Deinococcus knuensis (KCTC 33794, JCM 31406)

Name: Deinococcus knuensis (KCTC 33794, JCM 31406)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164050

Type strain

Culture col. no. KCTC 33794 JCM 31406

NCBI tax ID(s) 1837380

Special Collections JCM KCTC

History H.-Y. Jung; Kyungpook Natl. Univ., South Korea; 16F3H.

Links

Deinococcus knuensis JCM 31406 is a bacterium that was isolated from River water collected from the Han River.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 24655

KCTC 33794,JCM 31406

@ref 20215

Last LPSN update 2026-02-09 11:39:45

Domain Bacteria

Phylum Deinococcota

Class Deinococci

Order Deinococcales

Family Deinococcaceae

Genus Deinococcus

Species Deinococcus knuensis

Full scientific name Deinococcus knuensis Lee et al. 2017

Morphology

Cell morphology

@ref	Gram stain	Confidence	Motility
125439	positive	99.7
125439		95

Culture and growth conditions

Culture temp

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

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		93.1

Observation

67770

Observationquinones: MK-8

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	River water collected from the Han River	Seoul	Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence LC148307 (>99% sequence identity) for Deinococcus from Microbeatlas

Aquatic Samples	751
Soil Samples	19
Animal Samples	537
Plant Samples	16
Total Samples	1323

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1464815v1 assembly for Deinococcus knuensis JCM 31406	contig	GCA_014648155	1837380.3	8068684107	1837380	66.05

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Deinococcus knuensis gene for 16S ribosomal RNA, partial sequence	LC148307	1453		1837380
124043	Deinococcus knuensis strain JCM 31406 16S ribosomal RNA gene, partial sequence.	MT760416	1317		1837380

GC content

@ref	GC-content (mol%)	Method
67770	65.7	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Deinococcus knuensis JCM 31406
NCBI: GCA_014648155

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	93.10	no
125439	motility	BacteriaNetⓘ	no	95.00	no
125439	gram_stain	BacteriaNetⓘ	positive	99.70	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	89.60	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Deinococcus knuensis strain JCM 31406
PATRIC: 1837380.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	50.55	no
125438	anaerobic	anaerobicⓘ	no	92.90	no
125438	spore-forming	spore-formingⓘ	no	72.08	no
125438	aerobic	aerobicⓘ	yes	80.35	no
125438	thermophilic	thermophileⓘ	no	90.06	yes
125438	flagellated	motile2+ⓘ	no	73.18	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Deinococcus knuensis sp. nov., a bacterium isolated from river water.	Lee JJ, Lee YH, Park SJ, Lee SY, Park S, Lee DS, Kang IK, Ten LN, Jung HY	Antonie Van Leeuwenhoek	10.1007/s10482-016-0813-3	2016

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) .
#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 .
#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 )

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Deinococcus knuensis (KCTC 33794, JCM 31406)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Spore formation

Observation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_014648155

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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