Soil microbial diversity and functional capacity associated with the production of edible mushroom Stropharia rugosoannulata in croplands

Abstract

In recent years, a rare edible mushroom Stropharia rugosoannulata has become popular. S. rugosoannulata has the characteristics of easy cultivation, low cost, high output value, and low labor requirement, making its economic benefits significantly superior to those of other planting industries. Accumulating research demonstrates that cultivating edible fungus is advantageous for farming soil. The present experiment used idle croplands in winter for S. rugosoannulata cultivation. We explored the effects of S. rugosoannulata cultivation on soil properties and soil microbial community structure in paddy and dry fields, respectively. We cultivated S. rugosoannulata in the fields after planting chili and rice, respectively. The results showed that Chili-S. rugosoannulata and Rice-S. rugosoannulata planting patterns increased the yield, quality and amino acid content of S. rugosoannulata. By analyzing the soil properties, we found that the Chili-S. rugosoannulata and Rice-S. rugosoannulata cropping patterns increased the total nitrogen, available phosphorus, soil organic carbon, and available potassium content of the soil. We used 16s amplicons for bacteria and internal transcribed spacer (ITS) region for fungi to analyze the microbial communities in rhizosphere soils. Notably, S. rugosoannulata cultivation significantly increased the abundance of beneficial microorganisms such as Chloroflexi, Cladosporium and Mortierella and reduce the abundance of Botryotrichumin and Archaeorhizomyces. We consider S. rugosoannulata cultivation in cropland can improve soil properties, regulate the community structure of soil microorganisms, increase the expression abundance of beneficial organisms and ultimately improve the S. rugosoannulata yield and lay a good foundation for a new round of crops after this edible mushroom cultivation.

Keywords: Functional analysis; Soil bacterial communities; Soil fungal communities; Soil physicochemical properties; Stropharia rugosoannulata.

Figure 1. The quality and yield of S. rugosoannulata in different croplands.

(A) S. rugosoannulata produced in the NC group; (B) S. rugosoannulata produced in the Chili-S. rugosoannulata group; (C) S. rugosoannulata produced in the Rice-S. rugosoannulata group; (D) Yield per mu of S. rugosoannulata in different croplands. Data are mean ± SD (n = 3) and analyzed by one-way ANOVA. *p < 0.05.

Figure 2. Soil properties in different croplands.

(A) The total nitrogen content of Soil before, during, and after cultivating S. rugosoannulata under different rotation patterns; (B) The available phosphorus content of Soil before, during, and after cultivating S. rugosoannulata under different rotation patterns; (C) The organic carbon content of Soil before, during, and after cultivating S. rugosoannulata under different rotation patterns; (D) The available potassium content of Soil before, during, and after cultivating S. rugosoannulata under different rotation patterns; (E) The soil moisture before, during, and after cultivating S. rugosoannulata under different rotation patterns. Data are mean ± SD (n = 3) and analyzed by one-way ANOVA. *p < 0.05.

Figure 3. α-diversity of soil rhizosphere microorganisms after cultivating S. rugosoannulata in different croplands.

(A) ACE index; (B) Chao index; (C) Shannon index; (D) Simpson index of soil rhizosphere microorganisms after cultivating S. rugosoannulata.

Figure 4. Rhizosphere bacterial community structure at phylum level after cultivating S. rugosoannulata in different croplands.

(A) Relative abundance of rhizosphere microbiota at the phylum level after cultivating S. rugosoannulata; (B) percentage of Proteobacteria in each sample from the three groups after cultivating S. rugosoannulata; (C) percentage of Bacteroidetes in each sample from the three groups after cultivating S. rugosoannulata; (D) percentage of Chloroflexi in each sample from the three groups after cultivating S. rugosoannulata; (E) percentage of Actinobacteria in each sample from the three groups after cultivating S. rugosoannulata; (F) Relative abundance of rhizosphere microbiota at the genus level after cultivating S. rugosoannulata; (G) percentage of Sphingomonas in each sample from the three groups after cultivating S. rugosoannulata; (H) percentage of Candidatus_Solibacter in each sample from the three groups after cultivating S. rugosoannulata; (I) percentage of Granulicella in each sample from the three groups after cultivating S. rugosoannulata; (J) percentage of Gemmatimonas each sample from the three groups after cultivating S. rugosoannulata. Data are mean ± SD (n = 6) and analyzed by one-way ANOVA. *p < 0.05.

Figure 5. Rhizosphere fungal community structure at phylum level after cultivating S. rugosoannulata in different croplands.

(A) Relative abundance of rhizosphere fungal at the genus level after cultivating S. rugosoannulata; (B) percentage of Ascomycota in each sample from the three groups after cultivating S. rugosoannulata; (C) percentage of Chytridiomycota in each sample from the three groups after cultivating S. rugosoannulata; (D) percentage of Basidiomycota in each sample from the three groups after cultivating S. rugosoannulata; (E) percentage of Mortierellomycota each sample from the three groups after cultivating S. rugosoannulata; (F) Relative abundance of rhizosphere fungal at the genus level after cultivating S. rugosoannulata; (G) percentage of Stropharia in each sample from the three groups after cultivating S. rugosoannulata; (H) percentage of Myrmecridium in each sample from the three groups after cultivating S. rugosoannulata; (I) percentage of Chaetosphaeria in each sample from the three groups after cultivating S. rugosoannulata; (J) percentage of Scytalidium each sample from the three groups after cultivating S. rugosoannulata. Data are mean ± SD (n = 6) and analyzed by one-way ANOVA. *p < 0.05.

Figure 6. RDA analysis and correlation analysis of bacteria and fungi at the phylum level.

(A) RDA analysis between soil rhizosphere bacteria and environmental factors. (B) RDA analysis between soil rhizosphere fungi and environmental factors. (C) Correlation analysis of soil rhizosphere bacteria at phylum level and S. rugosoannulata amino acid content S. rugosoannulata. (da) Correlation analysis of soil rhizosphere fungi at phylum level and S. rugosoannulata amino acid content S. rugosoannulata.

Figure 7. Prediction of microbial Tax4Fun functional genes in different croplands.

(A) Differential bacterial functional genes between NC group and Chili-S. rugosoannulata group. (B) Differential bacterial functional genes between NC group and Rice-S. rugosoannulata group. (C) Differential fungi functional genes between NC group and Chili-S. rugosoannulata group. (D) Differential fungi functional genes between NC group and Rice-S. rugosoannulata group.