Open access
Bacteriology
Announcement
20 December 2024

Complete genome sequence of Chryseobacterium sp. strain KCF3-3, isolated from the body surface of channel catfish, Ictalurus punctatus

ABSTRACT

Here, we report the complete genome sequence of Chryseobacterium sp. strain KCF3-3, isolated from the body surface of channel catfish, Ictalurus punctatus. The de novo assembly revealed a chromosome size of 5,623,437 bp with an estimated 4,939 open reading frames.

ANNOUNCEMENT

Members of the genus Chryseobacterium are rod-shaped, non-spore-forming, nonmotile Gram-negative bacteria that are found in diverse environments (1). Here, we report the complete genome sequence of Chryseobacterium sp. KCF3-3 to enhance our understanding of its ecological diversity. We isolated the strain from the body surface of channel catfish, Ictalurus punctatus in 2019 (Table 1). Mucus samples were collected from four I. punctatus specimens and cultured on Reasoner’s 2A agar plates at 25°C for 24 h to obtain the isolates. After three rounds of purification, isolates were identified by molecular phylogenetic analysis based on the 16S rRNA gene sequences. The primers used for amplification were 27 F-W (5′-AGRGTTTGATCMTGGCTCAG-3′) and 1,492 R-W (5′-GGYTACCTTGTTACGACTT-3′). The neighbor-joining methods were used to analyze the genetic relationship (2). Consequently, the strain KCF3-3, which is classified within the genus Chryseobacterium, was obtained.
TABLE 1
TABLE 1 Genomic features of Chryseobacterium sp. strain KCF3-3
Parameter 
Description of location
 LocationLake Kasumigaura, Ibaraki, Japan
 Time26 October 2019
 TypeBody surface of I. punctatus
 Geographic coordinates36°05'39.0"N/140°24'09.3"E
Sequencing statistics
 Number of raw reads18,579
 Mean length13,306
 Total bases247,205,453
 Number of Filtlong filtered reads16,184
Genome statistics
 Assembly size (bp)5,623,437
 Number of contigs1
 GC content (%)36.0
 Genome coverage44.0
 Number of 5S rRNA6
 Number of 16S rRNA6
 Number of 23S rRNA6
 Number of tRNAs87
 Total number of coding sequence4,939
 Completeness (%)99.99
 Contamination (%)0.08
Data accession
 BioProjectPRJDB18362
 BioSampleSAMD00797993
 GenBank accession No.AP035792
The genomic DNA of strain KCF3-3 was extracted using NucleoBond HMW DNA (Macherey-Nagel) and further purified using DNA Clean Beads (MGI Tech Co., Ltd.) according to the manufacturer’s protocol. The concentration of the DNA solution was measured using the QuantiFluor dsDNA system on a Quantus Fluorometer (Promega). The DNA was fragmented to approximately 10–20 kbp using g-TUBE (Covaris) by centrifuging three times at 2,100 × g. Fragmented lengths were confirmed by measuring with a 5200 Fragment Analyzer (Agilent Technologies). The DNA library was prepared using the SMRTbell Express Template Prep Kit 2.0 according to the Procedure and Checklist instructions (Part number 101–730-400 ver. 06). Polymerase complexes were prepared by Revio Polymerase kit (PacBio), and sequencing was performed using Revio (PacBio) by Bioengineering Lab. Co., Ltd. in 2024. SMRT Link (ver. 13.0.0.207600) was used to remove overhang adaptors, and consensus sequence reads with an average quality value of less than 20 per read were removed. Filtlong (ver. 0.2.1) was used to eliminate reads shorter than 1,000 bases and yielded 18,579 reads with an N50 value of 14,599 bp. De novo assembly was performed using Flye (ver. 2.9.2-b1786) (3, 4), and Bandage (ver. 0.8.1) (5) and CheckM2 (ver. 1.0.1) (6) were used for quality assessment of the assembled genome. Flye detects overlapping contig ends as circular candidates and automatically circularizes them (3). Genome annotation was performed using the Prokka software (ver. 1.14.6) (7).
The chromosome size of the strain KCF3-3 was 5,623,437 bp, and the contig was a single circularized genome. The genome coverage was 44.0×, and the GC content was 36.0%. The genome contains 4,939 coding sequences. Prokka predicted 105 RNA genes (87 tRNA genes and 18 rRNA genes). These results and other genomic information are shown in Table 1. Clusters of Orthologous Groups (COG) categories were estimated using DFAST (https://dfast.ddbj.nig.ac.jp) (8, 9), and GC contents and GCskew were calculated using GCcalc (https://github.com/WenchaoLin/GCcalc). These results were visualized using Circos (ver. 0.69) (10) (Fig. 1). All software used default parameters, unless otherwise specified.
Fig 1
Circular genome map displays genomic features as colored bands around black circular chromosome, with inner lines representing GC content and skew across genome. Vertical color key lists labeled regions corresponding to specific features.
Fig 1 Circular representation of the genome of Chryseobacterium sp. strain KCF3-3. From outer circle to inner circle: color of inferred COG categories, GC skew (blue), and GC contents (orange). NC in COG color code indicates no classified category.

ACKNOWLEDGMENTS

This work was partially supported by the JST-Mirai Program of the Japan Science and Technology Agency (JST) Grant No. JPMJMI18CF and the Academic Research Grant of the Reiwa Environmental Foundation (No. JP0000008) for M.K. The authors express their gratitude to Dr. Motonori Kudou, Dr. Naoshige Izumikawa, and Dr. Hiroyuki Hamada for their collaboration in the sampling of channel catfish in Lake Kasumigaura. Computations were partially performed on the NIG supercomputer at ROIS National Institute of Genetics.

REFERENCES

1.
Hugo C, Bernardet J-F, Nicholson A, Kämpfer P. 2019. Chryseobacterium, p 1–107. In Trujillo ME, Dedysh SD, Hedlund B, Kämpfer P, Rainey FA, Whitman WB (ed), Bergey’s manual of systematics of archaea and bacteria. John Wiley & Sons, Inc, Hoboken, NJ.
2.
Saitou N, Nei M. 1987. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 4:406–425.
3.
Kolmogorov M, Yuan J, Lin Y, Pevzner PA. 2019. Assembly of long, error-prone reads using repeat graphs. Nat Biotechnol 37:540–546.
4.
Lin Y, Yuan J, Kolmogorov M, Shen MW, Chaisson M, Pevzner PA. 2016. Assembly of long error-prone reads using de Bruijn graphs. Proc Natl Acad Sci U S A 113:E8396–E8405.
5.
Wick RR, Schultz MB, Zobel J, Holt KE. 2015. Bandage: interactive visualization of de novo genome assemblies. Bioinformatics 31:3350–3352.
6.
Chklovski A, Parks DH, Woodcroft BJ, Tyson GW. 2023. CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning. Nat Methods 20:1203–1212.
7.
Seemann T. 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068–2069.
8.
Tanizawa Y, Fujisawa T, Kaminuma E, Nakamura Y, Arita M. 2016. DFAST and DAGA: web-based integrated genome annotation tools and resources. Biosci Microbiota Food Health 35:173–184.
9.
Tanizawa Y, Fujisawa T, Nakamura Y. 2018. DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication. Bioinformatics 34:1037–1039.
10.
Krzywinski M, Schein J, Birol I, Connors J, Gascoyne R, Horsman D, Jones SJ, Marra MA. 2009. Circos: an information aesthetic for comparative genomics. Genome Res 19:1639–1645.

Information & Contributors

Information

Published In

cover image Microbiology Resource Announcements
Microbiology Resource Announcements
Volume 14Number 211 February 2025
eLocator: e01058-24
Editor: Frank J. Stewart, Montana State University, Bozeman, Montana, USA
PubMed: 39705205

History

Received: 27 September 2024
Accepted: 26 November 2024
Published online: 20 December 2024

Keywords

  1. channel catfish
  2. Ictalurus punctatus
  3. mucus
  4. Chryseobacterium

Data Availability

The whole-genome shotgun project for the strain KCF3-3 has been deposited in GenBank under accession number AP035792. The raw reads and raw sequencing data are available under BioProject accession number PRJDB18362 and BioSample accession number SAMD00797993.

Contributors

Authors

Miho Kojima
Department of Life Sciences, Graduate School of Bioresources, Mie University, Tsu, Mie, Japan
Author Contributions: Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Visualization, Writing – original draft, and Writing – review and editing.
Kaho Tobioka
Department of Life Sciences, Graduate School of Bioresources, Mie University, Tsu, Mie, Japan
Author Contributions: Investigation and Writing – review and editing.
Mika Okazaki
Department of Life Sciences, Graduate School of Bioresources, Mie University, Tsu, Mie, Japan
Author Contributions: Investigation and Writing – review and editing.
Kiyonobu Yokota
Department of Life Sciences, Graduate School of Bioresources, Mie University, Tsu, Mie, Japan
Author Contributions: Funding acquisition, Project administration, and Writing – review and editing.
Dien Arista Anggorowati
Research Center for Marine and Land Bioindustry, National Research and Innovation Agency (BRIN), North Lombok, West Nusa Tenggara, Indonesia
Author Contributions: Investigation and Writing – review and editing.
Hajime Nakatani
Department of Biomolecular Engineering, Graduate School of Engineering, Nagoya University, Nagoya, Aichi, Japan
Author Contributions: Funding acquisition and Writing – review and editing.
Department of Biomolecular Engineering, Graduate School of Engineering, Nagoya University, Nagoya, Aichi, Japan
Author Contributions: Funding acquisition and Writing – review and editing.
Yutaka Tamaru
Department of Life Sciences, Graduate School of Bioresources, Mie University, Tsu, Mie, Japan
Section of Soft and Functional Materials, Tohoku University Green Crosstech Research Center, Sendai, Japan
Department of Molecular Bioengineering, Graduate School of Engineering, Tohoku University, Sendai, Japan
Author Contributions: Funding acquisition and Writing – review and editing.
Department of Life Sciences, Graduate School of Bioresources, Mie University, Tsu, Mie, Japan
Author Contributions: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Validation, and Writing – review and editing.

Editor

Frank J. Stewart
Editor
Montana State University, Bozeman, Montana, USA

Notes

The authors declare no conflict of interest.

Metrics & Citations

Metrics

Note:

  • For recently published articles, the TOTAL download count will appear as zero until a new month starts.
  • There is a 3- to 4-day delay in article usage, so article usage will not appear immediately after publication.
  • Citation counts come from the Crossref Cited by service.

Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. For an editable text file, please select Medlars format which will download as a .txt file. Simply select your manager software from the list below and click Download.

View Options

Figures

Tables

Media

Share

Share

Share the article link

Share with email

Email a colleague

Share on social media

American Society for Microbiology ("ASM") is committed to maintaining your confidence and trust with respect to the information we collect from you on websites owned and operated by ASM ("ASM Web Sites") and other sources. This Privacy Policy sets forth the information we collect about you, how we use this information and the choices you have about how we use such information.
FIND OUT MORE about the privacy policy