The use of computational modeling and simulation has increased in many biological fields, but despite their potential these techniques are only marginally applied in nutritional sciences. Nevertheless, recent applications of modeling have been instrumental in answering important nutritional questions from the cellular up to the physiological levels. Capturing the complexity of today's important nutritional research questions poses a challenge for modeling to become truly integrative in the consideration and interpretation of experimental data at widely differing scales of space and time. In this review, we discuss a selection of available modeling approaches and applications relevant for nutrition. We then put these models into perspective by categorizing them according to their space and time domain. Through this categorization process, we identified a dearth of models that consider processes occurring between the microscopic and macroscopic scale. We propose a "middle-out" strategy to develop the required full-scale, multilevel computational models. Exhaustive and accurate phenotyping, the use of the virtual patient concept, and the development of biomarkers from "-omics" signatures are identified as key elements of a successful systems biology modeling approach in nutrition research--one that integrates physiological mechanisms and data at multiple space and time scales.

Very low-carbohydrate, high-fat ketogenic diets (KDs) induce a pronounced shift in metabolic fuel utilization that elevates circulating ketone bodies; however, the consequences of these compounds for host-microbiome interactions remain unknown. Here, we show that KDs alter the human and mouse gut microbiota in a manner distinct from high-fat diets (HFDs). Metagenomic and metabolomic analyses of stool samples from an 8-week inpatient study revealed marked shifts in gut microbial community structure and function during the KD. Gradient diet experiments in mice confirmed the unique impact of KDs relative to HFDs with a reproducible depletion of bifidobacteria. In vitro and in vivo experiments showed that ketone bodies selectively inhibited bifidobacterial growth. Finally, mono-colonizations and human microbiome transplantations into germ-free mice revealed that the KD-associated gut microbiota reduces the levels of intestinal pro-inflammatory Th17 cells. Together, these results highlight the importance of trans-kingdom chemical dialogs for mediating the host response to dietary interventions.