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Hiseq Base Molecular Characterization of Soil Microbial Community, Diversity Structure, and Predictive Functional Profiling in Continuous Cucumber Planted Soil Affected by Diverse Cropping Systems in an Intensive Greenhouse Region of Northern China.

Ahmad Ali | Muhammad Imran Ghani | Yuhong Li | Haiyan Ding | Huanwen Meng | Zhihui Cheng
International journal of molecular sciences | 2019

Cover crops are key determinants of the ecological stability and sustainability of continuous cropping soils. However, their agro-ecological role in differentially reshaping the microbiome structure and functioning under a degraded agroecosystem remains poorly investigated. Therefore, structural and metabolic changes in soil bacterial community composition in response to diverse plant species were assessed. Winter catch leafy vegetables crops were introduced as cover plants in a cucumber-fallow period. The results indicate that cover crop diversification promoted beneficial changes in soil chemical and biological attributes, which increased crop yields in a cucumber double-cropping system. Illumina high-throughput sequencing of 16S rRNA genes indicated that the bacterial community composition and diversity changed through changes in the soil properties. Principal component analysis (PCA) coupled with non-metric multidimensional scaling (NMDS) analysis reveals that the cover planting shaped the soil microbiome more than the fallow planting (FC). Among different cropping systems, spinach-cucumber (SC) and non-heading Chinese cabbage-cucumber (NCCC) planting systems greatly induced higher soil nutrient function, biological activity, and bacterial diversity, thus resulting in higher cucumber yield. Quantitative analysis of linear discriminant analysis effect size (LEfSe) indicated that Proteobacteria, Actinobacteria, Bacteroidetes, and Acidobacteria were the potentially functional and active soil microbial taxa. Rhizospheres of NCCC, leaf lettuce-cucumber (LLC), coriander-cucumber (CC), and SC planting systems created hotspots for metabolic capabilities of abundant functional genes, compared to FC. In addition, the predictive metabolic characteristics (metabolism and detoxification) associated with host-plant symbiosis could be an important ecological signal that provides direct evidence of mediation of soil structure stability. Interestingly, the plant density of non-heading Chinese cabbage and spinach species was capable of reducing the adverse effect of arsenic (As) accumulation by increasing the function of the arsenate reductase pathway. Redundancy analysis (RDA) indicated that the relative abundance of the core microbiome can be directly and indirectly influenced by certain environmental determinants. These short-term findings stress the importance of studying cover cropping systems as an efficient biological tool to protect the ecological environment. Therefore, we can speculate that leafy crop diversification is socially acceptable, economically justifiable, and ecologically adaptable to meet the urgent demand for intensive cropping systems to promote positive feedback between crop-soil sustainable intensification.

Pubmed ID: 31141960

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Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.

This is a list of tools and resources that we have found mentioned in this publication.


UPARSE (tool)

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An open-source software package for describing and comparing microbial communities. It incorporates the functionality of a number of computational tools, calculators, and visualization tools.

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RRID:SCR_014609

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Algorithm for high-dimensional biomarker discovery and explanation that identifies genes, pathways, or taxa characterizing the differences between two or more biological conditions. The algorithm identifies features that are statistically different among biological classes, then performs additional tests to assess whether these differences are consistent with respect to expected biological behavior. Statistical significance and biological relevance are emphasized.

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Metastats (tool)

RRID:SCR_014610

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