High carbohydrate-low protein consumption maximizes Drosophila lifespan

Abstract

Dietary restriction extends lifespan in a variety of organisms, but the key nutritional components driving this process and how they interact remain uncertain. In Drosophila, while a substantial body of research suggests that protein is the major dietary component affecting longevity, recent studies claim that carbohydrates also play a central role. To clarify how nutritional factors influence longevity, nutrient consumption and lifespan were measured on a series of diets with varying yeast and sugar content. We show that optimal lifespan requires both high carbohydrate and low protein consumption, but neither nutrient by itself entirely predicts lifespan. Increased dietary carbohydrate or protein concentration does not always result in reduced feeding-the regulation of food consumption is best described by a constant daily caloric intake target. Moreover, due to differences in food intake, increased concentration of a nutrient within the diet does not necessarily result in increased consumption of that particular nutrient. Our results shed light on the issue of dietary effects on lifespan and highlight the need for accurate measures of nutrient intake in dietary manipulation studies.

Keywords: Aging; C:P; Dietary restriction; Drosophila; Feeding; Longevity; Nutrition; carbohydrate protein ratio.

Figure 1

Relationship between lifespan and macronutrient consumption. (A) Effects of protein and carbohydrate intake on median lifespan of Canton-S (left) and Dahomey (right) male flies. Protein and carbohydrate consumption are determined from accumulation of radiolabeled food over 24 h. Circle size scales with increasing longevity and the median lifespan at each point of protein and carbohydrate ingestion is shown. Longevity is maximized at an optimal C:P between 10:1 and 20:1, in agreement with previous studies on female Canton-S flies (Lee et al. 2008) that identified the optimum at 16:1 (solid line). Other carbohydrate:protein rails (1:1, 2:1, 4:1, 8:1, and 32:1) are shown as dashed lines. (B) Relationship between median lifespan and carbohydrate:protein ratio (C:P) for results from (A). Median lifespan is shown (solid points) and whiskers represent the interquartile range (1^st and 3^rd quartiles). Whiskers may be slightly offset horizontally for clarity.

Figure 2

Dietary casein mimics the effect of yeast extract on fly lifespan. (A) Dahomey males on a high yeast diet (5% yeast extract + 5% sucrose) are short-lived compared to those maintained on a low yeast diet (1% yeast extract + 5% sucrose; p = 0.002, log-rank). This effect is mimicked by supplementing the low yeast diet with casein (2%, w/v) to match the final protein content of the high yeast food (p = 0.0015, log-rank). There was no significant difference in lifespan between flies maintained on the high yeast and low yeast + casein diets (p = 0.73, log-rank). N = 84 (low yeast), 76 (high yeast), and 87 (low yeast + casein). (B) Food intake over 24 hours on high yeast, low yeast, and low yeast + casein diets. Ingestion by Dahomey males was determined using the radioisotope labeling method. Increased yeast concentration (high yeast diet) or the equivalent amount of protein (low yeast + casein) results in reduced consumption compared to that on low yeast food (***, p < 0.001; one-way ANOVA followed by Tukey post-hoc test). No difference in food intake was seen between the high yeast and low yeast + casein diets (p > 0.05, Tukey post-hoc). Results shown are averages ± s.d. of N = 6 vials of 10–13 flies each. (C) Observed lifespan differences are not due to dehydration. Lifespan of Dahomey males on a high yeast diet was measured with (N= 61) and without (N = 59) access to an independent water source. No difference in lifespan was observed (p = 0.96, log-rank).

Figure 3

Relationship between dietary concentration of a nutrient and its consumption. Actual consumption of nutrients can differ greatly from predictions based solely on dietary composition. As (A) caloric and (B) carbohydrate content of the diet increases, actual consumption of calories and carbohydrate, respectively, does not concurrently increase. (C) Protein content of the diet shows a positive trend with actual protein intake, although the correlation is statistically insignificant. Two-tailed p-values for the Pearson correlation coefficient are shown along with a linear trendline. All data are for Canton-S males.

Figure 4

Regulation of feeding rate by dietary nutrient concentration. (A) Food intake over 24 hours on radiolabeled medium (average ± s.d.). Consumption is reduced with increasing levels of sucrose and yeast extract (S and Y, respectively, all shown as w/v), except at the highest concentration of sucrose (20%), where the effect of yeast is muted. All pairwise comparisons are significantly different (p < 0.001, one-way ANOVA followed by Tukey post-hoc test) except between the three diets with 20% sucrose (p > 0.05). (B) Relationship between food intake volume and macronutrient content of the diet. The size and darkness of the circles are scaled with increasing food intake. In general, increasing the concentration of dietary protein or carbohydrate reduces intake. However, conditions can be found where a change in the concentration of a single nutrient does not trigger compensatory feeding. (C) Consumption shows a strong negative correlation with caloric value of the diet, best described by a power model, suggesting an inverse relationship between the two parameters (y = m/x^b; m = 0.40, b = 1.39). The power fit and R² value are shown. When b = 1, the product of food intake and dietary caloric content is a constant, m, which describes a daily caloric intake target. When b > 1, over-feeding occurs as the caloric value of the diet decreases. The non-linear relationship between food intake and dietary caloric content was also tested using Spearman’s correlation coefficient and confirmed a strong negative correlation (r = −0.90, p = 0.005). All results are for Canton-S males.