Methylobacterium sp. (DSM 23674, C61+2-34)

Name: Methylobacterium sp. (DSM 23674, C61+2-34)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 130982

Type strain

Strain Designation C61+2-34

Culture col. no. DSM 23674 C61+2-34

NCBI tax ID(s) 409

Special Collections DSMZ

Links

C61+2-34 is a mesophilic prokaryote that was isolated from leaf of Cerastium holosteoides.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 399941

DSM 23674

@ref 20215

Last LPSN update 2025-12-16 10:01:08

Domain Pseudomonadati

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Methylobacteriaceae

Genus Methylobacterium

Full scientific name Methylobacterium Patt et al. 1976 (Approved Lists 1980)

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	97.333
125439	negative	98.4

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
22274	METHYLOBACTERIUM MEDIUM (DSMZ Medium 125)		Medium recipe at MediaDive	Name: METHYLOBACTERIUM MEDIUM (DSMZ Medium 125) Composition: Agar 12.0 g/l KNO3 1.0 g/l Na2HPO4 0.23 g/l MgSO4 x 7 H2O 0.2 g/l NaH2PO4 0.07 g/l CaCl2 x 2 H2O 0.02 g/l FeSO4 x 7 H2O 0.001 g/l ZnSO4 x 7 H2O 7e-05 g/l H3BO3 1e-05 g/l MnSO4 x 5 H2O 1e-05 g/l MoO3 1e-05 g/l CuSO4 x 5 H2O 5e-06 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
22274	positive	growth	25	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	93.8

Spore formation

@ref	Spore formation	Confidence
125439		97.6

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Plants	#Herbaceous plants (Grass,Crops)
#Host Body-Site	#Plant	#Leaf (Phyllosphere)

Isolation

@ref	Sample type	Host species	Geographic location	Country	Country ISO 3 Code	Continent
22274	leaf of Cerastium holosteoides	Cerastium holosteoides	Thüringen, exploratory Hainich-Dün	Germany	DEU	Europe

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM2217964v1 assembly for Methylobacterium thuringiense DSM 23674	contig	GCA_022179645	1003091.3	8069157833	1003091	70.04

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Methylobacterium thuringiense DSM 23674
NCBI: GCA_022179645

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	97.60	no
125439	motility	BacteriaNetⓘ	yes	72.00	no
125439	gram_stain	BacteriaNetⓘ	negative	98.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	93.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methylobacterium thuringiense DSM 23674
NCBI: GCA_022179645.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.33	no
125438	anaerobic	anaerobicⓘ	no	92.44	no
125438	aerobic	aerobicⓘ	yes	85.36	no
125438	spore-forming	spore-formingⓘ	no	87.13	no
125438	thermophilic	thermophileⓘ	no	97.50	no
125438	flagellated	motile2+ⓘ	yes	68.30	no

Literature

References

#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 )
#22274	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 23674
#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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