Brevundimonas lenta (DSM 23960, JCM 14602, KCTC 12871)

Name: Brevundimonas lenta (DSM 23960, JCM 14602, KCTC 12871)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 2319

Type strain

Strain Designation DS-18

Culture col. no. DSM 23960 JCM 14602 KCTC 12871 DS-18

NCBI tax ID(s) 424796

Special Collections DSMZ JCM KCTC Literature strains

History DSMZ <- KCTC <- J. H. Joon, Korea Res. Inst. Biosci. & Biotechnol. (KRIBB), Taejon, South Korea JCM <-- J.-H. Yoon DS-18. KCTC <- JH Yoon, KRIBB

Links

Brevundimonas lenta DS-18 is an aerobe, Gram-negative, motile bacterium that was isolated from soil.

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

Name and taxonomic classification

SI-ID 310988

JCM 14602,KCTC 12871,DSM 23960

@ref 20215

Last LPSN update 2026-05-29 08:25:26

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Caulobacterales

Family Caulobacteraceae

Genus Brevundimonas

Species Brevundimonas lenta

Full scientific name Brevundimonas lenta Yoon et al. 2007

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
32178	negative	2.05 µm	0.4 µm	rod-shaped
67771	negative
125438	negative				97.328

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
17453	NUTRIENT AGAR (DSMZ Medium 1)		Medium recipe at MediaDive	Name: NUTRIENT AGAR (DSMZ Medium 1) Composition: Agar 15.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
17453	positive	growth	25
32178	positive	growth	04-34
32178	positive	optimum	25
67770	positive	growth	25
67771	positive	growth	25

Culture pH

@ref	Ability	Type	PH	PH range
32178	positive	optimum	6.75
32178	positive	growth	6.0-9.5	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
67771	aerobe
125439	obligate aerobe	98.727

Spore formation

@ref	Spore formation	Confidence
125438		90.469
125439		93.947

Halophily

@ref	Salt	Growth	Tested relation	Concentration
32178	NaCl	positive	growth	0-1 %

Observation

67770

Observationquinones: Q-10

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
32178	53424 ChEBI	tween 20	+	carbon source
32178	53423 ChEBI	tween 40	+	carbon source
32178	53425 ChEBI	tween 60	+	carbon source

Enzymes

@ref	Value	Activity	Ec
32178	acid phosphatase	+	3.1.3.2
32178	alkaline phosphatase	+	3.1.3.1
32178	catalase	+	1.11.1.6
32178	cytochrome oxidase	+	1.9.3.1
32178	gelatinase	+
32178	urease	+	3.5.1.5

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
17453	soil	Dokdo	Republic of Korea	KOR	Asia
67770	Soil
67771	From soil	Dokdo	Republic of Korea	KOR	Asia

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
17453	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	ASM1419633v1 assembly for Brevundimonas lenta DSM 23960	contig	GCA_014196335	424796.3	2829867983	424796	77.88
124043	ASM3952311v1 assembly for Brevundimonas lenta JCM 14602	scaffold	GCA_039523115			424796	72.36

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
17453	Brevundimonas lenta strain DS-18 16S ribosomal RNA gene, partial sequence	EF363713	1418		424796

GC content

@ref	GC-content (mol%)	Method
17453	68.7	high performance liquid chromatography (HPLC)
32178	68.7

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1419633v1 assembly for Brevundimonas lenta DSM 23960
BV-BRC: 424796.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	98.73	no
125439	gram_stain	BacteriaNetⓘ	negative	75.26	no
125439	motility	BacteriaNetⓘ	yes	40.78	no
125439	spore_formation	BacteriaNetⓘ	no	93.95	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Brevundimonas lenta strain DSM 23960
PATRIC: 424796.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.33	yes
125438	anaerobic	anaerobicⓘ	no	91.40	yes
125438	spore-forming	spore-formingⓘ	no	90.47	no
125438	aerobic	aerobicⓘ	yes	85.37	yes
125438	thermophilic	thermophileⓘ	no	98.83	no
125438	flagellated	motile2+ⓘ	yes	59.38	no

Literature

Topic	Title	Authors	Journal	DOI	Year
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	Pyomelanin-Producing Brevundimonas vitisensis sp. nov., Isolated From Grape (Vitis vinifera L.).	Jiang L, Jeon D, Kim J, Lee CW, Peng Y, Seo J, Lee JH, Paik JH, Kim CY, Lee J	Front Microbiol	10.3389/fmicb.2021.733612	2021
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
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
Phylogeny	Brevundimonas lenta sp. nov., isolated from soil.	Yoon JH, Kang SJ, Lee JS, Oh HW, Oh TK	Int J Syst Evol Microbiol	10.1099/ijs.0.65080-0	2007

References

#17453	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 23960
#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 )
#28420	IJSEM 2236 2007 ( DOI 10.1099/ijs.0.65080-0 , PubMed 17911289 )
#32178	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 #28420
#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;
#67771	Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC;
#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 )

Rate our new design

Content

About us

Brevundimonas lenta (DSM 23960, JCM 14602, KCTC 12871)

Name and taxonomic classification

Morphology

Cell morphology

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_014196335

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media