Diet significantly impacts the gut microbiome, which plays a crucial role in overall health. Prebiotics, non-digestible food ingredients, promote the growth of beneficial gut bacteria and confer health benefits. While traditional prebiotic indices (PI) focused on specific bacterial groups, their limitations (e.g., outdated taxonomic classifications) necessitate a more comprehensive approach. The Gut Microbiome Wellness Index (GMWI) offers a data-driven, species-level assessment of gut microbiome health based on the relative abundance of microbes associated with healthy and diseased states. This study aimed to evaluate the prebiotic effect of five common oligosaccharides (fructooligosaccharides (FOS), galactooligosaccharides (GOS), xylooligosaccharides (XOS), inulin (IN), and 2'-fucosyllactose (2FL)) using the GMWI as a novel prebiotic index. This would enable a quantitative, evidence-based method for assessing the impact of prebiotics on gut microbiome wellness and potentially guide the design of personalized diets.

The original prebiotic index (PI) and its modification (PIm) considered the relative abundances of certain bacterial groups, assuming some were beneficial and others harmful. However, this approach is limited by outdated taxonomic classifications and an oversimplified view of the complex roles of gut bacteria. Recent advances in understanding the gut microbiome highlight the need for a more nuanced and data-driven approach to evaluating prebiotic effects. The GMWI addresses these limitations by incorporating a species-level analysis of microbial communities and associating microbial composition with overall health status.

The study employed an *in vitro* anaerobic batch fermentation system to simulate human gut conditions. Fecal samples from 19 healthy adult volunteers were mixed with basal growth medium and one of the five prebiotic oligosaccharides (at 1% w/v). Two control groups were included: no substrate added at time 0 (NS0) and no substrate added for 24 hours (NS24). Samples were collected at 24 hours post-incubation. Shotgun metagenomics was used to analyze microbial composition. The GMWI was calculated using a web tool that incorporates relative abundances of 50 species (7 health-prevalent and 43 health-scarce) to generate a score reflecting the overall microbiome health. Statistical analysis (ANOVA and Tukey's HSD test) was used to compare GMWI values among different groups. Alpha-diversity metrics (Shannon index, species richness, evenness, and inverse Simpson's index) were also calculated and compared.

All five prebiotics (IN, FOS, XOS, GOS, and 2FL) resulted in positive GMWI values after 24 hours of fermentation. Inulin (IN) showed the highest average GMWI (0.48 ± 0.06), followed by FOS (0.47 ± 0.03). GOS and 2FL had lower, but still positive, GMWI values. The control groups without prebiotics had significantly lower GMWI values: NSO (0.21 ± 0.06) and NS24 (-0.60 ± 0.05). Analysis at the species level revealed that the relative abundances of several health-prevalent species increased after fermentation with prebiotics, while health-scarce species decreased. Principal component analysis (PCA) showed clear separation between the prebiotic-treated groups and the control groups. In contrast to the GMWI results, alpha-diversity indices were significantly lower in the prebiotic-treated groups compared to the NSO group, though still higher than the NS24 group. A comparison with the original PI showed largely consistent results in terms of the overall prebiotic effect.

The results demonstrate that the GMWI effectively assesses the prebiotic effect of oligosaccharides. The positive GMWI values for all prebiotics indicate a shift towards a healthier microbiome profile, characterized by increased abundance of health-prevalent species and decreased abundance of health-scarce species. The discrepancy between GMWI and alpha-diversity metrics underscores the limitation of using alpha-diversity as a sole indicator of gut microbiome health and highlights the advantage of GMWI's species-level analysis. The study reinforces the potential of GMWI as a more robust and nuanced approach compared to traditional indices, offering a valuable tool for evaluating prebiotic efficacy and potentially guiding personalized dietary interventions.

This study successfully utilized the GMWI as a novel prebiotic index to quantitatively assess the impact of five common oligosaccharides on gut microbiome wellness. The results highlight the superiority of GMWI over traditional methods. This data-driven approach has significant implications for designing personalized diets based on their effect on gut microbiome wellness. Future research could explore the application of GMWI in *in vivo* studies and integrate functional metagenomics to provide even more comprehensive insights into prebiotic effects.

This study utilized an *in vitro* fermentation model, which may not perfectly reflect the complex *in vivo* environment. The analysis focused primarily on the species level, neglecting strain-level variations that could influence the interpretation of results. Additionally, the current version of GMWI does not consider metagenomic functional profiles, potentially limiting the depth of interpretation. Lastly, the sample size and age range of participants could impact the generalizability of the findings.