Brevundimonas basaltis (DSM 25335, JCM 15911, KCTC 22177)

Name: Brevundimonas basaltis (DSM 25335, JCM 15911, KCTC 22177)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 2321

Type strain

Strain Designation J22

Culture col. no. DSM 25335 JCM 15911 KCTC 22177 J22

NCBI tax ID(s) 472166

Special Collections DSMZ JCM KCTC Literature strains

History DSMZ <- JCM <- J.-W. Bae, Kyung Hee Univ., Seoul, Republic of Korea JCM <-- J.-W. Bae J22.

Links

Brevundimonas basaltis J22 is an aerobe, Gram-negative, motile bacterium that was isolated from black sand.

Gram-negative motile rod-shaped aerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 399511

KCTC 22177,JCM 15911,DSM 25335

@ref 20215

Last LPSN update 2026-05-29 08:25:27

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Caulobacterales

Family Caulobacteraceae

Genus Brevundimonas

Species Brevundimonas basaltis

Full scientific name Brevundimonas basaltis Choi et al. 2010

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Motility	Confidence
29461	negative	rod-shaped
125438	negative			98.494

Pigmentation

29461

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
18004	R2A MEDIUM (DSMZ Medium 830)		Medium recipe at MediaDive	Name: R2A MEDIUM (DSMZ Medium 830) Composition: Agar 15.0 g/l Casamino acids 0.5 g/l Starch 0.5 g/l Glucose 0.5 g/l Proteose peptone 0.5 g/l Yeast extract 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
18004	positive	growth	28
29461	positive	growth	10-42
29461	positive	optimum	30
67770	positive	growth	30

Culture pH

@ref	Ability	Type	PH	PH range
29461	positive	optimum	7.5
29461	positive	growth	5.5-10	alkaliphile

Physiology and metabolism

Oxygen tolerance

29461

Oxygen toleranceaerobe

Spore formation

@ref	Spore formation	Confidence
125438		92.662
125439		97.305

Halophily

@ref	Salt	Growth	Tested relation	Concentration
29461	NaCl	positive	growth	0-4 %

Observation

29461

Observationaggregates in chains

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
29461	35391 ChEBI	aspartate	+	carbon source
29461	23652 ChEBI	dextrin	+	carbon source
29461	4853 ChEBI	esculin	+	hydrolysis

Enzymes

@ref	Value	Activity	Ec
29461	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
18004	black sand	Jeju Island, Soesoggak	Republic of Korea	KOR	Asia
67770	Black sand from Soesoggak Beach on Jeju		Republic of Korea	KOR	Asia

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
18004	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	ASM1420207v1 assembly for Brevundimonas basaltis DSM 25335	contig	GCA_014202075	472166.3	2861358767	472166	76.59
124043	ASM3952339v1 assembly for Brevundimonas basaltis JCM 15911	scaffold	GCA_039523395			472166	71.83

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
18004	Brevundimonas basaltis strain J22 16S ribosomal RNA gene, partial sequence	EU143355	1339		472166

GC content

@ref	GC-content (mol%)	Method
18004	66.3	thermal denaturation, midpoint method (Tm)
29461	66.3

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1420207v1 assembly for Brevundimonas basaltis DSM 25335
NCBI: GCA_014202075

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	89.89	no
125439	gram_stain	BacteriaNetⓘ	negative	81.99	no
125439	motility	BacteriaNetⓘ	yes	52.65	no
125439	spore_formation	BacteriaNetⓘ	no	97.31	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Brevundimonas basaltis strain DSM 25335
PATRIC: 472166.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.49	yes
125438	anaerobic	anaerobicⓘ	no	92.87	no
125438	spore-forming	spore-formingⓘ	no	92.66	no
125438	aerobic	aerobicⓘ	yes	81.16	yes
125438	thermophilic	thermophileⓘ	no	96.79	yes
125438	flagellated	motile2+ⓘ	yes	50.50	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Metabolism	Pyrosequencing analysis reveals high population dynamics of the soil microcosm degrading octachlorodibenzofuran.	Chen WY, Wu JH, Chang JE.	Microbes Environ	10.1264/jsme2.me14001	2014
Metabolism	Characterization of pure cultures isolated from sulfamethoxazole-acclimated activated sludge with respect to taxonomic identification and sulfamethoxazole biodegradation potential.	Herzog B, Lemmer H, Horn H, Muller E.	BMC Microbiol	10.1186/1471-2180-13-276	2013
Phylogeny	Brevundimonas denitrificans sp. nov., a denitrifying bacterium isolated from deep subseafloor sediment.	Tsubouchi T, Koyama S, Mori K, Shimane Y, Usui K, Tokuda M, Tame A, Uematsu K, Maruyama T, Hatada Y.	Int J Syst Evol Microbiol	10.1099/ijs.0.067199-0	2014
Genetics	Genome-Based Taxonomy of Brevundimonas with Reporting Brevundimonas huaxiensis sp. nov.	Liu L, Feng Y, Wei L, Zong Z.	Microbiol Spectr	10.1128/spectrum.00111-21	2021
Phylogeny	Brevundimonas basaltis sp. nov., isolated from black sand.	Choi JH, Kim MS, Roh SW, Bae JW	Int J Syst Evol Microbiol	10.1099/ijs.0.013557-0	2009

References

#18004	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 25335
#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 )
#25865	IJSEM 1488 2010 ( DOI 10.1099/ijs.0.013557-0 , PubMed 19671711 )
#29461	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 #25865
#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;
#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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Brevundimonas basaltis (DSM 25335, JCM 15911, KCTC 22177)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

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_014202075

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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