Shewanella frigidimarina (KCTC 23109, JCM 16723, IR 12)

Name: Shewanella frigidimarina (KCTC 23109, JCM 16723, IR 12)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 133709

Type strain

Strain Designation IR 12

Culture col. no. KCTC 23109 JCM 16723 IR 12

NCBI tax ID(s) 56812

Special Collections JCM KCTC Literature strains

History JCM <-- S.-J. Park IR12.

Links

Shewanella frigidimarina IR 12 is a facultative anaerobe, Gram-negative, motile bacterium that was isolated from marine sediment.

Gram-negative motile rod-shaped facultative anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 27932

KCTC 23109,JCM 16723

@ref 20215

Last LPSN update 2026-05-29 08:38:09

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Alteromonadales

Family Shewanellaceae

Genus Shewanella

Species Shewanella frigidimarina

Full scientific name Shewanella frigidimarina Bowman et al. 1997

Synonyms (1)

Shewanella arctica

BacDive ID	Other strains from **Shewanella frigidimarina** (1)	Type strain
14066	S. frigidimarina DSM 12253, ACAM 591, CIP 105515, ATCC 700753 (type strain)

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
30234	negative	1.75 µm	0.65 µm	rod-shaped
125438					92.246
125438	negative				98.5
125439	negative				97.497

Pigmentation

30234

Productionyes

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
30234	positive	growth	4-28
30234	positive	optimum	20
67770	positive	growth	20

Culture pH

@ref	Ability	Type	PH	PH range
30234	positive	optimum	7.5
30234	positive	growth	4.5-9	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
30234	facultative anaerobe
125439	obligate aerobe	99.756

Spore formation

@ref	Spore formation	Confidence
125439		98.879

Halophily

@ref	Salt	Growth	Tested relation	Concentration
30234	NaCl	positive	growth	0.5-3.5 %
30234	NaCl	positive	optimum	0.75 %

Observation

67770

Observationquinones: Q-7, Q-8, MK-7

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
30234	17057 ChEBI	cellobiose	+	carbon source
30234	4853 ChEBI	esculin	+	hydrolysis
30234	17234 ChEBI	glucose	+	carbon source
30234	25115 ChEBI	malate	+	carbon source
30234	17306 ChEBI	maltose	+	carbon source
30234	17632 ChEBI	nitrate	+	reduction
30234	33942 ChEBI	ribose	+	carbon source

Metabolite production

@ref	Chebi-ID	Metabolite	Production
30234	16136 ChEBI	hydrogen sulfide

Enzymes

@ref	Value	Activity	Ec
30234	catalase	+	1.11.1.6
30234	cytochrome oxidase	+	1.9.3.1

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Marine
#Environmental	#Aquatic	#Sediment

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
30234	marine sediment
67770	Arctic marine sediment at Tempelfjorden	a fjord branch on Spitsbergen, the island of the Norwegian Svalbard archipelago	Norway	NOR	Europe

Taxonmaps

69479

Global distribution of 16S sequence GU564402 (>99% sequence identity) for Shewanella from Microbeatlas

Aquatic Samples	8506
Soil Samples	472
Animal Samples	2645
Plant Samples	90
Total Samples	11713

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM379712v1 assembly for Shewanella frigidimarina KCTC 23109	scaffold	GCA_003797125	1659315.3	8117564262	56812	74.91

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
30234	Shewanella arctica Kim et al. 2012 strain IR12 16S ribosomal RNA gene, partial sequence	GU564402	1447		310683

GC content

@ref	GC-content (mol%)	Method
30234	40
67770	40	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: ASM379712v1 assembly for Shewanella frigidimarina KCTC 23109
NCBI: GCA_003797125

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	gram_stain	BacteriaNetⓘ	negative	97.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.76	no
125439	motility	BacteriaNetⓘ	yes	72.23	no
125439	spore_formation	BacteriaNetⓘ	no	98.88	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: 'Shewanella arctica' Qoura et al. 2014 strain KCTC 23109
PATRIC: 1659315.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.50	yes
125438	anaerobic	anaerobicⓘ	no	93.78	yes
125438	spore-forming	spore-formingⓘ	no	89.79	no
125438	aerobic	aerobicⓘ	yes	54.13	no
125438	thermophilic	thermophileⓘ	no	99.00	yes
125438	flagellated	motile2+ⓘ	yes	92.25	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Shewanella arctica sp. nov., an iron-reducing bacterium isolated from Arctic marine sediment.	Kim SJ, Park SJ, Oh YS, Lee SA, Shin KS, Roh DH, Rhee SK	Int J Syst Evol Microbiol	10.1099/ijs.0.031401-0	2011

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 )
#26576	IJSEM 1128 2012 ( DOI 10.1099/ijs.0.031401-0 , PubMed 21724958 )
#30234	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 #26576
#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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Shewanella frigidimarina (KCTC 23109, JCM 16723, IR 12)

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

Metabolite production

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_003797125

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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