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Targeted recovery of novel phylogenetic diversity from next-generation sequence data.

Lynch MD, Bartram AK, Neufeld JD - ISME J (2012)

Bottom Line: We combined BLASTN network analysis, phylogenetics and targeted primer design to amplify 16S rRNA gene sequences from unique potential bacterial lineages, comprising part of the rare biosphere from a multi-million sequence data set from an Arctic tundra soil sample.Demonstrating the feasibility of the protocol developed here, three of seven recovered phylogenetic lineages represented extremely divergent taxonomic entities.A comparison to twelve next-generation data sets from additional soils suggested persistent low-abundance distributions of these novel 16S rRNA genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, University of Waterloo, Waterloo, ON, Canada.

ABSTRACT
Next-generation sequencing technologies have led to recognition of a so-called 'rare biosphere'. These microbial operational taxonomic units (OTUs) are defined by low relative abundance and may be specifically adapted to maintaining low population sizes. We hypothesized that mining of low-abundance next-generation 16S ribosomal RNA (rRNA) gene data would lead to the discovery of novel phylogenetic diversity, reflecting microorganisms not yet discovered by previous sampling efforts. Here, we test this hypothesis by combining molecular and bioinformatic approaches for targeted retrieval of phylogenetic novelty within rare biosphere OTUs. We combined BLASTN network analysis, phylogenetics and targeted primer design to amplify 16S rRNA gene sequences from unique potential bacterial lineages, comprising part of the rare biosphere from a multi-million sequence data set from an Arctic tundra soil sample. Demonstrating the feasibility of the protocol developed here, three of seven recovered phylogenetic lineages represented extremely divergent taxonomic entities. These divergent target sequences correspond to (a) a previously unknown lineage within the BRC1 candidate phylum, (b) a sister group to the early diverging and currently recognized monospecific Cyanobacteria Gloeobacter, a genus containing multiple plesiomorphic traits and (c) a highly divergent lineage phylogenetically resolved within mitochondria. A comparison to twelve next-generation data sets from additional soils suggested persistent low-abundance distributions of these novel 16S rRNA genes. The results demonstrate this sequence analysis and retrieval pipeline as applicable for exploring underrepresented phylogenetic novelty and recovering taxa that may represent significant steps in bacterial evolution.

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Maximum likelihood phylogenies resolving UL sequences with proximity to organelle 16S rRNA gene sequences. (a) UL9 sequences with cyanobacterial and chloroplast 16S rRNA gene sequence data and (b) UL13 sequences with mitochondrial 16S rRNA gene sequence data. Node support values correspond to ML bootstrap (GTRGAMMA)/ML bootstrap (S16)/SH-like test (GTR+Γ). Note: size of collapsed wedges does not correspond to the number of taxa. *=full phylogenetic support (100/100/1.00). Support values <50% or 0.5 are not shown.
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fig5: Maximum likelihood phylogenies resolving UL sequences with proximity to organelle 16S rRNA gene sequences. (a) UL9 sequences with cyanobacterial and chloroplast 16S rRNA gene sequence data and (b) UL13 sequences with mitochondrial 16S rRNA gene sequence data. Node support values correspond to ML bootstrap (GTRGAMMA)/ML bootstrap (S16)/SH-like test (GTR+Γ). Note: size of collapsed wedges does not correspond to the number of taxa. *=full phylogenetic support (100/100/1.00). Support values <50% or 0.5 are not shown.

Mentions: As the phylogenetic backbone used here did not include organelle sequences, we performed additional phylogenetic analyses by including 16S rRNA gene sequences from chloroplasts and mitochondria to explore the origin of UL9 and UL13 sequences. Informative GenBank matches, most notably Gloeobacter, were also included. The cyanobacterial phylogenetic placement of UL9 sequences was consistent with previous phylogenies (Figures 3 and 4) even after chloroplast 16S rRNA sequences were included (Figure 5a). Experimental sequences were monophyletic with Gloeobacter and sister to the remaining Cyanobacteria and chloroplast sequences. Sequences in UL13 resolved as two monophyletic groups, both supported within clades corresponding to mitochondrial sequences from bikont (‘two flagella') organisms (Figure 5b). One clade was moderately supported as sister to mitochondrial sequences from Acanthamoeba sp., while the other group was strongly supported as monophyletic with uncultured organisms and grouped with organelles from predominantly algal lineages including Rhodophyta (red algae) and Chromalveolata. The 16S rRNA genes from mitochondria are poorly represented in current sequence databases and, in general, phylogenies inferred from mitochondrial sequences tended to be poorly supported here (Figure 5b).


Targeted recovery of novel phylogenetic diversity from next-generation sequence data.

Lynch MD, Bartram AK, Neufeld JD - ISME J (2012)

Maximum likelihood phylogenies resolving UL sequences with proximity to organelle 16S rRNA gene sequences. (a) UL9 sequences with cyanobacterial and chloroplast 16S rRNA gene sequence data and (b) UL13 sequences with mitochondrial 16S rRNA gene sequence data. Node support values correspond to ML bootstrap (GTRGAMMA)/ML bootstrap (S16)/SH-like test (GTR+Γ). Note: size of collapsed wedges does not correspond to the number of taxa. *=full phylogenetic support (100/100/1.00). Support values <50% or 0.5 are not shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475379&req=5

fig5: Maximum likelihood phylogenies resolving UL sequences with proximity to organelle 16S rRNA gene sequences. (a) UL9 sequences with cyanobacterial and chloroplast 16S rRNA gene sequence data and (b) UL13 sequences with mitochondrial 16S rRNA gene sequence data. Node support values correspond to ML bootstrap (GTRGAMMA)/ML bootstrap (S16)/SH-like test (GTR+Γ). Note: size of collapsed wedges does not correspond to the number of taxa. *=full phylogenetic support (100/100/1.00). Support values <50% or 0.5 are not shown.
Mentions: As the phylogenetic backbone used here did not include organelle sequences, we performed additional phylogenetic analyses by including 16S rRNA gene sequences from chloroplasts and mitochondria to explore the origin of UL9 and UL13 sequences. Informative GenBank matches, most notably Gloeobacter, were also included. The cyanobacterial phylogenetic placement of UL9 sequences was consistent with previous phylogenies (Figures 3 and 4) even after chloroplast 16S rRNA sequences were included (Figure 5a). Experimental sequences were monophyletic with Gloeobacter and sister to the remaining Cyanobacteria and chloroplast sequences. Sequences in UL13 resolved as two monophyletic groups, both supported within clades corresponding to mitochondrial sequences from bikont (‘two flagella') organisms (Figure 5b). One clade was moderately supported as sister to mitochondrial sequences from Acanthamoeba sp., while the other group was strongly supported as monophyletic with uncultured organisms and grouped with organelles from predominantly algal lineages including Rhodophyta (red algae) and Chromalveolata. The 16S rRNA genes from mitochondria are poorly represented in current sequence databases and, in general, phylogenies inferred from mitochondrial sequences tended to be poorly supported here (Figure 5b).

Bottom Line: We combined BLASTN network analysis, phylogenetics and targeted primer design to amplify 16S rRNA gene sequences from unique potential bacterial lineages, comprising part of the rare biosphere from a multi-million sequence data set from an Arctic tundra soil sample.Demonstrating the feasibility of the protocol developed here, three of seven recovered phylogenetic lineages represented extremely divergent taxonomic entities.A comparison to twelve next-generation data sets from additional soils suggested persistent low-abundance distributions of these novel 16S rRNA genes.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, University of Waterloo, Waterloo, ON, Canada.

ABSTRACT
Next-generation sequencing technologies have led to recognition of a so-called 'rare biosphere'. These microbial operational taxonomic units (OTUs) are defined by low relative abundance and may be specifically adapted to maintaining low population sizes. We hypothesized that mining of low-abundance next-generation 16S ribosomal RNA (rRNA) gene data would lead to the discovery of novel phylogenetic diversity, reflecting microorganisms not yet discovered by previous sampling efforts. Here, we test this hypothesis by combining molecular and bioinformatic approaches for targeted retrieval of phylogenetic novelty within rare biosphere OTUs. We combined BLASTN network analysis, phylogenetics and targeted primer design to amplify 16S rRNA gene sequences from unique potential bacterial lineages, comprising part of the rare biosphere from a multi-million sequence data set from an Arctic tundra soil sample. Demonstrating the feasibility of the protocol developed here, three of seven recovered phylogenetic lineages represented extremely divergent taxonomic entities. These divergent target sequences correspond to (a) a previously unknown lineage within the BRC1 candidate phylum, (b) a sister group to the early diverging and currently recognized monospecific Cyanobacteria Gloeobacter, a genus containing multiple plesiomorphic traits and (c) a highly divergent lineage phylogenetically resolved within mitochondria. A comparison to twelve next-generation data sets from additional soils suggested persistent low-abundance distributions of these novel 16S rRNA genes. The results demonstrate this sequence analysis and retrieval pipeline as applicable for exploring underrepresented phylogenetic novelty and recovering taxa that may represent significant steps in bacterial evolution.

Show MeSH
Related in: MedlinePlus