Although previous studies showing that fructose is capable of inducing damage to maternal DNA and that exercise has antioxidant capacity, little is known about the precise mechanisms of fetal programming. A good strategy to investigate and integrate information from different metabolic pathways, interventions, exposures and molecular pathways is the use of Systems Biology. This branch of bioinformatics has collaborated in solving complex biological problems, recognizing and understanding systems, elucidating, modeling and predicting the behavior of all components and interactions (gene, proteins and metabolites) in relation to external stimuli. Thus, a network represents a combination of nodes and connectors that connect the nodes. Thus, biological characteristics arise from a series of complex interactions that occur between the numerous molecules found in a cell. Thus, the objective of this study was to investigate, through an in silico test, with the tools of Systems Biology, the influence of fructose consumption and physical exercise in pregnant females on the fetal programming of the offspring. In the systems analysis, analyzes were used for network construction with gene expression data, construction of the basic interaction network, topological analysis, gene ontology analysis and centrality analysis. The FRUCTOSE chemical-protein interaction network, contain 7467 nodes and 64291 edges, where we can find all the clusters and the chemical-protein interaction network of FRUCTOSE+EXERCISE, contain 7697 nodes and 85942 edges, where we can find all clusters. Based on the network-based results obtained, we generated new hypotheses, represented in molecular models, regarding the potential influence of maternal fructose consumption and voluntary physical exercise on the offspring’s brain. These models suggest that biological processes such as post-translational modification, proteolysis, DNA damage repair, and oxidative stress response may participate in the integration of responses associated with fructose exposure and exercise. Among the proteins identified through network topology and centrality analyses, HDAC3 (histone deacetylase 3), MAT2B (methionine adenosyltransferase 2 beta), EP300 (histone acetyltransferase p300), and NEDD8 (neural precursor cell expressed developmentally downregulated 8) emerged as potentially relevant nodes. Importantly, these associations are derived from in silico interaction models and should be interpreted as hypothesis-generating rather than as experimentally validated mechanistic evidence.
Magenis et al. (Sun,) studied this question.