Methylobacterium sp. (DSM 102642, Leaf122)

Name: Methylobacterium sp. (DSM 102642, Leaf122)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131780

Type strain

Strain Designation Leaf122

Culture col. no. DSM 102642 Leaf122

NCBI tax ID(s) 409

Special Collections DSMZ Arabidopsis

Links

Leaf122 is a mesophilic prokaryote that was isolated from leaf of Arabidopsis thaliana, wild-type genotype.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 404769

DSM 102642

@ref 20215

Last LPSN update 2025-12-16 10:01:20

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	97.784
125439	negative	96

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
23575	MINIMAL MEDIA CONTAINING METHANOL (DSMZ Medium 1629)		Medium recipe at MediaDive	Name: MINIMAL MEDIA CONTAINING METHANOL (DSMZ Medium 1629) Composition: Agar 15.0 g/l Methanol 3.96 g/l K2HPO4 2.4 g/l NH4Cl 1.62 g/l NaH2PO4 x 2 H2O 1.1 g/l MgSO4 x 7 H2O 0.2 g/l Na2-EDTA 0.015 g/l ZnSO4 x 7 H2O 0.0045 g/l CaCl2 x 6 H2O 0.003 g/l FeSO4 x 6 H2O 0.003 g/l CoCl2 x 6 H2O 0.003 g/l H3BO3 0.001 g/l MnCl2 x 4 H2O 0.00064 g/l Na2MoO4 x 2 H2O 0.0004 g/l CuSO4 x 2 H2O 0.0003 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
23575	positive	growth	28	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	92.4

Spore formation

@ref	Spore formation	Confidence
125439		95.9

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	Latitude	Longitude
23575	leaf of Arabidopsis thaliana, wild-type genotype	Arabidopsis thaliana	Brugg (47.4816806N 8.217547222E)	Switzerland	CHE	Europe	47.4816	8.2175 47.4816/8.2175

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	Leaf122 assembly for Methylobacterium sp. Leaf122	scaffold	GCA_001423025	1736263.3	2643221882	1736263	45.75

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Methylobacterium sp. Leaf122
PATRIC: 1736263.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	95.90	no
125439	motility	BacteriaNetⓘ	yes	57.00	no
125439	gram_stain	BacteriaNetⓘ	negative	96.00	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	92.40	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methylobacterium sp. Leaf122
PATRIC: 1736263.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.78	no
125438	anaerobic	anaerobicⓘ	no	93.41	no
125438	spore-forming	spore-formingⓘ	no	85.46	no
125438	aerobic	aerobicⓘ	yes	85.73	no
125438	thermophilic	thermophileⓘ	no	97.50	yes
125438	flagellated	motile2+ⓘ	yes	77.94	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 )
#23575	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 102642
#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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