Strigolactones shape the rhizomicrobiome in rice (Oryza sativa)
•Strigolactone (SL) phytohormones determine the rhizomicrobiome in rice.•SL-mediated metabolic pathways are likely to be responsible for the regulation of rhizomicrobiome in rice.•Genetic modulation of rice SL biosynthesis and/or signaling may promote the abundance of specific beneficial bacterial t...
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| Published in | Plant science (Limerick) Vol. 286; pp. 118 - 133 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
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Ireland
Elsevier B.V
01.09.2019
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| Abstract | •Strigolactone (SL) phytohormones determine the rhizomicrobiome in rice.•SL-mediated metabolic pathways are likely to be responsible for the regulation of rhizomicrobiome in rice.•Genetic modulation of rice SL biosynthesis and/or signaling may promote the abundance of specific beneficial bacterial taxa.
The rhizomicrobiome helps the host plant to better adapt to environmental stresses. In contrast, plant-derived metabolic substances, including phytohormones, play an active role in structuring rhizomicrobiome. Although strigolactones (SLs), a group of phytohormones, serve as potential rhizosphere signaling molecules, their contributions in shaping the rice (Oryza sativa) rhizomicrobiome remain elusive. To address this issue, we compared the rhizomicrobiome of rice mutants defective in either SL biosynthesis or signaling and wild-type (WT) plants. To understand whether SL-regulated metabolic pathways shape the rhizomicrobiome, a correlation network analysis was conducted among the metabolic pathway-related genes and the rhizomicrobiome of rice. Compared to WT, higher bacterial richness (evidenced by the operational taxonomic unit richness) and lower fungal diversity (evidenced by the Shannon index) were observed in both SL deficient dwarf17 (d17) and signaling (d14) mutants. Additionally, remarkable differences were observed in the composition of a large number of bacterial communities than the fungal communities in the d17 and d14 mutants with respect to the WT. The abundance of certain beneficial bacterial taxa, including Nitrosomonadaceae and Rhodanobacter, were significantly decreased in both mutants relative to the WT. Correlation network analysis between SL-regulated metabolic pathway-associated genes and rhizomicrobiome proposed a role for SL-dependent metabolic pathways in shaping rhizomicrobiome composition. Taken together, our study suggests that SL biosynthesis and signaling play a key role in determining the rice rhizomicrobiome, directly or indirectly, through the mediation of distinct metabolic pathways. Based on our findings, the genetic modulation of rice SL biosynthesis and/or signaling pathways may help to recruit/increase the abundance of the desired rhizomicrobiome, which may assist in the stress resilience of rice. |
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| AbstractList | The rhizomicrobiome helps the host plant to better adapt to environmental stresses. In contrast, plant-derived metabolic substances, including phytohormones, play an active role in structuring rhizomicrobiome. Although strigolactones (SLs), a group of phytohormones, serve as potential rhizosphere signaling molecules, their contributions in shaping the rice (Oryza sativa) rhizomicrobiome remain elusive. To address this issue, we compared the rhizomicrobiome of rice mutants defective in either SL biosynthesis or signaling and wild-type (WT) plants. To understand whether SL-regulated metabolic pathways shape the rhizomicrobiome, a correlation network analysis was conducted among the metabolic pathway-related genes and the rhizomicrobiome of rice. Compared to WT, higher bacterial richness (evidenced by the operational taxonomic unit richness) and lower fungal diversity (evidenced by the Shannon index) were observed in both SL deficient dwarf17 (d17) and signaling (d14) mutants. Additionally, remarkable differences were observed in the composition of a large number of bacterial communities than the fungal communities in the d17 and d14 mutants with respect to the WT. The abundance of certain beneficial bacterial taxa, including Nitrosomonadaceae and Rhodanobacter, were significantly decreased in both mutants relative to the WT. Correlation network analysis between SL-regulated metabolic pathway-associated genes and rhizomicrobiome proposed a role for SL-dependent metabolic pathways in shaping rhizomicrobiome composition. Taken together, our study suggests that SL biosynthesis and signaling play a key role in determining the rice rhizomicrobiome, directly or indirectly, through the mediation of distinct metabolic pathways. Based on our findings, the genetic modulation of rice SL biosynthesis and/or signaling pathways may help to recruit/increase the abundance of the desired rhizomicrobiome, which may assist in the stress resilience of rice. •Strigolactone (SL) phytohormones determine the rhizomicrobiome in rice.•SL-mediated metabolic pathways are likely to be responsible for the regulation of rhizomicrobiome in rice.•Genetic modulation of rice SL biosynthesis and/or signaling may promote the abundance of specific beneficial bacterial taxa. The rhizomicrobiome helps the host plant to better adapt to environmental stresses. In contrast, plant-derived metabolic substances, including phytohormones, play an active role in structuring rhizomicrobiome. Although strigolactones (SLs), a group of phytohormones, serve as potential rhizosphere signaling molecules, their contributions in shaping the rice (Oryza sativa) rhizomicrobiome remain elusive. To address this issue, we compared the rhizomicrobiome of rice mutants defective in either SL biosynthesis or signaling and wild-type (WT) plants. To understand whether SL-regulated metabolic pathways shape the rhizomicrobiome, a correlation network analysis was conducted among the metabolic pathway-related genes and the rhizomicrobiome of rice. Compared to WT, higher bacterial richness (evidenced by the operational taxonomic unit richness) and lower fungal diversity (evidenced by the Shannon index) were observed in both SL deficient dwarf17 (d17) and signaling (d14) mutants. Additionally, remarkable differences were observed in the composition of a large number of bacterial communities than the fungal communities in the d17 and d14 mutants with respect to the WT. The abundance of certain beneficial bacterial taxa, including Nitrosomonadaceae and Rhodanobacter, were significantly decreased in both mutants relative to the WT. Correlation network analysis between SL-regulated metabolic pathway-associated genes and rhizomicrobiome proposed a role for SL-dependent metabolic pathways in shaping rhizomicrobiome composition. Taken together, our study suggests that SL biosynthesis and signaling play a key role in determining the rice rhizomicrobiome, directly or indirectly, through the mediation of distinct metabolic pathways. Based on our findings, the genetic modulation of rice SL biosynthesis and/or signaling pathways may help to recruit/increase the abundance of the desired rhizomicrobiome, which may assist in the stress resilience of rice. The rhizomicrobiome helps the host plant to better adapt to environmental stresses. In contrast, plant-derived metabolic substances, including phytohormones, play an active role in structuring rhizomicrobiome. Although strigolactones (SLs), a group of phytohormones, serve as potential rhizosphere signaling molecules, their contributions in shaping the rice (Oryza sativa) rhizomicrobiome remain elusive. To address this issue, we compared the rhizomicrobiome of rice mutants defective in either SL biosynthesis or signaling and wild-type (WT) plants. To understand whether SL-regulated metabolic pathways shape the rhizomicrobiome, a correlation network analysis was conducted among the metabolic pathway-related genes and the rhizomicrobiome of rice. Compared to WT, higher bacterial richness (evidenced by the operational taxonomic unit richness) and lower fungal diversity (evidenced by the Shannon index) were observed in both SL deficient dwarf17 (d17) and signaling (d14) mutants. Additionally, remarkable differences were observed in the composition of a large number of bacterial communities than the fungal communities in the d17 and d14 mutants with respect to the WT. The abundance of certain beneficial bacterial taxa, including Nitrosomonadaceae and Rhodanobacter, were significantly decreased in both mutants relative to the WT. Correlation network analysis between SL-regulated metabolic pathway-associated genes and rhizomicrobiome proposed a role for SL-dependent metabolic pathways in shaping rhizomicrobiome composition. Taken together, our study suggests that SL biosynthesis and signaling play a key role in determining the rice rhizomicrobiome, directly or indirectly, through the mediation of distinct metabolic pathways. Based on our findings, the genetic modulation of rice SL biosynthesis and/or signaling pathways may help to recruit/increase the abundance of the desired rhizomicrobiome, which may assist in the stress resilience of rice.The rhizomicrobiome helps the host plant to better adapt to environmental stresses. In contrast, plant-derived metabolic substances, including phytohormones, play an active role in structuring rhizomicrobiome. Although strigolactones (SLs), a group of phytohormones, serve as potential rhizosphere signaling molecules, their contributions in shaping the rice (Oryza sativa) rhizomicrobiome remain elusive. To address this issue, we compared the rhizomicrobiome of rice mutants defective in either SL biosynthesis or signaling and wild-type (WT) plants. To understand whether SL-regulated metabolic pathways shape the rhizomicrobiome, a correlation network analysis was conducted among the metabolic pathway-related genes and the rhizomicrobiome of rice. Compared to WT, higher bacterial richness (evidenced by the operational taxonomic unit richness) and lower fungal diversity (evidenced by the Shannon index) were observed in both SL deficient dwarf17 (d17) and signaling (d14) mutants. Additionally, remarkable differences were observed in the composition of a large number of bacterial communities than the fungal communities in the d17 and d14 mutants with respect to the WT. The abundance of certain beneficial bacterial taxa, including Nitrosomonadaceae and Rhodanobacter, were significantly decreased in both mutants relative to the WT. Correlation network analysis between SL-regulated metabolic pathway-associated genes and rhizomicrobiome proposed a role for SL-dependent metabolic pathways in shaping rhizomicrobiome composition. Taken together, our study suggests that SL biosynthesis and signaling play a key role in determining the rice rhizomicrobiome, directly or indirectly, through the mediation of distinct metabolic pathways. Based on our findings, the genetic modulation of rice SL biosynthesis and/or signaling pathways may help to recruit/increase the abundance of the desired rhizomicrobiome, which may assist in the stress resilience of rice. |
| Author | Nasir, Fahad Li, Xiujun Tian, Chunjie Tian, Lei Shi, Shaohua Gao, Yingzhi Ma, Lina Chang, Chunling |
| Author_xml | – sequence: 1 givenname: Fahad surname: Nasir fullname: Nasir, Fahad organization: Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin Province, China – sequence: 2 givenname: Shaohua surname: Shi fullname: Shi, Shaohua organization: Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin Province, China – sequence: 3 givenname: Lei surname: Tian fullname: Tian, Lei organization: Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin Province, China – sequence: 4 givenname: Chunling surname: Chang fullname: Chang, Chunling organization: Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin Province, China – sequence: 5 givenname: Lina surname: Ma fullname: Ma, Lina organization: Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin Province, China – sequence: 6 givenname: Xiujun surname: Li fullname: Li, Xiujun organization: Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin Province, China – sequence: 7 givenname: Yingzhi surname: Gao fullname: Gao, Yingzhi email: gaoyz108@nenu.edu.cn organization: Key Laboratory of Vegetation Ecology, Ministry of Education, Institute of Grassland Science, Northeast Normal University, Changchun 130024, Jilin Province, China – sequence: 8 givenname: Chunjie surname: Tian fullname: Tian, Chunjie email: tiancj@neigae.ac.cn organization: Key Laboratory of Mollisols Agroecology, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, Jilin Province, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31300137$$D View this record in MEDLINE/PubMed |
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| Keywords | RNA-sequencing Oryza sativa Strigolactones Metabolic pathways Rhizomicrobiome |
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| Snippet | •Strigolactone (SL) phytohormones determine the rhizomicrobiome in rice.•SL-mediated metabolic pathways are likely to be responsible for the regulation of... The rhizomicrobiome helps the host plant to better adapt to environmental stresses. In contrast, plant-derived metabolic substances, including phytohormones,... |
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| SubjectTerms | bacterial communities biochemical pathways biosynthesis fungal communities fungi genes host plants Lactones - metabolism Metabolic pathways Microbiota mutants Nitrosomonadaceae Oryza - metabolism Oryza sativa Rhizome - microbiology Rhizomicrobiome rhizosphere Rhodanobacter rice RNA-sequencing Signal Transduction Strigolactones |
| Title | Strigolactones shape the rhizomicrobiome in rice (Oryza sativa) |
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