Abstract
Sulfobacillus thermosulfidooxidans strain Cutipay is a mixotrophic, acidophilic, moderately thermophilic bacterium isolated from mining environments of the north of Chile, making it an interesting subject for studying the bioleaching of copper. We introduce the draft genome sequence and annotation of this strain, which provide insights into its mechanisms for heavy metal resistance.
GENOME ANNOUNCEMENT
Sulfobacillus thermosulfidooxidans strain Cutipay has been identified as a sulfur- and iron-oxidizing, Gram-positive, sporulating, acidophilic, and moderately thermophilic bacterium. It was microbiologically characterized as having an optimum growth temperature of 45°C and an optimum pH range of 2.0 to 2.5 when growing in the presence of Fe2+ and/or sulfur supplemented with yeast extract. It was originally named Cutipay from the indigenous Mapudungun word meaning “coming from the water,” because it was isolated from naturally occurring effluents in the extreme mining environment of the north of Chile. Using phylogenetic analyses, it was identified as a Sulfobacillus thermosulfidooxidans species first described by Golovacheva and Karaviako in 1978 (2).
The draft genome sequence of S. thermosulfidooxidans strain Cutipay was determined by whole-genome shotgun sequencing using a mixed technology strategy consisting of a run of the Ion Torrent PGM 316 Chip (8) on an unpaired library and two runs of the Roche 454–GS Junior pyrosequencing platform (6) on one 3-kb mate pair library and 1 unpaired library generating a 116× coverage. Assembly was performed using wgs-assembler (Celera Assembler) version 7 (7). Identification of coding regions and annotation were performed using protocols described in references 3 and 5.
The Sulfobacillus thermosulfidooxidans Cutipay strain draft genome was assembled in 47 contigs. Using mate information, the final assembly has 3,862,012 total bp in 35 scaffolds. The maximum scaffold length is 1,134,202 bp, and the minimum length is 1,007 bp. The scaffold length has a mean of 110,343 bp, a median of 30,355 bp, and an N50 length of 509,367 bp, while the genome has a GC content of 49.3%, which is similar to that of Sulfobacillus thermosulfidooxidans subspecies thermotolerans (4).
According to our analysis, 3,600 putative genes and 54 tRNAs were predicted. Three 5S, 16S, and 23S partial operons were found. Carbon and sulfur metabolism enzymes described previously have also been identified (1). Differences between arsenic resistances in the arsRB operon were found. The arsRB operon includes arsR regulator, arsB arsenite efflux pump, kumamolisin-As precursor, and glycosyl transferase codifying genes previously described in S. thermosulfidooxidans strain VKM B-1269 (9, 10). We have found another open reading frame (ORF) with no homology between the genes for glycosyl transferase and kumamolisin-As precursor present in S. thermosulfidooxidans strain Cutipay and a putative arsC in another region of the genome. The arsC gene codes for an arsenate reductase not previously described in S. thermosulfidooxidans (9, 10), indicating new arsenic resistance capacities for this species. Genome analysis shows putative copper-sensing genes copR and copS and the gene for a DNA-binding transcriptional activator of copper-responsive regulon genes cueR, indicating the presence of a copAZ resistance operon.
In summary, using a novel mixed-sequencing strategy for an acidophilic organism, we obtained a high-quality draft. This new draft reveals a heavy metal resistance for Sulfobacillus thermosulfidooxidans that has not been previously described, and it provides evidence for future experimental research and understanding of survival in acidic environments.
Nucleotide sequence accession numbers.
This Whole Genome Shotgun project has been deposited at DDBJ/EMBL/GenBank under the accession number ALWJ00000000. The version described in this paper is the first version, ALWJ01000000.
ACKNOWLEDGMENTS
This work was supported by BioSigma S.A. and Fondap grant 15090007, Center for Genome Regulation, Basal grant of the Center for Mathematical Modeling, UMI2807 UCHILE-CNRS.
We acknowledge the National Laboratory for High Performance Computing at the Center for Mathematical Modeling (PIA ECM-02.-CONICYT) and the sequencing center Omics Solutions.
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