Sulfurihydrogenibium yellowstonense (OCM 840, JCM 12773)

Name: Sulfurihydrogenibium yellowstonense (OCM 840, JCM 12773)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 161262

Type strain

Culture col. no. OCM 840 JCM 12773

NCBI tax ID(s) 304736

Special Collections JCM

History S. Nakagawa SS-5.

Links

Sulfurihydrogenibium yellowstonense JCM 12773 is a bacterium that was isolated from Calcite Hot Spring in Yellowstone National Park.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 281467

JCM 12773

@ref 20215

Last LPSN update 2026-02-09 11:39:06

Domain Bacteria

Phylum Aquificota

Class Aquificia

Order Aquificales

Family Hydrogenothermaceae

Genus Sulfurihydrogenibium

Species Sulfurihydrogenibium yellowstonense

Full scientific name Sulfurihydrogenibium yellowstonense Nakagawa et al. 2005

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	94.876
125439	negative	93.5

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	70

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125438		93.331

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Calcite Hot Spring in Yellowstone National Park	WY	USA	USA	North America

Taxonmaps

69479

Global distribution of 16S sequence AY686713 (>99% sequence identity) for Sulfurihydrogenibium from Microbeatlas

Aquatic Samples	11
Soil Samples
Animal Samples
Plant Samples
Total Samples	11

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM17361v1 assembly for Sulfurihydrogenibium yellowstonense SS-5	contig	GCA_000173615	432331.4	645058708	432331	12.97

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Sulfurihydrogenibium yellowstonense strain SS-5 16S ribosomal RNA gene, partial sequence	AY686713	1447		432331
124043	Sulfurihydrogenibium yellowstonense 16S-23S rRNA intergenic spacer containing tRNA-Ile and tRNA-Ala genes, type strain JCM 12773T	AM259516	456		432331

GC content

67770

GC-content (mol%)32

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Sulfurihydrogenibium yellowstonense SS-5
NCBI: GCA_000173615

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	87.60	no
125439	motility	BacteriaNetⓘ	no	66.90	no
125439	gram_stain	BacteriaNetⓘ	negative	93.50	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	82.50	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Sulfurihydrogenibium yellowstonense SS-5 SS-5
NCBI: GCA_000173615.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.88	no
125438	anaerobic	anaerobicⓘ	yes	57.29	no
125438	aerobic	aerobicⓘ	no	80.04	no
125438	spore-forming	spore-formingⓘ	no	93.33	no
125438	thermophilic	thermophileⓘ	yes	75.35	yes
125438	flagellated	motile2+ⓘ	no	52.43	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Sulfurihydrogenibium yellowstonense sp. nov., an extremely thermophilic, facultatively heterotrophic, sulfur-oxidizing bacterium from Yellowstone National Park, and emended descriptions of the genus Sulfurihydrogenibium, Sulfurihydrogenibium subterraneum and Sulfurihydrogenibium azorense.	Nakagawa S, Shtaih Z, Banta A, Beveridge TJ, Sako Y, Reysenbach AL	Int J Syst Evol Microbiol	10.1099/ijs.0.63708-0	2005

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 .
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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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Sulfurihydrogenibium yellowstonense (OCM 840, JCM 12773)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_000173615

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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