The effects of microbial fertilizer based Aspergillus brunneoviolaceus HZ23 on pakchoi growth, soil properties, rhizosphere bacterial community structure, and metabolites in newly reclaimed land

Abstract

Introduction: Pakchoi is an important leafy vegetable in China. Due to industrialization and urbanization, pakchoi has been cultivated in newly reclaimed mountainous lands in Zhejiang Province, China in recent years. However, immature soil is not suitable for plant growth and needs to be modified by the application of different organic fertilizer or microbial fertilizer based plant-growth-promoting microbe. In 2021, a high efficient plant-growth-promoting fungi (PGPF; Aspergillus brunneoviolaceus HZ23) was obtained from newly reclaimed land of Zhejiang Province, China. In order to valuate microbial fertilizer based A. brunneoviolaceus HZ23 (MF-HZ23) on pakchoi growth in immature soil, we investigated the effect of MF-HZ23 on soil properties, rhizosphere bacterial community structure, and metabolites of pakchoi rhizosphere soil samples.

Methods: The field experiment (four treatments, MF-HZ23, MF-ZH23 + CCF, CCF and the control) was completely randomly designed and carried out on newly reclaimed land in Yangqingmiao Village of Fuyang district, Hangzhou City, Zhejiang Province, China. In order to evaluate the influence of microbial fertilizer based A. brunneoviolaceus HZ23 on pakchoi in the newly reclaimed land, the number of pakchoi leaves, total fresh and dry weight of the seedlings was counted. In addition, the soil properties, including the pH, OMC, total N, AHN, available P, the genome sequencing, and metabolomics assay were also detected.

Results: The results revealed a significant difference between MF-HZ23 and the control in soil properties, bacterial community structure, and metabolites. Indeed, compared with the control, MF-HZ23 caused 30.66, 71.43, 47.31, 135.84, and 2099.90% increase in the soil pH, organic matter contents (OMC), total nitrogen (N), alkaline hydrolysis nitrogen (AHN), and available phosphorus (P), respectively. Meanwhile, MF-HZ23 caused 50.78, 317.47, and 34.40% increase in the relative abundance of Proteobacteria, Bacteroidota, and Verrucomicrobiota and 75.55, 23.27, 69.25, 45.88, 53.42, and 72.44% reduction in the relative abundance of Acidobacteriota, Actinobacteriota, Chloroflexi, Planctomycetota, Patescibacteria, and WPS-2, respectively, compared with the control based on 16S amplicon sequencing of soil bacteria. Furthermore, redundancy discriminant analysis (RDA) of bacterial communities and soil properties indicated that the main variables of bacterial communities included available P, AHN, pH, OMC, and total N. In addition, non-targeted metabolomics techniques (UHPLC-MS analysis) revealed that MF-HZ23 resulted in a great change in the kinds of metabolites in the rhizosphere soil. Indeed, in MF-HZ23 and the control group, there were six differentially expressed metabolites (DEMs) belong to organoheterocyclic compounds, organic acids and derivatives, organic nitrogen compounds, and these six DEMs were significantly positively correlated with 23 genus of bacteria, which showed complicated interactions between bacteria and DEMs in pakchoi rhizosphere soil.

Conclutions: Overall, the results of this study revealed significant modification in physical, chemical, and biological properties of pakchoi soil. Microbial fertilizer based PGPF A. brunneoviolaceus HZ23 (MF-HZ23) can be used as a good amendment for newly reclaimed land.

Keywords: MF-HZ23; bacterial community; commercial compound fertilizer; metabonomics; newly reclaimed land; pakchoi; soil property.

Figure 1

Effect of MF-HZ23 on the growth of pakchoi in the newly reclaimed filed. (A,E) MF-HZ23 at 3.00 kg/m² (T1); (B,F) MF-HZ23 at 3.00 kg/m² plus CCF at 0.02 kg/m² (T2); (C,G) CCF at 0.04 kg/m² (T3); and (D,H) control.

Figure 2

Effect of MF-HZ23 on the ASVs distribution (A), Chao1 richness index (B), and Shannon′s diversity index (C) of bacteria in pakchoi rhizosphere soil. T1: MF-HZ23 at 3.00 kg/m²; T2: MF-HZ23 at 3.00 kg/m² plus CCF at 0.02 kg/m²; T3: CCF at 0.04 kg/m²; T4: control. Different lower case letters above columns indicate statistical differences (p < 0.05).

Figure 3

Principal component analysis (PCA) of the rhizosphere bacterial communities based on ASVs abundance (A), and redundancy discriminant analysis (RDA) of the rhizosphere bacterial community compositions at genus levels with soil physicochemical properties (B). Ellipses have been drawn for each treatment with a confidence limit of 0.95. Sph, Sphingomonas; Bur, Burkholderia; Fla, Flavobacterium; Rho, Rhodanobacter; Muc, Mucilaginibacter; Sol, Solibacter; Sub, Subgroup2; Bry, Bryobacter; Aci, Acidibacter; and Ell, Ellin6067. OMC, organic matter contain; TN, total N; AP, available P; and AHN, alkaline hydrolysis N. Arrows indicate the direction and magnitude of soil physicochemical properties (pH, OMC, total N, AP, and AHN) associated with the different bacterial genus. T1: MF-HZ23 at 3.00 kg/m²; T2: MF-HZ23 at 3.00 kg/m² plus CCF at 0.02 kg/m²; T3: CCF at 0.04 kg/m²; and T4: control.

Figure 4

Relative abundance of bacteria at the phylum (A) and genus (B) level. T1: MF-HZ23 at 3.00 kg/m²; T2: MF-HZ23 at 3.00 kg/m² plus CCF at 0.02 kg/m²; T3: CCF at 0.04 kg/m²; and T4: control.

Figure 5

Linear discriminant analysis (LDA) effect size (LeFSe) of the bacterial taxa (A), which identifies the most differentially abundant taxa among MF-HZ23 and CCF in different treatments. Only taxa with LDA values greater than 4 (p < 0.05) are shown. Hierarchical clustering analysis and heat map at the family level (B). The tree plot represents a clustering analysis of the top 20 bacteria at family levels according to their Person correlation coefficient matrix and relative abundance, the upper tree plot represents a clustering analysis of soil samples according to the Euclidean distance of data. T1: MF-HZ23 at 3.00 kg/m²; T2: MF-HZ23 at 3.00 kg/m² plus CCF at 0.02 kg/m²; T3: CCF at 0.04 kg/m²; and T4: control.

Figure 6

Orthogonal partial least squares-discriminant analysis (OPLS-DA) score map of pakchoi rhizosphere soil of the MF-HZ23 (A), MF-HZ23 plus CCF (B), and CCF treatment (C). Volcano plot of differentially accumulated metabolites in MF-HZ23 vs. the control (D), MF-HZ23 plus CCF vs. the control (E), and CCF vs. the control (F). Each point represents a metabolite, blue point indicates metabolities with FC ﹤ 0.67 and p ﹤ 0.05, red point indicates metabolities with FC ﹥ 1.5 and p ﹤ 0.05, black point indicates non-significant metabolites.

Figure 7

Metabolite classification statistics (A), and DEMs in different treatment groups. (B,E) MF-HZ23 vs. the control; (C,F) MF-HZ23 plus CCF vs. the control; (D,G) CCF vs. the control. Red and green represents upregulated and downregulated, respectively.

Figure 8

Correlation heat map between DEMs and related bacteria in different treatment groups. (A) MF-HZ23 vs. the control; (B) MF-HZ23 plus CCF vs. the control; and (C) CCF vs. the control. Red and blue represent positive correlation and negative correlation, respectively. * indicated a significant correlation at p < 0.05.

Figure 9

Connection network between DEMs and related bacteria in different treatment groups. (A) MF-HZ23 vs. the control; (B) MF-HZ23 plus CCF vs. the control; and (C) CCF vs. the control. Green dots and orange prisms represent bacteria and metabolites, and the size of nodes and prisms represents the relative abundance of bacteria and metabolites, respectively. Red lines and blue lines represent positive correlation and negative correlation, respectively.