Effect of dietary arginine levels on growth performance, protein synthesis, antioxidant capacity and immunity of postlarval mud crab Scylla paramamosain - Wu, Duoting; Feng, Wenping; Li, Xinyu; Xu, Hanying; Luan, Xueyao; Han, Tao; Wang, Jiteng (Frontiers in Marine Science, 2022)
This study investigated the effects of different dietary arginine (Arg) levels on the growth, protein synthesis, antioxidant capacity, and immunity of postlarval Scylla Paramamosain. Six isonitrogenous and isolipidic diets were formulated to contain 1.51%, 1.81%, 2.16%, 2.35%, 2.73%, and 3.07% dietary Arg levels (dry matter). There were four replicates for each diet treatment (26 crabs per replicate, initial body weight: 7.40 ± 0.15 mg). After eight weeks of feeding trial, the survival and molting frequency (MF) of crabs were not affected by the experimental treatment (P＞0.05). Crabs fed the 2.50% Arg diet achieved the highest weight gain (WG) and specific growth rate (SGR) (P<0.05). The whole-body protein content of the 2.16% and 2.73% Arg groups were significantly higher than that of the 1.51% Arg group (P<0.05). Crabs in the 2.35% group obtained the highest levels of phenylalanine and leucine (P<0.05). Superoxide dismutase (SOD), catalase (CAT), and total antioxidant capacity (T-AOC) activity in the 2.16%, 2.35% and 2.73% Arg groups were significantly higher than that in other treatments (P<0.05). Malondialdehyde (MDA) concentration and alkaline phosphatase (AKP) activity were not significantly affected by the treatments. The transcript levels of insulin-like growth factor 1 (igf-1), rapamycinin (TOR), S6 kinase-polypeptide 1 (s6k1) in crabs fed with 2.16% and 2.35% dietary Arg were significantly higher than those in crabs fed with 1.51% and 3.07% dietary Arg (P<0.05). The lowest prophenoloxidase (proPO), relish, and lysozyme transcript levels were observed in crabs fed the 1.51% dietary Arg. The current study founded that the Arg requirement for postlaval S.paramamosain was 2.34% (5.81% of the dietary protein), based on the second order polynomial regression analysis of WG.