Short‐term probiotic supplementation affects the diversity, genetics, growth, and interactions of the native gut microbiome

The precise mechanisms through which probiotics interact with and reshape the native gut microbiota, especially at the species and genetic levels, remain underexplored. This study employed a high-dose probiotic regimen of Bifidobacterium animalis subsp. lactis [200 billion colony forming units (CFU)/day] over 7 days among healthy participants. Weekly fecal samples were collected for metagenomic sequencing analysis. We found that probiotic intake can significantly enhance the diversity of the gut microbiome and impact single nucleotide variations, growth rates, and network interactions of the resident intestinal bacteria. These adaptive changes in the gut microbiota indicate the swift evolutionary responses of native bacteria to the ecological disturbance presented by probiotic supplementation. Notably, the microbial community appears to undergo rapid and multifaceted ecological adjustments, potentially preceding longer-term evolutionary changes. This knowledge lays the groundwork for further exploration into the mechanisms underlying probiotic-mediated modulation of the gut microbiome, highlighting the necessity of encompassing ecological and evolutionary perspectives in the design and optimization of probiotic applications. The human gut harbors a highly diverse and dynamic microbiome that plays a crucial role in maintaining overall health and physiological homeostasis [1]. Probiotics, defined as live microorganisms that provide health benefits when administered in adequate amounts, represent a promising strategy for supporting gut health. Both preclinical and clinical studies have demonstrated the potential of probiotic supplementation in managing various health conditions. However, the effects of probiotics can vary significantly among individuals, highlighting the importance of tailoring probiotic interventions to individual microbiome characteristics. Exogenous probiotic strains, upon entering the gut, can influence the native microbiota not only at the species level but also at the strain level [2-4]. Since the functional contributions of the gut microbiome are largely determined by strain-level activity, it is essential to analyze microbial growth dynamics at this finer resolution to fully understand how probiotics regulate the gut microbiota. Currently, the most commonly used dosage of probiotics in clinical studies ranges from 106 to 109 colony forming units (CFU) per day [5-7], with the use of higher doses becoming increasingly common. However, there remains a significant knowledge gap regarding the persistence and colonization ability of these probiotics and whether these traits are reliably translated into enhanced health benefits, particularly in healthy individuals. Importantly, it is still unclear how high-dose probiotic interventions affect the host gut microbiome at finer taxonomic and genetic levels, as well as the nature of their interactions within the gut ecosystem. To address these gaps, we selected a well-characterized probiotic strain, Probio-M8, which has been demonstrated to have positive effects on gut health [8, 9], and administered it at a high dose of 200 billion CFU per day in a short-term intervention study involving healthy individuals. We performed deep metagenomic sequencing on multiple fecal samples to investigate the impact of the probiotic on gut microbiota from both macro and micro diversity perspectives (Figure 1A and Table S1). Additionally, we constructed an ecological regulation network centered on Probio-M8. Our findings suggest that the microbial community undergoes rapid and multifaceted ecological adjustments, which may precede longer-term evolutionary changes. To accurately evaluate the abundance and impact of probiotics within the gut microbiota, it is crucial to generate comprehensive and high-resolution data. To achieve this, we employed a sequencing depth that was 5–10 times greater than that of typical studies [10]. Following rigorous quality control and the removal of host DNA, we obtained a total of 4.98 TB (terabyte) of high-quality sequencing data, averaging 41.53 ± 5.20 GB (gigabyte) per sample, which ensured the robustness and reliability of downstream analyses. Leveraging this extensive metagenomic data set, we assembled 4878 high-quality genome bins (completeness > 80%, contamination < 5%), and ultimately identified 507 species-level genome bins (SGBs) with an average nucleotide identity of 95% and a genome alignment rate of 30%. We then assessed the overall impact of the probiotic intervention on the macro-diversity of the gut microbiota by analyzing Shannon and Simpson diversity indices. Initially, no significant differences were observed between the two groups on the 7 days before probiotic intervention and on day 0 (−7 d and 0 d), indicating stable gut microbiota diversity before intervention. Following the administration of Probio-M8, both diversity indices showed a significant increase (p < 0.05; Figure 1B,C, and Table S2), demonstrating that the intervention effectively enhanced the gut microbiota diversity. However, this increase in alpha diversity was transient as it remained stable thereafter, suggesting that while short-term and high-dose probiotic intake can enhance diversity, it may not be sufficient to induce persistent changes within the complex gut ecosystem. To further investigate the impact on gut microbiota composition, we conducted principal coordinates analysis (based on the Bray-Curtis dissimilarity) and ANOSIM (analysis of similarities). These analyses indicated no significant changes in the overall gut microbiota composition following intervention (Figure S1A,B). Thus, while short-term and high-dose administration of Probio-M8 effectively enhanced microbiota diversity, it did not significantly alter the community composition of the resident microbiota. To identify gut microbiota species with altered abundance during the intervention period, we conducted a taxonomic differential abundance analysis, which identified several significantly affected species, including Dialister hominis, Bifidobacterium animalis, and Eubacterium_G ventriosum (Figure 1D,E, and Table S3). Among them, Adlercreutzia equolifaciens, UMGS1474 sp900547105, and Eubacterium_G ventriosum increased in abundance after the intervention, which decreased after stopping probiotic intake, while Dorea_A longicatena_B and Dialister hominis also increased in abundance after the intervention, but their abundance fluctuated afterward. Notably, Bifidobacterium animalis demonstrated a significant increase in abundance at day 7 compared to days −7 and 0 (Figure 1E). Analysis using average nucleotide identity (ANI) confirmed that the increased abundance was primarily due to the administered Probio-M8 strain. However, this effect was transient, as the abundance of Bifidobacterium animalis was returned to baseline levels following the cessation of probiotic intervention. These findings indicate that Probio-M8 cannot maintain a high abundance in the gut of most individuals without continuous supplementation, highlighting the need for sustained probiotic intake to achieve prolonged effects. To further understand the subtle genetic shifts within the gut microbiota that may be driven by external factors, it is crucial to consider the role of evolutionary pressures. These pressures can induce microdiversity within microbial communities, influencing the overall structure and function of the gut ecosystem [11]. We subsequently examined single nucleotide variants (SNVs) within the gut microbiota. Our findings revealed a nonsignificant increase in the number of species harboring SNVs following Probio-M8 administration at day 7 compared to the baseline period (−7 d and 0 d; Figure 1F). We further analyzed species with a read mapping coverage of 0.4 at least, comparing base changes before and after the intervention (0 d and 7 d). SNV loci were classified as shared or non-shared, based on whether more than 50% of the loci differed between pre- and post-intervention. In total, 11 shared loci and 2442 non-shared loci were identified. Of these, six loci were synonymous mutations. Functional annotation based on the database of Clusters of Orthologous Genes (COGs) revealed functions, including myosin-crossreactive antigen, alpha-l-fucosidase, and argininosuccinate synthase (Figure 1G, and Table S4). The 2442 non-shared loci were distributed across 120 genes, 21 of which were associated with carbohydrate transport and metabolism (Figure 1H). The in situ bacterial replication rate was assessed using the iRep metric, which estimates genome replication rates from metagenomic datasets, thereby providing insights into bacterial growth and the proportion of live bacteria in the gut microbiota [12]. We used the iRep algorithm to evaluate the impact of Probio-M8 intervention on the growth rate profile of bacterial species within the gut. An iRep value closer to 2 signifies a higher replication rate. Our analysis revealed that different gut microbes responded variably to Probio-M8 intake (Figure 1I,J). For example, Enterocloster sp000431375 exhibited the greatest iRep value, but its growth rate decreased after the probiotic intervention. However, it is important to note that despite the high iRep value, it remained a non-dominant species within the gut microbiota. This observation underscores the fact that swift bacterial replication within complex microbial communities may not necessarily lead to a rise in population size due to various factors impacting the absolute bacterial abundance, such as the original species abundance and other ecological interactions like competition, predation, and cellular mortality. Furthermore, the replication rate of bacteria at different time points was studied, and it was found that the replication rate of different strains was different after probiotic consumption (Figure 1J). Unfortunately, our study on growth rate was contingent solely on the assessment of genome replication dynamics, leaving the cellular mortality rate undisclosed. Interestingly, upon analyzing Bifidobacterium animalis specifically, we observed an increased replication rate following Probio-M8 consumption, with the iRep value almost reaching 2 at 14 d (Figure 1K). To provide a comprehensive visualization of the iRep metric analysis, we employed a heatmap, which revealed varied changes in growth rates across different gut microbes (Figure 1L). Overall, these results demonstrate that the short-term and high-dose intake of the Probio-M8 probiotic formulation not only modulated the relative abundance of specific gut bacterial taxa but also influenced the microdiversity and growth dynamics of the indigenous gut microbiota. To assess whether the Probio-M8 intervention led to genetic changes within the gut microbial community, we focused our analysis on the SNVs of the top eight dominant species. These species were selected based on their prevalence and significant influence within the microbiome, making them prime candidates for detecting genetic changes in response to ecological shifts. Considering that SNV frequency is positively correlated with sequencing depth, we normalized the number of SNVs (nSNVs) to sequencing depth using the formula: nSNVs = number of SNVs/sequencing depth per sample. Despite significant post-interventional shifts in the relative abundance of certain dominant species, such as Faecalibaterium prausnitzii_G, Phocaeicola dorei, Escherichia coli, Alistipes putredinis, and Faecalibaterium prausnitzii, compared to baseline (Figure 2A,B, Figure S1C, p < 0.05), no significant differences were observed in the nSNV across these species at any time point. These findings indicate that while the Probio-M8 intervention led to notable ecological shifts within the gut microbial community, these changes were not accompanied by significant genetic adaptations within the dominant species over the study period. Additionally, our results align with a prior meta-analysis, which reported limited ecological changes after probiotic intake, while noting extensive genetic alterations within individual gut microbes [11]. These comparisons highlight the complexity of microbial responses to probiotics, indicating that while ecological shifts may occur rapidly, significant genetic adaptations may require more prolonged exposure or specific environmental conditions. Further research is needed to explore these dynamics more comprehensively, especially across different populations and extended time scales. To assess the impact of Probio-M8 intervention on the interaction dynamics within the gut microbial community, we employed Spearman correlation analyses to evaluate the changes in inter-bacterial relationships over time, focusing on shifts in interaction strength and patterns. Using a correlation coefficient threshold of 0.5 (p < 0.05), we visualized the microbial interactions by constructing a correlation matrix heatmap. Our analysis revealed that Probio-M8 administration influenced the strength and complexity of interactions within the gut microbial network (Figure S1D). A more detailed examination of correlations involving Probio-M8 provided additional insights. Visualization of the correlation-based interaction network demonstrated that Probio-M8 exhibited the highest number of associations with other resident gut microbes at day 7, indicating an expansion of its interaction network following the intervention (Figure 2C). Quantification of the nodes and edges in the network centered around Probio-M8 showed that both metrics peaked at day 7 but declined subsequently during follow-up, suggesting that the enhanced connectivity was transient (Figure 2D–G, and Table S5). Our findings indicate that Probio-M8 administration transiently enhanced interconnectivity within the gut microbial community, underscoring the dynamic ecological responses of the gut microbiota to probiotic interventions. The observed modulation of microbial interaction networks provides valuable insights into the transient nature of probiotic-induced shifts in microbial ecology. In summary, this study employed deep metagenomic sequencing to evaluate in situ changes in the gut microbiota in response to high-dose probiotic intervention. Our findings provide critical insights into the intricate interactions between probiotics and the indigenous gut microbial community. We observed that short-term administration of Probio-M8 enhanced gut microbial diversity and influenced key microbial properties, including nucleotide variation, growth dynamics, and inter-bacterial interactions, highlighting the significant impact of probiotics on the ecological balance of the gut ecosystem. Notably, our results indicate that gut microbes rapidly adapt to probiotic-induced pressures, with ecological changes often preceding genetic adaptations, underscoring the complexity and multifaceted nature of the microbiome response. Although the study is limited by its sample size, these findings offer valuable perspectives on the transient nature of probiotic-induced shifts in the gut microbiota. Further large-scale and multi-population studies are warranted to deepen our understanding of probiotic-microbiome interactions and to support the development of targeted and precision probiotics for optimizing gut health. Xin Shen: Visualization; writing—original draft. Hao Jin: Writing—original draft; validation. Feiyan Zhao: Conceptualization; methodology; software. Lai-Yu Kwok: Writing—review and editing. Zhixin Zhao: Validation; data curation. Zhihong Sun: Project administration; formal analysis; supervision. This work was supported by the National Natural Science Foundation of China (Nos. 32325040 and U22A20540), the National Key Research and Development Program of China (No. 2022YFD2100700), Inner Mongolia Science & Technology Planning Project (No. 2022YFSJ0017), Basic Research Operating Expenses Program for Colleges and Universities directly under the Inner Mongolia Autonomous Region (BR22-14-01), and the CARS. The authors declare no conflict of interest. This study protocol was reviewed and approved by the Ethical Committee of the Affiliated Hospital of Inner Mongolia Medical University [Approval NO.KY (2020013)], and the clinical trial has been registered with the Chinese Clinical Trials Registry (ChiCTR Identifier: ChiCTR2000039167). The data that supports the findings of this study are available in the supplementary material of this article. The sequencing data generated in this study was made available in the CNGB Sequence Archive (CNSA) (https://db.cngb.org/cnsa/) of China National Genebank DataBase (CNGBdb) with accession number CNP0005636. The data and scripts used are saved in GitHub https://github.com/shenx08/M8-high-dose.git. Supplementary materials (methods, figures, tables, graphical abstract, slides, videos, Chinese translated version, and update materials) may be found in the online DOI or iMeta Science http://www.imeta.science/. Table S1: Participants' information. Table S2: Differences in the alpha diversity of gut microbiota across time points. Table S3: Significantly differential species-level genome bins (SGBs) identified between time points. Table S4: Shared loci and COG (database of Cluster of Orthologous Genes) annotation results. Table S5: Correlation between Bifidobacterium animalis subsp. lactis Probio-M8 and SGBs. 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