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. 2011;1:135.
doi: 10.1038/srep00135. Epub 2011 Oct 31.

New Abundant Microbial Groups in Aquatic Hypersaline Environments

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Free PMC article

New Abundant Microbial Groups in Aquatic Hypersaline Environments

Rohit Ghai et al. Sci Rep. .
Free PMC article

Abstract

We describe the microbiota of two hypersaline saltern ponds, one of intermediate salinity (19%) and a NaCl saturated crystallizer pond (37%) using pyrosequencing. The analyses of these metagenomes (nearly 784 Mb) reaffirmed the vast dominance of Haloquadratum walsbyi but also revealed novel, abundant and previously unsuspected microbial groups. We describe for the first time, a group of low GC Actinobacteria, related to freshwater Actinobacteria, abundant in low and intermediate salinities. Metagenomic assembly revealed three new abundant microbes: a low-GC euryarchaeon with the lowest GC content described for any euryarchaeon, a high-GC euryarchaeon and a gammaproteobacterium related to Alkalilimnicola and Nitrococcus. Multiple displacement amplification and sequencing of the genome from a single archaeal cell of the new low GC euryarchaeon suggest a photoheterotrophic and polysaccharide-degrading lifestyle and its relatedness to the recently described lineage of Nanohaloarchaea. These discoveries reveal the combined power of an unbiased metagenomic and single cell genomic approach.

Figures

Figure 1
Figure 1. Comparison of GC% of sequences from four metagenomic datasets of increasing salinities.
DCM3: Deep Chlorophyll Maximum (3% salinity), PC6: Punta Cormoran (6% salinity), SS19: Solar Saltern (19% salinity) and SS37: Solar Saltern (37% salinity). GC% was computed for each read and the percentage of the dataset in intervals of bin width 5 is shown.
Figure 2
Figure 2. Comparison of isoelectric point profiles of the predicted proteins in the four metagenomic datasets of increasing salinities.
The reads that had a reliable hit to a protein sequence in the NR database were used for the analyses (see methods). The pI was computed for each translated read and is shown as a percentage of the dataset in intervals of bin width 1.
Figure 3
Figure 3. Taxonomic profiles using 16S rRNA sequences across the salinity gradient.
Figure 4
Figure 4. Phylogenetic affiliation of the 16S rRNA actinobacterial reads in the Punta Cormoran and the SS19 datasets.
The names of the actinobacterial clades are indicated to the right. Locations of the metagenomic reads from Punta Cormoran and SS19 datasets are indicated in bold with the number of reads shown within brackets. The scale bar represents 10 base substitutions per 100 nt positions.
Figure 5
Figure 5. Principal component analysis of tetranucleotide frequencies of assembled contigs from SS19.
Reference genomes are shown as larger circles. The following types of contigs are shown, Dark Yellow: Gammaproteobacterial contigs, Blue: High GC Euryarchaeota contigs, Green: Assembled contigs assigned to Haloquadratum walsbyi, Yellow: Assembled H. walsbyi contigs with only a single gene without a best hit to H. walsbyi (but still all hits to Euryarchaeota), Light Blue: Low GC Euryarchaeota contigs. The total number of contigs for each cluster (Gammaproteobacteria, High GC Euryarchaeota, H. walsbyi and Low GC Euryarchaeota), the total length, mean length and GC% range is also indicated.
Figure 6
Figure 6. Phylogeny of the rhodopsin gene fragments detected in the metagenomic datasets.
Reference sequences have been introduced to provide a framework and represent all major types of microbial rhodopsins described (identified by the name of the microbe and accession number in GenBank). The metagenomic reads are all identified by the name of the dataset from which they were identified except for the one retrieved from the Candidatus Haloredivivus genome. The numbers of identical sequences are indicated in brackets after each read identifier.

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