In a recent systematic review published in the journal Gut Microbes, researchers synthesized evidence from systematic reviews and primary studies to explore the relationship between diet and gut microbiota. They found that diet patterns, micro- and macronutrients, bioactive compounds, and food additives influence gut microbiota. However, the associations were found to be dominated by routinely analyzed nutrients rather than microbiota-relevant nutrients.
Review: Diet-microbiota associations in gastrointestinal research: a systematic review. Image Credit: CI Photos / Shutterstock
Background
The role of gut microbiota in health is increasingly being recognized and is reported to be influenced by dietary intake. However, the current assessment methods overlook microbiota-specific metabolism, thereby hindering our understanding. Advances in gene sequencing reveal microbiota-host metabolic interactions, but sample collection and study design continue to be challenging, limiting data consolidation. Improvements in dietary assessment methods are essential for precise microbiota-focused interventions for health optimization. Therefore, researchers in this systematic review aimed to identify foods and components affecting the human gut microbiota composition, highlighting the current gaps in the field.
About the study
The review systematically searched PubMed for systematic reviews on diet and gut microbiome associations in healthy individuals and those with gastrointestinal (GI) conditions. Primary studies (n = 106) were distinguished from systematic reviews (n = 38) and reference lists of narrative reviews. Data, including the study design, dietary assessment, and analysis methods, were extracted.
Results and discussion
“Healthy,” “plant-based,” and Mediterranean diets were associated with higher Bacteroidetes and Firmicutes, while Western diets showed lower microbiota levels. Vegan/vegetarian diets correlated with increased Prevotella and decreased Clostridium. Total energy intake variations were linked to Bacteroidetes and Firmicutes abundance changes and increased microbial diversity. However, dietary pattern classification methods varied, impacting the results.
Fiber-rich diets were generally associated with increased microbial diversity and beneficial bacteria like Bifidobacterium and Lactobacillus. Resistant starch intake influenced bacterial proliferation, with notable effects on Eubacteria and Ruminococcus. Prebiotic fibers also showed positive associations with microbial diversity and abundance, while the low FODMAP (short for fermentable oligosaccharides, disaccharides, monosaccharides, and polyols) diet impacted microbiota composition in individuals with irritable bowel syndrome.
Higher protein intake was associated with less beneficial bacterial profiles, while studies on dietary gluten intake showed inconsistent findings. Limited research explored the impact of individual amino acids on microbiota, with some studies reporting specific associations such as reduced Firmicutes:Bacteroidetes ratio following L-glutamine supplementation.
Higher total fat and saturated fatty acid intake was consistently associated with reduced microbiota richness and diversity, along with unfavorable microbial profiles. Studies showed mixed effects of unsaturated fats on microbiota, with generally less detrimental influences compared to saturated fats.
Vitamin B6 was found to be essential for certain microbial enzymatic activities, while vitamin B12 intake was associated with microbiome diversity and short-chain fatty acid (SCFA) production. Calcium and phosphorus administration increased Clostridium spp. and fecal SCFAs. Gut microbes were also involved in synthesizing vitamins like B12, B6, and folate, with Bifidobacterium using resistant starch to produce folate.
Polyphenols, including those found in foods like tea and fruits, were associated with increased beneficial bacteria like Bifidobacteria and Lactobacillus and bacteria that produce butyrate, improving gut integrity. Polyphenols also inhibited the growth of pathogenic bacteria like Clostridia and Salmonella. Additionally, natural food chemicals implicated in food intolerances, such as salicylates and amines, were found to have associations with gut microbiota and microbial metabolites, suggesting a potential role in GI disorders.
Emulsifiers like carboxymethylcellulose and polysorbate-80 induced dysbiosis, while maltodextrin altered microbiota Firmicutes, Bacteroidetes, Lactobacillus, and Bifidobacterium. Other additives like monosodium glutamate and carrageenan had variable effects. Some, like dishwashing detergents and certain sweeteners, increase pathogenic bacteria while decreasing beneficial ones. Preservatives like nisin showed beneficial effects by inhibiting harmful bacteria. Overall, food additives exhibit diverse effects on gut microbiota, with some showing dysbiotic effects and others exerting beneficial influences.
Nuts were found to have a prebiotic effect, particularly walnut consumption, which increased Roseburia and Clostridium. Alcoholic drinks, like red wine, also influenced microbiota composition. Fermented foods, including dairy products like yogurt and buttermilk, were associated with increased bacterial diversity and beneficial microbes like Lactobacillus and Bifidobacterium. Overall, these foods have the potential to impact gut microbiota composition positively.
Further, dietary factors associated with microbiota were categorized based on their digestibility and assessability in standard food composition databases as (1) “degradable, assessable,” (2) “digestible, assessable,” (3) “degradable, individually assessable,” or (4) “degradable, not assessed or not assessable.”
Although the review comprehensively assesses the associations between diet and microbiota, inconsistencies in reporting microbial sequencing methods hinder the comparability between studies, thereby limiting data synthesis.
Conclusion
In conclusion, the review highlights the need to improve diet-microbiome research by expanding dietary assessment to include microbiota-relevant data and integrating it with nutritional metabolomics. Future studies should align dietary assessment with standardized microbiota sampling and analysis in well-characterized cohorts. Refining food composition databases with microbiome-relevant data, particularly from human studies, could enable microbiome-specific nutrition therapy.
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