Environmental Factors Drive the Changes of Bacterial Structure and Functional Diversity in Rhizosphere Soil of Hippophae rhamnoides subsp. sinensis Rousi in Arid Regions of Northwest China

Abstract

Hippophae rhamnoides subsp. sinensis Rousi has high ecological and medicinal value, and it is an important plant resource unique to the arid regions of Northwest China. Exploring the influence of climate characteristics and soil factors on the composition, diversity, and function of the rhizosphere bacterial community of Chinese seabuckthorn is of great value for developing and popularizing characteristic plant resources in the arid regions of Northwest China. In this study, the rhizosphere soil of 13 Chinese seabuckthorn distribution areas in the northwest of China was taken as the research object, the bacterial community map was constructed based on 16S rRNA gene high-throughput sequencing technology, and the species abundance composition, structural diversity, molecular co-occurrence network, and phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt), as well as the function of rhizosphere soil bacterial community, were systematically studied. Combined with Mantel test and redundancy analysis (RDA), the key habitat factors driving the rhizosphere soil bacterial community structure of Chinese seabuckthorn were explored. The results showed that: (1) The number of amplicon sequence variants (ASVs) in rhizosphere soil bacterial community of Chinese seabuckthorn was the highest in S2(3072) and the S12(3637), and the lowest in the S11(1358) and S13(1996). The rhizosphere soil bacterial community was primarily composed of Proteobacteria, Actinobacteriota, and Acidobacteriota. Except for the S6 and S11 habitats, the dominant bacterial genera were mainly Achromobacter, Acidobacter (RB41), and Sphingomonas. (2) The α and β diversity of rhizosphere soil bacterial communities of Chinese seabuckthorn across 13 distribution areas were significantly different. The number of operational taxonomic units (OTUs), Ace index, and Chao 1 index of soil bacterial community in the S12 distribution area are the highest, and they are the lowest in S11 distribution area, with significant differences. The aggregation of soil bacterial communities in the S5 and S10 distribution areas is the highest, while it is the lowest in the S6 and S11 distribution areas. (3) PICRUSt function classification of soil bacteria showed that Metabolism and Genetic Information Processing functions were the strongest across all distribution areas, with S10 exhibiting higher functional capacity than other areas and S11 showing the weakest. (4) Cluster analysis revealed that soil bacteria across the 13 distribution areas were clustered into two groups, with S10 and S12 distribution areas as one group (Group 1) and the remaining 11 distribution areas as another group (Group 2). (5) Redundancy analysis revealed that pH was the key soil environmental factor driving the rhizosphere soil bacterial community α-diversity of Chinese seabuckthorn, followed by altitude (ALT) and soil water content (SWC). In summary, Chinese seabuckthorn prefers neutral to alkaline soils, and environmental factors play an important role in driving bacterial diversity, community structure, functional profiles, and co-occurrence networks in rhizosphere soil of Chinese seabuckthorn.

Keywords: Hippophae rhamnoides subsp. sinensis Rousi; function prediction; geographical pattern; pH; rhizosphere soil.

Figure 1

Geographic location of the 13 sampling sites. Note: This figure was created using the standard map (approval number: GS (Beijing, China) No. 1061 (2022) downloaded from the Standard Map Service Website of the China Bureau of Surveying and Mapping Geographic Information. The base map remains unaltered. The darker the blue on the map, the lower the altitude; closer to red means higher altitude.

Figure 2

Analysis of sequencing results quality and ASV quantity of 13 distribution regions. (a) Dilution curves; (b) species cumulative box plots; (c) Venn diagrams.

Figure 2

Analysis of sequencing results quality and ASV quantity of 13 distribution regions. (a) Dilution curves; (b) species cumulative box plots; (c) Venn diagrams.

Figure 3

Relative abundance of 13 distribution regions at phylum level and genus level. (a) Phylum level; (b) genus level.

Figure 4

LEfSe analysis of 13 species in the genus level. (a) LEfSe analysis (LDA > 4.0); (b) LDA value of indicator species (LDA > 4.0).

Figure 5

α-diversity of bacterial communities in 13 distribution regions. Note: *** represents p < 0.001. (a) Number of OUTs, (b) Shannon index, (c) Simpson index, (d) Pielou index, (e) Invsimpson index, (f) Chao1 index, (g) ACE index, (h) Goods coverage.

Figure 6

Differences in diversity of bacterial community β (PCoA) in 13 distribution regions.

Figure 7

Co-occurrence network diagram of soil bacteria in 13 distribution regions. Note: Node colours and sizes indicate species type and importance; line colours indicate positive or negative correlation, with pink being positive and green being negative.

Figure 8

Relative abundance map of PICRUSt function prediction of soil bacteria in 13 distribution regions. Note: (a) Level 1; (b) Level 2.

Figure 9

UPGMA cluster tree based on weighted Bray-Curtis distance. Note: The UPGMA cluster tree is on the left, and the relative abundance of soil bacteria at the door level is on the right.

Figure 10

Mantel analysis of climate characteristics, soil physicochemical characteristics, and soil bacterial community. Note: * denotes p < 0.05, ** denotes p < 0.01, *** denotes p < 0.001. (a) αdiversity, (b) Bacterial phylum level, (c) Bacterial genus level.

Figure 10

Mantel analysis of climate characteristics, soil physicochemical characteristics, and soil bacterial community. Note: * denotes p < 0.05, ** denotes p < 0.01, *** denotes p < 0.001. (a) αdiversity, (b) Bacterial phylum level, (c) Bacterial genus level.

Figure 11

RDA analysis of climate characteristics, soil physicochemical characteristics, and soil bacterial community structure. (a) Redundancy Analysis (RDA) between habitat factors and bacterial community alpha diversity, (b) Contribution rate of habitat factors to bacterial community alpha diversity, (c) Redundancy Analysis (RDA) between habitat factors and the top 5 abundant bacterial phyla, (d) Contribution rate of habitat factors to the top 5 abundant bacterial phyla, (e) Redundancy Analysis (RDA) between habitat factors and the top 5 abundant bacterial genera, (f) Contribution rate of habitat factors to the top 5 abundant bacterial genera.