Microbacterium radiodurans (DSM 25564, CCTCC M208212, NRRL B-24799)

Name: Microbacterium radiodurans (DSM 25564, CCTCC M208212, NRRL B-24799)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 7454

Type strain

Culture col. no. DSM 25564 CCTCC M208212 NRRL B-24799 GIMN 1.002

NCBI tax ID(s) 661398

Special Collections DSMZ Literature strains

Links

Microbacterium radiodurans DSM 25564 is an aerobe, mesophilic, Gram-positive prokaryote that was isolated from upper sand layers.

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

Name and taxonomic classification

SI-ID 405960

DSM 25564

@ref 20215

Last LPSN update 2025-12-16 09:48:35

Domain Bacillati

Phylum Actinomycetota

Class Actinomycetes

Order Micrococcales

Family Microbacteriaceae

Genus Microbacterium

Species Microbacterium radiodurans

Full scientific name Microbacterium radiodurans Zhang et al. 2010

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape
29631	positive	0.5-0.8 µm	0.4-0.6 µm	rod-shaped
125438
125438	positive
125439	positive

Pigmentation

29631

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
18049	TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)		Medium recipe at MediaDive	Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
18049	positive	growth	28	mesophilic
29631	positive	growth	18-30
29631	positive	optimum	28	mesophilic

Culture pH

@ref	Ability	Type	PH
29631	positive	optimum	7
29631	positive	growth	06-10

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance
29631	aerobe
125439	obligate aerobe

Halophily

@ref	Salt	Growth	Tested relation	Concentration
29631	NaCl	positive	growth	0-7 %
29631	NaCl	positive	optimum	0-7 %

Observation

29631

Observationaggregates in chains

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
29631	17057 ChEBI	cellobiose	+	carbon source
29631	28757 ChEBI	fructose	+	carbon source
29631	17234 ChEBI	glucose	+	carbon source
29631	25115 ChEBI	malate	+	carbon source
29631	17306 ChEBI	maltose	+	carbon source
29631	29864 ChEBI	mannitol	+	carbon source
29631	37684 ChEBI	mannose	+	carbon source
29631	51850 ChEBI	methyl pyruvate	+	carbon source
29631	30911 ChEBI	sorbitol	+	carbon source
29631	27082 ChEBI	trehalose	+	carbon source

Enzymes

@ref	Value	Activity	Ec
29631	catalase	+	1.11.1.6

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Sandy

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
18049	upper sand layers	Xinjiang, Gobi desert	China	CHN	Asia

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
18049	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM871070v1 assembly for Microbacterium radiodurans DSM 25564	contig	GCA_008710705	661398.3	2989672817	661398	77.75

Genome browser: GCA_008710705

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
18049	Microbacterium radiodurans strain GIMN 1.002 16S ribosomal RNA gene, partial sequence	GQ329713	1430		661398

GC content

@ref	GC-content (mol%)
18049	67.7
29631	67.74

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Microbacterium radiodurans DSM 25564
NCBI: GCA_008710705

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	87.80	no
125439	motility	BacteriaNetⓘ	no	54.60	no
125439	gram_stain	BacteriaNetⓘ	positive	94.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Microbacterium radiodurans strain DSM 25564
PATRIC: 661398.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	91.35	no
125438	anaerobic	anaerobicⓘ	no	97.85	yes
125438	spore-forming	spore-formingⓘ	no	77.30	no
125438	aerobic	aerobicⓘ	yes	81.93	yes
125438	thermophilic	thermophileⓘ	no	95.93	no
125438	flagellated	motile2+ⓘ	no	91.50	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Four new Microbacterium species isolated from seaweeds and reclassification of five Microbacterium species with a proposal of Paramicrobacterium gen. nov. under a genome-based framework of the genus Microbacterium.	Lee SD, Yang HL, Kim IS.	Front Microbiol	10.3389/fmicb.2023.1299950	2023
	Bioprospecting the Solar Panel Microbiome: High-Throughput Screening for Antioxidant Bacteria in a Caenorhabditis elegans Model.	Tanner K, Martorell P, Genoves S, Ramon D, Zacarias L, Rodrigo MJ, Pereto J, Porcar M.	Front Microbiol	10.3389/fmicb.2019.00986	2019
Phylogeny	Microbacterium caowuchunii sp. nov. and Microbacterium lushaniae sp. nov., isolated from plateau pika (Ochotona curzoniae) on the Qinghai-Tibet Plateau of PR China.	Tian Z, Yang J, Lai XH, Pu J, Jin D, Luo X, Huang Y, Li J, Zhang G, Wang S, Xu J	Int J Syst Evol Microbiol	10.1099/ijsem.0.004662	2021
Phylogeny	Microbacterium radiodurans sp. nov., a UV radiation-resistant bacterium isolated from soil.	Zhang W, Zhu HH, Yuan M, Yao Q, Tang R, Lin M, Yang SZ, Li ZK, Chen M	Int J Syst Evol Microbiol	10.1099/ijs.0.017400-0	2010

References

#18049	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 25564
#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 )
#29631	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 #26021 (see below)
#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) .
#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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Microbacterium radiodurans (DSM 25564, CCTCC M208212, NRRL B-24799)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Halophily

Observation

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_008710705

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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