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. 2014 Nov 10;9(11):e112609.
doi: 10.1371/journal.pone.0112609. eCollection 2014.

Functional potential of soil microbial communities in the maize rhizosphere

Affiliations
Free PMC article

Functional potential of soil microbial communities in the maize rhizosphere

Xiangzhen Li et al. PLoS One. .
Free PMC article

Abstract

Microbial communities in the rhizosphere make significant contributions to crop health and nutrient cycling. However, their ability to perform important biogeochemical processes remains uncharacterized. Here, we identified important functional genes that characterize the rhizosphere microbial community to understand metabolic capabilities in the maize rhizosphere using the GeoChip-based functional gene array method. Significant differences in functional gene structure were apparent between rhizosphere and bulk soil microbial communities. Approximately half of the detected gene families were significantly (p<0.05) increased in the rhizosphere. Based on the detected gyrB genes, Gammaproteobacteria, Betaproteobacteria, Firmicutes, Bacteroidetes and Cyanobacteria were most enriched in the rhizosphere compared to those in the bulk soil. The rhizosphere niche also supported greater functional diversity in catabolic pathways. The maize rhizosphere had significantly enriched genes involved in carbon fixation and degradation (especially for hemicelluloses, aromatics and lignin), nitrogen fixation, ammonification, denitrification, polyphosphate biosynthesis and degradation, sulfur reduction and oxidation. This research demonstrates that the maize rhizosphere is a hotspot of genes, mostly originating from dominant soil microbial groups such as Proteobacteria, providing functional capacity for the transformation of labile and recalcitrant organic C, N, P and S compounds.

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Conflict of interest statement

Competing Interests: Xiangzhen Li is a PLOS ONE Editorial Board member. This does not alter the authors’ adherence to PLOS ONE Editorial policies and criteria.

Figures

Figure 1
Figure 1. Normalized signal intensity of gyrB genes derived from different phylogenetic groups in the rhizosphere and bulk soil.
All data are presented as means ± standard errors (n = 3). *p<0.05, and **p<0.01.
Figure 2
Figure 2. Normalized signal intensity of genes involved in (a) carbon fixation, (b) carbon degradation pathways in the rhizosphere and bulk soil.
All data are presented as means ± standard errors (n = 3). *p<0.05, and **p<0.01.
Figure 3
Figure 3. Differences in the abundance of N cycling genes in the rhizosphere and bulk soil.
The numbers in brackets indicate the percentage difference of a functional gene signal intensity between rhizosphere and bulk soil samples relative to the normalized signal intensity in the bulk soil sample. The gray-colored genes were not detected by GeoChip 3.0. *p<0.05, and **p<0.01.
Figure 4
Figure 4. Normalized signal intensity of genes involved in (a) phosphorus utilization, (b) sulfur cycling in the rhizosphere and bulk soil.
All data are presented as means ± standard errors (n = 3). *p<0.05, and **p<0.01.
Figure 5
Figure 5. Normalized signal intensity of antibiotic resistance genes in the rhizosphere and bulk soil.
All data are presented as means ± standard errors (n = 3). *p<0.05, and **p<0.01.

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Grants and funding

This work was funded by the Energy Biosciences Institute, Environmental Impact and Sustainability of Feedstock Production Program at the University of Illinois, Urbana (http://www.energybiosciencesinstitute.org/program_project/environmental-impact-and-sustainability-feedstock-production). The author RJ was also supported from the National Natural Science Foundation of China (41371268, 41301272) (http://www.nsfc.gov.cn/publish/portal1/), Strategic Priority Research Program of the Chinese Academy of Sciences (XDB15010000) (http://english.cas.cn/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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