Cite this strain

Bradyrhizobium sp. (JCM 18382)

Name: Bradyrhizobium sp. (JCM 18382)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 162241

Type strain

Culture col. no. JCM 18382

NCBI tax ID(s) 1215384

Special Collections JCM

Links

JCM 18382 is a mesophilic prokaryote that was isolated from Riverbed sediment of Tonegawa River.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 131681

JCM 18382

@ref 20215

Last LPSN update 2025-12-16 10:08:56

Domain Pseudomonadati

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Nitrobacteraceae

Genus Bradyrhizobium

Full scientific name Bradyrhizobium Jordan 1982

Synonyms (1)

Agromonas

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	94.269
125439	negative	95.9

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	25	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	99.5

Spore formation

@ref	Spore formation	Confidence
125439		94.6

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Riverbed sediment of Tonegawa River	Ibaraki Pref.	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB672634 (>99% sequence identity) for Bradyrhizobium from Microbeatlas

Aquatic Samples	4833
Soil Samples	14338
Animal Samples	6732
Plant Samples	3278
Total Samples	29181

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
66792	ASM131294v1 assembly for Bradyrhizobium sp. 17-4 JCM 18382	contig	GCA_001312945	1215384.3	2734481923	1215384

Genome browser: GCA_001312945

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Bradyrhizobium sp. 17-4 gene for 16S ribosomal RNA, partial sequence	AB672634	1376		1215384

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Bradyrhizobium sp. 17-4 JCM 18382
NCBI: GCA_001312945

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.50	no
125439	gram_stain	BacteriaNetⓘ	negative	95.90	no
125439	motility	BacteriaNetⓘ	yes	50.40	no
125439	spore_formation	BacteriaNetⓘ	no	94.60	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Bradyrhizobium sp. 17-4 strain JCM 18382
PATRIC: 1215384.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.27	no
125438	anaerobic	anaerobicⓘ	no	90.33	no
125438	spore-forming	spore-formingⓘ	no	87.87	no
125438	aerobic	aerobicⓘ	yes	84.63	no
125438	thermophilic	thermophileⓘ	no	97.08	yes
125438	flagellated	motile2+ⓘ	yes	76.63	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 )
#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 .
#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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