Rhodanobacter thiooxydans (DSM 18863, KCTC 12771, LCS2)

Name: Rhodanobacter thiooxydans (DSM 18863, KCTC 12771, LCS2)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 17518

Type strain

Strain Designation LCS2

Culture col. no. DSM 18863 KCTC 12771 LCS2

NCBI tax ID(s) 416169

Special Collections DSMZ KCTC Literature strains

Links

Rhodanobacter thiooxydans LCS2 is an aerobe, mesophilic, Gram-negative prokaryote that was isolated from biofilm.

Gram-negative rod-shaped aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 397222

KCTC 12771,DSM 18863

@ref 20215

Last LPSN update 2025-12-16 09:51:07

Domain Pseudomonadati

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Lysobacterales

Family Rhodanobacteraceae

Genus Rhodanobacter

Species Rhodanobacter thiooxydans

Full scientific name Rhodanobacter thiooxydans Lee et al. 2007

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
32181	negative	2.25 µm	0.7 µm	rod-shaped
67771	negative
125438	negative				94.494
125439	negative				99.1

Pigmentation

32181

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
7753	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
7753	positive	growth	28	mesophilic
32181	positive	growth	05-40
32181	positive	optimum	30	mesophilic
67771	positive	growth	25	mesophilic

Culture pH

@ref	Ability	Type	PH
32181	positive	optimum	7.5
32181	positive	growth	05-08

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
32181	aerobe
67771	aerobe
125439	obligate aerobe	99.6

Spore formation

@ref	Spore formation	Confidence
32181
125439		98.3

Halophily

@ref	Salt	Growth	Tested relation	Concentration
32181	NaCl	positive	growth	01-02 %
32181	NaCl	positive	optimum	1.5 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
32181	4853 ChEBI	esculin	+	hydrolysis
32181	33984 ChEBI	fucose	+	carbon source
32181	17234 ChEBI	glucose	+	carbon source
32181	28087 ChEBI	glycogen	+	carbon source
32181	17306 ChEBI	maltose	+	carbon source
32181	506227 ChEBI	N-acetylglucosamine	+	carbon source
32181	17632 ChEBI	nitrate	+	reduction
32181	33942 ChEBI	ribose	+	carbon source
32181	31011 ChEBI	valerate	+	carbon source

Enzymes

@ref	Value	Activity	Ec
32181	catalase	+	1.11.1.6
32181	cytochrome oxidase	+	1.9.3.1
32181	gelatinase	+

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2
#Environmental	#Biofilm

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
7753	biofilm	Daejon	Republic of Korea	KOR	Asia
67771	From waste water		Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB286179 (>99% sequence identity) for Rhodanobacter from Microbeatlas

Aquatic Samples	515
Soil Samples	1614
Animal Samples	424
Plant Samples	459
Total Samples	3012

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
7753	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	Rh18863 assembly for Rhodanobacter thiooxydans LCS2	contig	GCA_000264375	1163409.3	2537561839	1163409	32.5

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
32181	Rhodanobacter thiooxydans gene for 16S rRNA, partial sequence	AB286179	1482		1163409

GC content

32181

GC-content (mol%)64.6

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Rhodanobacter thiooxydans LCS2
NCBI: GCA_000264375

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.60	no
125439	gram_stain	BacteriaNetⓘ	negative	99.10	no
125439	motility	BacteriaNetⓘ	yes	85.50	no
125439	spore_formation	BacteriaNetⓘ	no	98.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Rhodanobacter thiooxydans LCS2
PATRIC: 1163409.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.49	yes
125438	anaerobic	anaerobicⓘ	no	97.18	no
125438	spore-forming	spore-formingⓘ	no	87.73	no
125438	aerobic	aerobicⓘ	yes	83.23	yes
125438	thermophilic	thermophileⓘ	no	95.50	yes
125438	flagellated	motile2+ⓘ	yes	58.74	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Metabolism	Genome sequences for six Rhodanobacter strains, isolated from soils and the terrestrial subsurface, with variable denitrification capabilities.	Kostka JE, Green SJ, Rishishwar L, Prakash O, Katz LS, Marino-Ramirez L, Jordan IK, Munk C, Ivanova N, Mikhailova N, Watson DB, Brown SD, Palumbo AV, Brooks SC.	J Bacteriol	10.1128/jb.00871-12	2012
Phylogeny	Rhodanobacter thiooxydans sp. nov., isolated from a biofilm on sulfur particles used in an autotrophic denitrification process.	Lee CS, Kim KK, Aslam Z, Lee ST	Int J Syst Evol Microbiol	10.1099/ijs.0.65086-0	2007

References

#7753	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 18863
#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 )
#32181	Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #28423 (see below)
#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) .
#67771	Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC;
#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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Rhodanobacter thiooxydans (DSM 18863, KCTC 12771, LCS2)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_000264375

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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