Metabolic reprogramming in PGPR reveals cross-feeding-driven physiological shifts and metabolic adaptations.

Introduction: Microbial interactions in the rhizosphere are fundamental to soil health, plant growth, and ecosystem stability. Among these interactions, metabolic cross-feeding, the exchange of metabolites between microorganisms, plays a critical role in shaping microbial community structure and function. This study investigates the metabolic interplay between two PGPR (Priestia megaterium and Bacillus licheniformis), focusing on how metabolite exchange influences bacterial growth and metabolic reprogramming. Methods: An integrative metabolomics approach was employed to examine metabolic exchanges between P. megaterium and B. licheniformis. Cultures were grown individually and in co-culture, followed by extraction of extracellular metabolites at distinct growth phases. Metabolomic profiling was conducted using ultra-performance liquid chromatography-mass spectrometry (UPLC-MS). Data preprocessing and feature extraction were followed by molecular networking and multivariate statistical analysis to identify discriminant metabolites. Pathway enrichment and functional annotation were performed using KEGG and MetaboAnalyst to pinpoint key metabolic pathways altered during cross-feeding interactions. Results and discussion: Metabolomic analysis revealed distinct metabolic shifts driven by reciprocal metabolite exchange between P. megaterium and B. licheniformis. Metabolites secreted by B. licheniformis exhibited a growth-inhibitory effect on P. megaterium, while those from P. megaterium stimulated the growth of B. licheniformis. Multivariate data analysis demonstrated significant variation in the production of amino acids, fatty acids, and cyclic lipopeptides across growth phases. Pathway enrichment identified the phenylalanine, tyrosine, and tryptophan biosynthesis (PTTB) pathway as a central metabolic hub mediating these interactions. The regulation of aromatic amino acid metabolism appeared critical in determining whether interactions were cooperative or competitive. The observed metabolic reprogramming reflects adaptive strategies employed by PGPR to thrive under nutrient-limited conditions, balancing cooperation and competition through selective metabolite secretion. These findings offer systems-level insight into the mechanistic basis of cross-feeding and highlight the potential of integrating metabolomics to guide microbial consortia design for agricultural applications. Understanding these metabolic determinants supports the development of tailored biofertilizer formulations that enhance soil fertility and plant resilience. Conclusion: This study demonstrates that metabolite cross-feeding induces distinct metabolic reprogramming between Priestia megaterium and Bacillus licheniformis, underpinning adaptive interactions in nutrient-limited environments. These findings provide a mechanistic basis for microbial consortia design and biofertilizer optimization. Future multi-omics and systems-level investigations should elucidate the genetic and regulatory determinants of these metabolic exchanges, advancing sustainable biotechnological innovations aligned with SDGs 9, 12, and 13.