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Nature Biotechnology
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NRT1.1B is associated with root microbiota composition and nitrogen use in field-grown rice

Nature Biotechnologyvolume 37, pages676–684 (2019)Cite this article

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Abstract

Nitrogen-use efficiency ofindica varieties of rice is superior to that ofjaponica varieties. We apply 16S ribosomal RNA gene profiling to characterize root microbiota of 68indica and 27japonica varieties grown in the field. We find thatindica andjaponica recruit distinct root microbiota. Notably,indica-enriched bacterial taxa are more diverse, and contain more genera with nitrogen metabolism functions, thanjaponica-enriched taxa. Using genetic approaches, we provide evidence thatNRT1.1B, a rice nitrate transporter and sensor, is associated with the recruitment of a large proportion ofindica-enriched bacteria. Metagenomic sequencing reveals that the ammonification process is less abundant in the root microbiome of thenrt1.1b mutant. We isolated 1,079 pure bacterial isolates fromindica andjaponica roots and derived synthetic communities (SynComs). Inoculation of IR24, anindica variety, with anindica-enriched SynCom improved rice growth in organic nitrogen conditions compared with ajaponica-enriched SynCom. The links between plant genotype and root microbiota membership established in this study will inform breeding strategies to improve nitrogen use in crops.

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Fig. 1: Root microbiota ofindica andjaponica.
Fig. 2: Random-forest model detects bacterial taxa that accurately predictindica andjaponica subspeciation.
Fig. 3: Taxonomic and functional characteristics of differential bacteria between theindica andjaponica root microbiota.
Fig. 4:NRT1.1B contributes to the variation in the root microbiota ofindica andjaponica.
Fig. 5: Rice root-associated bacterial culture collections capture the majority of bacterial species that are reproducibly detectable by culture-independent sequencing.
Fig. 6:Indica-enriched SynCom have stronger ability to promote rice growth under the supply of organic nitrogen thanjaponica-enriched SynCom.

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Data availability

Raw sequence data reported in this paper have been deposited (PRJCA001214) in the Genome Sequence Archive in the BIG Data Center62, Chinese Academy of Sciences under accession codesCRA001372 for bacterial 16S rRNA gene sequencing data andCRA001362 for metagenomic sequencing data that are publicly accessible athttp://bigd.big.ac.cn/gsa. All pure strains (Supplementary Table11) are deposited in two national culture collection centers, the China Natural Gene Bank and the Agricultural Culture Collection of China. All information about these strains, such as the 16S rRNA gene sequences, taxonomy and isolation details, as well as any further updates are available athttp://bailab.genetics.ac.cn/culture_collection/.

Code availability

Scripts employed in the computational analyses are available athttps://github.com/microbiota/Zhang2019NBT.

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Acknowledgements

We thank P. Schulze-Lefert and S. Hacquard at the Max Planck Institute for Plant Breeding Research for their suggestions for improving the manuscript. This work was financially supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (grant nos. XDB11020700 to Y.B. and XDA08010104 to C.C.), the Key Research Program of Frontier Sciences of the Chinese Academy of Science (grant nos. QYZDB-SSW-SMC021 to Y.B. and QYZDJ-SSW-SMC014 to C.C.), the National Natural Science Foundation of China (grant nos. 31772400 to Y.B. and 31801945 to J.Z.), and the Key Research Program of the Chinese Academy of Sciences (grant no. KFZD-SW-219 to Y.B.). J.Z. is supported by the CPSF-CAS Joint Foundation for Excellent Postdoctoral Fellows (grant no. 2016LH00012). Y.B. is supported by the Thousand Youth Talents Plan (grant no. 2060299).

Author information

Author notes

  1. These authors contributed equally: Jingying Zhang, Yong-Xin Liu, Na Zhang, Bin Hu, Tao Jin.

Authors and Affiliations

  1. State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, The Innovative Academy of Seed Design, Chinese Academy of Sciences, Beijing, China

    Jingying Zhang, Yong-Xin Liu, Na Zhang, Bin Hu, Haoran Xu, Yuan Qin, Xiaoning Zhang, Xiaoxuan Guo, Shouyun Cao, Xin Wang, Chao Wang, Hui Wang, Baoyuan Qu, Chengcai Chu & Yang Bai

  2. CAS-JIC Centre of Excellence for Plant and Microbial Science, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China

    Jingying Zhang, Yong-Xin Liu, Na Zhang, Haoran Xu, Yuan Qin, Xiaoning Zhang, Xiaoxuan Guo, Xin Wang, Chao Wang, Hui Wang, Baoyuan Qu & Yang Bai

  3. College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China

    Na Zhang, Haoran Xu, Yuan Qin, Xiaoning Zhang, Hui Wang, Chengcai Chu & Yang Bai

  4. BGI-Shenzhen, Shenzhen, China

    Tao Jin, Pengxu Yan & Guangyi Fan

  5. BGI-Qingdao, BGI-Shenzhen, Qingdao, China

    Tao Jin, Pengxu Yan & Guangyi Fan

  6. China National Genebank-Shenzhen, BGI-Shenzhen, Shenzhen, China

    Tao Jin, Pengxu Yan & Guangyi Fan

  7. Key Lab of Plant–Soil Interactions, MOE, College of Resources and Environmental Sciences, China Agricultural University, Beijing, China

    Jing Hui & Lixing Yuan

  8. Department of Plant Microbe Interactions, Max Planck Institute for Plant Breeding Research, Cologne, Germany

    Ruben Garrido-Oter

  9. Cluster of Excellence on Plant Sciences, Dusseldorf, Germany

    Ruben Garrido-Oter

Authors
  1. Jingying Zhang

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  2. Yong-Xin Liu

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  3. Na Zhang

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  4. Bin Hu

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  5. Tao Jin

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  10. Xiaoxuan Guo

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  11. Jing Hui

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  13. Xin Wang

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  19. Ruben Garrido-Oter

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  20. Chengcai Chu

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Contributions

C.C. and Y.B. conceived the study and supervised the project. J.Z. and N.Z. performed the experiments. Y.-X.L. analyzed the data of 16S rRNA gene profiling. B.H. and L.Y. coordinated field experiments and revised the manuscript. T.J., P.Y. and R.G.-O. analyzed the metagenomic data. X.Z., Y.Q. and G.F. were involved in the informatics analysis. J.H. performed the soil properties analysis. S.C., H.X., X.W., C.W., H.W. and B.Q. participated in growing plants and harvesting samples. X.G. optimized the protocol of library preparation for the 16S rRNA gene profiling. J.Z., C.C. and Y.B. wrote the manuscript.

Corresponding authors

Correspondence toChengcai Chu orYang Bai.

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Integrated supplementary information

Supplementary Fig. 1 Coverage of members in the root bacterial microbiota by the representativeindica andjaponica varieties.

(a) Rarefaction curves of detected bacterial species of the root microbiota reach the saturation stage with increasing numbers of samples, indicating that the root microbiota in our population capture most root bacteria members from each rice subspecies.Indica andjaponica varieties in two locations are shown separately. (b) Rarefaction curves of detected bacterial OTUs of the root microbiota fromindica andjaponica varieties reach saturation stage with increasing sequencing depth. Each vertical bar represents standard error. The numbers of replicated samples in this figure are as follows: in field I,indica (n = 201),japonica (n = 80), soil (n = 12); in field II,indica (n = 201),japonica (n = 81), soil (n = 12).

Supplementary Fig. 2 Comparison of the root microbiota ofindica andjaponica varieties.

(a,b) Principal coordinate analysis with unweighted (a) and weighted (b) UniFrac distance show that the root microbiota ofindica separate from that ofjaponica in field I in the first two axes, indicating that the root microbiota ofindica are distinct from that ofjaponica (P < 0.001, PERMANOVA by Adonis). Ellipses cover 68% of the data for each rice subspecies. (c,d) Principal coordinate analysis with unweighted (c) and weighted (d) UniFrac distance showing that the root microbiota ofindica separate from those ofjaponica in field II in the first two axes, revealing that root microbiota ofindica are distinct from those ofjaponica (P < 0.001, PERMANOVA by Adonis). The numbers of replicated samples are as follows: in field I,indica (n = 201),japonica (n = 80); in field II,indica (n = 201),japonica (n = 81).

Supplementary Fig. 3 Comparison of the root microbiota in two fields.

(a,b) Unconstrained (a) and constrained (b) principal coordinate analysis ofindica in field I,japonica in field I,indica in field II, andjaponica in field II with Bray-Curtis distance. (c,d) Principal coordinate analysis ofindica in field I,japonica in field I,indica in field II, andjaponica in field II with unweighted (c) and weighted UniFrac (d) distance. Ellipses cover 68% of the data for each rice subspecies. The numbers of replicated samples are as follows: in field I,indica (n = 201),japonica (n = 80); in field II,indica (n = 201),japonica (n = 81).

Supplementary Fig. 4 Comparison of within-sample diversity (α-diversity) betweenindica andjaponica.

(a,b) Chao 1 (a) and observed OTUs (b) of the root microbiota ofindica,japonica, and corresponding unplanted bulk soils in two fields. The numbers of replicated samples are as follows: in field I,indica (n = 201),japonica (n = 80), soil (n = 12); in field II,indica (n = 201),japonica (n = 81), soil (n = 12). Data in two locations show the consistent trend that the root microbiota ofindica show higher alpha diversity than those ofjaponica. The horizontal bars within boxes represent median. The tops and bottoms of boxes represent 75th and 25th percentiles, respectively. The upper and lower whiskers extend to data no more than 1.5 × the interquartile range from the upper edge and lower edge of the box, respectively.

Supplementary Fig. 5 Taxonomic composition of theindica- andjaponica-enriched OTUs.

(a,b) The relative abundance ofindica-enriched (a) andjaponica-enriched (b) OTUs at the phylum level. Proteobacteria are shown at the class level.

Supplementary Fig. 6 Function and time-series shift of theindica- andjaponica-enriched OTUs.

(a) Functional annotation ofindica-enriched OTUs by FAPROTAX. The presence of functions is shown in red. (b) Shift of relative abundance ofindica-enriched OTUs according to time-course data from the rice root microbiota in the field in Changping Farm17. (c) Functional annotation ofjaponica-enriched OTUs by FAPROTAX. The presence of functions is shown in red. (d) Shift of relative abundance ofjaponica-enriched OTUs according to time-course data from the rice root microbiota in the field in Changping Farm17.

Supplementary Fig. 7 Correlation between the natural variation ofNRT1.1B and nitrogen-related functions inindica andjaponica populations.

(a–e) The natural variation inNRT1.1B inindica andjaponica populations is correlated with nitrogen-related functions in root microbiota fromindica andjaponica populations, including nitrite ammonification (a) (P = 2.2 × 10–16 in field I;P = 1.8 × 10–12 in field II, two-sidedt-test), nitrate reduction (b) (P = 1.1 × 10–13 in field I;P = 2.1 × 10–8 in field II, two-sidedt-test), respiration of nitrate (c) (P = 2.2 × 10–16 in field I;P = 6.1 × 10–13 in field II, two-sidedt-test), nitrite respiration (d) (P = 2.4 × 10–16 in field I;P = 7.2 × 10–13 in field II, two-sidedt-test) and nitrogen respiration (e) (P = 2.2 × 10–16 in field I;P = 6.8 × 10–13 in field II, two-sidedt-test).NRT1.1Bindica harbors a “T” at 980 bp downstream of the ATG start codon andNRT1.1Bjaponica harbors a “C” at the same position, resulting in an amino acid substitution (p. Met327Thr). The numbers of replicated samples are as follows: in field I,indica (n = 192),japonica (n = 86); in field II,indica (n = 192),japonica (n = 87).

Supplementary Fig. 8NRT1.1B and its natural variation modulate the assembly of the rice root microbiota.

(a,b) Principal coordinate analysis with unweighted (a) and weighted (b) UniFrac distance showing that the root microbiota of ZH11 (wild-type),nrt1.1b, NipponbareNRT1.1Bindica, and NipponbareNRT1.1Bjaponica separate in the first two axes. Ellipses cover 68% of the data for each genotype. (c) Constrained principal coordinate analysis showing that 57.1% of the root microbiota variations are explained by genotypes (ZH11,nrt1.1b,NRT1.1Bindica, andNRT1.1Bjaponica). The numbers of replicated samples are as follows: ZH11 (n = 16),nrt1.1b (n = 14),NRT1.1Bindica (n = 15),NRT1.1Bjaponica (n = 15). (d,e) A full factorial replication experiment validates the conclusion thatNRT1.1B and its natural variation modulate the assembly of the rice root microbiota. Unconstrained (d) and constrained (e) principal coordinate analysis with Bray-Curtis distance showing that the root microbiota of ZH11 (wild-type),nrt1.1b,NRT1.1Bindica, andNRT1.1Bjaponica separate in the first two axes. The plants were grown in different fields and at different time from the samples in Fig.4. Ellipses cover 68% of the data for each genotype. The numbers of replicated samples are as follows: ZH11 (n = 14),nrt1.1b (n = 10),NRT1.1Bindica (n = 15),NRT1.1Bjaponica (n = 15).

Supplementary Fig. 9 OTUs associated withNRT1.1B in the field condition related to Fig.4.

(a) Enrichment and depletion of OTUs in thenrt1.1b mutant compared with wild-type ZH11. Each point represents an individual OTU, and the position along the x axis represents the abundance fold change between thenrt1.1b mutant and wild-type. (b) Heat map showing the relative abundance of the differential OTUs between thenrt1.1b mutant and wild-type ZH11. (c) OTUs enriched inNRT1.1Bindica orNRT1.1Bjaponica. Each point represents an individual OTU, and the position along the x axis represents the abundance fold change betweenNRT1.1Bindica orNRT1.1Bjaponica. (d) Heat map showing the relative abundance of the differential OTUs betweenNRT1.1Bindica andNRT1.1Bjaponica. The numbers of replicated samples are as follows: ZH11 (n = 16),nrt1.1b (n = 14),NRT1.1Bindica (n = 15), andNRT1.1Bjaponica (n = 15).

Supplementary Fig. 10 Experimental procedure for isolation and identification of rice root-associated bacteria.

Step 1–4 illustrate the isolation procedure; Step 5–11 illustrate the identification of cultivated rice root-associated bacteria by the improved two-step barcoded system.

Supplementary Fig. 11 The scheme for the previous high-throughput barcoding system to determine 16S rRNA gene sequences covering regions V5–V7 of bacterial isolates.

A previously published two-step barcoded pyrosequencing procedure (Bai, Y.et al. Functional overlap of theArabidopsis leaf and root microbiota.Nature528, 364–369, 2015). Please note that the second step PCR generates chimera sequences that will contain mislabeled plate and well barcodes for bacterial identification.

Supplementary Fig. 12 Plant growth with or withoutindica-enriched SynCom under inorganic nitrogen conditions.

(a–c) IR24 (indica) rice plants were grown under different ratios of ammonium and nitrate (0:2, 2:0, and 1:1) with or withoutindica-enriched SynCom. After 2-week bacterial inoculation, rice plants were measured by root length (a), plant height (b), and shoot fresh weight (c). (d–f) Nipponbare (japonica) rice plants were grown under different ratios of ammonium and nitrate (0:2, 2:0, and 1:1) with or withoutindica-enriched SynCom. After 2-week bacterial inoculation, rice plants were measured by root length (d), plant height (e), and shoot fresh weight (f). Different letters indicate significantly different groups (P < 0.05, ANOVA, Tukey-HSD). Boxplots show combined data from three independent inoculation experiments with 4–5 technical replicates each (Supplementary Table13). The horizontal bars within boxes represent medians. The tops and bottoms of boxes represent 75th and 25th percentiles, respectively. The upper and lower whiskers extend to data no more than 1.5 × the interquartile range from the upper edge and lower edge of the box, respectively.

Supplementary Fig. 13 Plant growth withindica- orjaponica-enriched SynCom under inorganic nitrogen conditions.

IR24 rice plants were grown under the inorganic nitrogen condition with and without SynComs, includingindica-enriched SynCom,japonica-enriched SynCom, and corresponding heat-killed bacteria as controls, respectively (Supplementary Table13). After 2-week bacterial inoculation, rice plants were measured by root length (a), plant height (b), and shoot fresh weight (c). Different letters indicate significantly different groups (P < 0.05, ANOVA, Tukey-HSD). Boxplots show combined data from two independent inoculation experiments with 4–5 technical replicates each. The horizontal bars within boxes represent medians. The tops and bottoms of boxes represent 75th and 25th percentiles, respectively. The upper and lower whiskers extend to data no more than 1.5 × the interquartile range from the upper edge and lower edge of the box, respectively.

Supplementary information

Supplementary Figures

Supplementary Figs. 1–13

Supplementary Table 1

Soil properties and cultivation practices of field I and field II on Lingshui farm.

Supplementary Table 2

Information onindica andjaponica varieties.

Supplementary Table 3

Metadata, OTU representative sequences, taxonomy annotation and OTU table.

Supplementary Table 4

Differential phyla and classes of Proteobacteria betweenindica andjaponica.

Supplementary Table 5

Random-forest: accuracy of the random-forest model at each taxonomy level; feature importance at the family level; outcomes of prediction.

Supplementary Table 6

Differential abundance of OTUs betweenindica andjaponica; details of OTUs in each part of the Venn diagrams in Fig. 3.

Supplementary Table 7

Abundance of OTUs in time-course data and functional annotation by FAPROTAX.

Supplementary Table 8

Differential abundances of OTUs between thenrt1.1b mutant and wild-type ZH11; differential abundances of OTUs betweenNRT1.1Bindica andNRT1.1Bjaponica; details of OTUs in each part of the Venn diagrams of Fig. 4.

Supplementary Table 9

KEGG orthology of metagenomes in ZH11 and thenrt1.1b mutant.

Supplementary Table 10

Detailed information of all cultivated CFUs and unique bacterial sequences from rice root.

Supplementary Table 11

Taxonomy and sequences of 1,079 bacterial stocks in rice root bacterial culture collection.

Supplementary Table 12

Experimental design of synthetic communities on germ-free plants related to the nitrogen assay.

Supplementary Table 13

Phenotypes of rice plants under inorganic nitrogen and organic nitrogen conditions with and without SynComs.

Supplementary Table 14

Primer sequences and experimental procedures for culture-independent community profiling and bacterial identification.

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Zhang, J., Liu, YX., Zhang, N.et al.NRT1.1B is associated with root microbiota composition and nitrogen use in field-grown rice.Nat Biotechnol37, 676–684 (2019). https://doi.org/10.1038/s41587-019-0104-4

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