology
Downregulation and upregulation
medicine
Animals
chemometric techniques
Muscle, Skeletal
Longissimus dorsi
Skeletal
General Chemistry
longissimus dorsi
Tenderness
PFKM
longissimus dorsi, chemometric techniques, supervised Kohonen networks, PLS-DA, SWATH-MS
Multivariate Analysis
SWATH-MS
Muscle
Female
Cattle
Neural Networks, Computer
supervised Kohonen networks
medicine.symptom
General Agricultural and Biological Sciences
Carbonic anhydrase 3
Subjects
Details
- ISSN :
- 15205118 and 00218561
- Volume :
- 69
- Database :
- OpenAIRE
- Journal :
- Journal of Agricultural and Food Chemistry
- Accession number :
- edsair.doi.dedup.....ac1fd69f1060fa5ae612b90b698508a7