Deciphering the Functional Landscape of Microbiome-Mediated Invasion Resistance to Plant Pathogens
Abstract
Rational design of microbiomes requires a fundamental understanding of the community functional landscape, i.e., the mapping between community composition to function. The functional landscapes governing microbiome-mediated invasion resistance to pathogens, which is a critical function of host-associated microbiomes, are still poorly studied in vivo. In this study, we systematically assessed the invasion resistance of synthetic rhizosphere microbial communities (SynComs) to two distinct pathogens (Pseudomonas syringae DC3000, Pseudomonas brassicacearum Root401) in planta. Our experiments with two groups of SynComs revealed that communities with higher species richness exhibit significantly stronger resistance to pathogen invasion. We found that the invasion resistance can be accurately predicted by the community compositions using a linear regression model that account for additive effects of individual strains and pairwise epistasis. In particular, we inferred and validated that the invasion resistance is determined by a few species with strong inhibitory effects. Finally, using simulations of the generalized Lotka-Volterra model, we assessed the utility of linear regression in predicting invasion resistance of complex communities. In summary, our findings systematically profiled the functional landscape of invasion resistance and provided crucial insights for designing microbial communities to improve host health.
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Declaration of Competing Interests
The authors declare no competing interests to disclose.
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