Literature DB >> 32079632

Draft Genome Sequences of Vibrio alginolyticus Strain S6-61 and Vibrio diabolicus Strain S7-71, Isolated from Corals in the Andaman Sea.

Sushanta Deb1, Jhasketan Badhai1, Subrata K Das2.   

Abstract

We report the draft genome sequences of Vibrio alginolyticus strain S6-61 and Vibrio diabolicus strain S7-71, isolated from the corals Pocillopora verrucosa and Fungia danai, respectively. The genomes of strains S6-61 and S7-71 contain 4,880 and 4,641 protein coding genes, respectively, and harbor genes associated with the ectoine biosynthesis pathway.
Copyright © 2020 Deb et al.

Entities:  

Year:  2020        PMID: 32079632      PMCID: PMC7033269          DOI: 10.1128/MRA.01465-19

Source DB:  PubMed          Journal:  Microbiol Resour Announc        ISSN: 2576-098X


ANNOUNCEMENT

Vibrio alginolyticus is a halo-tolerant mesophilic Gram-negative bacterium and has been characterized as an opportunist pathogen in humans and marine animals (1). Earlier studies have reported that the type III secretion system (T3SS) in Vibrio alginolyticus leads to severe fish disease, resulting in economic losses in the aquaculture industry (2). In contrast, Vibrio diabolicus is a heterotrophic, facultatively anaerobic, mesophilic bacterium, first isolated from an annelid Alvinella pompejana collected from a deep-sea hydrothermal vent (3). This bacterium can produce exopolysaccharide (EPS), which has importance in the biotechnological industry and human health (4). The identified ectoine and 2C-methyl-d-erythritol 4-phosphate (MEP) pathways in these bacteria are known to be associated with osmotic regulation and pathogenicity of bacterial cells (5, 6). The bacterial strains used in this study were isolated from corals in the Andaman Sea. Coral samples were collected from Pocillopora verrucosa near North Bay (11°42′14.0″N, 92°45′05.7″E) and from Fungia danai near John Lawrence Island (12°01′33.8″N, 93°00′36.7″E). The isolation of bacteria and growth conditions were described earlier (7). Genomic DNA was isolated using the QIAamp DNA minikit (Qiagen, Germany). The quality (A260/280 ratio) and concentration of the DNA were determined using the NanoDrop 8000 UV-visible (UV-Vis) spectrophotometer and the Qubit 2.0 fluorometer (Thermo Fisher Scientific, USA). The DNA was sheared to an average length of 10 kb using a g-TUBE device, as per the manufacturer’s protocol (Covaris, Woburn, MA, USA). The fragmented DNA was used for SMRTbell library preparation as recommended by the manufacturer. The quantity and quality of the SMRTbell libraries were evaluated using the high-sensitivity double-stranded DNA (dsDNA) kit and Qubit fluorometer and the DNA 12000 kit on the 2100 Bioanalyzer (Agilent, Santa Clara, CA, USA), respectively. Sequencing was performed on the PacBio Sequel sequencing system (Pacific Biosciences, USA). Quality control of the sequence reads was performed using the –correct and –trim parameters built into the Canu 1.3 program. De novo genome assembly of PacBio reads was performed with the Canu 1.3 assembler (https://github.com/marbl/canu/) (parameters: correct; p, bacteria; merylMemory, 15; batThreads, 12; stopOnLowCoverage, 100; genomeSize, 5.2m) (8). Scaffolding was performed using the Single Molecular Integrative Scaffolding (SMIS) pipeline (https://github.com/fg6/smis) (parameters: score, 50; len, 2000; step, 200; contig, 3000; edge, 5) (9). Finally, the gaps were filled with the help of PBJelly (parameters: minMatch, 8; minPctIdentity, 70; bestn, 1; nCandidates, 10; maxScore, 500; nproc, 8; noSplitSubreads) (10). A total of 680,654 and 1,057,603 PacBio reads were assembled into two draft genomes with sequencing coverage of ∼500-fold. A Perl script (https://github.com/tomdeman-bio/Sequence-scripts/blob/master/calc_N50_GC_genomesize.pl) was used to calculate the statistical elements of the assembled genome (Table 1). The draft genomes were annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP version 4.9) with default parameters (11). The final draft genome assemblies of strains S6-61 and S7-71 are summarized in Table 1. Putative pathways in the bacterial genomes were identified using the KEGG pathway analysis tool (12). The Clusters of Orthologous Groups (COG) functional categories of the predicted protein coding genes were identified using the Perl script cdd2cog (https://github.com/aleimba/bac-genomics-scripts/tree/master/cdd2cog) (13).
TABLE 1

Characteristics of the draft genome sequences and accession numbers of the two Vibrio strains

StrainGenome size (Mbp)GC mol%No. of scaffoldsNo. of readsAvg read length (bp)N50 (Mbp)No. of CDSa % genes coding proteinsNo. of tRNAsNo. of rRNAs
S6-615.344.529680,6542,6001.95,03596.99221
S7-715.144.8951,057,6032,7061.84,81696.313344

CDS, coding DNA sequences.

Characteristics of the draft genome sequences and accession numbers of the two Vibrio strains CDS, coding DNA sequences. Comparative genomic analysis was performed for identification of the strains described in this study. Strains S6-61 and S7-71 showed 99.87% and 99.68% 16S rRNA gene sequence similarity to Vibrio alginolyticus strain NBRC 15630 and Vibrio diabolicus strain LMG 3418, respectively. In addition, the average nucleotide identity (ANI) was determined using the JSpeciesWS server (14). The ANI relatedness of strain S6-61 with the reference strain Vibrio alginolyticus NBRC15630 was 98.12%. Similarly, strain S7-71 had an ANI relatedness of 97.94% with the reference strain Vibrio diabolicus LMG 3418. These values are above the threshold ANI value (96%) for species delineation (15), suggesting that strains S6-61 and S7-71 belong to the species Vibrio alginolyticus and Vibrio diabolicus, respectively. Furthermore, in silico DNA-DNA hybridization (isDDH) values between strain S6-61 and Vibrio alginolyticus strain NBRC 15630 and between strain S7-71 and Vibrio diabolicus strain LMG 3418 were 85.60% and 83.30%, respectively, which are above the well-recognized cutoffs (≥70% isDDH) for bacterial species delineation. COG functional analysis revealed that the respective genomes of strains S6-61 and S7-71 contain genes involved in carbohydrate transport and metabolism (4.4% and 4.8%), lipid transport and metabolism (2.6% and 2.9%), transcription (7.1% and 6.8%), signal transduction mechanisms (5.6% and 6.0%), and unclassified functions (13.9% and 11.11%). The presence of predicted genes for ectoine biosynthesis suggests that these bacteria can resist osmotic stress in marine environments. In addition, the MEP pathway in V. alginolyticus strain S6-61 can be used as a potential drug target.

Data availability.

The whole-genome shotgun sequences of strains S6-61 and S7-71 have been deposited in DDBJ/ENA/GenBank under the accession numbers WAHT00000000 and VYYA00000000, respectively (Table 1). The SRA data are available at the NCBI SRA database under the accession numbers SRR10194733 and SRR10194627, respectively.
  14 in total

1.  Construction of a Vibrio alginolyticus hopPmaJ (hop) mutant and evaluation of its potential as a live attenuated vaccine in orange-spotted grouper (Epinephelus coioides).

Authors:  Huanying Pang; Mingsheng Qiu; Jingmin Zhao; Rowena Hoare; Sean J Monaghan; Dawei Song; Yunsheng Chang; Jichang Jian
Journal:  Fish Shellfish Immunol       Date:  2018-02-07       Impact factor: 4.581

2.  The type III secretion system of Vibrio alginolyticus induces rapid apoptosis, cell rounding and osmotic lysis of fish cells.

Authors:  Zhe Zhao; Chang Chen; Chao-Qun Hu; Chun-Hua Ren; Jing-Jing Zhao; Lv-Ping Zhang; Xiao Jiang; Peng Luo; Qing-Bai Wang
Journal:  Microbiology       Date:  2010-06-24       Impact factor: 2.777

3.  Genome sequence of Vibrio diabolicus and identification of the exopolysaccharide HE800 biosynthesis locus.

Authors:  David Goudenège; Vincent Boursicot; Typhaine Versigny; Sandrine Bonnetot; Jacqueline Ratiskol; Corinne Sinquin; Gisèle LaPointe; Frédérique Le Rous; Frédérique Le Roux; Christine Delbarre-Ladrat
Journal:  Appl Microbiol Biotechnol       Date:  2014-10-02       Impact factor: 4.813

Review 4.  Genes and enzymes of ectoine biosynthesis in halotolerant methanotrophs.

Authors:  Alexander S Reshetnikov; Valentina N Khmelenina; Ildar I Mustakhimov; Yuri A Trotsenko
Journal:  Methods Enzymol       Date:  2011       Impact factor: 1.600

Review 5.  Isoprenoid biosynthesis in bacterial pathogens.

Authors:  Sinéad Heuston; Máire Begley; Cormac G M Gahan; Colin Hill
Journal:  Microbiology       Date:  2012-03-30       Impact factor: 2.777

6.  Shifting the genomic gold standard for the prokaryotic species definition.

Authors:  Michael Richter; Ramon Rosselló-Móra
Journal:  Proc Natl Acad Sci U S A       Date:  2009-10-23       Impact factor: 11.205

7.  The phusion assembler.

Authors:  James C Mullikin; Zemin Ning
Journal:  Genome Res       Date:  2003-01       Impact factor: 9.043

8.  Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation.

Authors:  Sergey Koren; Brian P Walenz; Konstantin Berlin; Jason R Miller; Nicholas H Bergman; Adam M Phillippy
Journal:  Genome Res       Date:  2017-03-15       Impact factor: 9.043

9.  NCBI prokaryotic genome annotation pipeline.

Authors:  Tatiana Tatusova; Michael DiCuccio; Azat Badretdin; Vyacheslav Chetvernin; Eric P Nawrocki; Leonid Zaslavsky; Alexandre Lomsadze; Kim D Pruitt; Mark Borodovsky; James Ostell
Journal:  Nucleic Acids Res       Date:  2016-06-24       Impact factor: 16.971

10.  JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison.

Authors:  Michael Richter; Ramon Rosselló-Móra; Frank Oliver Glöckner; Jörg Peplies
Journal:  Bioinformatics       Date:  2015-11-16       Impact factor: 6.937

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.