Maize Kernel-Associated Metagenomes Reveal Potential Microbe–Microbe Interactions that Underlie Fusarium Ear Rot Disease

Abstract

As an alternative to host resistance, transgenic expression of entomocidal and antimicrobial proteins from Bacillus thuringiensis (Bt) in maize can mitigate Fusarium ear rot (FER). This study evaluated FER in Bt and conventional maize and the role of microbes in the kernel-associated metagenome using quantitative reduced representation sequencing. Our results revealed significant differences in FER severity across environments and varieties and between inoculation treatments. The lower FER scores of conventional maize Spectrum 6416 relative to other varieties highlighted resistant alleles in maize germplasm, whereas strong correlations indicated FER-induced yield loss. Mitigation of FER by transgenes was validated by about threefold enrichment of Fusarium verticillioides (Fv) postinoculation compared with nonsignificant Fv enrichment in conventional maize. Although the major causal pathogen of FER, Fv, was the most abundant species in the metagenomes (r = 0.41 to 0.49), a similar degree of correlation was observed between FER and several Fusarium spp. (r = 0.2 to 0.56). The potential FER-suppressing properties of Talaromyces stipitatus and Ustilago maydis were indicated by negative correlations with FER (r = –0.22 to –0.42), Fv, and some Fusarium spp. The more FER-resistant varieties consistently enriched for potential FER-suppressing Burkholderia cenocepacia (negatively correlated with Fv). This suggests host genetic background-dependent recruitment of beneficial microbes that suppress pathogens and that microbe–microbe interactions play a role in FER severity. Quantitative and species/strain-level metagenomic profiles hold promise for identifying robust disease-suppressing microbes and microbes that act in synergy with pathogens and for developing holobiont-aware breeding strategies that account for host–microbiome coevolution and host genotype, microbiome/metagenome, and environment interactions. [Graphic: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Keywords

• Fusarium verticillioides
• metabarcoding
• microbe–microbe interactions
• OmeSeq-qRRS
• quantitative reduced representation sequencing
• Zea mays