Food-microbe pairings may unlock personalized nutrition, experts reveal

Research has found that certain foods and diets shape the gut microbiome and might inspire future personalized nutrition interventions. The study examined 10,068 individuals from the Human Phenotype Project, dubbed “the world’s deepest phenotype multi-omic study.” 

The researchers note that the ways specific foods and dietary patterns shape microbial composition, diversity, and function are not fully understood. In the study, they were able to unveil some of these mysteries by looking at distinct food-microbe links, such as coffee with Lawsonibacter asaccharolyticus, yogurt with Streptococcus thermophilus, and milk with Bifidobacterium species.

Paper co-author Tomer Segev from the Department of Molecular Cell Biology at the Weizmann Institute of Science, Israel, tells Nutrition Insight about long-term impacts of these food-microbe links and how they could power personalized dietary recommendations, alongside the surprising role of food processing.

Promising outlook

The Nature Medicine paper shows that diet predicts 92% of gut species (669 of 724 species tested) and 98%, or 313 of 320, of microbial pathways.

On how near we are to turning these food-microbe links into personalized dietary recommendations, Segev states, “We’re getting closer.”

“Our findings hold up not just in our 10,068-person Israeli cohort, but also in an independent Australian population and an Israeli dietary intervention trial, so we’re confident these associations are generalizable.”

“We also built a simulation model that suggests personalized food changes and predicts how the microbiome and cardiometabolic health might respond,” he adds. “That’s a good step, but the simulation is based on observed associations, not controlled experiments. We haven’t proven causality yet, and that requires randomized dietary intervention trials as the next step.”

Moreover, Segev details that when the paper shows that diet predicts 92% of gut species and 98% of pathways, these models also include age, sex, body mass index (BMI) and comorbidities.

“That said, diet is doing most of the work — the improvement in predictive power when you add dietary data on top of those covariates is large and consistent.”

Food processing and microbial diversity

In the study, broader dietary patterns, especially food processing, emerged as a major driver of microbial diversity alongside foods like coffee, yogurt, and milk. Segev says two things stood out to him personally.

“First, food processing turned out to be a stronger driver of microbial diversity than the classic plant-versus-animal divide. The Alternative Healthy Eating Index, which rewards minimally processed, nutrient-rich foods, was the strongest positive predictor of diversity, as expected.”

“But an animal-based diet score also positively predicted diversity at a comparable level, despite having no plant fiber. The likely reason: people with high animal-based scores in our cohort were eating more whole, unprocessed animal foods and dairy and fewer ultra-processed foods (UPFs),” Segev suggests.

He adds that the takeaway of these findings points to the need to avoid UPFs. It matters just as much or even more for gut diversity as which food groups individuals eat.

UPFs lower diversity more than meat versus plants, says Segev, suggesting targeted tweaks for microbiome health.“Second, banana and nut consumption strongly predict the abundance of specific species that are not well characterized. Unlike the relationship between coffee and L. asaccharolyticus, which has more research around it, the relationship between bananas or nuts and their corresponding microbial species is a strong, specific link that is not well established,” notes Segev.

Long-term relationships

The study found that the food-microbe links were steady over four years for 82.5% of microbial species, showing significant longitudinal tracking between predicted and observed abundances.

“The 82.5% figure doesn’t mean your microbiome composition is frozen. It means the relationship between what you eat and which microbes you have is consistent across time points: diet predicts your microbiome composition in the same reliable way at baseline, two years, and four years later,” explains Segev.

On whether this means the microbiome “locks in” based on long-term eating patterns, he says that the picture is actually more optimistic.

“A stable diet-microbiome relationship means that changing your diet should reliably shift your microbiome, too. Our longitudinal data support this: the species best predicted by diet at baseline tend to be the ones that track dietary changes over time. The microbiome stays responsive.”

Small changes bring benefits

Based on their findings, the researchers built a simulator for personalized dietary interventions linked to cardiometabolic outcomes. Segev cautions that the simulation is exploratory and needs experimental validation, yet some consistent patterns were observed across individuals.

“The model frequently recommends reducing ultra-processed staples like white bread and processed meat and increasing fruits, nuts, and avocado. This aligns well with existing cardiometabolic dietary guidelines, which is reassuring.”

“On the microbial side, species like Akkermansia muciniphila and Faecalibacterium prausnitzii are among those most often predicted to change — all with independent evidence linking them to metabolic health,” he shares.

Segev finds it encouraging that the predicted improvements typically came from just one or two food changes per person.

“You don’t need a complete dietary overhaul — small, targeted adjustments may be enough to meaningfully shift the microbiome toward a healthier profile,” he concludes.