Unraveling the Gut Microbiome-Diet Connection: Exploring the Impact of Digital Precision and Personalized Nutrition on Microbiota Composition and Host Physiology

Abstract

The human gut microbiome, an intricate ecosystem housing trillions of microorganisms within the gastrointestinal tract, holds significant importance in human health and the development of diseases. Recent advances in technology have allowed for an in-depth exploration of the gut microbiome, shedding light on its composition and functions. Of particular interest is the role of diet in shaping the gut microbiome, influencing its diversity, population size, and metabolic functions. Precision nutrition, a personalized approach based on individual characteristics, has shown promise in directly impacting the composition of the gut microbiome. However, to fully understand the long-term effects of specific diets and food components on the gut microbiome and to identify the variations between individuals, longitudinal studies are crucial. Additionally, precise methods for collecting dietary data, alongside the application of machine learning techniques, hold immense potential in comprehending the gut microbiome's response to diet and providing tailored lifestyle recommendations. In this study, we investigated the complex mechanisms that govern the diverse impacts of nutrients and specific foods on the equilibrium and functioning of the individual gut microbiome of seven volunteers (four females and three males) with an average age of 40.9 ± 10.3 years, aiming at identifying potential therapeutic targets, thus making valuable contributions to the field of personalized nutrition. These findings have the potential to revolutionize the development of highly effective strategies that are tailored to individual requirements for the management and treatment of various diseases.

Keywords: dietary intervention; gut microbiome; longitudinal studies; nutrigenomics; personalized medicine; precision nutrition.

Figure 1

Data acquisition. Representation of the wearables, devices, and techniques used to extract the comprehensive data integrated into the personalized approach from the participants. An impedance scale allows evaluating anthropometric parameters; the smart band furnishes information regarding physiological parameters and physical activity data; the web app ArMOnIA ensures a detailed compilation of food diary; the collection of a stool sample is required for microbiome analysis.

Figure 2

Study timeline. Schematic representation of the study timeline. Purple rectangles show the microbiome sampling, the orange diamond represents the intervention, while in the blue circles, the starting point and the intermediate evaluation of the results are provided.

Figure 3

Beta diversity analysis between T1, T2, and T3. Beta diversity was investigated using Bray–Curtis distance and represented by principal coordinates analysis (PCoA). Statistical differences between the three groups (T1 and T2, as control groups, and T3 after diet) were assessed by Permutational Multivariate Analysis of Variance (PERMANOVA) test (p > 0.05). Different shapes represent different time points while varying colors are associated with the various studied samples.