Food as Biological Information: A Testable Dietome Framework for Precision Nutrition and Whole-Food Meal Design

Nutrition science has established the importance of energy, essential nutrients, dietary patterns, and food matrices, yet researchers often study these dimensions separately from the biological systems that transform and interpret a meal. This Perspective proposed the Dietome as a testable, systems-level description of food-derived inputs and the Informational Nutrition Framework (INF), comprising encoding, transmission, decoding, execution, and biological memory. The framework integrates sensory perception and eating behaviour with digestion, microbial metabolism, host signalling, and context-dependent responses. Its novelty is not the claim that food contains a literal code, but the proposal to connect food composition and structure to measurable, falsifiable predictions about meal-level responses. Evidence from personalized postprandial prediction, foodome network analysis, microbial short-chain fatty acid (SCFA)-associated chromatin regulation, and computational diet modelling illustrates both opportunity and limitations. A worked meal example shows how to evaluate minimally processed foods and their combinations before considering engineered formulations. The Perspective also identifies sustainability, developmental nutrition, and food-allergy prevention as domains requiring cautious, evidence-specific application. Dietary microRNAs and long-term nutritional memory remain less established than conventional nutrient and microbial-metabolite pathways. The framework should therefore be judged by prospective validation, causal evidence, clinical utility, cultural acceptability, and environmental performance, not by terminology alone.