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Phylogenetic analysis suggests that habitat filtering is structuring marine bacterial communities across the globe.

Pontarp M, Canbäck B, Tunlid A, Lundberg P - Microb. Ecol. (2012)

Bottom Line: Different bacterial types seem to have different ecological niches that dictate their survival in different habitats.Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed.The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

View Article: PubMed Central - PubMed

Affiliation: Theoretical Population Ecology and Evolution Group, Lund University, Lund, Sweden. mikael.pontarp@biol.lu.se

ABSTRACT
The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

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Net relatedness index (NRI) and nearest taxa index (NTI) for all phyla represented in each of the localities. One square per phylum and locality combination, upper left part represents NRI and the lower right part represents NTI. Colour code green denotes positive values (clustered community). Red denotes negative values (overdispersed community). *P < 0.05 and †P < 0.10 denote significant results. Blue denotes positive results, P < 0.05 with Bonferroni correction. Note that after Bonferroni correction, no significant negative results remain. a Analysis made on sequence level, terminal leaves in the phylogenetic tree consists of one single sequence. b Analysis made on OTU level, terminal leaves in phylogenetic tree consist of sequences clustered together based on phylogenetic similarity
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Fig4: Net relatedness index (NRI) and nearest taxa index (NTI) for all phyla represented in each of the localities. One square per phylum and locality combination, upper left part represents NRI and the lower right part represents NTI. Colour code green denotes positive values (clustered community). Red denotes negative values (overdispersed community). *P < 0.05 and †P < 0.10 denote significant results. Blue denotes positive results, P < 0.05 with Bonferroni correction. Note that after Bonferroni correction, no significant negative results remain. a Analysis made on sequence level, terminal leaves in the phylogenetic tree consists of one single sequence. b Analysis made on OTU level, terminal leaves in phylogenetic tree consist of sequences clustered together based on phylogenetic similarity

Mentions: When testing the structure of individual phyla within the different localities, once again a large proportion of the data subsets were clustered (Fig. 4). If single sequence-level data were used, significant phylogenetic structure was found in 34 out of the 77 phylum-by-locality data sets having sufficient data for Phylocom calculations (Fig. 4a). Only seven of the NRI or NTI values were found to be significantly negative. In the OTU-level analyses, significant phylogenetic structure was found in 29 out of the 77 phylum-by-locality combinations containing sufficient data for Phylocom calculations (Fig. 4b). Only two of the NRI or NTI values were found to be significantly negative. After Bonferroni correction, no significant negative results remained; however, 16 and 9 significant positive NRI or NTI values remained in the sequence-level and cluster-level analysis, respectively. Notably, 28 out of the 41 significant NRI and NTI values at the OTU level were recovered in the single sequence-level analysis. Although the two approaches give qualitatively similar results, the discrepancy between the two possibly is a result of reduction in noise, especially in the terminal parts of the phylogenetic trees, as individual sequences are clustered together.Figure 4


Phylogenetic analysis suggests that habitat filtering is structuring marine bacterial communities across the globe.

Pontarp M, Canbäck B, Tunlid A, Lundberg P - Microb. Ecol. (2012)

Net relatedness index (NRI) and nearest taxa index (NTI) for all phyla represented in each of the localities. One square per phylum and locality combination, upper left part represents NRI and the lower right part represents NTI. Colour code green denotes positive values (clustered community). Red denotes negative values (overdispersed community). *P < 0.05 and †P < 0.10 denote significant results. Blue denotes positive results, P < 0.05 with Bonferroni correction. Note that after Bonferroni correction, no significant negative results remain. a Analysis made on sequence level, terminal leaves in the phylogenetic tree consists of one single sequence. b Analysis made on OTU level, terminal leaves in phylogenetic tree consist of sequences clustered together based on phylogenetic similarity
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3375428&req=5

Fig4: Net relatedness index (NRI) and nearest taxa index (NTI) for all phyla represented in each of the localities. One square per phylum and locality combination, upper left part represents NRI and the lower right part represents NTI. Colour code green denotes positive values (clustered community). Red denotes negative values (overdispersed community). *P < 0.05 and †P < 0.10 denote significant results. Blue denotes positive results, P < 0.05 with Bonferroni correction. Note that after Bonferroni correction, no significant negative results remain. a Analysis made on sequence level, terminal leaves in the phylogenetic tree consists of one single sequence. b Analysis made on OTU level, terminal leaves in phylogenetic tree consist of sequences clustered together based on phylogenetic similarity
Mentions: When testing the structure of individual phyla within the different localities, once again a large proportion of the data subsets were clustered (Fig. 4). If single sequence-level data were used, significant phylogenetic structure was found in 34 out of the 77 phylum-by-locality data sets having sufficient data for Phylocom calculations (Fig. 4a). Only seven of the NRI or NTI values were found to be significantly negative. In the OTU-level analyses, significant phylogenetic structure was found in 29 out of the 77 phylum-by-locality combinations containing sufficient data for Phylocom calculations (Fig. 4b). Only two of the NRI or NTI values were found to be significantly negative. After Bonferroni correction, no significant negative results remained; however, 16 and 9 significant positive NRI or NTI values remained in the sequence-level and cluster-level analysis, respectively. Notably, 28 out of the 41 significant NRI and NTI values at the OTU level were recovered in the single sequence-level analysis. Although the two approaches give qualitatively similar results, the discrepancy between the two possibly is a result of reduction in noise, especially in the terminal parts of the phylogenetic trees, as individual sequences are clustered together.Figure 4

Bottom Line: Different bacterial types seem to have different ecological niches that dictate their survival in different habitats.Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed.The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

View Article: PubMed Central - PubMed

Affiliation: Theoretical Population Ecology and Evolution Group, Lund University, Lund, Sweden. mikael.pontarp@biol.lu.se

ABSTRACT
The phylogenetic structure and community composition were analysed in an existing data set of marine bacterioplankton communities to elucidate the evolutionary and ecological processes dictating the assembly. The communities were sampled from coastal waters at nine locations distributed worldwide and were examined through the use of comprehensive clone libraries of 16S ribosomal RNA genes. The analyses show that the local communities are phylogenetically different from each other and that a majority of them are phylogenetically clustered, i.e. the species (operational taxonomic units) were more related to each other than expected by chance. Accordingly, the local communities were assembled non-randomly from the global pool of available bacterioplankton. Further, the phylogenetic structures of the communities were related to the water temperature at the locations. In agreement with similar studies, including both macroorganisms and bacteria, these results suggest that marine bacterial communities are structured by “habitat filtering”, i.e. through non-random colonization and invasion determined by environmental characteristics. Different bacterial types seem to have different ecological niches that dictate their survival in different habitats. Other eco-evolutionary processes that may contribute to the observed phylogenetic patterns are discussed. The results also imply a mapping between phenotype and phylogenetic relatedness which facilitates the use of community phylogenetic structure analysis to infer ecological and evolutionary assembly processes.

Show MeSH