Nutrigonometry I: using right-angle triangles to quantify nutritional trade-offs in performance landscapes

Nutritional optima for life-history traits vary with temperature and across locally-adapted populations

As the climate changes, populations must overcome more frequent and more extreme exposure to a wide range of stressors. However, our knowledge of how locally-adapted populations respond to combinations of stressors remains incomplete. Recent studies show that elevated temperatures can interact with nutrition to accentuate the negative effects of a poor diet, suggesting higher costs of nutritional stress when individuals experience temperatures outside of their locally-adapted conditions. This can translate into reduced nutrient optima under thermal stress in life-history trait landscapes, a hypothesis that remains to be tested. Here, we used the Geometric Framework for Nutrition to test this hypothesis using two locally-adapted populations of Drosophila melanogaster from opposing ends of a well-characterised adaptive gradient along the east coast of Australia (tropical vs. temperate). We found that the negative effects of nutritional stress were significantly greater in the tropical population under warmer temperatures. In contrast, the temperate population was able to utilise a broader nutritional space to maintain high viability and a large wing size across the range of fluctuating temperatures. Our findings reveal the ways in which local adaptation impacts how populations navigate and explore the nutritional space in response to increasingly stressful thermal conditions. These data suggest that certain populations may be better able to cope with increasingly stressful and variable environments, while others may be more vulnerable to local extinctions.

Nutritional Trade-Offs in Drosophila melanogaster

Animals often regulate their nutrient intake according to their physiological needs. There is evidence that different traits require specific nutrient blends, and that animals cannot always maximize all traits with a single diet ("nutritional trade-offs"). However, we still do not have a clear understanding of which traits might be involved in nutritional trade-offs. I compiled data from the Geometric Framework of Nutrition literature on the ratio of proteins and carbohydrates that maximize (best PC ratios) or minimize (worst PC ratios) several larval and adult traits in Drosophila melanogaster. Best and worst PC ratios clustered into three regions in the protein-carbohydrate nutrient space: (1) Low PC ratios (1:8 or higher) are best for lifespan but worst for growth or reproductive traits; (2) High PC ratios (1:1 or lower) are best for adult body mass, male reproduction, and larval developmental time but worst for lifespan; and (3) Intermediate PC ratios (<1:1 and >1:8) are best for female lifetime egg production, female reproductive rate, and larval survival. These findings support lifespan-reproduction nutritional trade-offs, highlight the potential for metamorphosis to solve nutritional trade-offs across life stages, and underscore the potential for intralocus sexual conflict to emerge over the expression of metabolic genes.

Optimum ratio of dietary protein and carbohydrate that maximises lifespan is shared among related insect species

Animals often regulate the intake and quantity of nutrients to maximise fitness through life-history traits such as lifespan, but we still lack a proper understanding of how specific nutrients influence these traits. Here, I developed an algorithm which allowed me to create a nutrient-specific database from literature data, and investigated how the requirements of protein (P) and carbohydrate (C) needed to maximise lifespan evolved across nine insect species. I found moderate evidence of a phylogenetic signal on the optimal ratio of protein to carbohydrate ratio (PC ratio) that maximised lifespan, suggesting that optimal PC ratio for lifespan could have evolved non-independently among related species. I also found evidence for weak-to-strong sex-specific optimal PC ratios for lifespan, suggesting that sex-specific nutritional needs to maximise lifespan can emerge and persist in some species. Although limited in the number of species, the approach adopted here is portable to experiments withn number of nutrients and, thus, can be used in complex comparative precision nutrition studies for insights into the evolution of animal nutrition.

Mapping the nutritional landscape in the yellow mealworm: testing the nutrient-mediated life-history trade-offs

Animals must acquire an ideal amount and balance of macronutrients to optimize their performance, health and fitness. The nutritional landscape provides an integrative framework for analysing how animal phenotypes are associated with multiple nutritional components. Here, we applied this powerful approach to examine how the intake of protein and carbohydrate affects nutrient acquisition and performance in the yellow mealworm (Tenebrio molitor) reared on one of 42 synthetic foods varying in protein and carbohydrate content. Tenebrio molitor larvae increased their food consumption rate in response to nutrient dilution, but this increase was not sufficient to fully compensate for the dilution. Diluting the food nutrient content with cellulose reduced the efficiency of post-ingestive nutrient utilization, further restricting macronutrient acquisition. Tenebrio molitor larvae utilized macronutrients most efficiently at a protein to carbohydrate (P:C) ratio of 1.77:1, but became less efficient at imbalanced P:C ratios. Survivorship was high at high protein intake and fell with decreasing protein intake. Pupal mass and growth rate exhibited a bell-shaped landscape, with the nutritional optima being located around protein-biased P:C ratios of 1.99:1 to 2.03:1 and 1.66:1 to 2.86:1, respectively. The nutritional optimum for development time was also identified at high P:C ratios (1.66:1  to 5.86:1). Unlike these performance traits, lipid content was maximized at carbohydrate-biased P:C ratios of 1:3.88 to 1:3.06. When given a food choice, T. molitor larvae self-composed a slightly carbohydrate-biased P:C ratio of 1:1.24, which lies between the P:C ratios that maximize performance and lipid content. Our findings indicate the occurrence of a nutrient-mediated trade-off between performance and energy storage in this insect.

Nutrigonometry I: using right-angle triangles to quantify nutritional trade-offs in performance landscapes

AbstractAnimals regulate their food intake to maximize the expression of fitness traits but are forced to trade off the optimal expression of some fitness traits because of differences in the nutrient requirements of each trait ("nutritional trade-offs"). Nutritional trade-offs have been experimentally uncovered using the geometric framework for nutrition (GF). However, current analytical methods to measure such responses rely on either visual inspection or complex models of vector calculations applied to multidimensional performance landscapes, making these approaches subjective or conceptually difficult, computationally expensive, and, in some cases, inaccurate. Here, we present a simple trigonometric model to measure nutritional trade-offs in multidimensional landscapes (nutrigonometry) that relies on the trigonometric relationships of right-angle triangles and thus is both conceptually and computationally easier to understand and use than previous quantitative approaches. We applied nutrigonometry to a landmark GF data set for comparison of several standard statistical models to assess model performance in finding regions in the performance landscapes. This revealed that polynomial (Bayesian) regressions can be used for precise and accurate predictions of peaks and valleys in performance landscapes, irrespective of the underlying structure of the data (i.e., individual food intakes vs. fixed diet ratios). We then identified the known nutritional trade-off between life span and reproductive rate in terms of both nutrient balance and concentration for validation of the model. This showed that nutrigonometry enables a fast, reliable, and reproducible quantification of nutritional trade-offs in multidimensional performance landscapes, thereby broadening the potential for future developments in comparative research on the evolution of animal nutrition.