Low-protein diet accelerates wound healing in mice post-acute injury Journal Articles uri icon

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abstract

  • AbstractBackgroundWound healing processes are influenced by macronutrient intake (protein, carbohydrate and fat). The most favourable diet for cutaneous wound healing is not known, although high-protein diets are currently favoured clinically. This experimental study investigates the optimal macronutrient balance for cutaneous wound healing using a mouse model and the Geometric Framework, a nutrient modelling method, capable of analyzing the individual and interactive effects of a wide spectrum of macronutrient intake.MethodsTwo adjacent and identical full-thickness skin excisions (1 cm2) were surgically created on the dorsal area of male C57BL/6 mice. Mice were then allocated to one of 12 high-energy diets that varied in protein, carbohydrate and fat content. In select diets, wound healing processes, cytokine expression, energy expenditure, body composition, muscle and fat reserves were assessed.ResultsUsing the Geometric Framework, we show that a low-protein intake, coupled with a balanced intake of carbohydrate and fat is optimal for wound healing. Mice fed a low-protein diet progressed quickly through wound healing stages with favourable wound inflammatory cytokine expression and significantly accelerated collagen production. These local processes were associated with an increased early systemic inflammatory response and a higher overall energy expenditure, related to metabolic changes occurring in key macronutrient reserves in lean body mass and fat depots.ConclusionsThe results suggest that a low-protein diet may have a greater potential to accelerate wound healing than the current clinically used high-protein diets.

authors

  • Hew, Jonathan J
  • Parungao, Roxanne J
  • Mooney, Craig P
  • Smyth, Julian K
  • Kim, Sarah
  • Tsai, Kevin H-Y
  • Shi, Huaikai
  • Chong, Cassandra
  • Chan, Renee CF
  • Attia, Beba
  • Nicholls, Caroline
  • Li, Zhe
  • Solon-Biet, Samantha M
  • Le Couteur, David G
  • Simpson, Stephen J
  • Jeschke, Marc
  • Maitz, Peter K
  • Wang, Yiwei

publication date

  • January 1, 2021