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. 2011 Oct;193(19):5543. doi: 10.1128/JB.05689-11

Draft Genome Sequence of the Marine Sediment-Derived Actinomycete Streptomyces xinghaiensis NRRL B24674T

Xinqing Zhao 1,*, Tianhong Yang 1
PMCID: PMC3187413  PMID: 21914869

Abstract

Actinobacteria are a rich source of novel natural products. We recently characterized Streptomyces xinghaiensis NRRL B24674T as a novel species of marine origin. Here we report the draft genome sequence of this species. This is the first validly published marine streptomycete for which a genome sequence has been presented.

GENOME ANNOUNCEMENT

Streptomyces xinghaiensis NRRL B24674T, a novel species of Streptomyces (10), was isolated from a marine sediment sample collected from Xinghai Bay, Dalian, China. Herein we present a draft genome sequence of S. xinghaiensis.

The nucleotide sequence was determined using Roche/454 pyrosequencing and Illumina/Solexa sequencing by synthesis technology. The Mate-paired reads generated by the Solexa sequencer were assembled by SOAP (6), and the contigs were split into fragments. Then 454 reads and the Solexa sequence fragments were assembled with the Newbler assembler. Coding sequences (CDSs) were predicted by Prodigal (4). Functional assignment was obtained by performing a sequence similarity search with BLAST (http://blast.ncbi.nlm.nih.gov/Blast.cgi) against the COG (http://www.ncbi.nlm.nih.gov/COG/) reference database and the nonredundant GenBank CDS database. A set of in-house Perl scripts and EMBOSS (http://emboss.sourceforge.net/) were used for sequence manipulation. Functional annotation was based on BLASTP with the KEGG databases. tRNA genes were directly predicted using the tRNAscan-SE tool (8). The phylogenetic tree was reconstructed by the CVTree server (7).

The S. xinghaiensis draft genome contains 7,618,725 bp with a GC content of 72.5%, representing approximately 92.7% of the 8.2-Mb estimated size of the genome. The genome consists of one linear chromosome with 6 rRNA operons, 65 tRNA genes, and 6,654 CDSs. For the CDSs, 5,563 proteins could be assigned to COG families. Four thousand nine hundred eighty putative proteins were matched to Streptomyces spp., and 1,091 CDSs encode proteins with no match to any known proteins in the databases.

Genome analysis revealed a number of genes related to biosynthesis of secondary metabolites. At least 15 clusters involved in secondary metabolism were identified; these include one gene cluster that highly resembles the gene cluster of ribostamycin (9), an aminoglycoside antibiotic. Other gene clusters for the biosynthesis of polyketides, terpenes, and nonribosomal peptide antibiotics were also inferred. Many putative antibiotic biosynthesis genes show low identity with the known ones, which indicates that the species is a potential producer of novel natural products.

The S. xinghaiensis draft genome also contains genes encoding cellulases, xylanases, and chitinases, as well as genes encoding protease, lipase, peptidase, and esterase. Genes involved in the resistance to heavy metals mercury, copper, and nickel were also identified, indicating the potential application of this strain in biomass bioconversion and environmental bioremediation.

Although the genomic sequences of marine sediment-derived strains Streptomyces strain PP-C42 (2) and Streptomyces griseoaurantiacus M045 (5) were reported recently, S. xinghaiensis is the first validly published marine streptomycete for which a genome sequence has been reported. Comparison of the genomes of these marine sediment-derived strains with those of terrestrial origin will provide insight into the environmental adaptation and evolution of Streptomyces species. The genome mining of S. xinghaiensis will further explore the chemical diversity and genetic diversity of this species for discovery of novel compounds and enzymes for biotechnology applications (1, 3).

Nucleotide sequence accession numbers.

The genome sequence has been deposited at DDBJ/EMBL/GenBank under accession no. AFRP00000000. The version described in this paper is the first version, deposited under AFRP01000000.

Acknowledgments

This work was supported by a grant from the Open Project of the State Key Laboratory of Bioreactor Engineering, China.

We are grateful to the Tianjin Biochip Corporation, China, and for the help of Junning-Wang for bioinformatic analysis.

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