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Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea.

Zhang Y, Zhao Z, Dai M, Jiao N, Herndl GJ - Mol. Ecol. (2014)

Bottom Line: Although the composition of both the total and active bacterial community was strongly correlated with environmental factors and weakly correlated with geographic distance, the active bacterial community displayed higher environmental sensitivity than the total community and particularly a greater distance effect largely caused by the active assemblage from deep waters.This might be due to a high competition between active bacterial taxa as indicated by our community network models.Based on these analyses, we speculate that high competition could cause some dispersal limitation of the active bacterial community resulting in a distinct distance-decay relationship.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Marine Environmental Sciences, Xiamen University, Xiang'an, Xiamen, 361101, China; Institute of Marine Microbes and Ecospheres, Xiamen University, Xiang'an, Xiamen, 361101, China.

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Network interactions of OTUs (force-directed layout). (a) DNA data set of the shallow water; (b) DNA data set of the deep water; (c) RNA data set of the shallow water; (d) RNA data set of the deep water. Each node represents an OTU indicating an individual species. The edge between each two nodes represents positive (red) or negative (blue) interactions between those two species. Colours of the nodes indicate the different major phyla.
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fig07: Network interactions of OTUs (force-directed layout). (a) DNA data set of the shallow water; (b) DNA data set of the deep water; (c) RNA data set of the shallow water; (d) RNA data set of the deep water. Each node represents an OTU indicating an individual species. The edge between each two nodes represents positive (red) or negative (blue) interactions between those two species. Colours of the nodes indicate the different major phyla.

Mentions: Based on the spatial structure of the bacterial community, two large clusters of heterotrophic bacterial communities corresponding to shallow and deep waters (Fig.2a: cluster II and IV; Fig.2b: cluster III and IV + V) were used for ecological network analysis (sample number within each cluster must be ≥8). All curves of network connectivity fitted with the power-law model (R2 > 0.7). Substantial differences were observed in terms of network size and structure between the DNA- and RNA-based libraries (Fig.7; Table S3 and S4 Supporting information). The active bacterial taxa displayed tighter interactions than the total bacterial community as revealed by average path distance and harmonic geodesic distance (Table S3 and S4 Supporting information). Notably, distinctly contrasting interactions between bacterial taxa within the total and active communities were observed. Positive connections dominated the interactions between taxa in the DNA-based networks (Fig. S1a and b Supporting information), whereas negative connections dominated in the RNA-based networks (Fig. S1c and d Supporting information), suggesting more cooperation in the former and more competition in the latter networks.


Drivers shaping the diversity and biogeography of total and active bacterial communities in the South China Sea.

Zhang Y, Zhao Z, Dai M, Jiao N, Herndl GJ - Mol. Ecol. (2014)

Network interactions of OTUs (force-directed layout). (a) DNA data set of the shallow water; (b) DNA data set of the deep water; (c) RNA data set of the shallow water; (d) RNA data set of the deep water. Each node represents an OTU indicating an individual species. The edge between each two nodes represents positive (red) or negative (blue) interactions between those two species. Colours of the nodes indicate the different major phyla.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4230472&req=5

fig07: Network interactions of OTUs (force-directed layout). (a) DNA data set of the shallow water; (b) DNA data set of the deep water; (c) RNA data set of the shallow water; (d) RNA data set of the deep water. Each node represents an OTU indicating an individual species. The edge between each two nodes represents positive (red) or negative (blue) interactions between those two species. Colours of the nodes indicate the different major phyla.
Mentions: Based on the spatial structure of the bacterial community, two large clusters of heterotrophic bacterial communities corresponding to shallow and deep waters (Fig.2a: cluster II and IV; Fig.2b: cluster III and IV + V) were used for ecological network analysis (sample number within each cluster must be ≥8). All curves of network connectivity fitted with the power-law model (R2 > 0.7). Substantial differences were observed in terms of network size and structure between the DNA- and RNA-based libraries (Fig.7; Table S3 and S4 Supporting information). The active bacterial taxa displayed tighter interactions than the total bacterial community as revealed by average path distance and harmonic geodesic distance (Table S3 and S4 Supporting information). Notably, distinctly contrasting interactions between bacterial taxa within the total and active communities were observed. Positive connections dominated the interactions between taxa in the DNA-based networks (Fig. S1a and b Supporting information), whereas negative connections dominated in the RNA-based networks (Fig. S1c and d Supporting information), suggesting more cooperation in the former and more competition in the latter networks.

Bottom Line: Although the composition of both the total and active bacterial community was strongly correlated with environmental factors and weakly correlated with geographic distance, the active bacterial community displayed higher environmental sensitivity than the total community and particularly a greater distance effect largely caused by the active assemblage from deep waters.This might be due to a high competition between active bacterial taxa as indicated by our community network models.Based on these analyses, we speculate that high competition could cause some dispersal limitation of the active bacterial community resulting in a distinct distance-decay relationship.

View Article: PubMed Central - PubMed

Affiliation: State Key Laboratory of Marine Environmental Sciences, Xiamen University, Xiang'an, Xiamen, 361101, China; Institute of Marine Microbes and Ecospheres, Xiamen University, Xiang'an, Xiamen, 361101, China.

Show MeSH
Related in: MedlinePlus