Purpose: This review examines the bidirectional interactions between gut microbiota and the brain, with a specific focus on their implications for sport performance. The main research question addresses how gut-brain communication responds to physical activity and actively contributes to athletic performance in elite athletes subjected to high physiological demands. Methods: A comprehensive review was conducted analysing the characteristics and development of gut microbiota, the methods used to investigate microbiota-brain interactions and the bidirectional communication pathways. The analysis distinguished the two directions of interaction brain-induced effects on microbiota and microbiota-induced effects on brain activity, with specific integration into sports contexts. Results: The review identified that gut-brain communication constitutes a dynamic system that responds to physical activity through multiple pathways. Elite athletes, subjected to high-intensity training regimens, specialized nutritional approaches and specific performance goals, exhibit distinctive microbiota conditions. Brain-derived neurotrophic factor (BDNF), serotonin and butyrate emerged as key mediators that contribute to adaptive gut microbiota conditions and facilitate microbiota-brain interactions. Conclusion: The microbiota-gut-brain axis represents a fundamental system actively contributing to sport performance. The interdisciplinary evidence from neuroscientists, microbiologists, nutritionists and sports scientists demonstrates that understanding these interactions opens new frontiers for optimizing athletic performance through targeted modulation of this bidirectional communication system.

The growing interest in the role of the gut microbiome in athletic performance has led to the application of various sequencing technologies in this field. This review critically examines the sequencing methodologies used in microbiome studies on physical performance and sport, comparing their advantages, limitations, and applicability. In particular, the focus is on 16S metabarcoding and shotgun metagenomics, evaluating how these methodological approaches influence the interpretation of results in sports contexts. Close attention is directed toward technical challenges, methodological biases, and future perspectives, including emerging technologies and multi-omics approaches. This review aims to bridge the gap between methodological rigor and sports-specific applicability, providing evidence-based methodological guidance to support researchers in designing robust athlete microbiome studies and translating sequencing-derived findings into concrete applications for performance and sports health.

Background: The gut microbiota is an emerging factor in athletic performance. Methodological limitations persist in longitudinal microbiome studies, particularly regarding the compositional nature of microbiota data and the lack of standardized performance metrics in team sports. The present study applies a Compositional Data Analysis (CoDA) framework with ANOVA-Simultaneous Component Analysis (ASCA) to investigate longitudinal gut microbiota dynamics in elite volleyball athletes and introduces a novel Technical Performance Level (TPL) metric for objective performance quantification. Methods: Seven elite male volleyball athletes from the Italian SuperLega Championship were monitored across four sampling timepoints (T0, T1, T2, T3) during the Regular Season, Rest Period, and Tournament Period. Fecal samples underwent 16S rRNA metabarcoding. CLR-transformed data were analyzed at the Phylum, Family, and Genus level using ASCA with Season, Player, and their interaction. Statistical significance was assessed using the Freedman-Lane permutation test (10,000 iterations). Within-subject associations between TPL and CLR-transformed microbial features were assessed by repeated-measures correlation. Results: Season and Player effects were statistically significant at all taxonomic levels (p ≤ 0.0004), whereas the Season × Player interaction was significant at the Family and Genus levels (p ≤ 0.002) but not at the Phylum level (p = 0.108). The Player effect represented the largest source of variance at the Family (51.31%) and Genus (50.75%) levels. At the Phylum level, the Season × Player interaction accounted for the largest share of variance (36.23%), although it did not reach significance. Within-subject correlation analyses revealed no statistically significant association between microbial features and TPL at any taxonomic level, and none remained significant after correction for multiple comparisons. Conclusions: The application of a compositional data analysis framework modifies the interpretation of gut microbiota dynamics in elite volleyball athletes compared to standard approaches. Individual athlete identity accounted for most of the compositional variance in the microbiota, whereas exploratory within-subject analyses did not reveal statistically significant associations between taxa and TPL. Given the small cohort, any observed trends should be interpreted as exploratory and hypothesis-generating until confirmed in adequately powered cohorts. Longitudinal monitoring of gut microbiota could support individualized surveillance of gut health in elite sport.