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. 2023 Nov 21;11(12):2829.
doi: 10.3390/microorganisms11122829.

The Salinity Survival Strategy of Chenopodium quinoa: Investigating Microbial Community Shifts and Nitrogen Cycling in Saline Soils

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The Salinity Survival Strategy of Chenopodium quinoa: Investigating Microbial Community Shifts and Nitrogen Cycling in Saline Soils

Xuli Zhao et al. Microorganisms. .

Abstract

Quinoa is extensively cultivated for its nutritional value, and its exceptional capacity to endure elevated salt levels presents a promising resolution to the agricultural quandaries posed by salinity stress. However, limited research has been dedicated to elucidating the correlation between alterations in the salinity soil microbial community and nitrogen transformations. To scrutinize the underlying mechanisms behind quinoa's salt tolerance, we assessed the changes in microbial community structure and the abundance of nitrogen transformation genes across three distinct salinity thresholds (1 g·kg-1, 3 g·kg-1, and 6 g·kg-1) at two distinct time points (35 and 70 days). The results showed the positive effect of quinoa on the soil microbial community structure, including changes in key populations and its regulatory role in soil nitrogen cycling under salt stress. Choroflexi, Acidobacteriota, and Myxococcota were inhibited by increased salinity, while the relative abundance of Bacteroidota increased. Proteobacteria and Actinobacteria showed relatively stable abundances across time and salinity levels. Quinoa possesses the ability to synthesize or modify the composition of keystone species or promote the establishment of highly complex microbial networks (modularity index > 0.4) to cope with fluctuations in external salt stress environments. Furthermore, quinoa exhibited nitrogen (N) cycling by downregulating denitrification genes (nirS, nosZ), upregulating nitrification genes (Archaeal amoA (AOA), Bacterial amoA (AOB)), and stabilizing nitrogen fixation genes (nifH) to absorb nitrate-nitrogen (NO3-_N). This study paves the way for future research on regulating quinoa, promoting soil microbial communities, and nitrogen transformation in saline environments.

Keywords: Chenopodium quinoa; microbial community; nitrogen transformations; saline soils; salt tolerance.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The average temperature of the greenhouse.
Figure 2
Figure 2
Experiential design. (Untreated and artificially treated soil was filled in each experimental pot; height 22 cm; diameter 18 cm).
Figure 3
Figure 3
Microbial community diversity and composition of bacteria and fungi. (a) Boxplots display the Shannon index, and the difference in α-diversity of bacteria and fungi was detected by the Kruskal–Wallis test; ‘*’ for p < 0.05. (b) Non-metric multidimensional scaling (NMDS) analysis was based on Bray–Curtis distance for microbial communities, stress < 0.2 (bacteria) and stress < 0.1 (fungi). (c) Venn diagrams display the shared and system-specific OTUs of bacteria and fungi.
Figure 4
Figure 4
Basic physical and chemical properties of soil; ‘*’ for p < 0.05; ‘**’ for p < 0.01; ‘***’ for p < 0.001.
Figure 5
Figure 5
Differentially abundant microbiome at the phylum level; ‘*’ for p < 0.05; ‘**’ for p < 0.01.
Figure 6
Figure 6
Relative abundance of microbial communities at the phylum level in six treatments.
Figure 7
Figure 7
Co-occurrence networks of microbial communities in different treatment groups at the genus level. Topological properties of co-occurrence networks were indicated under each network, including the number of nodes, number of edges, mean degree, density, and the ratio of positive to negative interactions (P/N) of the whole network. (a) Networks of bacterial communities, (b) Networks of fungal communities.
Figure 8
Figure 8
Co-occurrence networks of the microbial communities in the different treatment groups.
Figure 9
Figure 9
Significant responses of keystone taxa. These keystone taxa are further annotated at the phylum level in the heatmap. Calculating the distance between samples using Euclidean Distance, average linkage clustering determines the relationship between the samples.
Figure 10
Figure 10
Redundancy analysis based on the relationships between environmental variables, top 5 phyla (a), and nitrogen functional genes (b) during the overall experimental process. The red arrow represents environmental factors, while the blue arrows respectively represent phyla and nitrogen functional genes.
Figure 11
Figure 11
Relative abundance of nitrogen genes; ‘*’ for p < 0.05; ‘**’ for p < 0.01; ‘***’ for p < 0.001.

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