Geobacillus thermodenitrificans (JCM 32406)

Name: Geobacillus thermodenitrificans (JCM 32406)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164256

Type strain

Culture col. no. JCM 32406

NCBI tax ID(s) 33940

Special Collections JCM

History JCM <-- H. Suzuki; Tottori Univ., Japan; OS27.

Links

Geobacillus thermodenitrificans JCM 32406 is a bacterium that was isolated from Red seaweed collected along with seawater from the coast of Sakenotsu Bay.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 133002

JCM 32406

@ref 20215

Last LPSN update 2026-05-29 08:45:22

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Bacillaceae

Genus Geobacillus

Species Geobacillus thermodenitrificans

Full scientific name Geobacillus thermodenitrificans (Manachini et al. 2000 ex Klaushofer and Hollaus 1970) Nazina et al. 2001

Synonyms (1)

Bacillus thermodenitrificans

BacDive ID	Other strains from **Geobacillus thermodenitrificans** (4)	Type strain
150170	G. thermodenitrificans CCUG 39164
151703	G. thermodenitrificans CCUG 44674
151705	G. thermodenitrificans CCUG 44679
151973	G. thermodenitrificans CCUG 45409

Morphology

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	60

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	facultative anaerobe	91.169

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Host species	Geographic location	Country	Country ISO 3 Code	Continent
67770	Red seaweed (Polyopes lancifolia) collected along with seawater from the coast of Sakenotsu Bay	Polyopes lancifolia	Tottori	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence LC259311 (>99% sequence identity) for Geobacillus from Microbeatlas

Aquatic Samples	1277
Soil Samples	2618
Animal Samples	3638
Plant Samples	757
Total Samples	8290

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM306150v1 assembly for Geobacillus thermodenitrificans OS27	contig	GCA_003061505	33940.14	2915745605	33940	48.47

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Geobacillus thermodenitrificans gene for 16S ribosomal RNA, partial sequence, strain: OS27	LC259311	1479		33940

GC content

@ref	GC-content (mol%)	Method
67770	49.2	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM306150v1 assembly for Geobacillus thermodenitrificans OS27
NCBI: GCA_003061505

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	91.17	no
125439	motility	BacteriaNetⓘ	yes	55.11	no
125439	gram_stain	BacteriaNetⓘ	variable	50.66	no
125439	spore_formation	BacteriaNetⓘ	yes	54.47	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Geobacillus thermodenitrificans OS27
NCBI: GCA_003061505.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	72.82	no
125438	anaerobic	anaerobicⓘ	no	93.93	no
125438	aerobic	aerobicⓘ	yes	75.83	no
125438	spore-forming	spore-formingⓘ	yes	89.33	no
125438	thermophilic	thermophileⓘ	yes	73.69	yes
125438	flagellated	motile2+ⓘ	yes	82.22	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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