Effects of supplementing coated methionine in a high plant-protein diet on growth, antioxidant capacity, digestive enzymes activity and expression of TOR signaling pathway associated genes in gibel carp, Carassius auratus gibelio

This study explored the impacts of supplementation of different levels of coated methionine (Met) in a high-plant protein diet on growth, blood biochemistry, antioxidant capacity, digestive enzymes activity and expression of genes related to TOR signaling pathway in gibel carp (Carassius auratus gibeilo). A high-plant protein diet was formulated and used as a basal diet and supplemented with five different levels of coated Met at 0.15, 0.30, 0.45, 0.60 and 0.75%, corresponding to final analyzed Met levels of 0.34, 0.49, 0.64, 0.76, 0.92 and 1.06%. Three replicate groups of fish (initial mean weight, 11.37 ± 0.02 g) (20 fish per replicate) were fed the test diets over a 10-week feeding period. The results indicated that with the increase of coated Met level, the final weight, weight gain (WG) and specific growth rate initially boosted and then suppressed, peaking at 0.76% Met level (P< 0.05). Increasing dietary Met level led to significantly increased muscle crude protein content (P< 0.05) and reduced serum alanine aminotransferase activity (P< 0.05). Using appropriate dietary Met level led to reduced malondialdehyde concentration in hepatopancreas (P< 0.05), improved superoxide dismutase activity (P< 0.05), and enhanced intestinal amylase and protease activities (P< 0.05). The expression levels of genes associated with muscle protein synthesis such as insulin-like growth factor-1, protein kinase B, target of rapamycin and eukaryotic initiation factor 4E binding protein-1 mRNA were significantly regulated, peaking at Met level of 0.76% (P< 0.05). In conclusion, supplementing optimal level of coated Met improved on fish growth, antioxidant capacity, and the expression of TOR pathway related genes in muscle. The optimal dietary Met level was determined to be 0.71% of the diet based on quadratic regression analysis of WG. Copyright © 2024 Du, Lin, Shao, Zhao, Xu, de Cruz and Xu.

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