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      Rhizobiome engineering: Unveiling complex rhizosphere interactions to enhance plant growth and health

      , , , ,
      Microbiological Research
      Elsevier BV

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          Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences

          Profiling phylogenetic marker genes, such as the 16S rRNA gene, is a key tool for studies of microbial communities but does not provide direct evidence of a community’s functional capabilities. Here we describe PICRUSt (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States), a computational approach to predict the functional composition of a metagenome using marker gene data and a database of reference genomes. PICRUSt uses an extended ancestral-state reconstruction algorithm to predict which gene families are present and then combines gene families to estimate the composite metagenome. Using 16S information, PICRUSt recaptures key findings from the Human Microbiome Project and accurately predicts the abundance of gene families in host-associated and environmental communities, with quantifiable uncertainty. Our results demonstrate that phylogeny and function are sufficiently linked that this ‘predictive metagenomic’ approach should provide useful insights into the thousands of uncultivated microbial communities for which only marker gene surveys are currently available.
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            Structure and functions of the bacterial microbiota of plants.

            Plants host distinct bacterial communities on and inside various plant organs, of which those associated with roots and the leaf surface are best characterized. The phylogenetic composition of these communities is defined by relatively few bacterial phyla, including Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. A synthesis of available data suggests a two-step selection process by which the bacterial microbiota of roots is differentiated from the surrounding soil biome. Rhizodeposition appears to fuel an initial substrate-driven community shift in the rhizosphere, which converges with host genotype-dependent fine-tuning of microbiota profiles in the selection of root endophyte assemblages. Substrate-driven selection also underlies the establishment of phyllosphere communities but takes place solely at the immediate leaf surface. Both the leaf and root microbiota contain bacteria that provide indirect pathogen protection, but root microbiota members appear to serve additional host functions through the acquisition of nutrients from soil for plant growth. Thus, the plant microbiota emerges as a fundamental trait that includes mutualism enabled through diverse biochemical mechanisms, as revealed by studies on plant growth-promoting and plant health-promoting bacteria.
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              Going back to the roots: the microbial ecology of the rhizosphere.

              The rhizosphere is the interface between plant roots and soil where interactions among a myriad of microorganisms and invertebrates affect biogeochemical cycling, plant growth and tolerance to biotic and abiotic stress. The rhizosphere is intriguingly complex and dynamic, and understanding its ecology and evolution is key to enhancing plant productivity and ecosystem functioning. Novel insights into key factors and evolutionary processes shaping the rhizosphere microbiome will greatly benefit from integrating reductionist and systems-based approaches in both agricultural and natural ecosystems. Here, we discuss recent developments in rhizosphere research in relation to assessing the contribution of the micro- and macroflora to sustainable agriculture, nature conservation, the development of bio-energy crops and the mitigation of climate change.
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                Author and article information

                Journal
                Microbiological Research
                Microbiological Research
                Elsevier BV
                09445013
                October 2022
                October 2022
                : 263
                : 127137
                Article
                10.1016/j.micres.2022.127137
                4053a701-a262-4be3-b5cf-0c7c19429aa6
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

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