Soil Geochemical Properties Influencing the Diversity of Bacteria and Archaea in Soils of the Kitezh Lake Area, Antarctica

Abstract

It is believed that polar regions are influenced by global warming more significantly, and because polar regions are less affected by human activities, they have certain reference values for future predictions. This study aimed to investigate the effects of climate warming on soil microbial communities in lake areas, taking Kitezh Lake, Antarctica as the research area. Below-peak soil, intertidal soil, and sediment were taken at the sampling sites, and we hypothesized that the diversity and composition of the bacterial and archaeal communities were different among the three sampling sites. Through 16S rDNA sequencing and analysis, bacteria and archaea with high abundance were obtained. Based on canonical correspondence analysis and redundancy analysis, pH and phosphate had a great influence on the bacterial community whereas pH and nitrite had a great influence on the archaeal community. Weighted gene coexpression network analysis was used to find the hub bacteria and archaea related to geochemical factors. The results showed that in addition to pH, phosphate, and nitrite, moisture content, ammonium, nitrate, and total carbon content also play important roles in microbial diversity and structure at different sites by changing the abundance of some key microbiota.

Keywords: Antarctica; climate change; high-throughput sequencing; microbial diversity; seasonal meltwater lakes; weighted gene coexpression network analysis.

Figure 1

Sampling sites in the Kitezh Lake area.

Figure 2

Bar charts of relative species abundance of bacteria at the phylum level (a) and genus level (b).

Figure 3

Bar charts of relative species abundance of archaea at the phylum level (a) and genus level (b).

Figure 4

Canonical correspondence analysis of bacterial community. Dots with different colors represent different sampling sites, arrows represent geochemical properties, and the longer the length, the greater the correlation between the geochemical property and the sample distribution.

Figure 5

Redundancy analysis of archaeal community. Dots with different colors represent different sampling sites, arrows represent geochemical properties, and the longer the length, the greater the correlation between the geochemical property and the sample distribution.

Figure 6

Module–geochemical property relationships of bacteria (a) and archaea (b). The abscissa is the geochemical properties, and the ordinate is the modules. The red squares show a positive correlation, and the green ones show a negative correlation. The darker the color, the stronger the correlation.

Figure 7

The network diagrams of bacteria (a) and archaea (b). The nodes represent OTUs, and the lines represent the connections between them. The bigger the size, the stronger the correlation of this OTU with others, and the larger the weight value of the OTU is to identify it as the hub OTU. A total of 200 OTUs were used to draw the network diagrams, which resulted in two networks in module blue of (a). However, they will eventually be connected through the OTUs with a relatively low weight value.