Multi-omics analysis of soil microbiota and metabolites in dryland wheat fields under different tillage methods

No-tillage and subsoiling can improve soil aggregate structure and realize a synergistic effect of soil carbon and nitrogen retention compared with deep tillage. This study aimed to investigate the effects of different tillage methods on the microbiome and metabolites in wheat rhizosphere. Results indicated that no significant differences in the diversity of soil bacterial and fungal communities were observed among the tillage methods. Analysis revealed that no-tillage enriched specific genera such as Cryptosporangium, Crossiella, Rhodothermaceae, Leptothrix, Stilbella, Diutina, and Pyrenochaetopsis, while subsoiling was associated with Rubrobacter, Latescibacteraceae, Nitrospira, Rokubacteriales, and Ctenomyces. Deep tillage, on the other hand, showed significant associations with Nocardia, Aeromicrobium, Sphingopyxis, Cordyceps, and Subulicystidium. Metabolomic analysis identified differential metabolites involved in various pathways, including the biosynthesis of plant secondary metabolites, ABC transporters, and starch and sucrose metabolism. Correlation analysis revealed a significant interaction between microorganisms and metabolites in wheat rhizosphere. Bacteria at the genus level exhibited greater associations with differential metabolites. In conclusion, different tillage practices can alter the composition of microbial communities and metabolites in wheat rhizosphere, and their interactions may affect soil fertility and wheat growth.

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Publication Details

Journal
Scientific Reports
Published
2024-10-14
DOI
https://doi.org/10.1038/s41598-024-74620-0
Citations
4
Primary Topic
Soil Carbon and Nitrogen Dynamics
Type
article
Field-Weighted Citation Impact
1.33

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article

Multi-omics analysis of soil microbiota and metabolites in dryland wheat fields under different tillage methods

Shuangdui Yan, Lihao Chen, Longxing Wang, Ruifu Zhang et al.
4 citations
Scientific Reports
Soil Carbon and Nitrogen Dynamics
1.33
article

Multi-omics analysis of soil microbiota and metabolites in dryland wheat fields under different tillage methods

Shuangdui Yan, Lihao Chen, Longxing Wang, Ruifu Zhang, Tong Xu, Qiuyan Yan, Fei Dong, Feng Li
article en
4 citations

Abstract

No-tillage and subsoiling can improve soil aggregate structure and realize a synergistic effect of soil carbon and nitrogen retention compared with deep tillage. This study aimed to investigate the effects of different tillage methods on the microbiome and metabolites in wheat rhizosphere. Results indicated that no significant differences in the diversity of soil bacterial and fungal communities were observed among the tillage methods. Analysis revealed that no-tillage enriched specific genera such as Cryptosporangium, Crossiella, Rhodothermaceae, Leptothrix, Stilbella, Diutina, and Pyrenochaetopsis, while subsoiling was associated with Rubrobacter, Latescibacteraceae, Nitrospira, Rokubacteriales, and Ctenomyces. Deep tillage, on the other hand, showed significant associations with Nocardia, Aeromicrobium, Sphingopyxis, Cordyceps, and Subulicystidium. Metabolomic analysis identified differential metabolites involved in various pathways, including the biosynthesis of plant secondary metabolites, ABC transporters, and starch and sucrose metabolism. Correlation analysis revealed a significant interaction between microorganisms and metabolites in wheat rhizosphere. Bacteria at the genus level exhibited greater associations with differential metabolites. In conclusion, different tillage practices can alter the composition of microbial communities and metabolites in wheat rhizosphere, and their interactions may affect soil fertility and wheat growth.

Scientific ReportsVol. 14(1)
Nanjing Agricultural University (CN), Shanxi Agricultural University (CN)
National Natural Science Foundation of China, Shanxi Agricultural University, National Key Research and Development Program of China
Zero hunger
Openalex Percentile: Top 18%
Soil Carbon and Nitrogen Dynamics
1.33
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