Methylobacterium brachiatum (DSM 19569, NBRC 103629, NCIMB 14379)

Name: Methylobacterium brachiatum (DSM 19569, NBRC 103629, NCIMB 14379)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 7186

Type strain

Strain Designation B0021

Culture col. no. DSM 19569 NBRC 103629 NCIMB 14379 B0021 HKI 0752 1 more

NCBI tax ID(s) 269660

Special Collections DSMZ Literature strains JMRC

History DSMZ <- Y. Kato, Microbiol. and Analytical Group, Food Res. Lab., Mitsui Norin Co. Ltd., Shizuoka, Japan; B0021

Links

Methylobacterium brachiatum B0021 is an aerobe, Gram-negative, motile bacterium that was isolated from water samples from food factories.

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

Name and taxonomic classification

SI-ID 400752

NBRC 103629,NCIMB 14379,DSM 19569

@ref 20215

Last LPSN update 2026-05-29 08:26:35

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Methylobacteriaceae

Genus Methylobacterium

Species Methylobacterium brachiatum

Full scientific name Methylobacterium brachiatum Kato et al. 2008

BacDive ID	Other strains from **Methylobacterium brachiatum** (2)	Type strain
7184	M. brachiatum RB603B, DSM 19567
7185	M. brachiatum Hojyo2, DSM 19568

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
32496	negative	3.4 µm	1.1 µm	rod-shaped
125439	negative				90.394
125438	negative				96.802

Pigmentation

32496

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
8184	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)
8184	positive	growth	28
32496	positive	growth	10-35
32496	positive	optimum	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
32496	aerobe
125439	obligate aerobe	94.901

Spore formation

@ref	Spore formation	Confidence
125439		98.53

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
32496	22599 ChEBI	arabinose	+	carbon source
32496	18222 ChEBI	xylose	+	carbon source

Enzymes

@ref	Value	Activity	Ec
32496	catalase	+	1.11.1.6
32496	cytochrome oxidase	+	1.9.3.1

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Food production	#Food
#Engineered	#Industrial	#Plant (Factory)
#Environmental	#Aquatic	-

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
8184	water samples from food factories	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB175649 (>99% sequence identity) for Methylobacterium from Microbeatlas

Aquatic Samples	142
Soil Samples	88
Animal Samples	737
Plant Samples	195
Total Samples	1162

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
8184	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
124043	ASM3081519v1 assembly for Methylobacterium brachiatum DSM 19569	contig	GCA_030815195	269660.13	2928975616	269660	69.31
66792	ASM2052382v1 assembly for Methylobacterium brachiatum B0021	scaffold	GCA_020523825	269660.10	8117132289	269660	67.39

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
8184	Methylobacterium brachiatum gene for 16S rRNA, partial sequence, strain: B0021	AB175649	1433		269660

GC content

32496

GC-content (mol%)69.2-69.7

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM3081519v1 assembly for Methylobacterium brachiatum DSM 19569
NCBI: GCA_030815195

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	94.90	no
125439	gram_stain	BacteriaNetⓘ	negative	90.39	no
125439	motility	BacteriaNetⓘ	yes	47.15	no
125439	spore_formation	BacteriaNetⓘ	no	98.53	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methylobacterium brachiatum B0021
NCBI: GCA_020523825.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	96.80	no
125438	anaerobic	anaerobicⓘ	no	95.30	yes
125438	aerobic	aerobicⓘ	yes	89.85	yes
125438	spore-forming	spore-formingⓘ	no	87.88	no
125438	thermophilic	thermophileⓘ	no	98.43	yes
125438	flagellated	motile2+ⓘ	yes	70.37	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Methylobacterium trifolii sp. nov. and Methylobacterium thuringiense sp. nov., methanol-utilizing, pink-pigmented bacteria isolated from leaf surfaces.	Wellner S, Lodders N, Glaeser SP, Kampfer P	Int J Syst Evol Microbiol	10.1099/ijs.0.047787-0	2013
Phylogeny	Methylobacterium soli sp. nov. a methanol-utilizing bacterium isolated from the forest soil.	Cao YR, Wang Q, Jin RX, Tang SK, Jiang Y, He WX, Lai HX, Xu LH, Jiang CL	Antonie Van Leeuwenhoek	10.1007/s10482-010-9535-0	2011
Phylogeny	Methylobacterium dankookense sp. nov., isolated from drinking water.	Lee SW, Oh HW, Lee KH, Ahn TY	J Microbiol	10.1007/s12275-009-0126-6	2010

References

#8184	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 19569
#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 )
#20216	Curators of the JMRC: Jena Microbial Resource Collection (JMRC):
#28716	IJSEM 1134 2008 ( DOI 10.1099/ijs.0.65583-0 , PubMed 18450702 )
#32496	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 #28716
#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) .
#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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Methylobacterium brachiatum (DSM 19569, NBRC 103629, NCIMB 14379)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_030815195

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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