Oceanobacillus sojae (DSM 23151, CIP 109918, JCM 15792)

Name: Oceanobacillus sojae (DSM 23151, CIP 109918, JCM 15792)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 1379

Type strain

Strain Designation Y27

Culture col. no. DSM 23151 CIP 109918 JCM 15792 NBRC 105379 NCIMB 14542 3 more

NCBI tax ID(s) 582851

Special Collections DSMZ JCM KCTC CIP

Links

Oceanobacillus sojae Y27 is a facultative anaerobe, mesophilic, Gram-positive prokaryote that was isolated from surface of soy sauce production equipment.

Gram-positive motile rod-shaped facultative anaerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 364728

CIP 109918,NRRL B-59181,JCM 15792,NBRC 105379,NCIMB 14542,DSM 23151

@ref 20215

Last LPSN update 2025-12-16 09:47:05

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Bacillaceae

Genus Oceanobacillus

Species Oceanobacillus sojae

Full scientific name Oceanobacillus sojae corrig. Tominaga et al. 2009

Synonyms (1)

Oceanobacillus soja

BacDive ID	Other strains from **Oceanobacillus sojae** (1)	Type strain
154794	O. sojae CCUG 55219

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Motility
122650	positive	rod-shaped

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
16735	CASO AGAR (MERCK 105458) (DSMZ Medium 220)	Medium recipe at MediaDive	Name: CASO AGAR (Merck 105458) (DSMZ Medium 220; with strain-specific modifications) Composition: Agar 15.0 g/l Casein peptone 15.0 g/l NaCl 5.0 g/l Soy peptone 5.0 g/l MnSO4 Distilled water
37892	MEDIUM 29- Brain heart agar		Distilled water make up to (1000.000 ml);Brain heart infusion agar (52.000 g)
122650	CIP Medium 29	Medium recipe at CIP

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
16735	positive	growth	30	mesophilic
37892	positive	growth	30	mesophilic
67770	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
122650	facultative anaerobe
125439	obligate aerobe	96.3

Spore formation

@ref	Spore formation	Confidence
125438		91.01
125439		93.7

Observation

67770

Observationquinones: MK-7

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
122650	17632 ChEBI	nitrate	-	reduction
122650	16301 ChEBI	nitrite	-	reduction

Metabolite production

@ref	Chebi-ID	Metabolite	Production
122650	35581 ChEBI	indole

Enzymes

@ref	Value	Activity	Ec
68382	acid phosphatase	+	3.1.3.2	from API zym
68382	alkaline phosphatase	+	3.1.3.1	from API zym
68382	alpha-chymotrypsin	+	3.4.21.1	from API zym
68382	alpha-fucosidase	-	3.2.1.51	from API zym
68382	alpha-galactosidase	-	3.2.1.22	from API zym
68382	alpha-glucosidase	+	3.2.1.20	from API zym
68382	alpha-mannosidase	-	3.2.1.24	from API zym
68382	beta-galactosidase	-	3.2.1.23	from API zym
68382	beta-glucosidase	+	3.2.1.21	from API zym
68382	beta-glucuronidase	-	3.2.1.31	from API zym
122650	catalase	+	1.11.1.6
68382	cystine arylamidase	-	3.4.11.3	from API zym
68382	esterase (C 4)	+		from API zym
68382	esterase lipase (C 8)	+		from API zym
68382	leucine arylamidase	+	3.4.11.1	from API zym
68382	lipase (C 14)	-		from API zym
68382	N-acetyl-beta-glucosaminidase	-	3.2.1.52	from API zym
68382	naphthol-AS-BI-phosphohydrolase	+		from API zym
122650	oxidase	+
68382	trypsin	+	3.4.21.4	from API zym
122650	urease	-	3.5.1.5
68382	valine arylamidase	-		from API zym

API zym

@ref	Control	Alkaline phosphatase	Esterase (C 4)	2-naphtyl caprylateEsterase Lipase (C 8)	Lipase (C 14)	L-leucyl-2-naphthylamideLeucine arylamidase	L-valyl-2-naphthylamideValine arylamidase	L-cystyl-2-naphthylamideCystine arylamidase	Trypsin	alpha- Chymotrypsin	Acid phosphatase	Naphthol-AS-BI-phosphateNaphthol-AS-BI-phosphohydrolase	alpha- Galactosidase	beta- Galactosidase	beta- Glucuronidase	alpha- Glucosidase	beta- Glucosidase	N-acetyl-beta- glucosaminidase	alpha- Mannosidase	alpha- Fucosidase
122650	-	+	+	+	-	+	-	-	+	+	+	+	-	-	-	+	+	-	-	-

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Food production	-
#Engineered	#Industrial	#Engineered product

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
16735	surface of soy sauce production equipment	Japan	JPN	Asia
67770	Surface of soy sauce production equipment	Japan	JPN	Asia
122650	Surface of equiment in food plant	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence AB473561 (>99% sequence identity) for Oceanobacillus sojae from Microbeatlas

Aquatic Samples	7
Soil Samples	16
Animal Samples	40
Plant Samples	42
Total Samples	105

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
16735	1	Risk group (German classification) According to TRBA 466
122650	1	Risk group (French 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	ASM799151v1 assembly for Oceanobacillus sojae NBRC 105379	contig	GCA_007991515	582851.8	8067345362	582851	52.77

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20218	Oceanobacillus sojae gene for 16S rRNA, partial sequence, strain: NBRC 105379	AB682253	1488		582851
16735	Oceanobacillus sojae gene for 16S ribosomal RNA, partial sequence	AB473561	1518		582851

GC content

@ref	GC-content (mol%)	Method
16735	38.0	high performance liquid chromatography (HPLC)
67770	38	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Oceanobacillus sojae NBRC 105379
NCBI: GCA_007991515

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	93.70	no
125439	motility	BacteriaNetⓘ	yes	89.80	no
125439	gram_stain	BacteriaNetⓘ	variable	83.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	96.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Oceanobacillus sojae strain NBRC 105379
PATRIC: 582851.8

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	79.95	no
125438	anaerobic	anaerobicⓘ	no	92.72	no
125438	spore-forming	spore-formingⓘ	yes	91.01	no
125438	aerobic	aerobicⓘ	yes	51.77	yes
125438	thermophilic	thermophileⓘ	no	95.71	yes
125438	flagellated	motile2+ⓘ	yes	84.92	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Oceanobacillus aidingensis sp. nov., a moderately halophilic bacterium.	Liu W, Yang SS	Antonie Van Leeuwenhoek	10.1007/s10482-014-0128-1	2014
Phylogeny	Oceanobacillus soja sp. nov. isolated from soy sauce production equipment in Japan.	Tominaga T, An SY, Oyaizu H, Yokota A	J Gen Appl Microbiol	10.2323/jgam.55.225	2009

References

#16735	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 23151
#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 )
#20218	Verslyppe, B., De Smet, W., De Baets, B., De Vos, P., Dawyndt P.: StrainInfo introduces electronic passports for microorganisms.. Syst Appl Microbiol. 37: 42 - 50 2014 ( DOI 10.1016/j.syapm.2013.11.002 , PubMed 24321274 )
#37892	; Curators of the CIP;
#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) .
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#68382	Automatically annotated from API zym .
#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 .
#122650	Collection of Institut Pasteur ; Curators of the CIP; CIP 109918
#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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Oceanobacillus sojae (DSM 23151, CIP 109918, JCM 15792)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Metabolite utilization

Metabolite production

Enzymes

API zym

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_007991515

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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