Methylobacterium aerolatum (DSM 19013, KACC 11766, 5413S-11)

Name: Methylobacterium aerolatum (DSM 19013, KACC 11766, 5413S-11)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 7182

Type strain

Strain Designation 5413S-11

Culture col. no. DSM 19013 KACC 11766 5413S-11 JCM 16406

NCBI tax ID(s) 418708

Special Collections DSMZ JCM Literature strains

History <- S.-W. Kwon, KACC; 5413S-11 KACC 11766 <-- H.-Y. Weon 5413S-11.

Links

Methylobacterium aerolatum 5413S-11 is an aerobe, Gram-negative, motile bacterium that was isolated from air sample.

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

Name and taxonomic classification

SI-ID 401352

JCM 16406,DSM 19013

@ref 20215

Last LPSN update 2026-02-09 11:19:24

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Methylobacteriaceae

Genus Methylobacterium

Species Methylobacterium aerolatum

Full scientific name Methylobacterium aerolatum Weon et al. 2008

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Motility	Confidence
32155	negative	2.25 µm	1 µm	rod-shaped
125439	negative					93.6

Pigmentation

32155

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
7831	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)
7831	positive	growth	30
32155	positive	growth	10-35
32155	positive	optimum	28
67770	positive	growth	30

Culture pH

@ref	Ability	Type	PH	PH range
32155	positive	optimum	7
32155	positive	growth	05-09	alkaliphile

Physiology and metabolism

Oxygen tolerance

32155

Oxygen toleranceaerobe

Spore formation

@ref	Spore formation	Confidence
125439		94.4

Halophily

@ref	Salt	Growth	Tested relation	Concentration
32155	NaCl	positive	growth	<2 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
32155	15740 ChEBI	formate	+	carbon source
32155	17754 ChEBI	glycerol	+	carbon source
32155	24996 ChEBI	lactate	+	carbon source
32155	51850 ChEBI	methyl pyruvate	+	carbon source
32155	30031 ChEBI	succinate	+	carbon source

Enzymes

@ref	Value	Activity	Ec
32155	catalase	+	1.11.1.6
32155	cytochrome oxidase	+	1.9.3.1

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2
#Environmental	#Air

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
7831	air sample	Suwon city	Republic of Korea	KOR	Asia
67770	Air sample in Suwon City		Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence EF174498 (>99% sequence identity) for Methylobacterium from Microbeatlas

Aquatic Samples	31
Soil Samples	30
Animal Samples	129
Plant Samples	28
Total Samples	218

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
7831	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	ASM3081475v1 assembly for Methylobacterium aerolatum DSM 19013	contig	GCA_030814755	418708.4	2928195108	418708	69.67
124043	ASM4265688v1 assembly for Methylobacterium aerolatum KACC 11766	scaffold	GCA_042656885			418708	66.59
66792	ASM2217908v1 assembly for Methylobacterium aerolatum DSM 19013	contig	GCA_022179085	418708.3	8049326529	418708	64.24

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
7831	Methylobacterium aerolatum strain 5413S-11 16S ribosomal RNA gene, partial sequence	EF174498	1332		418708

GC content

@ref	GC-content (mol%)	Method
7831	73.2
67770	73.2	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: Methylobacterium aerolatum DSM 19013
NCBI: GCA_022179085

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	94.40	no
125439	motility	BacteriaNetⓘ	yes	69.10	no
125439	gram_stain	BacteriaNetⓘ	negative	93.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	81.40	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Methylobacterium iners sp. nov. and Methylobacterium aerolatum sp. nov., isolated from air samples in Korea.	Weon HY, Kim BY, Joa JH, Son JA, Song MH, Kwon SW, Go SJ, Yoon SH	Int J Syst Evol Microbiol	10.1099/ijs.0.65047-0	2008

References

#7831	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 19013
#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 )
#28398	IJSEM 93 2008 ( DOI 10.1099/ijs.0.65047-0 , PubMed 18175690 )
#32155	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 #28398
#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 .
#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 aerolatum (DSM 19013, KACC 11766, 5413S-11)

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

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_030814755

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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