Metagenomic analysis of stress genes in microbial mat communities from Antarctica and the High Arctic

Abstract

Polar and alpine microbial communities experience a variety of environmental stresses, including perennial cold and freezing; however, knowledge of genomic responses to such conditions is still rudimentary. We analyzed the metagenomes of cyanobacterial mats from Arctic and Antarctic ice shelves, using high-throughput pyrosequencing to test the hypotheses that consortia from these extreme polar habitats were similar in terms of major phyla and subphyla and consequently in their potential responses to environmental stresses. Statistical comparisons of the protein-coding genes showed similarities between the mats from the two poles, with the majority of genes derived from Proteobacteria and Cyanobacteria; however, the relative proportions differed, with cyanobacterial genes more prevalent in the Antarctic mat metagenome. Other differences included a higher representation of Actinobacteria and Alphaproteobacteria in the Arctic metagenomes, which may reflect the greater access to diasporas from both adjacent ice-free lands and the open ocean. Genes coding for functional responses to environmental stress (exopolysaccharides, cold shock proteins, and membrane modifications) were found in all of the metagenomes. However, in keeping with the greater exposure of the Arctic to long-range pollutants, sequences assigned to copper homeostasis genes were statistically (30%) more abundant in the Arctic samples. In contrast, more reads matching the sigma B genes were identified in the Antarctic mat, likely reflecting the more severe osmotic stress during freeze-up of the Antarctic ponds. This study underscores the presence of diverse mechanisms of adaptation to cold and other stresses in polar mats, consistent with the proportional representation of major bacterial groups.

Fig 1

Statistical analyses of taxonomic profiles for the Arctic (combined MIS and WHI samples) and Antarctic (MCM sample) metagenomes. Orders or classes overrepresented in the Antarctic have a negative difference between proportions (green dots); those overrepresented in the Arctic community have a positive-value difference between proportions (blue dots). Features (orders or classes) with a q value of >0.05 were considered significant.

Fig 2

Comparison of metabolic profiles for the Arctic (combined MIS-WHI samples) and Antarctic (MCM sample) metagenomes. Scatter plot of metabolic profiles of Arctic and Antarctic subsystems. Blue dots represent Arctic subsystems, and green dots represent Antarctic subsystems. Dots on either side of the dashed trend line are enriched in one of the two samples. Labeled dots indicate subsystems with the greatest distances from the dashed trend line; these subsystems had the greatest proportional differences (%) between Arctic and Antarctic metagenomes. Significant differences are shown in Fig. 3. The green bar graph (right) indicates the numbers of Antarctic subsystems as proportions of the total number of sequences in the Antarctic metagenome. The blue bar graph (top) indicates the numbers of Arctic subsystems as proportions of the Arctic metagenome, indicating that most subsystems represent a low proportion of the total number of sequences. The point in the upper right-hand corner is the tRNA aminoacylation subsystem, which accounted for a relatively high proportion of identified subsystems; however, since this was the same in both metagenomes, it was not labeled.

Fig 3

Statistical analyses of metabolic profiles for the Arctic microbial mats (combined MIS-WHI samples) and the Antarctic metagenome (MCM sample). Total numbers of sequences in the different categories are shown in the left bar graph; the left side (blue) represents the Arctic mats, while the right side (green) represents the Antarctic mat. Subsystems in the Antarctic microbial mat community have negative differences between proportions (green dots). Subsystems overrepresented in the Arctic microbial mat samples have positive differences between proportions (blue dots). Features (orders or classes) with a q value of >0.05 were considered significant.