Photobacterium ganghwense (DSM 109767, C2.2)

Name: Photobacterium ganghwense (DSM 109767, C2.2)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 169571

Type strain

Strain Designation C2.2

Culture col. no. DSM 109767 C2.2

NCBI tax ID(s) 320778

Special Collections DSMZ

History <- I. Mereuta; <- A.-M. Tanase, Univ. Bucharest; C2.2

Links

Photobacterium ganghwense C2.2 is a bacterium that was isolated from Seashore sediment.

genome sequence Bacteria

Name and taxonomic classification

SI-ID 398629

DSM 109767

@ref 20215

Last LPSN update 2026-02-09 11:41:04

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order "Vibrionales"

Family Vibrionaceae

Genus Photobacterium

Species Photobacterium ganghwense

Full scientific name Photobacterium ganghwense Park et al. 2006

BacDive ID	Other strains from **Photobacterium ganghwense** (1)	Type strain
17233	P. ganghwense FR1311, DSM 22954, IMSNU 60287, JCM 12487, ... (type strain)

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	100
125439	negative	96.5

Multimedia

@ref:	68877
multimedia content:	DSM_109767.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_109767.jpg
caption:	DSM 109767 in medium 514f at 20 °C
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
68877	MARINE BROTH (ROTH CP73) (DSMZ Medium 514f)		Medium recipe at MediaDive	Name: MARINE BROTH (ROTH CP73) (DSMZ Medium 514f) Composition: NaCl 19.4 g/l Agar 15.0 g/l MgCl2 8.8 g/l Peptone 5.0 g/l Na2SO4 3.24 g/l CaCl2 1.8 g/l Yeast extract 1.0 g/l KCl 0.55 g/l NaHCO3 0.16 g/l Fe(III) citrate 0.1 g/l KBr 0.08 g/l SrCl2 0.034 g/l H3BO3 0.022 g/l Na2HPO4 0.008 g/l Na-silicate 0.004 g/l NaF 0.0024 g/l (NH4)NO3 0.0016 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
68877	positive	growth	25

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		91.1

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68369	17128 ChEBI	adipate	-	assimilation	from API 20NE
68369	29016 ChEBI	arginine	+	hydrolysis	from API 20NE
68369	17634 ChEBI	D-glucose	+	assimilation	from API 20NE
68369	17634 ChEBI	D-glucose	+	fermentation	from API 20NE
68369	16899 ChEBI	D-mannitol	+	assimilation	from API 20NE
68369	16024 ChEBI	D-mannose	-	assimilation	from API 20NE
68369	27689 ChEBI	decanoate	+	assimilation	from API 20NE
68369	4853 ChEBI	esculin	-	hydrolysis	from API 20NE
68369	5291 ChEBI	gelatin	+	hydrolysis	from API 20NE
68369	24265 ChEBI	gluconate	+	assimilation	from API 20NE
68369	30849 ChEBI	L-arabinose	-	assimilation	from API 20NE
68369	25115 ChEBI	malate	+	assimilation	from API 20NE
68369	17306 ChEBI	maltose	+	assimilation	from API 20NE
68369	59640 ChEBI	N-acetylglucosamine	+	assimilation	from API 20NE
68369	17632 ChEBI	nitrate	+	reduction	from API 20NE
68369	27897 ChEBI	tryptophan	+	energy source	from API 20NE
68369	16199 ChEBI	urea	-	hydrolysis	from API 20NE

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68369	35581 ChEBI	indole		from API 20NE

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68369	35581 ChEBI	indole	+	from API 20NE

Enzymes

@ref	Value	Activity	Ec
68369	arginine dihydrolase	+	3.5.3.6	from API 20NE
68369	beta-glucosidase	-	3.2.1.21	from API 20NE
68369	cytochrome oxidase	+	1.9.3.1	from API 20NE
68369	gelatinase	+		from API 20NE
68369	urease	-	3.5.1.5	from API 20NE

API 20NE

@ref	Reduction of nitratesNO3	TRP	GLU_ Ferm	ADH (Arg)	URE	ESC	GEL	PNPG	GLU_ Assim	ARA	MNE	MAN	NAG	MAL	GNT	CAP	ADI	MLT	CIT	PAC	OX
68877	+	+	+	+	-	-	+	+	+	-	-	+	+	+	+	+	-	+	+	+	+

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
68877	Seashore sediment	Constanta (44° 05' 1.5 '' N, 28° 38' 36.4'' E)	Romania	ROU	Europe

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
68877	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1732954v1 assembly for Photobacterium ganghwense C2.2	complete	GCA_017329545	320778.9	8057765864	320778	95.26

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Photobacterium ganghwense C2.2
NCBI: GCA_017329545

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	91.10	no
125439	motility	BacteriaNetⓘ	yes	78.70	no
125439	gram_stain	BacteriaNetⓘ	negative	96.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	68.10	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Photobacterium ganghwense C2.2
NCBI: GCA_017329545.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	100.00	no
125438	anaerobic	anaerobicⓘ	no	96.33	no
125438	aerobic	aerobicⓘ	no	57.96	no
125438	spore-forming	spore-formingⓘ	no	84.65	no
125438	thermophilic	thermophileⓘ	no	99.50	yes
125438	flagellated	motile2+ⓘ	yes	89.52	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Complete genome sequence of Photobacterium ganghwense C2.2: A new polyhydroxyalkanoate production candidate.	Lascu I, Mereuta I, Chiciudean I, Hansen H, Avramescu SM, Tanase AM, Stoica I	Microbiologyopen	10.1002/mbo3.1182	2021
Genetics	Revealing the Phenotypic and Genomic Background for PHA Production from Rapeseed-Biodiesel Crude Glycerol Using Photobacterium ganghwense C2.2.	Lascu I, Tanase AM, Jablonski P, Chiciudean I, Preda MI, Avramescu S, Irgum K, Stoica I	Int J Mol Sci	10.3390/ijms232213754	2022

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 )
#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) .
#68369	Automatically annotated from API 20NE .
#68877	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 109767
#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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Photobacterium ganghwense (DSM 109767, C2.2)

Name and taxonomic classification

Morphology

Cell morphology

Multimedia

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Spore formation

Metabolite utilization

Metabolite production

Metabolite tests

Enzymes

API 20NE

Isolation, sampling and environmental information

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_017329545

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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