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

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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 (NMDS) of the bacterial community composition in the Baltic Sea. (A) NMDS of all samples (stress 0.24); (B) only surface-water samples (stress 0.13); (C) NMDS plot of the July samples (stress 0.17); and (D) NMDS plot of the bacterial community composition in the February samples (stress 0.09). The environmental variables salinity, depth, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Bold symbols are surface samples (0–10 m), and open symbols the mesopelagic (11–300 m). Samples from the February cruise are indicated in blue and those from the July cruise in red.
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Figure 3: Non-metric multidimensional scaling (NMDS) of the bacterial community composition in the Baltic Sea. (A) NMDS of all samples (stress 0.24); (B) only surface-water samples (stress 0.13); (C) NMDS plot of the July samples (stress 0.17); and (D) NMDS plot of the bacterial community composition in the February samples (stress 0.09). The environmental variables salinity, depth, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Bold symbols are surface samples (0–10 m), and open symbols the mesopelagic (11–300 m). Samples from the February cruise are indicated in blue and those from the July cruise in red.

Mentions: An analysis of bacterial community composition by NMDS plots indicated a separation of the bacterial communities, with salinity inversely correlating with the first coordinate (Pearson correlation r = -0.93) and differences between the July and February samples (season) correlating with the second coordinate (Pearson correlation r = 0.70; Figure 3A). The second coordinate was also inversely correlated with depth (Pearson correlation r = -0.31). The analysis of the surface water samples supported the results obtained with the complete dataset and confirmed a clear separation between the July and February samples along the second coordinate (Figure 3B). Analyzing the July and February samples separately revealed a clear separation between surface and mesopelagic samples (stratification) along the second NMDS coordinate for the July samples (Figure 3C), but not for the February samples (Figure 3D). This is consistent with the bigger difference in temperature between these water layers in July (average 15°C, ± 2°C and average 7°C, ± 4°C for surface and mesopelagic samples, respectively) than in February (2 ± 1°C and 4 ± 2°C, respectively). For both the February and July samples the first NMDS coordinate correlated with salinity.


Phylogenetic Signals of Salinity and Season in Bacterial Community Composition Across the Salinity Gradient of the Baltic Sea
Non-metric multidimensional scaling (NMDS) of the bacterial community composition in the Baltic Sea. (A) NMDS of all samples (stress 0.24); (B) only surface-water samples (stress 0.13); (C) NMDS plot of the July samples (stress 0.17); and (D) NMDS plot of the bacterial community composition in the February samples (stress 0.09). The environmental variables salinity, depth, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Bold symbols are surface samples (0–10 m), and open symbols the mesopelagic (11–300 m). Samples from the February cruise are indicated in blue and those from the July cruise in red.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC5121245&req=5

Figure 3: Non-metric multidimensional scaling (NMDS) of the bacterial community composition in the Baltic Sea. (A) NMDS of all samples (stress 0.24); (B) only surface-water samples (stress 0.13); (C) NMDS plot of the July samples (stress 0.17); and (D) NMDS plot of the bacterial community composition in the February samples (stress 0.09). The environmental variables salinity, depth, and temperature were added as post hoc vectors to the NMDS graph representing the correlation coefficients between the environmental variables and the NMDS scores. Bold symbols are surface samples (0–10 m), and open symbols the mesopelagic (11–300 m). Samples from the February cruise are indicated in blue and those from the July cruise in red.
Mentions: An analysis of bacterial community composition by NMDS plots indicated a separation of the bacterial communities, with salinity inversely correlating with the first coordinate (Pearson correlation r = -0.93) and differences between the July and February samples (season) correlating with the second coordinate (Pearson correlation r = 0.70; Figure 3A). The second coordinate was also inversely correlated with depth (Pearson correlation r = -0.31). The analysis of the surface water samples supported the results obtained with the complete dataset and confirmed a clear separation between the July and February samples along the second coordinate (Figure 3B). Analyzing the July and February samples separately revealed a clear separation between surface and mesopelagic samples (stratification) along the second NMDS coordinate for the July samples (Figure 3C), but not for the February samples (Figure 3D). This is consistent with the bigger difference in temperature between these water layers in July (average 15°C, ± 2°C and average 7°C, ± 4°C for surface and mesopelagic samples, respectively) than in February (2 ± 1°C and 4 ± 2°C, respectively). For both the February and July samples the first NMDS coordinate correlated with salinity.

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.