Complete genome of Polaribacter huanghezhanensis KCTC 32516T isolated from glaciomarine fjord sediment of Svalbard.

Polaribacter huanghezhanensis KCTC 32516T is an aerobic, non-flagellated, Gram-negative, orange-colony-forming bacterium that was isolated from the surficial glaciomarine sediment of inner basin of Kongsfjorden, Svalbard. The sampling site is characterized by a sedimentation of organic depleted lithogenous particles from the nearby glaciers, resulting in reduction of organic matter concentration. In order to understand microbial adaptation to the oligotrophic environment, we here sequenced the complete genome of the P. huanghezhanensis KCTC 32516T. The genome consists of 2,587,874 bp (G + C content of 31.5%) with a single chromosome, 2391 protein-coding genes, 39 tRNAs, and 2 rRNA operons. Our comparative analysis revealed that the P. huanghezhanensis possess the smallest genome in fifteen Polaribacter species with genome. The streamlined genome of this species, required less resource in replication, could evolved by the nutrient deficiency in surrounding environment. Simultaneously, the 15 KOs involved in amino acid biosynthesis and anaplerotic carbon fixation is uniquely absent in the P. huanghezhanensis. In addition, although the advantage of small genome, other 15 KOs involved in resource recycling and stress resistance is uniquely present in sequenced genome. This result demonstrates that the sequenced genome serves as a valuable model for further studies aimed at elucidating the molecular mechanisms associated with adaptation to oligotrophic habitat.

Complete genome of Nocardioides aquaticus KCTC 9944T isolated from meromictic and hypersaline Ekho Lake, Antarctica.

Nocardioides aquaticus KCTC 9944T is an aerobic, non-motile, Gram-positive, psychrotolerant, non-spore-forming bacterium isolated from the surface water of Ekho Lake in the Vestfold Hills, East Antarctica. This meromictic lake separated from Antarctic seawater thousands of years ago exhibits steep gradients of salinity and temperature in the upper layer of the water column. The cells of N. aquaticus thriving in Ekho Lake are able to grow in wide ranges of temperature (3 to 43.5 °C) and salinity (0 to 15% NaCl). Here, we sequenced the complete genome of N. aquaticus KCTC 9944T, aiming to better understand the adaptation of this bacterium to the strong environmental gradients at the molecular level. The genome consists of 4,580,814 bp (G + C content of 73.2%) with a single chromosome, 4432 protein-coding genes, 51 tRNAs and 2 rRNA operons. The genome possesses genes for the Entner-Doudoroff pathway, photoheterotrophy, the conversion of acetate to acetyl-CoA, gluconeogenesis, and energy storage that are all advantageous to oligotrophic bacteria. The presence of genes involved in osmotic balance, fatty acid desaturation, cold and heat shock responses, and the oxygen affinities of respiratory oxidases are likely associated with high tolerance to strong gradients of salinity, temperature and oxygen concentration.

Complete genome of Polaromonas vacuolata KCTC 22033T isolated from beneath Antarctic Sea ice.

Polaromonas vacuolata KCTC 22033T is an obligate aerobic, Gram-negative, psychrophilic and rod-shaped bacterium isolated from beneath the sea ice off the coast of the Palmer Peninsula, Anvers Islands, Antarctica. P. vacuolata is the type species of Polaromonas genus and the first example of gas vacuolate Betaproteobacteria isolated from marine habitats. Here, we report a complete genome of P. vacuolata KCTC 22033T, which consists of 3,837,686 bp (G + C content of 52.07%) with a single chromosome, 3461 protein-coding genes, 56 tRNAs and 6 rRNA operons. Genomic analysis revealed the presence of genes involved in bacterial adaptation under saline conditions, cold adaptation via the production of gas vesicles and cell adhesion proteins, and a photoheterotrophic lifestyle when challenged by starvation. Intriguingly, several of these genes were likely acquired from species outside the Polaromonas genus. The genomic information therefore describes the unique evolution and adaptation of P. vacuolata to its extraordinary habitat, i.e., beneath the Antarctic sea ice.

Genomic Insight Into the Predominance of Candidate Phylum Atribacteria JS1 Lineage in Marine Sediments.

Candidate phylum Atribacteria JS1 lineage is one of the predominant bacterial groups in anoxic subseafloor sediments, especially in organic-rich or gas hydrate-containing sediments. However, due to the lack of axenic culture representatives, metabolic potential and biogeochemical roles of this phylum have remained elusive. Here, we examined the microbial communities of marine sediments of the Ross Sea, Antarctica, and found candidate phylum Atribacteria JS1 lineage was the most abundant candidate phylum accounting for 9.8-40.8% of the bacterial communities with a single dominant operational taxonomic unit (OTU). To elucidate the metabolic potential and ecological function of this species, we applied a single-cell genomic approach and obtained 18 single-cell amplified genomes presumably from a single species that was consistent with the dominant OTU throughout the sediments. The composite genome constructed by co-assembly showed the highest genome completeness among available Atribacteria JS1 genomes. Metabolic reconstruction suggested fermentative potential using various substrates and syntrophic acetate oxidation coupled with hydrogen or formate scavenging methanogens. This metabolic potential supports the predominance of Atribacteria JS1 in anoxic environments expanding our knowledge of the ecological function of this uncultivated group.

CLUSTOM-CLOUD: In-Memory Data Grid-Based Software for Clustering 16S rRNA Sequence Data in the Cloud Environment.

High-throughput sequencing can produce hundreds of thousands of 16S rRNA sequence reads corresponding to different organisms present in the environmental samples. Typically, analysis of microbial diversity in bioinformatics starts from pre-processing followed by clustering 16S rRNA reads into relatively fewer operational taxonomic units (OTUs). The OTUs are reliable indicators of microbial diversity and greatly accelerate the downstream analysis time. However, existing hierarchical clustering algorithms that are generally more accurate than greedy heuristic algorithms struggle with large sequence datasets. To keep pace with the rapid rise in sequencing data, we present CLUSTOM-CLOUD, which is the first distributed sequence clustering program based on In-Memory Data Grid (IMDG) technology-a distributed data structure to store all data in the main memory of multiple computing nodes. The IMDG technology helps CLUSTOM-CLOUD to enhance both its capability of handling larger datasets and its computational scalability better than its ancestor, CLUSTOM, while maintaining high accuracy. Clustering speed of CLUSTOM-CLOUD was evaluated on published 16S rRNA human microbiome sequence datasets using the small laboratory cluster (10 nodes) and under the Amazon EC2 cloud-computing environments. Under the laboratory environment, it required only ~3 hours to process dataset of size 200 K reads regardless of the complexity of the human microbiome data. In turn, one million reads were processed in approximately 20, 14, and 11 hours when utilizing 20, 30, and 40 nodes on the Amazon EC2 cloud-computing environment. The running time evaluation indicates that CLUSTOM-CLOUD can handle much larger sequence datasets than CLUSTOM and is also a scalable distributed processing system. The comparative accuracy test using 16S rRNA pyrosequences of a mock community shows that CLUSTOM-CLOUD achieves higher accuracy than DOTUR, mothur, ESPRIT-Tree, UCLUST and Swarm. CLUSTOM-CLOUD is written in JAVA and is freely available at http://clustomcloud.kopri.re.kr.

Halocynthiibacter arcticus sp. nov., isolated from Arctic marine sediment.

A Gram-staining-negative, oxidase- and catalase-positive, non-motile, aerobic and rod-shaped bacterium producing white colonies, PAMC 20958T, was isolated from a marine sediment of the Arctic. PAMC 20958T grew at 10-27 °C (optimally at 21 °C), at pH 5.5-9.5 (optimally at pH 7.0-7.5) and in the presence of 0.5-7.5 % (w/v) (optimally at 2.0 %) NaCl. PAMC 20958T showed 97.5 % 16S rRNA gene sequence similarity with Halocynthiibacter namhaensis KCTC 32362T and formed a robust phylogenetic clade with this species. The average nucleotide identity value between strain PAMC 20958T and H. namhaensis KCTC 32362T was 79.7 % and the genome-to-genome distance was 13.0 % on average. The genomic DNA G+C content calculated from the genome sequence was 53.2 mol%. The major fatty acids were C18 : 1ω7c and/or C18 : 1ω6c. The major respiratory isoprenoid quinone was ubiquinone-10 (Q-10) and major polar lipids were phosphatidylcholine, phosphatidylglycerol, an unidentified aminolipid and two unidentified lipids. On the basis of phylogenetic analysis and genotypic and phenotypic data obtained in this study, it is concluded that strain PAMC 20958T ( = KCTC 42129T = JCM 30530T) represents the type strain of a novel species of the genus Halocynthiibacter, for which the name Halocynthiibacter arcticus sp. nov. is proposed.

A tree of cellular life inferred from a genomic census of molecular functions.

Phylogenomics aims to describe evolutionary relatedness between organisms by analyzing genomic data. The common practice is to produce phylogenomic trees from molecular information in the sequence, order, and content of genes in genomes. These phylogenies describe the evolution of life and become valuable tools for taxonomy. The recent availability of structural and functional data for hundreds of genomes now offers the opportunity to study evolution using more deep, conserved, and reliable sets of molecular features. Here, we reconstruct trees of life from the functions of proteins. We start by inferring rooted phylogenomic trees and networks of organisms directly from Gene Ontology annotations. Phylogenies and networks yield novel insights into the emergence and evolution of cellular life. The ancestor of Archaea originated earlier than the ancestors of Bacteria and Eukarya and was thermophilic. In contrast, basal bacterial lineages were non-thermophilic. A close relationship between Plants and Metazoa was also identified that disagrees with the traditional Fungi-Metazoa grouping. While measures of evolutionary reticulation were minimum in Eukarya and maximum in Bacteria, the massive role of horizontal gene transfer in microbes did not materialize in phylogenomic networks. Phylogenies and networks also showed that the best reconstructions were recovered when problematic taxa (i.e., parasitic/symbiotic organisms) and horizontally transferred characters were excluded from analysis. Our results indicate that functionomic data represent a useful addition to the set of molecular characters used for tree reconstruction and that trees of cellular life carry in deep branches considerable predictive power to explain the evolution of living organisms.

CLUSTOM: a novel method for clustering 16S rRNA next generation sequences by overlap minimization.

The recent nucleic acid sequencing revolution driven by shotgun and high-throughput technologies has led to a rapid increase in the number of sequences for microbial communities. The availability of 16S ribosomal RNA (rRNA) gene sequences from a multitude of natural environments now offers a unique opportunity to study microbial diversity and community structure. The large volume of sequencing data however makes it time consuming to assign individual sequences to phylotypes by searching them against public databases. Since ribosomal sequences have diverged across prokaryotic species, they can be grouped into clusters that represent operational taxonomic units. However, available clustering programs suffer from overlap of sequence spaces in adjacent clusters. In natural environments, gene sequences are homogenous within species but divergent between species. This evolutionary constraint results in an uneven distribution of genetic distances of genes in sequence space. To cluster 16S rRNA sequences more accurately, it is therefore essential to select core sequences that are located at the centers of the distributions represented by the genetic distance of sequences in taxonomic units. Based on this idea, we here describe a novel sequence clustering algorithm named CLUSTOM that minimizes the overlaps between adjacent clusters. The performance of this algorithm was evaluated in a comparative exercise with existing programs, using the reference sequences of the SILVA database as well as published pyrosequencing datasets. The test revealed that our algorithm achieves higher accuracy than ESPRIT-Tree and mothur, few of the best clustering algorithms. Results indicate that the concept of an uneven distribution of sequence distances can effectively and successfully cluster 16S rRNA gene sequences. The algorithm of CLUSTOM has been implemented both as a web and as a standalone command line application, which are available at http://clustom.kribb.re.kr.