Brevibacillus parabrevis (DSM 8376, ATCC 10027, CIP 103840)

Name: Brevibacillus parabrevis (DSM 8376, ATCC 10027, CIP 103840)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 11415

Type strain

Culture col. no. DSM 8376 ATCC 10027 CIP 103840 IFO 12334 JCM 8506 7 more

NCBI tax ID(s) 54914

Special Collections DSMZ JCM CIP

Links

Brevibacillus parabrevis DSM 8376 is a mesophilic prokaryote of the family Paenibacillaceae.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 8370

LMG 15971,ATCC 10027,CIP 103840,DSM 8376,IFO 12334,JCM 8506,NCIMB 13346,NRRL NRS-605,NBRC 12334,KCTC 3833,BCRC 15922,CCRC 15922,KACC 10926,VTT E-981069

@ref 20215

Last LPSN update 2025-12-16 09:49:35

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Paenibacillaceae

Genus Brevibacillus

Species Brevibacillus parabrevis

Full scientific name Brevibacillus parabrevis (Takagi et al. 1993) Shida et al. 1996

Synonyms (1)

Bacillus parabrevis

BacDive ID	Other strains from **Brevibacillus parabrevis** (9)	Type strain
11410	B. parabrevis BG, DSM 362, ATCC 8185, CCM 1089, IAM 1031, ...
11411	B. parabrevis Gibson 108, DSM 370, CCM 1463, IFO 12374, ...
11412	B. parabrevis Oka, 779, DSM 5550, ATCC 8186, CIP 110335, ...
11413	B. parabrevis LBa, DSM 5608, NRS 781
11414	B. parabrevis TC, DSM 5618, NRS 780
145077	B. parabrevis CCUG 27608, LMG 15101
145840	B. parabrevis CCUG 29760
156102	B. parabrevis CCUG 60383
156965	B. parabrevis CCUG 67681 Q

Morphology

Cell morphology

@ref	Motility	Confidence
125439		90.2

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
3274	NUTRIENT AGAR (DSMZ Medium 1)	Medium recipe at MediaDive	Name: NUTRIENT AGAR (DSMZ Medium 1; with strain-specific modifications) Composition: Agar 15.0 g/l Peptone 5.0 g/l Meat extract 3.0 g/l Yeast extract 2.0 g/l Distilled water
37952	MEDIUM 3 - Columbia agar		Columbia agar (39.000 g);distilled water (1000.000 ml)
121540	CIP Medium 3	Medium recipe at CIP

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
3274	positive	growth	30	mesophilic
37952	positive	growth	30	mesophilic
67770	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	91.2

Spore formation

@ref	Spore formation	Confidence
125439		93.1
125438		90.161

Observation

67770

Observationquinones: MK-7

Isolation, sampling and environmental information

Taxonmaps

69479

Global distribution of 16S sequence D78463 (>99% sequence identity) for Brevibacillus from Microbeatlas

Aquatic Samples	479
Soil Samples	119
Animal Samples	42
Plant Samples	13
Total Samples	653

Interaction and safety

Risk assessment

@ref	Pathogenicity human	Biosafety level	Biosafety level comment
3274	yes, in single cases	1	Risk group (German classification) According to TRBA 466
121540		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
67770	ASM371090v1 assembly for Brevibacillus parabrevis NRRL NRS 605	contig	GCA_003710905	54914.7	2854269921	54914	63.35
124043	ASM5047646v1 assembly for Brevibacillus parabrevis NRS-605	contig	GCA_050476465			54914	56.09
67770	ASM653906v1 assembly for Brevibacillus parabrevis NBRC 12334	contig	GCA_006539065	54914.8	8116496750	54914	48.26

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
20218	Brevibacillus parabrevis gene for 16S rRNA, partial sequence	AB006943	263	54914
20218	Brevibacillus parabrevis gene for 16S rRNA, partial sequence, strain:IFO 12334T	AB112714	1486	54914
20218	Brevibacillus parabrevis DNA for 16S ribosomal RNA	D78463	1419	54914
20218	Brevibacillus parabrevis gene for 16S rRNA, partial sequence, strain: NBRC 12334	AB680274	1461	54914
124043	Brevibacillus parabrevis strain IFO 12334 16S ribosomal RNA gene, partial sequence.	OQ874668	758	54914
124043	Brevibacillus parabrevis strain NBRC 12334 16S ribosomal RNA gene, partial sequence.	MG645254	783	54914

GC content

@ref	GC-content (mol%)	Method
3274	51.8	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: Brevibacillus parabrevis NBRC 12334
NCBI: GCA_006539065

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	93.10	no
125439	motility	BacteriaNetⓘ	yes	90.20	no
125439	gram_stain	BacteriaNetⓘ	variable	85.90	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	91.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Brevibacillus parabrevis strain NBRC 12334
PATRIC: 54914.8

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	56.77	no
125438	anaerobic	anaerobicⓘ	no	97.79	no
125438	spore-forming	spore-formingⓘ	yes	90.16	no
125438	aerobic	aerobicⓘ	yes	76.10	no
125438	thermophilic	thermophileⓘ	no	93.28	no
125438	flagellated	motile2+ⓘ	yes	84.55	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Investigation of the potential of Brevibacillus spp. for the biosynthesis of nonribosomally produced bioactive compounds by combination of genome mining with MALDI-TOF mass spectrometry.	Jahne J, Herfort S, Doellinger J, Lasch P, Tam LTT, Borriss R, Vater J.	Front Microbiol	10.3389/fmicb.2023.1286565	2023
	Phylogenetically diverse bacteria isolated from tattoo inks, an azo dye-rich environment, decolorize a wide range of azo dyes.	Nho SW, Cui X, Kweon O, Jin J, Chen H, Moon MS, Kim SJ, Cerniglia CE.	Ann Microbiol	10.1186/s13213-021-01648-2	2021
Phylogeny	Brevibacillus gelatini sp. nov., isolated from a hot spring.	Inan K, Ozer A, Ibrahim Guler H, Osman Belduz A, Canakci S	Int J Syst Evol Microbiol	10.1099/ijsem.0.000780	2015

References

#3274	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 8376
#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 )
#37952	; Curators of the CIP;
#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 .
#121540	Collection of Institut Pasteur ; Curators of the CIP; CIP 103840
#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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Brevibacillus parabrevis (DSM 8376, ATCC 10027, CIP 103840)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Isolation, sampling and environmental information

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_003710905

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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