Halomonas jeotgali (KCTC 22487, JCM 15645)

Name: Halomonas jeotgali (KCTC 22487, JCM 15645)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 161613

Type strain

Culture col. no. KCTC 22487 JCM 15645

NCBI tax ID(s) 553386

Special Collections JCM KCTC

Links

Halomonas jeotgali JCM 15645 is a mesophilic prokaryote that was isolated from Jeotgal, traditional Korean fermented seafood.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 27955

JCM 15645,KCTC 22487

@ref 20215

Last LPSN update 2025-12-16 10:08:47

Domain Pseudomonadati

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Oceanospirillales

Family Halomonadaceae

Genus Halomonas

Species Halomonas jeotgali

Full scientific name Halomonas jeotgali Kim et al. 2011

Synonyms (1)

Vreelandella jeotgali

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	97.5
125439	negative	99.4

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	25	mesophilic

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		99.5

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Jeotgal, traditional Korean fermented seafood	Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence EU909458 (>99% sequence identity) for Halomonas jeotgali subclade from Microbeatlas

Aquatic Samples	49
Soil Samples	20
Animal Samples	108
Plant Samples	27
Total Samples	204

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	Hwa assembly for Vreelandella jeotgali Hwa	contig	GCA_000334215	1238190.3	2524614508	1238190	73.45

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Halomonas jeotgali strain Hwa 16S ribosomal RNA gene, partial sequence	EU909458	1437		1238190

GC content

@ref	GC-content (mol%)	Method
67770	61.7	thermal denaturation, midpoint method (Tm)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Halomonas jeotgali Hwa
NCBI: GCA_000334215

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.50	no
125439	motility	BacteriaNetⓘ	yes	85.60	no
125439	gram_stain	BacteriaNetⓘ	negative	99.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	84.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Halomonas jeotgali Hwa Hwa
NCBI: GCA_000334215.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.50	no
125438	anaerobic	anaerobicⓘ	no	92.09	no
125438	aerobic	aerobicⓘ	yes	67.71	no
125438	spore-forming	spore-formingⓘ	no	89.76	no
125438	thermophilic	thermophileⓘ	no	95.12	yes
125438	flagellated	motile2+ⓘ	yes	68.51	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Validation List no. 216. Valid publication of new names and new combinations effectively published outside the IJSEM.	Oren A, Goker M.	Int J Syst Evol Microbiol	10.1099/ijsem.0.006229	2024
Phylogeny	Halomonas jeotgali sp. nov., a new moderate halophilic bacterium isolated from a traditional fermented seafood.	Kim MS, Roh SW, Bae JW	J Microbiol	10.1007/s12275-010-0032-y	2010

References

#20215	Parte, A.C., Sardà Carbasse, J., Meier-Kolthoff, J.P., Reimer, L.C. and Göker, M.: List of Prokaryotic names with Standing in Nomenclature (LPSN) moves to the DSMZ. IJSEM ( DOI 10.1099/ijsem.0.004332 )
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#69479	João F Matias Rodrigues, Janko Tackmann,Gregor Rot, Thomas SB Schmidt, Lukas Malfertheiner, Mihai Danaila,Marija Dmitrijeva, Daniela Gaio, Nicolas Näpflin and Christian von Mering. University of Zurich.: MicrobeAtlas 1.0 beta .
#125438	Julia Koblitz, Lorenz Christian Reimer, Rüdiger Pukall, Jörg Overmann: Predicting bacterial phenotypic traits through improved machine learning using high-quality, curated datasets. 2024 ( DOI 10.1101/2024.08.12.607695 )
#125439	Philipp Münch, René Mreches, Martin Binder, Hüseyin Anil Gündüz, Xiao-Yin To, Alice McHardy: deepG: Deep Learning for Genome Sequence Data. R package version 0.3.1 .
#126262	A. Lissin, I. Schober, J. F. Witte, H. Lüken, A. Podstawka, J. Koblitz, B. Bunk, P. Dawyndt, P. Vandamme, P. de Vos, J. Overmann, L. C. Reimer: StrainInfo—the central database for linked microbial strain identifiers. ( DOI 10.1093/database/baaf059 )

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Halomonas jeotgali (KCTC 22487, JCM 15645)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_000334215

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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