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Plant growth-promoting rhizobacteria (PGPR) engage in complex chemical exchange and signalling processes to enhance their survival, rhizosphere colonisation, and plant-beneficial roles. These microbial interactions are mediated by various chemical cues, including quorum sensing (QS) molecules, cyclic peptides, lipopeptides, nutrients, volatile organic compounds (VOC), and phytohormones. Cross-feeding, where one microorganism consumes metabolites produced by another, exemplifies direct chemical communication that shapes community dynamics and metabolic cooperation. However, the effects of cross-feeding among different PGPR strains remain insufficiently characterised. In this study, an LC–MS-based metabolomics approach, combined with multivariate statistical analysis, was employed to investigate metabolic perturbations induced by cross-feeding among PGPR strains. Growth curve analysis revealed that cross-fed PGPR exhibited growth patterns comparable to controls, with a slight reduction in biomass. Metabolic profiling indicated time-dependent shifts in the metabolic state of the cross-fed organisms, suggesting adaptive metabolic reprogramming in response to the donor-conditioned media. Multivariate analysis identified distinct metabolite alterations between cross-fed and control groups across different time points, highlighting the influence of nutrient availability on microbial growth dynamics. Notably, cross-fed groups showed decreased levels of primary metabolites such as amino acids and sugars alongside increased production of secondary metabolites, including surfactins, salicylic acid, and carboxylic acids. These secondary metabolites are implicated in plant growth promotion and defence, indicating their potential as natural biostimulants. The findings advance the understanding of PGPR interactions and chemical communication in the rhizosphere, supporting the development of sustainable agricultural practices by leveraging beneficial microbial interactions. Future research should explore these interactions within more complex microbial communities.
Details
Agricultural practices;
Communication;
Rhizosphere;
Growth curves;
Nutrient availability;
Multivariate analysis;
Volatile organic compounds--VOCs;
Metabolites;
Metabolism;
Plant growth;
Amino acids;
Chemical communication;
Carboxylic acids;
Microorganisms;
Growth patterns;
Salicylic acid;
Quorum sensing;
Plant growth substances;
Peptides;
Multivariate statistical analysis;
Statistical methods;
Plants;
Sustainable development;
Secondary metabolites;
Biostimulants;
Strains (organisms);
Motility;
Time dependence;
Design of experiments;
Biofilms;
Organic compounds;
Metabolomics;
Nutrient dynamics;
Lipopeptides;
Feeding;
Statistical analysis;
Plant hormones;
Chemical stimuli;
Sustainable practices;
Microbial activity;
Syntrophism;
Abiotic stress;
Sustainable agriculture;
Pseudomonas fluorescens
1 University of Johannesburg, Imbewu Metabolomics Research Group, Department of Biochemistry, Faculty of Science, Auckland Park, South Africa (GRID:grid.412988.e) (ISNI:0000 0001 0109 131X); University of Johannesburg, Research Centre for Plant Metabolomics, Faculty of Science, Auckland Park, South Africa (GRID:grid.412988.e) (ISNI:0000 0001 0109 131X)
2 University of Johannesburg, Ubuntu Lab, Department of Biochemistry, Faculty of Science, Auckland Park, South Africa (GRID:grid.412988.e) (ISNI:0000 0001 0109 131X)
3 Estación Experimental del Zaidín, CSIC, Department of Stress, Development and Signalling in Plants, Granada, Spain (GRID:grid.418877.5) (ISNI:0000 0000 9313 223X)
4 University of Venda, Department of Biochemistry and Microbiology, Faculty of Science, Engineering and Agriculture, Thohoyandou, South Africa (GRID:grid.412964.c) (ISNI:0000 0004 0610 3705)