Continuous cropping of Patchouli alters soil physiochemical properties and rhizosphere microecology revealed by metagenomic sequencing

Abstract

Continuous cropping (CC) profoundly impacts soil ecosystems, including changes in soil factors and the structure and stability of microbial communities. These factors are interrelated and together affect soil health and plant growth. In this research, metagenomic sequencing was used to explore the effects of CC on physicochemical properties, enzyme activities, microbial community composition, and functional genes of the rhizosphere soil of patchouli. We found that this can lead to changes in various soil factors, including the continuous reduction of pH and ${\text{NH}}_4^{+}$ -N and the unstable changes of many factors. In addition, S-PPO enzyme activity increased significantly with the cropping years, but S-NAG increased in the first 2 years and decreased in the third cropping year. Metagenomic sequencing results showed that CC significantly changed the diversity and composition of rhizosphere microbial communities. The relative abundance of Pseudomonas and Bacteroides decreased substantially from the phylum level. At the genus level, the number of microbial genera specific to the zero-year cropping (CK) and first (T1), second (T2), and third (T3) years decreased significantly, to 1798, 172, 42, and 44, respectively. The abundance of many functional genes changed, among which COG0823, a gene with the cellular process and signaling functions, significantly increased after CC. In addition, ${\text{NH}}_4^{+}$ -N, S-CAT, S-LAP, and SOC were the main environmental factors affecting rhizosphere-dominant microbial communities at the phylum level, while pH, SOC, and AK were the key environmental factors affecting rhizosphere functional genes of Pogostemon cablin. In summary, this study showed the dynamic changes of soil factors and rhizosphere microorganisms during CC, providing a theoretical basis for understanding the formation mechanism and prevention of CC obstacles and contributing to the formulation of scientific soil management and fertilization strategies.

Keywords: Pogostemon cablin; continuous cropping; metagenomic; microbial community diversity; rhizosphere soil.

Figure 1

CC impact on soil microbial community composition and classification. (A) The classification of bacteria, archaea, eukaryotes, and viruses at different CC years was analyzed (n = 4). (B) NMDS (non-metric multidimensional scaling) analysis based on Bray-Curtis differences showed significant species-level differences in soil microbial composition. The stress value indicates the model's applicability. The model is deemed a good fit (P < 0.001) when the stress value is <0.05.

Figure 2

Hierarchical clustering analysis of soil microbial communities based on Bray-Curtis distance (A), stacked plot of soil microbial abundance based on phylum level (B).

Figure 3

Soil microbial communities abundance at phylum level changes in CC of patchouli. Due to the long-term CC, the abundance of Acidobacteriota (A), Pseudomonadota (B), Chloroflexota (C), Actinomycetota (D), Bacteroidota (E), and Eisenbacteria (F) has changed. Different alphabets showed notable variations (p < 0.05, n = 4).

Figure 4

Soil microbial community domain genera affected by CC IN patchouli plant. (A) The Upset graph shows common and unique microbial community characteristics at the genus level. (B) The heat-map shows the differences between the Top 20 dominant microbial community at the genus level.

Figure 5

Heat map of functional gene abundance (eggNOG, top30) in microbial communities at 4 soil sampling points. COG ID, function, description, and categories are shown in Supplementary Table S1.

Figure 6

Top 15 functional genes (A) and top 20 soil microbial community at phylum level (B) correlation network diagram. This link is indicated by node connections (Spearman correlation coefficient, r = 0.6; p = 0.05). The abundance is proportional to the node size. Supplementary Table S1 displays each category's functional gene database ID, function, category, and description.

Figure 7

Soil chemical assays and enzyme activities influence microbial composition and functional genes. (A) Mantel-test analysis demonstrates the relationship between dominating microbial diversity at the phylum level and soil chemical characteristics and enzyme activities. (B) RDA (Redundancy analysis) analysis reveals the effects of soil chemical assays and enzyme activities on functional genes. (C) VPA analysis shows the contribution of soil chemistry and enzyme activities to the diversity of dominant microbial communities. Supplementary Table S1 displays each category's functional gene database ID, function, category, description, and meaning.

Figure 8

The co-occurrence network is constructed based on patchouli rhizosphere microorganisms' grade coefficient (r) at the species level under CC. Through network analysis, the co-occurrence pattern of patchouli rhizosphere microbial communities under different CC years is revealed. Nodes are colored according to different modularities. The size of each node is proportional to the degrees. A join indicates a strong (SparCC |r| > 0.5) and significant (P < 0.05) correlation.

Figure 9

Average degree and network robustness during network invulnerability test in the CC of patchouli.