Chicken manure application alters microbial community structure and the distribution of antibiotic-resistance genes in rhizosphere soil of Cinnamomum camphora forests

Abstract

The distribution of antibiotic-resistance genes (ARGs) in environmental soil is greatly affected by livestock and poultry manure fertilization, the application of manure will lead to antibiotic residues and ARGs pollution, and increase the risk of environmental pollution and human health. Cinnamomum camphora is an economically significant tree species in Fujian Province, China. Here, through high-throughput sequencing analysis, significant differences in the composition of the bacterial community and ARGs were observed between fertilized and unfertilized rhizosphere soil. The application of chicken manure organic fertilizer significantly increased the relative abundance and alpha diversity of the bacterial community and ARGs. The content of organic matter, soluble organic nitrogen, available phosphorus, nitrate reductase, hydroxylamine reductase, urease, acid protease, β-glucosidase, oxytetracycline, and tetracycline in the soil of C. camphora forests have significant effects on bacterial community and ARGs. Significant correlations between environmental factors, bacterial communities, and ARGs were observed in the rhizosphere soil of C. camphora forests according to Mantel tests. Overall, the findings of this study revealed that chicken manure organic fertilizer application has a significant effect on the bacterial community and ARGs in the rhizosphere soil of C. camphora forests, and several environmental factors that affect the bacterial community and ARGs were identified.

Keywords: Cinnamomum camphora; antibiotic-resistance genes; bacterial community; chicken manure organic fertilizer; environmental factor.

Figure 1.

Beta-diversity and alpha-diversity analysis of bacterial communities and functional genes in fertilized and unfertilized samples. PCoA plot showing variation in (A) bacterial communities based on the Bray–Curtis distance and (B) ARGs, Tet ARGs, COG genes, and KEGG pathway functional genes in fertilized and unfertilized rhizosphere soil samples (the significance of differences was evaluated using PERMANOVA). The x-axis and y-axis represent the two selected principal axes, and the percentage represents the interpretation value of the principal axis for the difference in sample composition; the scale of x-axis and y-axis is a relative distance, which has no practical significance. (C) Alpha diversity (based on the Shannon index) of the bacterial community in all fertilized and unfertilized samples, and (D) alpha diversity (based on the Shannon index) of ARGs, Tet ARGs, COG genes, and KEGG pathway functional genes in fertilized and unfertilized rhizosphere soil samples. Each point represents different samples with and without fertilization, and the value of y-axis represents the Shannon index value of each sample. Kruskal–Wallis nonparametric test was used to obtain the P-value of the difference between groups, and Dunn’s test was used to test the significance of the difference. * indicates significant differences at P < .05; ** indicates highly significant differences at P < .01.

Figure 2.

Analysis of the differentially expressed genes of bacterial OTUs and ARGs in fertilized and unfertilized samples. (A) Differences in the number of bacterial OTUs between all fertilized and unfertilized samples, bulk soil, rhizosphere soil, and root endosphere. (B) Enriched and depleted bacterial OTUs in fertilized bulk soil, rhizosphere soil, and root endosphere using unfertilized bulk soil, rhizosphere soil, and root endosphere as controls, respectively. Each point represents an individual OTU, and the position along the x-axis represents the abundance fold change compared to unfertilized bulk soil, rhizosphere soil, and root endosphere. The y-axis is −Log 10 (FDR) obtained by correcting the P-value of the significant difference. The closer the point is to the top of the graph, the more significant the difference is. (C) Differences in the number of all ARGs, Tet ARGs, COG genes, and KEGG pathway genes. (D) Enriched and depleted ARGs, Tet ARGs, COG genes, and KEGG pathway genes in fertilized samples compared with ARGs, Tet ARGs, COG genes, and KEGG pathway genes in unfertilized samples, respectively.

Figure 3.

Relative abundances of the top 10 differential bacterial (A) phyla and (B) classes in fertilized and unfertilized samples; (C) relative abundances of the top 10 differential ARGs of different antibiotic classes in fertilized and unfertilized rhizosphere soil samples.

Figure 4.

Soil environmental factors in fertilized and unfertilized sample plots of C. camphora forests. * indicates significant differences (P < .05). Soil physical and chemical properties include pH, EC, SOM, SON, AP, TC, TN, and SMC. Soil enzymes include S-NiR, S-NR, S-HR, S-UE, S-ACP, S-POD, S-ACPT, S-DHA, S-α-GC, and S-β-GC. Each point represents bulk soil with fertilization and without fertilization, and the y-axis value represents the values of soil physical and chemical properties and enzyme activity of each sample. Kruskal–Wallis nonparametric test was used to obtain the P-value of the difference between groups, and Dunn’s test was used to test the significance of the difference.

Figure 5.

Correlation analysis of functional genes, bacterial communities, and environmental factors. Fertilized and unfertilized rhizosphere soil samples. (A) Functional gene composition and correlation heatmaps of bacterial phyla and classes and environmental factors. Correlations between different environmental factors were represented by Spearman correlation coefficients. The size and color depth in the boxes indicate the correlations. Dunn’s test was used to test the significance of the difference. * indicates that the difference is significant (P < .05), and ** indicates that the difference is highly significant (P < .01). The thickness of the line indicates the strength of the correlation inferred by the Mantel tests, and the different colors indicate significant differences. (B) RDA based on the Bray–Curtis distance was used to characterize the relationship of ARGs with soil physicochemical factors, OTC, Tet, and soil enzyme activity. The x-axis and y-axis represent the two selected principal axes, and the percentage represents the interpretation value of the principal axis for the correlation of samples; the scale of x-axis and y-axis is the relative distance, which has no practical significance. The arrows indicate the lengths and angles between explanatory and response variables and reflect their correlations. Different samples are marked with different colors.

Figure 6.

Correlation analysis between environmental factors and network-level topological features. In both fertilized and unfertilized samples, (A) a Wilcoxon rank-sum test was used to compare the network-level topological features of bacterial communities to evaluate the significance of differences between fertilized and unfertilized samples; (B) the correlations between environmental factors and network-level topological features were calculated based on MRMs, and the size and color depth of bubbles in the squares indicate the magnitude of the correlation (positive R² values indicate positive correlations, and negative values indicated negative correlations). Wilcoxon rank-sum test was used to test the significance of the difference. * indicates significant differences (P < .05), and *** indicates highly significant differences (P < .001). The y-axis value represents the value of each network-level topological features.