The core microbiota as a predictor of soil functional traits promotes soil nutrient cycling and wheat production in dryland farming
Lei Liu
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorYa Gao
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorZhiyuan Gao
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorLi Zhu
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorRong Yan
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorWenjie Yang
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorYu Yang
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorCorresponding Author
Jinshan Liu
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Correspondence
Jinshan Liu
Email: [email protected]
Search for more papers by this authorLei Liu
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorYa Gao
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorZhiyuan Gao
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorLi Zhu
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorRong Yan
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorWenjie Yang
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorYu Yang
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Search for more papers by this authorCorresponding Author
Jinshan Liu
Key Laboratory of Plant Nutrition and Agro-Environment in Northwest China, Ministry of Agriculture and Rural Affairs/College of Natural Resources and Environment, Northwest A&F University, Yangling, China
Correspondence
Jinshan Liu
Email: [email protected]
Search for more papers by this authorAbstract
- Host plants and the microbiota living in the rhizosphere are interdependent, mutually reinforced and mutually beneficial but the assembly, functions and microbial interactions of the host-associated microbiota are still unclear.
- Herein, winter wheat was selected as a test plant to explore the assembly process of total bacteria from bulk soil (BS) and rhizosphere soil (RS), and phoD-harbouring bacteria in RS at a long-term (14 years) trial site. We also identified core microbes that are potentially relevant to soil carbon (C), nitrogen (N) and phosphorus (P) cycling genes and soil biogeochemical properties, and investigated the relationships between soil variables, functional genes and wheat productivity.
- The results showed that the microhabitat of the plant, rather than P fertilizer input, was the main factor affecting the microbial diversity, composition and co-occurrence networks. The BS bacterial community was driven by deterministic processes but the RS and phoD bacterial communities were dominated by stochastic processes. The influence of deterministic processes decreased with increasing soil nutrient content. A core microbial community consisted of 10 OTUs in different microhabitats and was significantly related to soil functional genes and properties. In the rhizosphere soil, significant correlations were found between soil variables, soil functional bacteria and genes, and crop productivity.
- Synthesis and applications. This study provides empirical evidence that the assembly process of the microbial community is governed by environmental factors in various soil environments and provides new perspectives on the sustainable improvement of crop productivity.
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CONFLICT OF INTEREST STATEMENT
The authors declare that they have no conflict of interest.
Open Research
DATA AVAILABILITY STATEMENT
All the raw sequencing data were uploaded to the China National GeneBank Sequence Archive with the accession number CNP0000424.
Supporting Information
| Filename | Description |
|---|---|
| fec14388-sup-0001-Supinfo.docxWord 2007 document , 3 MB |
Appendix S1. Description of experimental design. Appendix S2. Description of soil physical and chemical determination. Appendix S3. Details on amplicon sequencing, PCR amplification and pyrosequencing. Table S1. Spearman correlations between βNTI of BS, RS or phoD bacterial communities and the changes of soil nutrients (based on Euclidean Distance). Table S2. The topological parameters of co-occurrence networks of bacterial and functional genes. Table S3. Fit of the neutral model for the BS and RS and phoD bacterial communities in Low-P and High-P fertilizer input treatments. m indicates the estimated migration rate; R2 indicates the fit to the neutral model. Table S4. The topological parameters of co-occurrence networks of BS, RS and phoD-bacterial communities. Table S5. The topological parameters of co-occurrence networks of functional genes from BS and RS bacteria communities. Table S6. The mantel test between the bacteria and functional genes and soil properties in BS. Table S7. The mantel test between the bacteria and functional genes and soil properties in the RS. Figure S1. The composition and diversity of bulk soil (BS), rhizosphere soil (RS) and phoD bacterial communities with low-P and high-P fertilizer input treatments. (a) OTU Shannon, (b) richness, and (c) Bray–Curtis dissimilarity between low-P and high-P fertilizer input. *p < 0.05; **p < 0.01; ***p < 0.001 for Kruskal–Wallis tests. Figure S2. (a) NTI and (b) βMNTD indices of different bacterial communities with low-P and high-P fertilizer input. (c) PCoA plot based on Bray–Curtis distances depicting the distribution patterns of low-P and high-P fertilizer input. The PERMANOVA and ANOSIM tests were used to assess the significant differences between d low-P and high-P fertilizer input. *p < 0.05; **p < 0.01, ***p < 0.001. Figure S3. Taxonomic composition of (a) BS, (b) RS, and (c) phoD bacterial communities with low-P and high-P fertilizer input at the phylum level. Figure S4. Enrichment and depletion of OTUs between low-P and high-P fertilizer input in (a) BS, (b) RS, and (c) phoD bacterial communities. The contribution of determinism and stochasticity on (d) BS, (e) RS, and (f) phoD bacterial communities’ assembly with low-P and high-P fertilizer input. Figure S5. Variation analysis of the abundance of bacteria in different bacterial communities (a–c) and between low-P and high-P fertilizer input in (c) RS and (d) phoD bacterial communities. Figure S6. Ternary plots depicting the (a) bacterial at phylum level and (b) potential ecological functions significantly enriched in BS, RS and phoD bacterial communities. The size of each circle indicates the relative abundance. Different-colored dots show that function and bacteria are significantly higher in BS, RS, and phoD bacterial communities (p < 0.05), and the numbers in the parentheses denote the numbers of the differentiated functions and bacteria. Figure S7. Phylogenetic Mantel correlogram showing significant phylogenetic signal across short phylogenetic distances in (a) BS, (b) RS and (c) phoD bacterial communities. Solid and open symbols denote significant and nonsignificant correlations, respectively, relating between-OTU niche differences to between-OTU phylogenetic distances across a given phylogenetic distance. Figure S8. Random forest analysis showed the associations between βNTI of the (a) BS, (b) RS, and (c) phoD bacterial communities and the changes in environmental variables. Figure S9. Community potential ecological functions and co-occurrence patterns of BS, RS, and phoD bacterial communities. (a) Metacommunity co-occurrence network of microbial taxa. (b) Differences in degree, (c) betweenness centrality, and (d) closeness centrality between the different bacterial communities. (e-g) Variation analysis of the potential ecological functions of different bacterial communities (BS, RS, and phoD) based on FAPROTAX (top 15). ***p < 0.001 for Kruskal–Wallis tests. The basic topological properties of these networks are shown in Table S2. Figure S10. Phylogenetic Mantel correlogram showing significant phylogenetic signal across short phylogenetic distances in (a) BS, (b) RS, and (c) phoD bacterial communities with low-P and high-P fertilizer input. Solid and open symbols denote significant and nonsignificant correlations, respectively, relating between-OTU niche differences to between-OTU phylogenetic distances across a given phylogenetic distance. Figure S11. Metacommunity co-occurrence network of (a) BS, (b) RS, and (c) phoD bacterial communities with low-P and high-P fertilizer input. Each node represents a significantly enriched OTU in low-P and high-P fertilizer input, respectively. The basic topological properties of these networks are shown in Table S4. Figure S12. Variation analysis of the potential ecological functions of (a) BS, (b) RS, and (c) phoD bacterial communities with low-P and high-P fertilizer input based on FAPROTAX. Figure S13. Occurrence network analysis showing genes involved in soil C, N, and P cycle under (a) BS and (B) RS bacterial communities. Nodes with pink, blue, and green colors represent soil C, N, and P genes. The colored line shows the correlation of the two nodes, with the red line for the positive relationship and the blue line for the negative relationship. The basic topological properties of these networks are shown in Table S5. Figure S14. Difference in the relative abundance of soil C, N, and P cycle genes. Different letters in the same row mean a significant difference at p < 0.05 among the BS and RS bacterial communities (Duncan's test). |
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