Combining deep sequenching omics approaches to translate an altered microbial composition towards health benefits
In multiple diseases the onset of disease is potentially linked to the microbiota composition. However, only knowing the infants microbial composition is not powerful enough to understand the role that microbiota plays in establishing certain health benefits and how this relationship can be influenced by nutritional interventions. Therefore, in this project an integrated approach is used to predict whether an infant received a specific nutritional intervention based on fecal parameters like microbiota, metabolites and clinical parameters. This knowledge will be used to improve and substantiate new infant formulas. Furthermore, it improves the modeling work combining deep sequencing with complex mathematical modelling that helps to understand biology of the gut in early life.
The goal of the project is to improve our understanding of the connection between nutrition, health and gut physiology as a whole. Instead of looking at microbiota or metabolites or clinical parameters individually, the chosen integrated approach to use deep sequencing and artificial intelligence will give us new insights in the relationship between nutrition and gut health in early life.
This project is needed within the Agri&Food Gezond en Veilig since it will add to the understanding of the importance of nutrition in early life on a healthy gut. In early life the gut still has to mature and the choice for the type of nutrition is thought to be very important for this maturation. This project helps to understand the effect of nutrition on the physiological processes in the gut. This will lead to improved nutritional formulations and ingredients to support a healthy start in life.
In 2018 FrieslandCampina (FC) conducted a study in which the impact of a specific infant formula containing milk fat on gut comfort was studied. Microbiota analysis through deep sequencing technique of Erasmus MC (EMC) was conducted and modeling was performed by HorAIzon Technologies B.V. (HT). This proof of principle study showed that technically the approach was feasible, yet the power was too low to obtain significant results. Therefore, an additional intervention study was performed as part of this TKI project in 2019. The execution of this study (writing protocol, performing the intervention study, sample collection) were all finished that year.
Conducted Activities 2020:
Q1 2020 fecal samples of the second intervention trial were processed. FC extracted DNA from the fecal samples of the trial. Metabolites and fatty acid soaps in feces were analyzed, reported and used for modeling part (see Q4).
Q2 2020 EMC sequenced the samples using deep sequencing.
Q3 2020 HT processed, cleaned and extracted data through their metagenomics pipeline.
Q4 2020 The modeling was conducted by HT and presented by the TKI consortium to the FC stakeholders.
The modeling approach by HT showed that a highly significant prediction can be made based on a specific subset of the >400 measured parameters (clinical, microbiota, metabolites) to determine who of the infants was receiving which nutritional intervention. New associations were obtained between nutrition and gut health parameters in early life.