Navigating the translational labyrinth of the gut microbiota

Abstract

Modern gut microbiota research, enabled by high-throughput sequencing, has established gastrointestinal microbial communities as integral components of host biology across the animals and humans. Animal studies established their roles in polysaccharide fermentation, nutrient utilization, and host physiology, while human investigations linked microbiota variation to metabolic and inflammatory conditions. The Gut Microbiota Collection (https://www.nature.com/collections/jhdjahhcea) brings together studies across host species, populations, and systems to offer more insights in how diet, geography, and host physiology shape microbiota composition and function.

Modern gut microbiota research emerged with the advancement of high-throughput sequencing and post-genomic biology. From the mid-2000s onward, landmark studies characterized dense, structured gastrointestinal microbial communities across animals, revealed their metabolic functions independent from host genomes, including polysaccharide degradation, vitamin biosynthesis, and metabolite production that regulates immune signaling and epithelial homeostasis^1–4. This Editorial highlights the metabolic and functional diversity of gut microbiota across different host species, and discusses the translational gaps between animal and human studies from gut microbiota perspectives. It also touches on how environmental influences interact with hosts and/or gut microbiota, adding further complexity to our understanding of microbiota–host relationships.

Animal studies have been central in establishing the functional and translational relevance of gut microbiota. In herbivores and omnivores, microbial fermentation enables energy extraction from plant polysaccharides inaccessible to host enzymes, expanding metabolic capacity. In livestock and aquaculture, microbiota composition influences feed efficiency, growth performance, and disease susceptibility, demonstrating measurable physiological and economic consequences of host–microbiome interactions⁵. Animals adapted to chemically complex or toxin-rich diets harbor microbial consortia enriched in carbohydrate-active enzymes, xenobiotic metabolism pathways, and detoxification systems, enabling utilization of otherwise inaccessible substrates^2,6. These findings position animal gut microbiotas, including those of humans⁷, as reservoirs of metabolic diversity with relevance for nutrition, biotechnology, and therapeutic discovery.

Human microbiota research built on these foundations. Early studies revealed substantial inter-individual variability and identified associations between gut microbiota composition and metabolic, immune, and neurological diseases, generating expectations that microbiota manipulation could yield therapeutic benefit. However, clinical translation has been limited^8,9. Interventions such as probiotics, prebiotics, and fecal microbiota transplantation often produce disappointing or nuanced results in human trials despite pronounced physiological effects in controlled experimental systems^8,9.

The sources of this translational gap are becoming clearer. Gut microbiota composition is strongly influenced by host physiological and environmental variables that confound disease associations. Large cohort analyses showed that bowel movement frequency, diet, and medication use explain substantial microbiome variation previously attributed to disease status¹⁰. Direct physiological measurements further demonstrated that intestinal transit time and luminal conditions are major determinants of microbial composition and metabolic output, with intestinal transit alone accounting for consistent inter-individual differences independent of disease¹¹. In chronic kidney disease (CKD), quantitative microbiome profiling revealed that microbiota composition and functional potential correlated primarily with transit time, diet, and medication exposure, while associations with kidney function were markedly attenuated after adjustment¹². Importantly, interpretation has been constrained by reliance on relative abundance data, which do not account for variation in total microbial load^13–15. Quantitative microbiome profiling incorporating absolute abundance has revised several reported disease associations¹⁶. Apparent enrichment of oral bacteria in fecal samples across multiple diseases reflects depletion of resident gut microbiota rather than true expansion of oral taxa, supporting a marker-of-depletion interpretation¹⁷. Likewise, the proposed role of Fusobacterium nucleatum in colorectal cancer has been reassessed when absolute abundance distinguishes true proliferation from compositional shifts¹⁸. Animal models have been essential for demonstrating causal microbiota–host interactions, including germ-free mouse studies showing microbiota-dependent effects on metabolism and obesity-related phenotypes¹⁹. However, physiological differences between mice and humans, including but not limited to gut structure and microbial carrying capacity, limit direct translation. Even in human microbiota-associated mouse models, microbial community behavior is constrained by the mouse host environment, reducing their ability to replicate human microbial ecology²⁰. Quantitative analysis further illustrates these limitations: microbiota-derived fermentation products contribute a substantially larger proportion of host energy balance in mice than in humans²¹, suggesting that equivalent microbiota perturbations may produce stronger physiological effects in mice.

While the breakthroughs mentioned above recalibrate the evidentiary standards and expectations for translational gut microbiota research, confirmatory studies remain essential to distinguish reproducible microbiota–host associations from context-dependent effects. This Collection supports that objective by presenting data across diverse human populations, host species, and experimental systems, reinforcing the empirical basis for microbiota research with translational relevance. Udomkarnjananun et al. analyzed 135 non-dialysis CKD patients and 19 controls, combining 3-day dietary records with fecal 16S rRNA profiling and plasma measurements of trimethylamine-N-oxide (TMAO) and cytokines²². CKD was associated with reduced short-chain fatty acid-producing taxa and elevated TMAO and inflammatory markers. Within the CKD cohort, a low-protein, high-fiber diet was linked to greater abundance of saccharolytic taxa such as Lachnospiraceae NK4A136 group and Eubacterium ruminantium group, whereas a high-protein, low-fiber pattern was enriched in proteolytic genera including Klebsiella and showed higher TMAO, IL-18, and MCP-1. Although based on relative abundance data, these findings are to some extent consistent with the quantitative microbiome profiling-based study indicating that diet- and/or transit-associated shifts from saccharolytic to proteolytic metabolism are key drivers of microbiota variation in CKD¹². Jamaluddin et al. analyzed gut microbiota profiles from adults in three Malaysian communities—urban Kuala Lumpur and the rural regions of Gua Musang and Tasik Banding—representing an understudied Global South population²³. Rural participants exhibited higher phylogenetic diversity, although Shannon diversity was comparable across groups, indicating similar evenness but greater lineage breadth in rural microbiotas. Community structure differed markedly by urban versus rural status, with locality explaining the largest proportion of variation, while age, stool consistency, and BMI contributed more modestly. Rural microbiotas were enriched in Prevotella, whereas urban samples showed higher relative abundance of genera such as Phocaeicola, Vescimonas, and Megasphaera. Functional predictions suggested that these compositional differences may reflect local dietary practices and cultural habits, including the carbohydrate-rich and urbanized dietary patterns characteristic of Kuala Lumpur. These findings underscore that microbiota-targeted interventions may need to be evaluated within their geographic and dietary context. In the case of probiotics, colonization and functional effects depend on compatibility between the administered strain, the resident microbiota, and host conditions²⁴. Probiotic selection and outcome measures should therefore be grounded in local microbiome baselines and tested in the populations where they are intended to be applied²⁴. Sharma et al. evaluated whether early-life administration of a defined poultry-derived Lactobacillus consortium (delivered in ovo and/or post-hatch) alters gut microbiota development and immune gene expression in broiler chickens²⁵. A single in ovo dose increased cecal Lactobacillus and reduced Enterococcus and Klebsiella during the first week after hatching, accompanied by lower expression of pro-inflammatory cytokines (IFN-γ, IL-1β, IL-8) in cecal tonsils. These differences were not sustained once the microbiota stabilized by weeks 4–5²⁵. The study shows that early microbial exposure can modify initial colonization dynamics and immune transcriptional responses, but lasting effects require sustained ecological persistence within the host gut.

As with early genomics, early hopes that microbiome discoveries would quickly lead to new therapies have given way to a more realistic view: most microbiota–host relationships are shaped by host physiology, environmental exposures, and ecological constraints, rather than single causal organisms. The long-term progress of the field depends on clarifying causal inference by defining which microbiota effects are consistent, which are context-dependent, and which simply reflect underlying host states. The studies assembled in this Collection contribute to that cumulative effort by providing evidence across populations and species, helping refine how we interpret microbiota variation and its physiological and/or environmental relevance.

Declarations

Competing interests

The author declares no competing interests.