Article Search
닫기

Microbiology and Biotechnology Letters

Genome Report(Note)

View PDF

Genome Report  |  Genome Report

Microbiol. Biotechnol. Lett. 2024; 52(2): 204-207

https://doi.org/10.48022/mbl.2404.04004

Received: April 4, 2024; Revised: May 7, 2024; Accepted: May 8, 2024

Complete Genome Sequence of Myxococcus stipitatus KYC2006, a Myxobacterium That Affects the Growth of Photosynthetic Microorganisms

Junyeong Park1, Hyeran Lee1, Sunjin Lee2, Hyesook Hyun1, Hyun Gi Koh3, Min-Jin Kim4, Buyng Su Hwang4*, and Bongsoo Lee1*

1Department of Microbial Biotechnology, Mokwon University, Daejeon 35349, Republic of Korea
2Macrogen, Inc., Seoul 06221, Republic of Korea
3Department of Biological and Chemical Engineering, Hongik University, Sejong 30016, Republic of Korea
4Nakdonggang National Institute of Biological Resources (NNIBR), Sangju 37242, Republic of Korea

Correspondence to :
Buyng Su Hwang,       hwang1531@nnibr.re.kr
Bongsoo Lee,            bongsoolee@mokwon.ac.kr

Here, we report the whole-genome sequence of Myxococcus stipitatus KYC2006, a bacterium whose conditioned media affect the growth of photosynthetic microorganisms such as cyanobacteria and microalgae. The genome of M. stipitatus KYC2006 was assembled into a 10,311,252 bp circular genome with 68.5% of GC content, containing 7,949 protein-coding genes, 12 rRNA genes, and 79 tRNA genes. Further analysis revealed that there are 29 secondary metabolite biosynthetic gene clusters in M. stipitatus KYC2006. These results suggest that M. stipitatus KYC2006 holds a significant potential as a resource for research on the development of biocontrol agents and value-added products from photosynthetic microorganisms.

Keywords: Myxococcus stipitatus, whole-genome sequencing, secondary metabolite biosynthetic gene clusters

Myxobacteria are members of gram-negative δ-proteobacteria, classified into the order Myxococcales. Myxobacteria exhibit a complex life cycle distinguished by a large genome, multicellular social behaviors, cell differentiation including fruiting body formation and gliding motility [1, 2]. Thus, the best characterized myxobacterium, Myxococcus xanthus, has been a model system for social behaviors and motility in prokaryotes over the past few decades [3]. On the other hand, another major feature of the myxobacteria is that they produce a number of bioactive secondary metabolites with antiviral, antibacterial, antifungal, and anticancer effects [4, 5]. Known as predators in their natural habitat, they secrete a wide variety of bioactive molecules such as alkaloids, polyketides, and terpenes produced from polyketide synthases (PKS), nonribosomal peptide synthetases (NRPS), and their hybrids [5, 6].

During the evaluation process of various myxobacteria isolated from domestic soil, we found that M. stipitatus KYC2006 affects the growth of photosynthetic microorganisms such as cyanobacteria and microalgae. Briefly, the conditioned media and its extract of M. stipitatus KYC2006 not only showed the superior algicidal effects against various kind of cyanobacteria causing algal bloom, but also enhanced the productivity of the value added chemicals derived from microalgae. This strain was subsequently subjected to de novo whole genome sequencing for further study.

M. stipitatus KYC2006 was isolated from the forest soil of Maisan National Park in Jinan-gun, Jeollabuk-do, South Korea. The soil samples were collected and spread onto ST21CX medium supplemented with cycloheximide to ST21 medium [7]. The resulting fruiting bodies were identified and isolated from the ST21CX medium. Subsequently, pure isolation was achieved by selecting the edge of swarm on CYE medium, which is a modified medium by adding yeast extract in CY medium [7]. M. stipitatus KYC2006 was cultured in CYE broth medium at 32℃ with 120 rpm agitation, and the genomic DNA was extracted using the AccuPrep® Genomic DNA Extraction Kit (Bioneer, Republic of Korea). The whole genome was sequenced using the PacBio Sequel I system and Illumina HiSeq sequencing platform at Macrogen, Inc., Republic of Korea.

In total, 147,692 raw reads (1,017,368,088 bp) were obtained using the PacBio Sequel I system (N50 value 9,935 and genome coverage 98.6x) and 8,475,802 short reads (1,276,651,899 bp) were sequenced using the Illumina platform. De novo assembly was conducted using the Flye assembler (v2.4.2) with PacBio raw reads, followed by error correction of the contig bases with Illumina reads using Pilon (v1.21) [8]. The resulting whole genome of M. stipitatus KYC2006 is constructed as a circular chromosome of 10,311,252 bp with 68.5% of GC content. Based on the calculations using the OrthoANIu algorithm [9], the genome of strain KYC2006 had an average nucleotide identity of 90.54% with strain DSM 14675T (GenBank accession number: CP004025), the type strain of M. stipitatus, and the 16S rRNA sequence showed the 99.54% similarity.

Next, the whole genome was annotated using NCBI Prokaryotic Genome Annotation Pipeline (PGAP) Pipeline (v6.7). In total, 8,095 genes were identified, and the genome comprises 7,949 protein-coding genes, 51 CDSs without protein, 12 rRNAs (5S:4, 16S:4, 23S:4), 79 tRNAs, 4 ncRNAs (Table 1). A circular map displaying CDS, CDS on the reverse strand, tRNA, rRNA, GC content and GC skew information of the KYC2006 genome was generated (Fig. 1). The quality of the complete genome of strain KYC2006 was assessed using the Benchmarking Universal Single-Copy Orthologs (BUSCO) database for bacteria or eukaryote, resulting in 97.58% complete BUSCOs.

Table 1 . Genome features of M. stipitatus KYC2006.

Genome featureValue
Genome size (bp)10,311,252
Number of contig1
GC content (%)68.5%
Number of genes8,095
Protein coding genes7,949
CDSs without protein51
rRNA genes (5S, 16S, 23S)12 (4, 4, 4)
tRNA genes79
ncRNA genes4
Predicted secondary metabolite biosynthetic gene clusters29
GeneBank accession NumberCP147913


Figure 1.Circular map was drawn by applying M. stipitatus KYC2006’s annotation result. Marked characteristics are shown from outside to the center; CDS on forward strand, CDS on reverse strand, tRNA, rRNA, GC content and GC skew.

In an effort to identify the genes associated with bioactive compound production, we analyzed the secondary metabolite biosynthetic clusters present in the genome of M. stipitatus KYC2006 using the antiSMASH program [10]. This analysis uncovered a total of 29 secondary metabolite biosynthetic clusters, including NRPS and PKS (Table 2). These findings suggest that M. stipitatus KYC2006, along with its complete genomic data is expected to be a valuable resource for further research into the development of bioactive compounds. Specifically, it shows potential for environmental control of cyanobacteria and the production of value-added chemicals from microalgae.

Table 2 . Secondary metabolite gene clusters within M. stipitatus KYC2006 genome.

ClustersProtein IDs in NCBINumber of genestype
Cluster 100001 - 0001818NRPSa
Cluster 200275 - 0031642arylpolyne
Cluster 300817 - 0084933NRPS
Cluster 400988 - 0102033NRPS
Cluster 501386 - 0145166NRPS, T1PKSb, NRPS-like
Cluster 601521 - 0155333transAT-PKS-like
Cluster 701663 - 0169432NRPS
Cluster 801743 - 0177634NRPS-like
Cluster 902146 - 0218035T1PKS, NRPS
Cluster 1002641 - 0265717terpene
Cluster 1102921 - 0297858NRPS-like, NRPS
Cluster 1204508 - 0454235T3PKSc
Cluster 1304941 - 0495212terpene
Cluster 1405404 - 0542320thioamitides
Cluster 1505515 - 0555238NRPS
Cluster 1605646 - 0570156T1PKS, NRPS, RiPP-liked
Cluster 1705801 - 0582121terpene
Cluster 1806238 - 0624811RiPP-like
Cluster 1906712 - 0675847NRPS, T1PKS
Cluster 2006949 - 0696315RiPP-like
Cluster 2106966 - 0701449T1PKS
Cluster 2207267 - 072759RiPP-like
Cluster 2307381 - 073888RiPP-like
Cluster 2407430 - 0750273NRPS, T1PKS, NRP-metallophore
Cluster 2507553 - 0757422RRE-containinge
Cluster 2607615 - 0765137T1PKS, NRPS
Cluster 2707844 - 0787734NRPS, T1PKS
Cluster 2807979 - 079868RiPP-like
Cluster 2908157 - 0817721NRPS, T1PKS

aNRPS: Nonribosomal peptide synthetases, bT1PKS: Type I polyketide synthases, cT3PKS: Type III polyketide synthases, dRiPP-like: Ribosomally synthesized and post-translationally modified peptides, eRRE-containing: RiPP recognition element.


The complete genome sequence of M. stipitatus KYC2006 has been deposited in GenBank under accession number CP147913. The BioProject and Bio-Sample accession number are PRJNA1084090 and SAMN40270259, respectively.

This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Ministry of Science and ICT, Korea government (2021R1F1A105127511) and a grant from the Nakdonggang National Institute of Biological Resources (NNIBR), funded by the Ministry of Environment(MOE) of the Republic of Korea (NNIBR20243111). The authors are also grateful to Prof. Kyungyun Cho (Hoseo University) for providing the M. stipitatus KYC2006.

The authors have no financial conflicts of interest to declare.

  1. Kaiser D, Robinson M, Kroos L. 2010. Myxobacteria, polarity, and multicellular morphogenesis. Cold Spring Harb. Perspect. Biol. 2: a000380.
    Pubmed KoreaMed CrossRef
  2. Sharma G, Khatri I, Subramanian S. 2016. Complete genome of the starch-degrading myxobacteria Sandaracinus amylolyticus DSM 53668T. Genome Biol. Evol. 29: 2520-2529.
    Pubmed KoreaMed CrossRef
  3. Muñoz-Dorado J, Marcos-Torres FJ, García-Bravo E, Moraleda-Muñoz A, Pérez J. 2016. Myxobacteria: Moving, killing, feeding, and surviving together. Front. Microbiol. 26: 781.
    Pubmed KoreaMed CrossRef
  4. Wrótniak-Drzewiecka W, Brzezińska AJ, Dahm H, Ingle AP, Rai M. 2016. Current trends in myxobacteria research. Ann. Microbiol. 66: 17-33.
    CrossRef
  5. Herrmann J, Fayad AA, Müller R. 2017. Natural products from myxobacteria: novel metabolites and bioactivities. Nat. Prod. Rep. 34: 135-160.
    Pubmed CrossRef
  6. Hyun H, Cho K. 2018. Secondary metabolites of myxobacteria. Korean J. Microbiol. 54: 175-187.
  7. Development of a quantitative induction method for Chondromyces crocatus fruiting body formation. Korean J. Microbiol. 50: 173-178.
  8. Walker BJ, Abeel T, Shea T, Priest M, Abouelliel A, Sakthikumar S, et al. 2014. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS One 9: e112963.
    Pubmed KoreaMed CrossRef
  9. Yoon SH, Ha SM, Lim JM, Kwon SJ, Chun J. 2017. A large-scale valuation of algorithms to calculate average nucleotide identity. Antonie Van Leeuwenhoek 110: 1281-1286.
    Pubmed CrossRef
  10. Blin K, Shaw S, Augustijn HE, Reitz ZL, Biermann F, Alanjary M, et al. 2023. antiSMASH 7.0: new and improved predictions for detection, regulation, chemical structures, and visualization. Nucleic Acids Res. 51: 46-50.
    Pubmed KoreaMed CrossRef

Starts of Metrics

Share this article on :

Related articles in MBL

Most Searched Keywords ?

What is Most Searched Keywords?

  • It is most registrated keyword in articles at this journal during for 2 years.