Verrucosispora sp. strain FIM060022 shows multiple biological activities and produces polytype structure compounds, including abyssomicins, proximicin A, lumichrome, denosine, and desferrioxamine-like compounds.
ABSTRACT
Verrucosispora sp. strain FIM060022 shows multiple biological activities and produces polytype structure compounds, including abyssomicins, proximicin A, lumichrome, denosine, and desferrioxamine-like compounds. We present the draft genome sequence of the strain to help predict the biosynthesis of these compounds, identify further biosynthetic potential, and facilitate directed secondary metabolite production.
ANNOUNCEMENT
The strain FIM060022 was isolated from a sponge collected from Putian, in the Fujian Province of China, and identified as a Verrucosispora sp., which is most closely related to Verrucosispora maris based on 16S rRNA sequencing and morphological and physiological characteristics (GenBank accession number KJ143624) (1–5). Turbidity tests revealed that it exhibited broad-spectrum antibacterial activity against Escherichia coli, Bacillus subtilis, Candida albicans, Rhodotorula, Staphylococcus aureus, and Cryptococcus neoformans (3). Its compound diversity also corresponded to the broad-spectrum antibacterial diversity (6). To further probe the relationship between the mechanism of secondary metabolite production and the antibacterial activity, the genomic DNA of strain FIM060022 was extracted using the DNA-winding protocol (7). Whole-genome shotgun sequencing was then performed using the MiSeq sequencing platform (Illumina, Inc., San Diego, CA) after generating paired-end libraries with an insert size of 400 bp (8). The sequences were then filtered using AdapterRemoval version 2.1.7 (9) to remove any 3′-terminal contamination. Using SOAPec version 2.0 software (10), we performed quality correction of all reads based on k-mer frequency, with the k-mer used for correction set to 17. The final genome was assembled de novo using A5-miseq version 20150522 (11). All the assembled scaffolds were then subjected to gene prediction using GLIMMER 3.0 (12). The metabolic pathways were explored using the Gene Ontology (GO) and Cluster of Orthologous Groups (COG) databases. The GO annotation of protein-coded genes was performed using the Blast2GO software (13). The annotation of protein-coding genes was completed by the BLAST software, and the database used for BLAST was EggNOG (14). The biosynthesis gene clusters underlying secondary metabolite production in strain FIM060022 were predicted using anti-SMASH (15). A BLASTP search against the NCBI nonredundant protein database was performed for predicting the function of proteins encoded in this gene cluster. Default settings were used for all software.
A total of 2,845,130 clean paired-end reads were generated with a 98-fold depth of coverage of the whole genome. The draft genome sequence of strain FIM060022 contained 29 scaffolds (N50 value of 453,524 bp) with a total size of 6,426,968 bp and had a mean GC content of 70.93%. The results from GLIMMER 3.0 predicted 5,806 open reading frames (ORFs) with an average length of 978.86 bp and a coding density of 88.43%. Strain FIM060022 also had many predicted protein-coding genes; 3,245 coding DNA sequences (CDSs) were found in 77 functional GO groups, and 3,269 CDSs were found in 21 COG groups. Among these, 178 CDSs were associated with secondary metabolite biosynthesis, transport, and catabolism (3.07% of the total draft genome), 395 CDSs were associated with amino acid transport and metabolism (6.80%), 147 CDSs were associated with coenzyme transport and metabolism (2.53%), and 177 CDSs were associated with lipid transport and metabolism (3.05%).
Various putative gene clusters that may be involved in the mechanism behind bacterial secondary metabolite biosynthesis were identified, including the abyssomicin biosynthetic gene cluster and the desferrioxamine B biosynthetic gene cluster.
Data availability.
This whole-genome shotgun project has been deposited at DDBJ/EMBL/GenBank under the accession number RQIV00000000. The SRA accession number is PRJNA505761.
ACKNOWLEDGMENTS
This work was supported by the National Key R&D Program of China under grant number 2018YFC0311001, the Drug Innovation Major Project under grant number 2018ZX0971001-007-007, and the Fujian Natural Science Foundation under grant number 2016J01345.
Sequencing services were provided by Personal Biotechnology Co., Ltd., Shanghai, People’s Republic of China.
REFERENCES
- 1.Roh H, Uguru GC, Ko H-J, Kim S, Kim B-Y, Goodfellow M, Bull AT, Kim KH, Bibb MJ, Choi I-G, Stach JEM. 2011. Genome sequence of the abyssomicin- and proximicin-producing marine actinomycete Verrucosispora maris AB-18-032. J Bacteriol 193:3391–3392. doi: 10.1128/JB.05041-11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Chun J, Goodfellow M. 1995. A phylogenetic analysis of the genus Nocardia with 16S rRNA gene sequences. Int J Syst Bacteriol 45:240–245. doi: 10.1099/00207713-45-2-240. [DOI] [PubMed] [Google Scholar]
- 3.Zhao W, Xie Y, Chen LJ, Lian YY, Jiang H. 2018. Polyphasic identification of strain FIM060022 based on gene screening and antibacterial activities. J Microbiol (China) 6:44–49. [Google Scholar]
- 4.De Rosa S, Mitova M, Tommonaro G. 2003. Marine bacteria associated with sponge as source of cyclic peptides. Biomol Eng 20:311–316. doi: 10.1016/S1389-0344(03)00038-8. [DOI] [PubMed] [Google Scholar]
- 5.Ji-Sheng R, Ying H. 2011. Rapid identification and systematic classification of actinomycetes. Science Press, Beijing, China. [Google Scholar]
- 6.Chen YY, Peng F, Lin R, Xie Y, Fang DS, Lian YY. 2014. Studies on the antimicrobial metabolites produced by the sponge-associated Verrucosispora sp. FIM060022. Chin J Antibiot 39:641–645. doi: 10.3969/j.issn.1001-8689.2014.09.001. [DOI] [Google Scholar]
- 7.Hopwood DA. 1988. Genetic manipulation of Streptomyces: a laboratory manual. Hunan Science and Technology Press, Changsha, China. [Google Scholar]
- 8.Bentley DR, Balasubramanian S, Swerdlow HP, Smith GP, Milton J, Brown CG, Hall KP, Evers DJ, Barnes CL, Bignell HR, Boutell JM, Bryant J, Carter RJ, Keira Cheetham RK, Cox AJ, Ellis DJ, Flatbush MR, Gormley NA, Humphray SJ, Irving LJ, Karbelashvili MS, Kirk SM, Li H, Liu X, Maisinger KS, Murray LJ, Obradovic B, Ost T, Parkinson ML, Pratt MR, Rasolonjatovo IMJ, Reed MT, Rigatti R, Rodighiero C, Ross MT, Sabot A, Sankar SV, Scally A, Schroth GP, Smith ME, Smith VP, Spiridou A, Torrance PE, Tzonev SS, Vermaas EH, Walter K, Wu X, Zhang L, Alam MD, Anastasi C, et al. 2008. Accurate whole human genome sequencing using reversible terminator chemistry. Nature 456:53–59. doi: 10.1038/nature07517. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Mikkel S, Stinus L, Ludovic O. 2016. AdapterRemoval v2: rapid adapter trimming, identification, and read merging. BMC Res Notes 9:88. doi: 10.1186/s13104-016-1900-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Luo R, Liu B, Xie Y, Li Z, Huang W, Yuan J, He G, Chen Y, Pan Q, Liu Y, Tang J, Wu G, Zhang H, Shi Y, Liu Y, Yu C, Wang B, Lu Y, Han C, Cheung DW, Yiu S-M, Peng S, Xiaoqian Z, Liu G, Liao X, Li Y, Yang H, Wang J, Lam T-W, Wang J. 2012. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 1:18. doi: 10.1186/2047-217X-1-18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Coil D, Jospin G, Darling AE. 2015. A5-miseq: an updated pipeline to assemble microbial genomes from Illumina MiSeq data. Bioinformatics 31:587–589. doi: 10.1093/bioinformatics/btu661. [DOI] [PubMed] [Google Scholar]
- 12.Delcher AL, Harmon D, Kasif S, White O, Salzberg SL. 1999. Improved microbial gene identification with GLIMMER. Nucleic Acids Res 27:4636–4641. doi: 10.1093/nar/27.23.4636. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Conesa A, Götz S. 2008. Blast2GO: a comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics 2008:1–12. doi: 10.1155/2008/619832. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Powell S, Forslund K, Szklarczyk D, Trachana K, Roth A, Huerta-Cepas J, Gabaldón T, Rattei T, Creevey C, Kuhn M, Jensen LJ, von Mering C, Bork P. 2014. eggNOG v4.0: nested orthology inference across 3686 organisms. Nucleic Acids Res 42:D231–D239. doi: 10.1093/nar/gkt1253. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Blin K, Medema MH, Kazempour D, Fischbach MA, Breitling R, Takano E, Weber T. 2013. antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers. Nucleic Acids Res 41:W204–W212. doi: 10.1093/nar/gkt449. [DOI] [PMC free article] [PubMed] [Google Scholar]
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Data Availability Statement
This whole-genome shotgun project has been deposited at DDBJ/EMBL/GenBank under the accession number RQIV00000000. The SRA accession number is PRJNA505761.
