bioRxiv2025
1In this study, we examined phenotypic and compositional patterns in rhizosphere microbial communities across conventionally and organically managed farms to assess impacts on soil microbiomes. We employed newly developed single-cell Raman microspectroscopy (SCRS)-based community phenotypic profiling analysis with microbiome 16S rRNA gene amplicon sequencing to compare the soil microbial communities of alfalfa, carrot, corn, lettuce, potato, soybean, squash, tomato, triticale, wheat, oat, and pea grown under either conventional or organic agriculture across farms in New York State (USA). Distinct microbiome clustering patterns indicated that organic and conventional production methods imposed strong selective pressures, shaping microbial assemblages within each group more distinctly than site or plant species variations. Using SCRS-based microbial phenotyping, we identified distinct microbial adaptations in agricultural soils, with organic systems favoring lipid-accumulating phenotypes for energy storage and stress resilience in low-input environments, while higher nutrient availability in conventional systems promoted carbon-rich phenotypes, enhancing rapid carbon assimilation and biomass production. Through network analysis of ecological hub species, we identified Pseudomonas, a plant growth-promoting rhizobacteria (PGPR), along with several nitrogen-fixing prokaryotes as core members within conventional agricultural systems. In contrast, organically managed soils featured PGPR taxa from the Bacilli class and contained microorganisms carrying antibiotic resistance genes, potentially indicating the presence of antibiotic resistance genes within organic agricultural environments. Overall, we found that the novel inclusion of microbial phenotyping methods, such as SCRS, can describe unique linkages between microbiome structure and their physiology that are distinctive between conventional and organic agricultural systems. 2 ImportanceOur study successfully integrated single-cell Raman microspectroscopy and amplicon sequencing, two established techniques for analyzing microbial communities and their functions, enabling a link between genotype and phenotype to better characterize ecosystem dynamics. While few studies have explored microbial phenotypes alongside community composition to infer agricultural management differences, our research offered key insights into functional relevance of microbial communities to agricultural practices, demonstrating how management strategies influenced microbial adaptation. These findings advance microbial ecology research, demonstrating how agricultural management strategies influence microbiome structure and function, reinforcing the importance of phenotypic profiling in sustainable agriculture.