Mapping the Chemical Language of Bacillus Consortia: Toward the Rational Design of Microbial Biostimulants

The application of microbial consortia as biostimulant formulations for improving plant growth and productivity has gained momentum as a promising approach to agricultural sustainability. However, the underlying biochemical and molecular mechanisms that govern the modes of action of microbial biostimulants, as well as microbial interactions in a consortium, remain an area of ongoing research. This knowledge gap limits the design and implementation of microbial biostimulants for sustainable agriculture. Thus, this computational metabolomics study aims to comprehensively characterize the metabolome of three (3) microbial consortia formulated from different combinations of Bacillus strains. Three consortia were cultured in liquid media, and metabolites were extracted from the extracellular and intracellular milieu at different bacterial growth stages. The samples were analyzed using a liquid chromatography-mass spectrometry (LC-MS/MS) system. Molecular networking and machine learning methods were employed to mine and interpret the acquired spectral data. The results revealed differential metabolite profiles that define the chemical space of the 3 microbial consortia. The annotated metabolome was characterized by diverse molecular families, including amino acids and peptides, antimicrobials, phytohormones, lipids, organic acids, carbohydrates, and pyrimidines. Each consortium was characterized by differential metabolite profiles at different growth stages. Thus, the findings of this study provide actionable insights into the differential metabolomic landscapes of Bacillus consortia, charting a chemical lexicon for both microbe-microbe and microbe-plant interactions. These findings contribute to the rational design of next-generation microbial biostimulant formulations, supporting the realization of the United Nations Sustainable Development Goals, particularly zero hunger (SDG 2) and climate action (SDG 13).