Integration analysis of metabolome and transcriptome profiles revealed the age-dependent dynamic change in chicken meat. (June 2022)

• Record Type: Journal Article
• Authors: Li, Jingjing; Zhang, Donghao; Yin, Lingqian; Li, Zhiqiang; Yu, Chunlin; Du, Huarui; Jiang, Xiaosong; Yang, Chaowu; Liu, Yiping
• Is Part Of: Food research international. Volume 156(2022)
• Publication Date: 2022-06
• Subjects: Metabolite -- LC-MS/MS -- Meat quality -- Integration analysis; Food -- Analysis -- Periodicals; Food industry and trade -- Periodicals; Food industry and trade -- Canada -- Periodicals; Food Technology -- Periodicals; Food -- Periodicals; Food-Processing Industry -- Periodicals; Aliments -- Industrie et commerce -- Périodiques; Aliments -- Industrie et commerce -- Canada -- Périodiques; Aliments -- Recherche -- Périodiques; Food industry and trade; Canada; Periodicals; Electronic journals; 664.005
• DOI: 10.1016/j.foodres.2022.111171
• Languages: English
• ISSNs: 0963-9969

Abstract

Graphical abstract: Highlights: Untargeted metabolomic profile of chicken meat was performed. Significant differences in metabolic composition of chicken meat were observed during five growth and development periods. The dynamic alterations of metabolites influencing meat quality were performed. Chicken meat at 180 days of age has more umami and antioxidant compounds. We identified key genes responsible for specific metabolite accumulation. Abstract: To explore the chemical composition of chicken meat during different growth and development periods, the dynamic alterations of the metabolite composition were determined using LC-MS/MS-based metabolomics. Together, 573 metabolites were identified in chicken meat from five age stages. Generally, pentadecanoic acid, stearic acid, creatine, carnosine, IMP, L-histidine and L-isoleucine presented an upward trend with age, while anserine, DHA, L-aspartic acid, LPA 18:1 and LPI 18:1 decreased with age. The main pathways of chicken meat metabolism affected by age were fructose and mannose metabolism, arachidonic acid metabolism, steroid hormone biosynthesis, riboflavin metabolism, biosynthesis of unsaturated fatty acids, and linoleic acid metabolism. Using transcriptomic profiling data, we conducted Pearson correlation analysis between gene expression and metabolite profile data in each age comparison. Integration analysis of metabolome and transcriptome would be helpful to understand the biological processes underlying the development of meat quality and explore valuable biomarkers for specific metabolite accumulation.