Gut Commensal Induced Modulation of the Global Metabolome of Caco-2 cells

Abstract

The gut microbiota plays a fundamental role in maintaining intestinal homeostasis, modulating host metabolism, and influencing overall health. However, the specific metabolic interactions between gut commensals and intestinal epithelial cells remain insufficiently understood. This study aims to investigate the impact of selected gut commensals on the global metabolome of Caco-2 cells, a well-established in vitro model of the human intestinal epithelium. By employing untargeted metabolomic analysis, this research seeks to characterize microbial-induced metabolic changes and identify key cellular pathways influenced by bacterial exposure. The study involves screening gut commensals for their potential to induce favorable effects on Caco-2 cells, followed by metabolic profiling to assess their influence on cellular function. Mapping these metabolic modulations will provide insights into how gut microbes regulate nutrient metabolism, energy production, and other essential biological processes in intestinal epithelial cells. Understanding these microbial interactions is crucial for elucidating their role in gut health and disease, as well as for identifying potential microbiome-based therapeutic targets for gastrointestinal and metabolic disorders. This research contributes to the growing body of knowledge on host-microbe interactions and paves the way for future studies exploring microbiota-driven metabolic regulation in the human gut. Aim: Characterize the global metabolomic changes in Caco-2 cells induced by gut commensals. Identify key metabolic pathways modulated by microbial interactions. Methods: A total of 12 bacterial strains, including Lactobacillus plantarum, L. rhamnosus, E. coli Nissle 1917, and Enterococcus faecium, were obtained from MTCC and CSIR-Imtech and heat-killed for further study. Human intestinal Caco-2 cells were cultured and treated with these bacteria under controlled conditions to assess cytotoxic effects and metabolic responses. Biochemical assays such as MTT (cell viability), Nitric Oxide (NO) release, and Lactate Dehydrogenase (LDH) release were performed to screen for beneficial and harmful bacterial effects. Based on these results, E. coli Nissle 1917 (beneficial) and Enterococcus faecium (harmful) were selected for in-depth metabolomic analysis. 12 Cells were subjected to metabolite extraction using methanol-water, followed by ultrasonication and derivatization. The samples were analyzed using GC-MS, and peaks were identified using AMDIS and the NIST library. Identified metabolites were further processed and mapped using PubChem, KEGG, and HMDB databases. Enrichment and pathway analysis were conducted using MetaboAnalyst 6.0 to determine the impact of bacterial treatment on cellular metabolomic profiles. Results: Caco-2 cells were cultured under standard sterile conditions and exposed to 12 different bacterial strains, each tested in five biological replicates, along with control wells containing only cells and media. After 24 hours of co-incubation, cell morphology was examined microscopically, and supernatants were collected for further biochemical assays. The effects of bacterial exposure on Caco-2 cells were evaluated using MTT (cell viability), LDH (cytotoxicity), and nitric oxide (oxidative stress) assays. These assays were used to screen and distinguish between potentially beneficial and harmful bacteria. Bacterial strains that preserved high cell viability, induced low LDH release, and caused minimal nitric oxide production were considered non-pathogenic or beneficial. In contrast, strains that significantly decreased cell viability, elevated LDH levels, and increased NO production were classified as harmful or cytotoxic. Also, the metabolites, identified and characterized using GC-MS-based metabolomics, were used for identifying disease signatures, enriched metabolisms and pathways, and classes of molecules specific to each treatment. One-way ANOVA (Dunnett's multiple comparisons test) was used as a statistical tool to investigate independent single variables (each treatment) for significant variations (P<0.05). A P value less than 0.05 indicate a significant difference between the two values. Conclusion: This study reveals that gut bacterial composition significantly shapes host epithelial cell viability, inflammation, and metabolism. Beneficial strains support gut homeostasis, while harmful ones trigger cytotoxic and inflammatory responses. These findings emphasize the role of gut microbes in health and disease and suggest potential for targeted microbiota-based therapies.