Draft Genome Sequence of Desulfovibrio sp. Strain CSMB_222, Isolated from Coal Seam Formation Water

ABSTRACT Subsurface coal seams contain microbial consortia with various taxa, each with a different role in the degradation of coal organic matter. This study presents the sequenced and annotated genome of Desulfovibrio sp. strain CSMB_222, a bacterium isolated from eastern Australian coal seams.

C oal seams harbor microbial consortia that catabolize organic matter in coal to methane (1,2). This generation of biogenic methane has important environmental and economic significance. Methane has value as a transition fuel and a source of blue hydrogen (3). Thus, investigation of coal microbes and their roles in coal-to-methane transformations is critical to enhance methane yields and to improve our understanding of subsurface microbiology.
The Desulfovibrio sp. strain CSMB_222 genome contained two CRISPR arrays with 96 spacer sequences, suggesting that viral predation is common, as in many other taxa in coal seam subsurface environments (14)(15)(16). The role of this taxon in sulfate-poor coal seams in Australia is unknown; however, it seems likely to be engaged in syntrophy with hydrogenotrophic methanogens, similar to Desulfovibrio desulfuricans (17) and Desulfovibrio vulgaris (18)(19)(20).
Data availability. This whole-genome shotgun project has been deposited in DDBJ/ ENA/GenBank under the accession number JAHLVU000000000, BioProject number PRJNA734375, and BioSample number SAMN19490895. The version described in this paper is version JAHLVU010000000. The raw sequencing reads are available from the Sequence Read Archive (SRA) under BioProject number PRJNA734375.

ACKNOWLEDGMENTS
We acknowledge Nai Tran-Dinh and Silas Vick for assistance with anaerobic culturing and advice on experimental strategies, respectively, Debra Lock for logistical assistance, and Kaydy Pinetown for geological insight.
A.G.M. is funded by a postgraduate scholarship from Macquarie University, with additional support from the CSIRO Energy strategic research initiative. FIG 1 Phylogenetic tree based on 16S rRNA sequences, using a similarity matrix generated by PUP v1.0 analysis (21) (https://github.com/PaulGreenfieldOz/WorkingDogs). The similarity matrix was converted to the Newick format using hierarchical clustering (22) for phylogenetic visualization with TreeDyn v198.3 (23,24). The numbers in parentheses are GenBank accession numbers.