Metabolomics-Based Selection of Biostimulant and Biocontrol Microbial Consortia

Microbial biostimulants and microbial plant protection products overlap in biological function, creating both R&D opportunities and regulatory challenges. In particular, multi-strain bacterial consortia may simultaneously affect nutrient mobilisation and abiotic stress tolerance, induce resistance, and demonstrate direct antagonism against phytopathogens. This multifunctionality complicates early product development because strain identity alone is sometimes insufficient in predicting product function, efficacy, or the most appropriate regulatory and claims strategy. Here, we used non-targeted LC-MS metabolomics as a hypothesis-generating tool to support formulation decisions for microbial consortia. Three bacterial consortia were compared: a full soil-oriented consortium C1 containing Bacillus spp., Rhodopseudomonas palustris, Nitrosomonas europaea, and Nitrobacter winogradskyi; a Bacillus-only consortium C2 intended for foliar stress-resilience applications; and a Bacillus-only consortium C3 grown with a chitin-related inducer to promote biocontrol-associated metabolism. Metabolomic profiling revealed clear differences between formulations. The full consortium C1 showed higher relative abundances of features putatively associated with biofertilising and growth support, whereas the Bacillus-only consortium C2 contained features putatively associated with biocontrol and induced resistance that were not detected in C1 under the applied criteria. The addition of the chitin-related inducer (C3) did not yield a completely distinct metabolite profile but increased the relative abundance of selected features putatively associated with biocontrol, while decreasing features putatively annotated as auxin-related or associated with abiotic stress responses. These results suggest that non-targeted metabolomics can help differentiate metabolic profiles putatively associated with biostimulant- and plant-protection-oriented formulations and thereby support prioritisation before extensive greenhouse or field testing. By linking formulation, medium composition, and microbial interactions to measurable metabolic signatures, metabolomics provides an evidence-based, hypothesis-generating framework for formulation development and the prioritisation of subsequent efficacy trials.