Cite this strain

Variovorax sp. (JCM 16519)

Name: Variovorax sp. (JCM 16519)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 161802

Type strain

Culture col. no. JCM 16519

NCBI tax ID(s) 662548

Special Collections JCM

History K. Satsuma RA8.

Links

JCM 16519 is a bacterium that was isolated from Sediment of the Kinugawa River.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 390779

JCM 16519

@ref 20215

Last LPSN update 2026-02-09 11:39:15

Domain Bacteria

Phylum Pseudomonadota

Class Betaproteobacteria

Order Burkholderiales

Family Comamonadaceae

Genus Variovorax

Full scientific name Variovorax Willems et al. 1991

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	94.704

Culture and growth conditions

Culture temp

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

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	95.7

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Sediment of the Kinugawa River	Ibaraki Pref.	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB513921 (>99% sequence identity) for Variovorax from Microbeatlas

Aquatic Samples	220
Soil Samples	1409
Animal Samples	220
Plant Samples	450
Total Samples	2299

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
66792	ASM131236v1 assembly for Variovorax sp. RA8 JCM 16519	contig	GCA_001312365	662548.6	2728369721	662548

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Variovorax sp. RA8 gene for 16S rRNA, partial sequence	AB513921	1526		662548

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Variovorax sp. RA8 JCM 16519
NCBI: GCA_001312365

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	89.40	no
125439	motility	BacteriaNetⓘ	no	51.10	no
125439	gram_stain	BacteriaNetⓘ	negative	80.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	95.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Variovorax sp. RA8 strain JCM 16519
PATRIC: 662548.6

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.70	no
125438	anaerobic	anaerobicⓘ	no	96.99	no
125438	spore-forming	spore-formingⓘ	no	84.82	no
125438	aerobic	aerobicⓘ	yes	86.87	no
125438	thermophilic	thermophileⓘ	no	90.96	no
125438	flagellated	motile2+ⓘ	yes	61.81	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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