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

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          ABSTRACT

          Switchgrass ( Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-impact 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 remain unclear. To address this, wild-type 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 wild-type, QsuB-engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB-engineered plants had a lower relative 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 AMF and Actinobacteriota 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 nontarget impacts of engineered plant traits on the plant microbiome.

          IMPORTANCE

          Bioenergy crops provide an important strategy for mitigating climate change. Reducing the lignin in bioenergy crops could improve fermentable sugar yields for more efficient conversion into bioenergy and bioproducts. In this study, we assessed how switchgrass engineered for low lignin impacted aboveground and belowground switchgrass microbiome. Our results show unexpected reductions in mycorrhizas and actinobacteria in belowground tissues, raising questions on the resilience and function of genetically engineered plants in agricultural systems.

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review and editing
                Role: Data curationRole: Formal analysisRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – review and editing
                Role: ConceptualizationRole: Funding acquisitionRole: Writing – review and editing
                Role: ConceptualizationRole: Funding acquisitionRole: InvestigationRole: Project administrationRole: ValidationRole: Writing – original draftRole: Writing – review and editing
                Role: Editor
                Journal
                Microbiol Spectr
                Microbiol Spectr
                spectrum
                Microbiology Spectrum
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2165-0497
                January 2025
                26 November 2024
                26 November 2024
                : 13
                : 1
                : e01546-24
                Affiliations
                [1 ]Department of Plant, Soil, and Microbial Sciences, Michigan State University; , East Lansing, Michigan, USA
                [2 ]DOE Great Lakes Bioenergy Research Center, Michigan State University; , East Lansing, Michigan, USA
                [3 ]Department of Plant Biology, Rutgers University; , New Brunswick, New Jersey, USA
                [4 ]DOE Joint BioEnergy Institute; , Emeryville, California, USA
                [5 ]Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory; , Berkeley, California, USA
                USDA-ARS-NPRL; , Dawson, Georgia, USA
                Author notes
                Address correspondence to Gregory Bonito, bonito@ 123456mail.msu.edu

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0003-1589-947X
                https://orcid.org/0000-0002-7262-8978
                Article
                spectrum01546-24 spectrum.01546-24
                10.1128/spectrum.01546-24
                11705929
                39589120
                ce3e84db-3e96-467c-a295-448abc5d3311
                Copyright © 2024 Liu et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 27 June 2024
                : 28 October 2024
                Page count
                supplementary-material: 2, authors: 5, Figures: 6, References: 84, Pages: 18, Words: 9802
                Funding
                Funded by: U.S. Department of Energy (DOE);
                Award ID: DE-FC02-07ER64494
                Award Recipient :
                Funded by: U.S. Department of Energy (DOE);
                Award ID: DE-SC0018409
                Award Recipient :
                Funded by: U.S. Department of Energy (DOE);
                Award ID: DE-AC02-05CH11231
                Award Recipient :
                Categories
                Research Article
                environmental-microbiology, Environmental Microbiology
                Custom metadata
                January 2025

                fungal and bacterial communities,bioenergy crops,genetic engineering,mycorrhizal fungi,actinobacteria

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