Abstract
INTRODUCTION: Optimizing nitrogen sources and rootstock selection is crucial for sustainable watermelon production. However, the synergistic mechanisms between organic nitrogen forms and rootstocks remain poorly understood. This study investigates whether glycine, as an organic nitrogen source, modulates root-associated bacterial communities through rootstock-mediated effects to enhance watermelon growth. METHODS: Grafted watermelon plants (scion: watermelon; rootstocks: self-grafted watermelon (CK), wild watermelon (T1), bottle gourd (T2), pumpkin (T3) were cultivated under glycine (G) or ammonium nitrate (A) treatments for 25 days. Plant growth, soil enzyme activity, rhizosphere bacterial communities (16S rRNA sequencing), and root metabolomes (UPLC-MS/MS) were analyzed. RESULTS: Relative to ammonium nitrate, glycine to some extent increased bacterial α-diversity but there was no significant difference and altered β-diversity, whereas enhancing microbial network complexity. Rootstock genotype is the main driver of bacterial α diversity and shaped the bacterial network architecture: T1-supported networks exhibited strong associations enriched in two-component systems, whereas T3 networks reflected intensified resource competition. Rootstock identity also influenced root exudate profiles. T3 secreted high levels of amino acids and nucleotides with metabolic and defensive roles, correlating with the abundance of Edaphobacter and Actinomadura. In contrast, T1 increased Acidibacter abundance via lipid secretion. The rootstock-bacteria-metabolite interplay modulated soil enzyme activities, supported photochemical efficiency, and promoted biomass accumulation. DISCUSSION: These findings demonstrate the potential of glycine as a sustainable nitrogen source and identify compatible scion-rootstock combinations that enhance rhizosphere microbial dynamics and plant performance. The study provides mechanistic insights into how root exudates shape bacterial community assembly, although further work is needed to elucidate the complexity of microbe-microbe interactions.