Genetic modification of the shikimate pathway to reduce lignin content in switchgrass (Panicum virgatum L.) significantly impacts plant microbiomes

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Genetic modification of the shikimate pathway to reduce lignin content in switchgrass (Panicum virgatum L.) significantly impacts plant microbiomes

Authors

Liu, S.; Chou, M.-Y.; Benucci, G. M. N.; Eudes, A.; Bonito, G.

Abstract

Switchgrass (Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-growth, low input requirements, and high biomass yields. Improvements in bioenergy conversion efficiency of switchgrass could be made by reducing its lignin content. Engineered switchgrass that expresses a bacterial 3-dehydroshikimate dehydratase (QsuB) has reduced lignin content and improved biomass saccharification due to the rerouting of the shikimate pathway towards the simple aromatic protocatechuate at the expense of lignin biosynthesis. However, the impacts of this QsuB trait on switchgrass microbiome structure and function remains unclear. To address this, wildtype and QsuB engineered switchgrass were grown in switchgrass field soils and samples were collected from inflorescences, leaves, roots, rhizospheres, and bulk soils for microbiome analysis. We investigated how QsuB expression influenced switchgrass-associated fungal and bacterial communities using high-throughput Illumina MiSeq amplicon sequencing of ITS and 16S rDNA. Compared to wildtype, QsuB engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB engineered plants had a lower abundance of arbuscular mycorrhizal fungi (AMF). Additionally, QsuB engineered plants had fewer Actinobacteriota in root and rhizosphere samples. These findings may indicate that changes in the plant metabolism impact both organismal groups similarly, or potential interactions between AMF and the bacterial community. This study enhances understanding of plant-microbiome interactions by providing baseline microbial data for developing beneficial bioengineering strategies and by assessing non-target impacts of engineered plant traits on the plant microbiome.

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