Methylobacterium sp. (DSM 102624, Leaf104)

Name: Methylobacterium sp. (DSM 102624, Leaf104)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131763

Type strain

Strain Designation Leaf104

Culture col. no. DSM 102624 Leaf104

NCBI tax ID(s) 409

Special Collections DSMZ Arabidopsis

Links

Leaf104 is a mesophilic prokaryote that was isolated from leaf of Arabidopsis thaliana, wild-type genotype.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 406775

DSM 102624

@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	98.333

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
23558	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)	Range
23558	positive	growth	28	mesophilic

Physiology and metabolism

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
23558	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	Leaf104 assembly for Methylobacterium sp. Leaf104	contig	GCA_001422885	1736254.3	2643221801	1736254	71.7
66792	ASM2280306v1 assembly for Methylobacterium goesingense DSM 102624	contig	GCA_022803065	243690.6		243690	52.88

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Methylobacterium sp. Leaf104
NCBI: GCA_001422885

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	89.40	no
125439	motility	BacteriaNetⓘ	no	52.20	no
125439	gram_stain	BacteriaNetⓘ	negative	67.30	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	77.60	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Methylobacterium sp. Leaf104
PATRIC: 1736254.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.33	no
125438	anaerobic	anaerobicⓘ	no	94.65	no
125438	spore-forming	spore-formingⓘ	no	89.24	no
125438	aerobic	aerobicⓘ	yes	88.55	no
125438	thermophilic	thermophileⓘ	no	97.50	yes
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 )
#23558	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 102624
#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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