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Phylogenetic Signals of Salinity and Season in Bacterial Community Composition Across the Salinity Gradient of the Baltic Sea

View Article: PubMed Central - PubMed

ABSTRACT

Understanding the key processes that control bacterial community composition has enabled predictions of bacterial distribution and function within ecosystems. In this study, we used the Baltic Sea as a model system to quantify the phylogenetic signal of salinity and season with respect to bacterioplankton community composition. The abundances of 16S rRNA gene amplicon sequencing reads were analyzed from samples obtained from similar geographic locations in July and February along a brackish to marine salinity gradient in the Baltic Sea. While there was no distinct pattern of bacterial richness at different salinities, the number of bacterial phylotypes in winter was significantly higher than in summer. Bacterial community composition in brackish vs. marine conditions, and in July vs. February was significantly different. Non-metric multidimensional scaling showed that bacterial community composition was primarily separated according to salinity and secondly according to seasonal differences at all taxonomic ranks tested. Similarly, quantitative phylogenetic clustering implicated a phylogenetic signal for both salinity and seasonality. Our results suggest that global patterns of bacterial community composition with respect to salinity and season are the result of phylogenetically clustered ecological preferences with stronger imprints from salinity.

No MeSH data available.


Non-metric multidimensional scaling of bacterial communities from a congruent dataset (surface water and marine and mesohaline only) at different phylogenetic levels based on SILVA rank taxonomy. NMDS at: (A) the OTU level (stress: 0.13); (B) the genus level (stress: 0.13); (C) the family level (stress: 0.14); (D) the order level (stress: 0.17); (E) the class level (stress: 0.15); and (F) the phylum level (stress: 0.13). The environmental variables salinity, season, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Samples from the February cruise are indicated in blue and those from the July cruise in red.
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Figure 4: Non-metric multidimensional scaling of bacterial communities from a congruent dataset (surface water and marine and mesohaline only) at different phylogenetic levels based on SILVA rank taxonomy. NMDS at: (A) the OTU level (stress: 0.13); (B) the genus level (stress: 0.13); (C) the family level (stress: 0.14); (D) the order level (stress: 0.17); (E) the class level (stress: 0.15); and (F) the phylum level (stress: 0.13). The environmental variables salinity, season, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Samples from the February cruise are indicated in blue and those from the July cruise in red.

Mentions: To exclude the effects of increasing depth, which is linked to the stratification of temperature, light, and nutrients, on bacterial community composition, the following analysis included only the communities in the surface water samples. To make the summer and winter dataset consistent we only included stations sampled both in February and July (Supplementary Figure S1; Table 1). This resulted in 34 surface water samples and excluded the oligohaline stations that could not be sampled in February, due to ice cover. ANOSIM-based comparisons of the bacterial communities at the different salinities and during the two seasons revealed a larger R-value for salinity (ANOSIM p < 0.01, R = 0.84) than for season (ANOSIM p < 0.01, R = 0.41; Table 2). When the analysis was performed from the OTU to the phylum level, the R-values were lower but the salinity values were still higher than the seasonal values (Table 2). Consistent with these results, NMDS plots of the bacterial community composition at different taxonomic ranks showed a separation based on salinity along the first coordinate and separation of the July and February samples along the second coordinate (Figure 4). The separation based on the first and second coordinates of the NMDS plots was strongest at the OTU level (Figure 4A). At the genus level, the separation between the July and February samples and between salinity levels was still obvious, but the degree of correlation of the vectors with the first and second coordinates decreased. A decrease in the correlation with the first and second coordinates of the NMDS continued from the family level to the phylum level, together with a decrease in the strict separation between the July and February samples (Figures 4C,D,F). The separation at the class level of both the February and July samples and the marine and mesohaline samples was relatively clear (Figure 4E).


Phylogenetic Signals of Salinity and Season in Bacterial Community Composition Across the Salinity Gradient of the Baltic Sea
Non-metric multidimensional scaling of bacterial communities from a congruent dataset (surface water and marine and mesohaline only) at different phylogenetic levels based on SILVA rank taxonomy. NMDS at: (A) the OTU level (stress: 0.13); (B) the genus level (stress: 0.13); (C) the family level (stress: 0.14); (D) the order level (stress: 0.17); (E) the class level (stress: 0.15); and (F) the phylum level (stress: 0.13). The environmental variables salinity, season, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Samples from the February cruise are indicated in blue and those from the July cruise in red.
© Copyright Policy
Related In: Results  -  Collection

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Show All Figures
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Figure 4: Non-metric multidimensional scaling of bacterial communities from a congruent dataset (surface water and marine and mesohaline only) at different phylogenetic levels based on SILVA rank taxonomy. NMDS at: (A) the OTU level (stress: 0.13); (B) the genus level (stress: 0.13); (C) the family level (stress: 0.14); (D) the order level (stress: 0.17); (E) the class level (stress: 0.15); and (F) the phylum level (stress: 0.13). The environmental variables salinity, season, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Samples from the February cruise are indicated in blue and those from the July cruise in red.
Mentions: To exclude the effects of increasing depth, which is linked to the stratification of temperature, light, and nutrients, on bacterial community composition, the following analysis included only the communities in the surface water samples. To make the summer and winter dataset consistent we only included stations sampled both in February and July (Supplementary Figure S1; Table 1). This resulted in 34 surface water samples and excluded the oligohaline stations that could not be sampled in February, due to ice cover. ANOSIM-based comparisons of the bacterial communities at the different salinities and during the two seasons revealed a larger R-value for salinity (ANOSIM p < 0.01, R = 0.84) than for season (ANOSIM p < 0.01, R = 0.41; Table 2). When the analysis was performed from the OTU to the phylum level, the R-values were lower but the salinity values were still higher than the seasonal values (Table 2). Consistent with these results, NMDS plots of the bacterial community composition at different taxonomic ranks showed a separation based on salinity along the first coordinate and separation of the July and February samples along the second coordinate (Figure 4). The separation based on the first and second coordinates of the NMDS plots was strongest at the OTU level (Figure 4A). At the genus level, the separation between the July and February samples and between salinity levels was still obvious, but the degree of correlation of the vectors with the first and second coordinates decreased. A decrease in the correlation with the first and second coordinates of the NMDS continued from the family level to the phylum level, together with a decrease in the strict separation between the July and February samples (Figures 4C,D,F). The separation at the class level of both the February and July samples and the marine and mesohaline samples was relatively clear (Figure 4E).

View Article: PubMed Central - PubMed

ABSTRACT

Understanding the key processes that control bacterial community composition has enabled predictions of bacterial distribution and function within ecosystems. In this study, we used the Baltic Sea as a model system to quantify the phylogenetic signal of salinity and season with respect to bacterioplankton community composition. The abundances of 16S rRNA gene amplicon sequencing reads were analyzed from samples obtained from similar geographic locations in July and February along a brackish to marine salinity gradient in the Baltic Sea. While there was no distinct pattern of bacterial richness at different salinities, the number of bacterial phylotypes in winter was significantly higher than in summer. Bacterial community composition in brackish vs. marine conditions, and in July vs. February was significantly different. Non-metric multidimensional scaling showed that bacterial community composition was primarily separated according to salinity and secondly according to seasonal differences at all taxonomic ranks tested. Similarly, quantitative phylogenetic clustering implicated a phylogenetic signal for both salinity and seasonality. Our results suggest that global patterns of bacterial community composition with respect to salinity and season are the result of phylogenetically clustered ecological preferences with stronger imprints from salinity.

No MeSH data available.