Paenibacillus sp. (DSM 28492, 1-49)

Name: Paenibacillus sp. (DSM 28492, 1-49)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 169425

Type strain

Strain Designation 1-49

Culture col. no. DSM 28492 1-49

NCBI tax ID(s) 58172

Special Collections DSMZ

History <- J. Xie, China Agric. Univ., Beijing; 1-49 <- L. Wang

Links

1-49 is a bacterium that was isolated from rhizosphere soil.

16S sequence Bacteria

Name and taxonomic classification

SI-ID 402215

DSM 28492

@ref 20215

Last LPSN update 2026-02-09 11:41:02

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Paenibacillaceae

Genus Paenibacillus

Full scientific name Paenibacillus Ash et al. 1994

Synonyms (1)

"Aerobacillus"

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
68706	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)
68706	positive	growth	30

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125438		90.813

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
68706	rhizosphere soil	Shanxi, Jingle (111° 93' E 38° 37'N)	China	CHN	Asia	38.6167	112.55 38.6167/112.55

Interaction and safety

Sequence information

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
68706	Paenibacillus maysiensis 16S ribosomal RNA gene, partial sequence	JN873138.2	1480		1155954

GC content

68706

GC-content (mol%)46.44

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Paenibacillus sp. 1-49
PATRIC: 1155954.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	71.70	no
125439	gram_stain	BacteriaNetⓘ	variable	81.60	no
125439	motility	BacteriaNetⓘ	yes	79.50	no
125439	spore_formation	BacteriaNetⓘ	yes	89.10	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Paenibacillus sp. 1-49
PATRIC: 1155954.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	63.75	no
125438	anaerobic	anaerobicⓘ	no	92.77	no
125438	spore-forming	spore-formingⓘ	yes	90.81	no
125438	aerobic	aerobicⓘ	no	66.06	no
125438	thermophilic	thermophileⓘ	no	94.71	yes
125438	flagellated	motile2+ⓘ	yes	87.62	no

Literature

Topic	Title	Authors	Journal	Year
Metabolism	Medium optimization for nitrogen fixer Paenibacillus sp. 1-49.	Deng Z, Chen H, Chen S	Wei Sheng Wu Xue Bao	2016

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 )
#68706	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 28492
#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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Paenibacillus sp. (DSM 28492, 1-49)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Isolation

Interaction and safety

Sequence information

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

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