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Stimulation of distinct rhizosphere bacteria drives phosphorus and nitrogen mineralization in oilseed rape under field conditions

Lidbury, I. D. E. A. ORCID: https://orcid.org/0000-0001-7190-315X, Raguideau, S., Borsetto, C. ORCID: https://orcid.org/0000-0003-4848-9522, Murphy, A. R. J. ORCID: https://orcid.org/0000-0001-6586-2363, Bottrill, A., Liu, S., Stark, R., Fraser, T., Goodall, A., Jones, A., Bending, G. D., Tibbett, M. ORCID: https://orcid.org/0000-0003-0143-2190, Hammond, J. P. ORCID: https://orcid.org/0000-0002-6241-3551, Quince, C., Scanlan, D. J., Pandhal, J. ORCID: https://orcid.org/0000-0002-0316-8031 and Wellington, E. M. H. ORCID: https://orcid.org/0000-0002-4329-0699 (2022) Stimulation of distinct rhizosphere bacteria drives phosphorus and nitrogen mineralization in oilseed rape under field conditions. mSystems, 7 (4). ISSN 2379-5077

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To link to this item DOI: 10.1128/msystems.00025-22

Abstract/Summary

Advances in DNA sequencing technologies have drastically changed our perception of the structure and complexity of the plant microbiome. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and its specific functional role in augmenting plant health is relatively limited. Important ecological interactions being performed by microbes can be investigated by analyzing the extracellular protein fraction. Here, we combined a unique protein extraction method and an iterative bioinformatics pipeline to capture and identify extracellular proteins (metaexoproteomics) synthesized in the rhizosphere of Brassica spp. We first validated our method in the laboratory by successfully identifying proteins related to a host plant (Brassica rapa) and its bacterial inoculant, Pseudomonas putida BIRD-1. This identified numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients in P. putida. Next, we analyzed natural field-soil microbial communities associated with Brassica napus L. (oilseed rape). By combining metagenomics with metaexoproteomics, 1,885 plant, insect, and microbial proteins were identified across bulk and rhizosphere samples. Metaexoproteomics identified a significant shift in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This included stimulation of rhizosphere-specialized bacteria, such as Gammaproteobacteria, Betaproteobacteria, and Flavobacteriia, and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralization. Our metaproteomic assessment of the “active” plant microbiome at the field-scale demonstrates the importance of moving beyond metagenomics to determine ecologically important plant-microbe interactions underpinning plant health. IMPORTANCE Plant-microbe interactions are critical to ecosystem function and crop production. While significant advances have been made toward understanding the structure of the plant microbiome, learning about its full functional role is still in its infancy. This is primarily due to an incomplete ability to determine in situ plant-microbe interactions actively operating under field conditions. Proteins are the functional entities of the cell. Therefore, their identification and relative quantification within a microbial community provide the best proxy for which microbes are the most metabolically active and which are driving important plant-microbe interactions. Here, we provide the first metaexoproteomics assessment of the plant microbiome using field-grown oilseed rape as the model crop species, identifying key taxa responsible for specific ecological interactions. Gaining a mechanistic understanding of the plant microbiome is central to developing engineered plant microbiomes to improve sustainable agricultural approaches and reduce our reliance on nonrenewable resources.

Item Type:Article
Refereed:Yes
Divisions:Life Sciences > School of Agriculture, Policy and Development > Department of Crop Science
ID Code:107187
Uncontrolled Keywords:Computer Science Applications, Genetics, Molecular Biology, Modeling and Simulation, Ecology, Evolution, Behavior and Systematics, Biochemistry, Physiology, Microbiology
Publisher:American Society for Microbiology

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