Core microbial functional activities in ocean environments revealed by global metagenomic profiling analyses

Abstract

Metagenomics-based functional profiling analysis is an effective means of gaining deeper insight into the composition of marine microbial populations and developing a better understanding of the interplay between the functional genome content of microbial communities and abiotic factors. Here we present a comprehensive analysis of 24 datasets covering surface and depth-related environments at 11 sites around the world's oceans. The complete datasets comprises approximately 12 million sequences, totaling 5,358 Mb. Based on profiling patterns of Clusters of Orthologous Groups (COGs) of proteins, a core set of reference photic and aphotic depth-related COGs, and a collection of COGs that are associated with extreme oxygen limitation were defined. Their inferred functions were utilized as indicators to characterize the distribution of light- and oxygen-related biological activities in marine environments. The results reveal that, while light level in the water column is a major determinant of phenotypic adaptation in marine microorganisms, oxygen concentration in the aphotic zone has a significant impact only in extremely hypoxic waters. Phylogenetic profiling of the reference photic/aphotic gene sets revealed a greater variety of source organisms in the aphotic zone, although the majority of individual photic and aphotic depth-related COGs are assigned to the same taxa across the different sites. This increase in phylogenetic and functional diversity of the core aphotic related COGs most probably reflects selection for the utilization of a broad range of alternate energy sources in the absence of light.

Figure 1. Clustering of the 176 depth-related COGs.

(A) Hierarchical clustering of the 176 depth-related COGs in the 24 datasets. Clustering analysis is based on the normalized abundance profile of the 176 depth-related COGs that were shared by the three reference water columns (ATII, ALOHA and BATS) and significantly differed in abundance within at least one of them (details in Materials and Methods). The height indicates the relative distance between datasets. Bootstrap confidence values above 60 for the nodes are shown. The heatmap is shown in fig. S3A. (B) Location of the boundary between the photic and aphotic zones in each of the four water columns. The arrows indicate the depth at which PAR reaches 1% of the level at the surface. (C) Hierarchical clustering of the photic/aphotic global-core depth-related COGs. 82 COGs that showed statistically significant difference (Welch's test, FDR-corrected, p≤1E-04) in their normalized abundance between the photic and the aphotic groups of datasets were selected to establish a photic/aphotic global-core, depth-related reference set. 54 COGs had significantly higher abundance in the photic datasets (Group I, table S4A in file S1); contrary to the remaining 28 aphotic related COGs (Group II, table S4B in file S1). Bootstrap confidence values for the major nodes are shown. Heatmap coloring reflects the Z score of normalized abundances of each COG across all clustered datasets (details in Materials and Methods).

Figure 2. Abundance ratios of photic to aphotic related COGs.

(A) Mean abundance ratios of photic to aphotic related COGs for datasets from the reference water columns, the Iquique water column, and from single-depth datasets. This analysis was initially determined using the 82-COG global-core, depth-related reference set, as described in Materials and Methods. Applying the ratios for the photic and aphotic datasets from the reference water columns, ratio ranges (mean±two SD) were established to indicate photic or aphotic functional genomic content enrichment. Mean abundance ratios for the Iquique water column and the single-depth datasets were calculated to verify their balance between photic and aphotic related biological functions. The arrows at the top of the diagram indicate the approximate depth of the boundary between photic and aphotic zones in each water column (fig. 1B). (B) Normalized abundance of the deoxyribodipyrimidine photolyase gene (COG0415; table S4A in file S1) in the 24 datasets obtained from the indicated depths. The average normalized abundance was calculated for the photic and for the aphotic groups of datasets. The bars represent two SD of the mean.

Figure 3. Effect of oxygen concentration on the functional genomic content of microbial communities represented in the 24 datasets.

(A) Hierarchical clustering of COGs that significantly influenced by extreme oxygen limitation. Datasets analysis are based on the abundance profile of 18 COGs which significantly differed in abundance levels between an extremely hypoxic environment (Iquique 85-, 110 and 200 m deep, permanent OMZ) and environments with higher D.O. (Fisher's exact test, FDR-corrected, p≤0.05). Bootstrap confidence values for the nodes are shown. Heatmap coloring reflects the Z score of normalized abundances of each COG across all clustered datasets. Roman numbers on the left side of the figure present different groups of COGs as determined by abundance profile across the clustered datasets. (B) Mean abundances of the COGs in group I (figure 3A) as a function of the oxygen concentration. Inset shows the gradual increase in the abundance of these genes in datasets from Marmara 1000 m, Iquique 85 m, Iquique 110 m, and Iquique 200 m, as oxygen concentration drops from 30 µmol.kg⁻¹ to 3.2 µmol.kg⁻¹.

Figure 4. Taxonomical assignments of photic and aphotic depth-related COGs at the phylum level for the selected datasets.

Reads assigned to COGs were compared to the NCBI nr database using BLASTX (E-value cutoff 1e-05) and the taxonomical identifiers of the best matches were retrieved. Subsequently, tables of relative frequency of taxa per COG per dataset were generated (tables S6A and S6B in file S1) and presented as heatmaps. The 10 phyla that have the highest average numbers of photic (A) and aphotic (B) COGs per site are presented. The taxa are sorted by the decreasing of their abundance. Datasets of the shallowest samples of the ALOHA, ATII and BATS water columns and single-depth datasets from GOS018, GOS023, GOS034, GOS114 and Mediterranean sites were used for the analysis of the photic related COGs, whereas the deepest datasets from the ALOHA, ATII and BATS water columns, and single-depth datasets from Marmara, PRT and ALOHA (4,000 m), were employed in the case of the aphotic related COGs. This analysis was based on a total of 36,938 sequences (24919 sequences are photic, and 12019 are aphotic).