Personalized Nutrition

The principles of a healthy diet – increasingly recognized as a promoter of physical and mental health – are nowadays based on population-wide patterns. By following one-size-fits-most recipes to meet the diet requirements of ‘average’ humans, these principles tend to overlook a key element at the core of the diet/health nexus: the personal traits of each individual. Every person hosts a unique, highly dynamic, and enzymatically rich microbiome community in their gut, which converts thousands of nutrients into bioavailable and bioactive compounds.

Aware of the multitude of responses to the same dietary recipe, research is needed to pave the way that will lead humanity to a new era of nutrition, settled on personalized diet guidance informed at the small dietary molecule and microbiome levels. To allow this paradigm shift we need a deep understanding of the complex mechanistic links between food molecules, gut microbiome, and health outcomes.


At the Department of Microbiome Dynamics, we try to build the research foundations and proofs-of-concept to realize our vision for truly personalized human nutrition.

We exploit the molecular interactions between nutrients and microbiome to achieve scientific breakthroughs at two distinct, yet complementary, levels, namely:

(i) Mapping the human gut microbiota-diet interactome, providing mechanistic links between food’s small molecules, microbial enzymes, main taxonomic drivers, and biomarker-based health status

(ii) Building the scientific basis for the development of a new generation of highly nutritional foods, prebiotics, probiotics, and postbiotics, based on a deep understanding of microbial metabolism of food compounds


Yueqiong (Bernard) Ni
Lu Zhang


Ni Y, Jensen K, Kouskoumvekaki I**, Panagiotou G** (2017) NutriChem 2.0: exploring the effect of plant-based foods on human health and drug efficacy. Database (2017),
Zheng T, Ni Y, Li J, Chow BKC, Panagiotou G** (2017) Designing Dietary Recommendations Using System Level Interactomics Analysis and Network-Based Inference. Front Physiol 8, 753.