Mass spectral molecular networking to decode the chemical space of biostimulant Bacillus strains

Abstract Beneficial soil microbes like plant growth-promoting rhizobacteria (PGPR) significantly contribute to plant growth and development through various mechanisms activated by plant-PGPR interactions. However, decoding this belowground chemical intercommunication is still enigmatic, thus hindering the use of PGPR formulations for sustainable agriculture. Therefore, we report the application of mass spectrometry (MS)-based untargeted metabolomics and molecular networking (MN) to interrogate and profile the intracellular chemical space of PGPR Bacillus strains: B. laterosporus, B. amyloliquefaciens, B. licheniformis 1001 and B. licheniformis M017 and their consortium. The results revealed differential and diverse chemistries in the four Bacillus strains when grown separately, and also differing from when grown as a consortium. MolNetEnhancer networks revealed 11 differential molecular families that are comprised of lipids and lipid-like molecules, benzenoids, nucleotide-like, and organic acids and derivatives. Consortium and B. amyloliquefaciens were characterized by the high abundance of surfactins, whereas B. licheniformis strains were characterized by the unique presence of lichenysins. Thus, this work demonstrates that the application of metabolome mining tools offers unique opportunities to map the microbial chemical space, thus providing unprecedented access and insights to molecular information of microbial systems. Such fundamental knowledge is essential for the informed future formulation of PGPR-based biostimulants.