Chromohalobacter japonicus (CECT 7219, CCM 7416, 43)

Name: Chromohalobacter japonicus (CECT 7219, CCM 7416, 43)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 134283

Type strain

Strain Designation 43

Culture col. no. CECT 7219 CCM 7416 43

NCBI tax ID(s) 223900

Special Collections Literature strains

Links

Chromohalobacter japonicus 43 is an aerobe, mesophilic, Gram-negative prokaryote that was isolated from food product.

Gram-negative motile rod-shaped aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 310968

CCM 7416,CECT 7219

@ref 20215

Last LPSN update 2025-12-16 10:02:01

Domain Pseudomonadati

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Oceanospirillales

Family Halomonadaceae

Genus Chromohalobacter

Species Chromohalobacter japonicus

Full scientific name Chromohalobacter japonicus Sánchez-Porro et al. 2007

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Motility	Confidence
32259	negative	2.85 µm	0.4 µm	rod-shaped
125438	negative					100

Pigmentation

32259

Productionyes

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
32259	positive	growth	32.5	mesophilic
32259	positive	optimum	15-42

Culture pH

@ref	Ability	Type	PH	PH range
32259	positive	optimum	7.5
32259	positive	growth	5.5-9.0	alkaliphile

Physiology and metabolism

Oxygen tolerance

32259

Oxygen toleranceaerobe

Spore formation

@ref	Spore formation	Confidence
32259
125439		98.9
125438		91.579

Halophily

@ref	Salt	Growth	Tested relation	Concentration
32259	NaCl	positive	growth	05-25 %
32259	NaCl	positive	optimum	10 %

Observation

32259

Observationaggregates in chains

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
32259	16449 ChEBI	alanine	+	carbon source
32259	22599 ChEBI	arabinose	+	carbon source
32259	22653 ChEBI	asparagine	+	carbon source
32259	35391 ChEBI	aspartate	+	carbon source
32259	16947 ChEBI	citrate	+	carbon source
32259	28757 ChEBI	fructose	+	carbon source
32259	28260 ChEBI	galactose	+	carbon source
32259	24265 ChEBI	gluconate	+	carbon source
32259	17234 ChEBI	glucose	+	carbon source
32259	29987 ChEBI	glutamate	+	carbon source
32259	17754 ChEBI	glycerol	+	carbon source
32259	27570 ChEBI	histidine	+	carbon source
32259	24996 ChEBI	lactate	+	carbon source
32259	29864 ChEBI	mannitol	+	carbon source
32259	17632 ChEBI	nitrate	+	reduction
32259	26271 ChEBI	proline	+	carbon source
32259	26546 ChEBI	rhamnose	+	carbon source
32259	17822 ChEBI	serine	+	carbon source
32259	26986 ChEBI	threonine	+	carbon source

Enzymes

@ref	Value	Activity	Ec
32259	catalase	+	1.11.1.6
32259	gelatinase	+

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Food production	#Food

Isolation

32259

Sample typefood product

Taxonmaps

69479

Global distribution of 16S sequence AB105159 (>99% sequence identity) for Chromohalobacter from Microbeatlas

Aquatic Samples	74
Soil Samples	8
Animal Samples	45
Plant Samples	38
Total Samples	165

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM2306117v1 assembly for Chromohalobacter japonicus CECT 7219	contig	GCA_023061175	223900.17	8046145814	223900	64.97
124043	ASM4243315v1 assembly for Chromohalobacter japonicus CCM 7416	contig	GCA_042433155			223900	63.04

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
32259	Chromohalobacter japonicus gene for 16S ribosomal RNA, partial sequence	AB105159	1501		223900
124043	Chromohalobacter japonicus strain TMW 2.2368 16S ribosomal RNA gene, partial sequence.	OM585590	1447		223900

GC content

32259

GC-content (mol%)62.9

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Chromohalobacter japonicus CECT 7219
NCBI: GCA_023061175

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.90	no
125439	motility	BacteriaNetⓘ	yes	77.90	no
125439	gram_stain	BacteriaNetⓘ	negative	89.30	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	63.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Chromohalobacter japonicus CECT 7219
NCBI: GCA_023061175.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	100.00	yes
125438	anaerobic	anaerobicⓘ	no	97.20	yes
125438	aerobic	aerobicⓘ	yes	86.66	yes
125438	spore-forming	spore-formingⓘ	no	91.58	no
125438	thermophilic	thermophileⓘ	no	97.80	no
125438	flagellated	motile2+ⓘ	yes	83.33	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Chromohalobacter japonicus sp. nov., a moderately halophilic bacterium isolated from a Japanese salty food.	Sanchez-Porro C, Tokunaga H, Tokunaga M, Ventosa A	Int J Syst Evol Microbiol	10.1099/ijs.0.65212-0	2007

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 )
#28500	IJSEM 2262 2007 ( DOI 10.1099/ijs.0.65212-0 , PubMed 17911293 )
#32259	Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #28500
#66792	Julia Koblitz, Joaquim Sardà, Lorenz Christian Reimer, Boyke Bunk, Jörg Overmann: Automatically annotated for the DiASPora project (Digital Approaches for the Synthesis of Poorly Accessible Biodiversity Information) .
#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 .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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 )

Rate our new design

Content

About us

Chromohalobacter japonicus (CECT 7219, CCM 7416, 43)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Observation

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_023061175

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media