Table 1. Contribution of metabolic hierarchical system level 1 to the dissimilarity of the hydrocarbon-impacted and non-hydrocarbon-impacted metagenomes.
Avg. Abundance
|
||||
---|---|---|---|---|
Metabolic Processes | Hydrocarbon-Impacted | Non-Impacted | Diss/SD | Cum % |
Cofactors, Vitamins, Prosthetic Groups, Pigments | 0.1 | 0.19 | 2.24 | 11.43 |
Virulence, Disease and Defence | 0.1 | 0.19 | 2.24 | 22.86 |
Phages, Prophages, Transposable elements, Plasmids | 0.1 | 0.19 | 2.24 | 34.29 |
Fatty Acids, Lipids, and Isoprenoids | 0.1 | 0.19 | 2.24 | 45.71 |
Iron acquisition and metabolism | 0.84 | 0.79 | 1.63 | 52.68 |
Dormancy and Sporulation | 0.71 | 0.68 | 1.49 | 57.48 |
Motility and Chemotaxis | 0.83 | 0.81 | 1.58 | 61.17 |
Metabolism of Aromatic Compounds | 0.87 | 0.85 | 1.73 | 64.81 |
Secondary Metabolism | 0.76 | 0.75 | 1.16 | 68.32 |
Regulation and Cell signalling | 0.86 | 0.83 | 1.86 | 71.55 |
Protein Metabolism | 0.94 | 0.96 | 3.42 | 74.53 |
Carbohydrates | 0.97 | 1 | 3.5 | 77.49 |
Nitrogen Metabolism | 0.84 | 0.82 | 1.74 | 80.17 |
Photosynthesis | 0.69 | 0.69 | 1.3 | 82.75 |
Amino Acids and Derivatives | 0.96 | 0.98 | 2.89 | 85.24 |
Clustering-based subsystems | 0.98 | 0.99 | 1.96 | 87.06 |
Miscellaneous | 0.94 | 0.96 | 3.14 | 88.7 |
Hydrocarbon-impacted samples include a hydrocarbon-impacted foreshore and a biopile from Australia [40; Smith et al., unpublished data], and 2 biopiles from the Arctic region [40], while the non- impacted samples included 2 marine sediment samples from Australia and 3 sediment samples from the Coorong [50]. Average dissimilarity between the two groups is 1.78 % (Table S1 in File S1). Only metabolisms that were consistent (i.e. Diss/SD > 1.4) are shown here. The larger value in each case (i.e. the potential indicator of that condition) is shown in bold.
Cut-off percentage = 90% of the total dissimilarity, Diss=dissimilarity; SD=Standard Deviation; Cum %=cumulative percentage of contribution to overall dissimilarity, Avg. Abundance values are reported for square-root transformed data