Cite this strain

Rhodococcus sp. (JCM 6824)

Name: Rhodococcus sp. (JCM 6824)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 165425

Type strain

Culture col. no. JCM 6824

NCBI tax ID(s) 194249

Special Collections JCM

History JCM <-- H. Shimizu No. 04.

Links

JCM 6824 is a bacterium of the family Nocardiaceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 64894

JCM 6824

@ref 20215

Last LPSN update 2026-05-29 08:45:38

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Mycobacteriales

Family Nocardiaceae

Genus Rhodococcus

Full scientific name Rhodococcus Zopf 1891 (Approved Lists 1980)

Synonyms (3)

"Prescottella"
Rhodococcoides
"Prescottia"

Morphology

Cell morphology

@ref	Gram stain	Confidence	Motility
125438	positive	91.159
125438		92

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	28

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	95.073

Metabolite production

@ref	Metabolite	Production
67770	aurachin RE

Isolation, sampling and environmental information

Taxonmaps

69479

Global distribution of 16S sequence AB429533 (>99% sequence identity) for Nocardiaceae from Microbeatlas

Aquatic Samples	6494
Soil Samples	7777
Animal Samples	11681
Plant Samples	2835
Total Samples	28787

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM74774v1 assembly for Rhodococcus erythropolis JCM 6824	scaffold	GCA_000747745	1833.79	2597490290	1833	0

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Rhodococcus erythropolis gene for 16S rRNA, partial sequence, strain: JCM 6824	AB429533	1440		1833

GC content

@ref	GC-content (mol%)	Method
67770	61.2	thermal denaturation, midpoint method (Tm)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM74774v1 assembly for Rhodococcus erythropolis JCM 6824
BV-BRC: 1833.79

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	95.07	no
125439	motility	BacteriaNetⓘ	no	78.73	no
125439	gram_stain	BacteriaNetⓘ	positive	63.19	no
125439	spore_formation	BacteriaNetⓘ	no	86.58	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Rhodococcus erythropolis strain JCM 6824
PATRIC: 1833.79

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	91.16	no
125438	anaerobic	anaerobicⓘ	no	98.47	no
125438	spore-forming	spore-formingⓘ	yes	55.36	no
125438	aerobic	aerobicⓘ	yes	83.69	no
125438	thermophilic	thermophileⓘ	no	97.50	yes
125438	flagellated	motile2+ⓘ	no	92.00	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 )
#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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