Complete genome sequence of Thioalkalivibrio paradoxus type strain ARh 1T, an obligately chemolithoautotrophic haloalkaliphilic sulfur-oxidizing bacterium isolated from a Kenyan soda lake

Thioalkalivibrio paradoxus strain ARh 1T is a chemolithoautotrophic, non-motile, Gram-negative bacterium belonging to the Gammaproteobacteria that was isolated from samples of haloalkaline soda lakes. It derives energy from the oxidation of reduced sulfur compounds and is notable for its ability to grow on thiocyanate as its sole source of electrons, sulfur and nitrogen. The full genome consists of 3,756,729 bp and comprises 3,500 protein-coding and 57 RNA-coding genes. This organism was sequenced as part of the community science program at the DOE Joint Genome Institute.


Introduction
Soda lakes are characterized by a high and stable pH (>9) due to the presence of molar concentrations of soluble carbonates as the dominant anions and a moderate to high salinity [1]. They are found in arid zones in many parts of the world, for example, in the Kulunda Steppe in Russia, North-Eastern China, the Rift Valley in Africa and the arid regions of California and Nevada (e.g., Mono Lake, Big Soda Lake). Despite their (extremely) haloalkaline character, these environments harbor a rich microbial diversity that is responsible for driving highly active biogeochemical cycles [2], of which the sulfur cycle is the most active. Our current research focuses on a group of chemolithoautotrophic sulfur-oxidizing bacteria that belong to the genus Thioalkalivibrio in the class Gammaproteobacteria. These organisms are of interest because of their role in the oxidative part of the sulfur cycle in soda lakes [3] and their application in the sustainable removal of sulfur from wastewater and gas streams [4]. To better understand the success of this group of organisms, we have sequenced the genomes of a large number of Thioalkalivibrio isolates. Here we present the genome sequence of T. paradoxus ARh 1 T (= DSM 13531 T = JCM 11367 T ).

Classification and features
This obligate aerobic and haloalkaliphilic strain, which was isolated from a mixed sample of sediments from Kenyan soda lakes, is a non-motile coccoid rod forming intracellular sulfur as an obligate intermediate during oxidation of thiosulfate and thiocyanate (Fig. 1). It is an obligate chemolithoautotroph, capable of using a variety of reduced, inorganic sulfur compounds, including sulfide, thiosulfate and polysulfide, as electron donor for carbon fixation. It can also oxidize CS 2 (carbon disulfide). Of special interest is its ability to grow with thiocyanate (NCS − ) as electron donor, with a relatively high growth rate of 0.08-0.1 h −1 in continuous culture, compared to 0.01-0.015 h -1 for growth on thiosulfate [5]. Phylogenetic analysis based on 16S rRNA sequences shows that T. paradoxus is closely related to Thioalkalivibrio nitratireducens ALEN 2 T (Fig. 2). An overview of basic features of the organism is provided in Table 1.

Genome project history
In order to better understand the diversity within the genus Thioalkalivibrio, as well as their biogeochemical role in soda lakes, a large number of isolates (approximately 70) was sequenced at the Joint Genome Institute. The full genome of the type strain of Thioalkalivibrio paradoxus presented here contains 3.8 million basepairs. Sequencing was performed at the JGI under project number 401912 and the sequence data was subsequently released in Genbank on December 31, 2013. A project overview is provided in Table 2.

Growth conditions and genomic DNA preparation
A buffer using sodium carbonate and bicarbonate, with a total salt concentration of 0.6 M Na + , was used for cultivation of the organism; the energy source was thiosulfate (40 mM). After harvesting, the cells were stored at −80°C for further processing. Genomic DNA was extracted using a standard chloroform-phenol-isoamyl alcohol mixture, followed by ethanol precipitation. After vacuum drying, the pellet was dissolved in water and the quantity and quality of the DNA determined using the JGI-provided Mass Standard Kit.

Genome sequencing and assembly
The draft genome of Thioalkalivibrio paradoxus ARh 1 T was generated at the DOE Joint Genome Institute (JGI) using Illumina data [6]. For this genome, we constructed and sequenced an Illumina short-insert paired-end library with an average insert size of 270 bp which generated 18,589,770 reads and an Illumina long-insert paired-end library with an average insert size of 7,058.67 +/-3247.54 bp which generated 20,051,794 reads totaling 5,796 Mbp of Illumina data (unpublished, Feng Chen). All general aspects of library construction and sequencing performed at the JGI can be found at http://www.jgi. doe.gov/. The initial draft assembly contained 83 contigs in 11 scaffolds. The initial draft data was assembled with ALLPATHS [7], version 39750, and the consensus was computationally shredded into 10 Kbp overlapping fake reads (shreds). The Illumina draft data was also assembled with Velvet, version 1.1.05 [8], and the consensus sequences were computationally shredded into 1.5 Kbp overlapping fake reads (shreds). The Illumina draft data was assembled again with Velvet using the shreds from the first Velvet assembly to guide the next assembly. The consensus from the second Velvet assembly was shredded into 1.5 Kbp overlapping fake reads. The fake reads from the ALLPATHS assembly and both Velvet assemblies and a subset of the Illumina CLIP paired-end reads were assembled using parallel phrap, version 4.24 (High Performance Software, LLC). Possible mis-assemblies were corrected with manual editing in Consed [9][10][11]. Gap closure was accomplished using repeat resolution software (Wei Gu, unpublished), and sequencing of bridging PCR fragments with Sanger and/or PacBio (unpublished, Cliff Han) technologies. A total of 50 additional sequencing reactions were completed to close gaps and to raise the quality of the final sequence. The size of the genome is 3.8 Mb and the final assembly is based on 5,796 Mbp of Illumina draft data, which provides an average 1,486X coverage of the genome.

Genome annotation
The assembled sequence was annotated using the JGI prokaryotic annotation pipeline [12] and was further reviewed a b Fig. 1 Thin section electron microscopy photographs of cells of strain ARh 1 T grown with thiocyanate in batch (a) and chemostat (b) cultures at pH 10 and 0.6 M total Na + . S(in) -intracellular sulfur globe; S(out)excreted sulfur globe damaging the cell membrane and the wall; N -nucleoid; C -carboxysomes using the Integrated Microbial Genomes -Expert Review (IMG-ER) platform [13]. Genes were identified using Prodigal [14], followed by manual curation using GenePRIMP [15]. Predicted CDSs were translated and used to search the NCBI non-redundant, UniProt, TIGRFam, Pfam, KEGG, COG and InterPro databases. The tRNAS-canSE tool [16] was used to detect tRNA genes and ribosomal RNA genes were detected using models contructed from SILVA [17]. Other RNA genes were predicted using Rfam profiles in Infernal [18]. CRISPR elements were detected using CRT [19] and PILER-CR [20]. Further annotation was performed using the Integrated Microbial Genomics (IMG) platform [21].

Genome properties
The finished genome with a G + C percentage of 66.06 % comprises a single chromosome of approximately 3.8 Mb (Fig. 3). There are 3557 genes of which 3,500 are proteincoding genes (a summary of genome properties is shown    2 Phylogenetic tree, based on 16S rRNA sequences, of Thioalkalivibrio and various members of the Ectothiorhodospiraceae family. ARB [22] was used for tree construction and MEGA6 [23] for the bootstrap analysis. Alphaproteobacteria were used as the outgroup and pruned from the finished tree  Table 3). Approximately two-thirds of the protein coding genes could be assigned to a COG functional category (Table 4).

Conclusions
The availability of high-quality genomic sequences of the type strains of Thioalkalivibrio, the dominant genus of sulfur-oxidizing bacteria in soda lakes, is an invaluable tool for gaining a more complete understanding of the biogeochemistry of these extreme environments. Additionally, this information may provide new insights into the exact mechanisms of adaptation these bacteria have evolved to not only survive, but thrive in this habitat. Finally, the genome may contain clues that will help improve the existing biotechnological applications of this organism in bioremediation. The total is based on the total number of protein coding genes in the genome