Rhodococcus ruber (DSM 44190, 219)

Name: Rhodococcus ruber (DSM 44190, 219)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 10942

Type strain

Strain Designation 219

Culture col. no. DSM 44190 219

NCBI tax ID(s) 1830

Special Collections DSMZ

History <- H. Diekmann, 219

Links

Rhodococcus ruber 219 is a mesophilic prokaryote that was isolated from effluents of a chemical factory.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 50518

DSM 44190

@ref 20215

Last LPSN update 2026-02-09 11:20:24

Domain Bacteria

Phylum Actinomycetota

Class Actinomycetes

Order Mycobacteriales

Family Nocardiaceae

Genus Rhodococcus

Species Rhodococcus ruber

Full scientific name Rhodococcus ruber (Kruse 1896) Goodfellow and Alderson 1977 (Approved Lists 1980)

Synonyms (2)

"Streptothrix rubra"
Rhodococcus electrodiphilus

BacDive ID	Other strains from **Rhodococcus ruber** (41)	Type strain
10927	R. ruber M-1, N361, A-0205, CCUG 51069, DSM 43338, ... (type strain)
10921	R. ruber An213, DSM 6264, IMET 7643
10922	R. ruber Sm-1, DSM 7511, ATCC 51239
10923	R. ruber Wrink, DSM 7512
10924	R. ruber Propb, DSM 8425
10925	R. ruber Pellegrino 327, DSM 43232, SN 5101
10926	R. ruber N324, DSM 43335, ATCC 15998, CCUG 23602, ...
10928	R. ruber Pellegrino 330, DSM 43560, SN 5102
10929	R. ruber DSM 43561, SN 5108
10930	R. ruber DSM 43562, SN 5109
10931	R. ruber DSM 43563, SN 5110
10932	R. ruber DSM 43564, SN 5202
10933	R. ruber DSM 43565, SN 5203
10934	R. ruber DSM 43566, SN 5204
10935	R. ruber DSM 43567, SN 5205
10936	R. ruber DSM 43571, CBS 245.53, SN 6000
10937	R. ruber 81 N grün, DSM 43588
10938	R. ruber 81 N Mo, DSM 43589
10939	R. ruber NI, N_I, DSM 43594
10940	R. ruber NIIa, N_I_I_a, ...
10941	R. ruber N453, DSM 43961
10943	R. ruber S679, ES3-T, FH2170, FERM-P 3374, DSM 44319, ...
10944	R. ruber CD4=CD+1-4II, CD4=CD⁺₁-4II, ...
10945	R. ruber CD4, DSM 44495
10946	R. ruber SM 1790, TB1, DSM 44539
10947	R. ruber EH1, SM1789, DSM 44540
10949	R. ruber ES 1-T, FERM-P 2882, DSM 44755, ATCC 31191, ...
10950	R. ruber DSM 44758
10951	R. ruber 373, N 123, DSM 46008, CBS 334.51, CCM 198, ...
10952	R. ruber 906B, Casenuovo, Inst. Sup, Gdf N325, Casenuovo, ...
10953	R. ruber McClung M-122, DSM 46043, CIP 104660, IMET ...
10954	R. ruber B113, DSM 46646, IMET 7358
10955	R. ruber Chol-4, DSM 45280
10956	R. ruber C208, DSM 45332
103875	R. ruber ST004516(HKI),
130482	R. ruber A5, DSM 46851, CECT 8556
130483	R. ruber EE1, DSM 46852, CECT 8555
130484	R. ruber EE6, DSM 46853, CECT 8612
136328	R. ruber CIP 104637, CCUG 23577, PCM 2171
136331	R. ruber CIP 104640, CCUG 20988
151928	R. ruber CCUG 45236

Morphology

Cell morphology

@ref	Motility	Confidence	Gram stain
125438		93
125439		97.5	positive

Multimedia

@ref:	11588
multimedia content:	DSM_44190.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_44190.jpg
caption:	Medium 215 28°C
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
11588	TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535)		Medium recipe at MediaDive	Name: TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Distilled water
11588	GYM STREPTOMYCES MEDIUM (DSMZ Medium 65)		Medium recipe at MediaDive	Name: GYM STREPTOMYCES MEDIUM (DSMZ Medium 65) Composition: Agar 18.0 g/l Malt extract 10.0 g/l Yeast extract 4.0 g/l Glucose 4.0 g/l CaCO3 2.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
11588	positive	growth	28	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	aerobe	92.034

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Industrial	#Plant (Factory)
#Engineered	#Waste	#Industrial wastewater

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
11588	effluents of a chemical factory	Germany	DEU	Europe

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
11588	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
66792	ASM2185298v1 assembly for Rhodococcus ruber 219	contig	GCA_021852985	1830.77	1830	72.78

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Rhodococcus ruber 219
NCBI: GCA_021852985

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	56.10	no
125439	motility	BacteriaNetⓘ	no	84.50	no
125439	gram_stain	BacteriaNetⓘ	positive	97.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	77.80	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Rhodococcus ruber 219
NCBI: GCA_021852985.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	87.98	no
125438	anaerobic	anaerobicⓘ	no	98.36	no
125438	aerobic	aerobicⓘ	yes	92.03	no
125438	spore-forming	spore-formingⓘ	no	62.21	no
125438	thermophilic	thermophileⓘ	no	96.90	yes
125438	flagellated	motile2+ⓘ	no	93.00	no

Literature

References

#11588	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 44190
#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) .
#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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