Shewanella psychromarinicola (KCCM 43258, JCM 32089)

Name: Shewanella psychromarinicola (KCCM 43258, JCM 32089)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164189

Type strain

Culture col. no. KCCM 43258 JCM 32089

NCBI tax ID(s) 2487742

Special Collections JCM

History C. Y. Hwang; Korea Polar Res. Inst., South Korea; R106.

Shewanella psychromarinicola JCM 32089 is a bacterium that was isolated from Pelagic surface sediment of the Ross Sea.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

Culture Collection Numbers

KCCM 43258 JCM 32089

@ref 20215

Last LPSN update 2026-02-09 11:39:47

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Alteromonadales

Family Shewanellaceae

Genus Shewanella

Species Shewanella psychromarinicola

Full scientific name Shewanella psychromarinicola Hwang et al. 2019

BacDive ID	Other strains from **Shewanella psychromarinicola** (1)	Type strain
164190	S. psychromarinicola M2, JCM 32090, KCCM 43257 (type strain)

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	99.2
125438		91.53
125438	negative	98.5

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	15

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	98.4

Spore formation

@ref	Spore formation	Confidence
125439		99.3

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Pelagic surface sediment of the Ross Sea	Antarctica	ATA	Antarctica

Taxonmaps

69479

Global distribution of 16S sequence MH630150 (>99% sequence identity) for Shewanella from Microbeatlas

Aquatic Samples	692
Soil Samples	13
Animal Samples	131
Plant Samples	6
Total Samples	842

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM379716v1 assembly for Shewanella psychromarinicola R106	scaffold	GCA_003797165	2487742.7	2902552904	2487742	67.83

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Shewanella psychromarinicola strain R106 16S ribosomal RNA gene, partial sequence	MH630150	1446		50422

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Shewanella psychromarinicola R106
NCBI: GCA_003797165

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	99.30	no
125439	motility	BacteriaNetⓘ	yes	77.30	no
125439	gram_stain	BacteriaNetⓘ	negative	99.20	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	98.40	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Shewanella psychromarinicola R106
NCBI: GCA_003797165.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.50	no
125438	anaerobic	anaerobicⓘ	no	90.30	no
125438	aerobic	aerobicⓘ	no	54.75	no
125438	spore-forming	spore-formingⓘ	no	87.29	no
125438	thermophilic	thermophileⓘ	no	98.00	yes
125438	flagellated	motile2+ⓘ	yes	91.53	no

Literature

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 .

Rate our new design

Content

About us