Peribacillus butanolivorans (DSM 102576, Leaf13)

Name: Peribacillus butanolivorans (DSM 102576, Leaf13)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 131648

Type strain

Strain Designation Leaf13

Culture col. no. DSM 102576 Leaf13

NCBI tax ID(s) 421767

Special Collections DSMZ Arabidopsis

History DSMZ <- J. A. Vorholt, Institute of Microbiology, ETH Zurich, Switzerland; Leaf13 <- D. B. Müller, E. Potthoff and M. Remus-Emsermann

Peribacillus butanolivorans Leaf13 is a bacterium that was isolated from leaf of Arabidopsis thaliana, wild-type genotype.

genome sequence Bacteria

Name and taxonomic classification

Culture Collection Numbers

DSM 102576 Leaf13

@ref 20215

Last LPSN update 2026-05-29 08:37:40

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Bacillaceae

Genus Peribacillus

Species Peribacillus butanolivorans

Full scientific name Peribacillus butanolivorans (Kuisiene et al. 2008) Patel and Gupta 2020

Synonyms (1)

Bacillus butanolivorans

BacDive ID	Other strains from **Peribacillus butanolivorans** (3)	Type strain
1271	P. butanolivorans K9, DSM 18926, LMG 23974 (type strain)
131651	P. butanolivorans Soil768D1, DSM 102773
163656	P. butanolivorans JCM 28850

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
23444	CASO AGAR (MERCK 105458) (DSMZ Medium 220)		Medium recipe at MediaDive	Name: CASO AGAR (Merck 105458) (DSMZ Medium 220) Composition: Agar 15.0 g/l Casein peptone 15.0 g/l NaCl 5.0 g/l Soy peptone 5.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
23444	positive	growth	30

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	facultative anaerobe	94.296

Spore formation

@ref	Spore formation	Confidence
125438		93.549
125439		90.134

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Plants	#Herbaceous plants (Grass,Crops)
#Host Body-Site	#Plant	#Leaf (Phyllosphere)

Isolation

@ref	Sample type	Host species	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
23444	leaf of Arabidopsis thaliana, wild-type genotype	Arabidopsis thaliana	Tuebingen Farm (48.5560194N 9.134944444E)	Germany	DEU	Europe	48.556	9.1349 48.556/9.1349

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	Leaf13 assembly for Bacillus sp. Leaf13	scaffold	GCA_001426005	1736211.3	2643221949	1736211	31.44

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Leaf13 assembly for Bacillus sp. Leaf13
BV-BRC: 1736211.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	94.30	no
125439	motility	BacteriaNetⓘ	yes	82.41	no
125439	gram_stain	BacteriaNetⓘ	variable	67.30	no
125439	spore_formation	BacteriaNetⓘ	yes	90.13	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Bacillus sp. Leaf13 Leaf13
NCBI: GCA_001426005.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	76.89	no
125438	anaerobic	anaerobicⓘ	no	95.37	no
125438	aerobic	aerobicⓘ	yes	77.00	no
125438	spore-forming	spore-formingⓘ	yes	93.55	no
125438	thermophilic	thermophileⓘ	no	94.66	yes
125438	flagellated	motile2+ⓘ	yes	81.32	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 )
#23444	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 102576
#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) .
#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 .

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