Matching Dietary Amino Acid Balance to the In Silico-Translated Exome Optimizes Growth and Reproduction without Cost to Lifespan

Abstract

SummaryBalancing the quantity and quality of dietary protein relative to other nutrients is a key determinant of evolutionary fitness. A theoretical framework for defining a balanced diet would both reduce the enormous workload to optimize diets empirically and represent a breakthrough toward tailoring diets to the needs of consumers. Here, we report a simple and powerful in silico technique that uses the genome information of an organism to define its dietary amino acid requirements. We show for the fruit fly Drosophila melanogaster that such “exome-matched” diets are more satiating, enhance growth, and increase reproduction relative to non-matched diets. Thus, early life fitness traits can be enhanced at low levels of dietary amino acids that do not impose a cost to lifespan. Exome matching also enhanced mouse growth, indicating that it can be applied to other organisms whose genome sequence is known.

Sexual dimorphism in the nutritional requirement for adult lifespan in Drosophila melanogaster

“…Together, this pattern is consistent with a model in which the flies continuously invest amino acids to maintain the soma at maximal health, channeling only surplus amino acids into reproduction. However, very high levels of amino acids shorten lifespan, not because of an insufficiency for somatic maintenance, but because of some damaging effect of long‐term exposure to high amounts (Fanson, Fanson, & Taylor, ; Piper et al, ). Males exhibited an approximately fivefold to 10‐fold lower minimal requirement for dietary amino acids for maximal lifespan (2.5 mM N) than did females (10–30 mM N) indicating an extremely low protein requirement to support male life.…”

“…This is consistent with an argument that the higher costs of reproduction in fertile females over that in males and nonreproducing females deprive somatic maintenance of resources, and this results in shortened lifespan (Kirkwood, ). But our previous work has shown that rebalancing the proportion of dietary amino acids can provide a single nutritional optimum for maximal lifespan and maximal reproduction (Piper et al, ), indicating that rather than lifespan being governed by an obligate trade‐off with reproduction, there is some other reason for why chronic exposure to high levels of food shortens lifespans. More recent work to alter DB, instead of simply restricting all nutrients as in DR, indicates that this is caused by chronic ingestion of high protein, low carbohydrate diets (Lee et al, ; Mair et al, ; Skorupa et al, ; Solonbiet et al, )—an effect that has been summarized in the lethal protein hypothesis (Fanson et al, ; Raubenheimer & Simpson, ; Sanz, Caro, & Barja, ; Simpson & David, ; Victoria et al, ).…”

Improving natural product research translation: From source to clinical trial

“…Clinical and preclinical interventions should be as similar or, where more appropriate, as equivalent as is feasible, bearing in mind species differences, 185 as well as any age-, sex-, size-, or health status-related differences which may affect behavior, absorption, metabolism, and/or toxicity. In the context of NP-diet interactions, it is critical to consider species-specific dietary requirements and optimal diets (eg, differences in ascorbic acid requirements, 187 optimal amino acid or lipid compositions), 185 as well as species differences in biosynthetic abilities 188 and digestive anatomies. 151,184,186 Background diet, as well as other environmental exposures, including medications, alcohol, smoking, and air quality may also have important effects on NP bioavailability, metabolism, and biological effects in both humans and animal models.…”

Feeding the Genome: In Silico Optimization of Dietary Amino Acid Composition

“…In this issue, Piper et al (2017) present an in silico method of essential amino acid optimization based on the translated portion of an organism’s genome, or exome. …”

“…In this issue of Cell Metabolism , Piper et al used an in silico approach to optimize dietary AAs based on their hypothesis that optimal AA requirements are encoded in an organism’s genome (Piper et al., 2017). To test this, they translated the nearly 20,000 predicted protein coding genes from Drosophila melanogaster and Mus musculus genomes into AA sequences and derived a relative proportion for each AA based on its prevalence in the entire translated portion, or “exome.” They used these proportions to design an artificial “exome-matched” protein source, which differed markedly in AA composition from natural or laboratory protein sources.…”