Paenibacillus yonginensis (KCTC 33428, JCM 19885)

Name: Paenibacillus yonginensis (KCTC 33428, JCM 19885)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 162650

Type strain

Culture col. no. KCTC 33428 JCM 19885

NCBI tax ID(s) 1462996

Special Collections JCM KCTC

History D.-C. Yang and Y.-J. Kim DCY84.

Links

Paenibacillus yonginensis JCM 19885 is a bacterium that was isolated from Humus soil of Yongin forest.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 391073

JCM 19885

@ref 20215

Last LPSN update 2026-02-09 11:39:27

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Paenibacillaceae

Genus Paenibacillus

Species Paenibacillus yonginensis

Full scientific name Paenibacillus yonginensis Sukweenadhi et al. 2016

Morphology

Cell morphology

@ref	Motility	Confidence
125439		93

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	28

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125438		93.224
125439		96.7

Observation

67770

Observationquinones: MK-7

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
67770	Humus soil of Yongin forest	Gyeonggi Province	Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence KF915796 (>99% sequence identity) for Paenibacillus yonginensis subclade from Microbeatlas

Aquatic Samples	6
Soil Samples	9
Animal Samples	17
Plant Samples	4
Total Samples	36

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM168539v1 assembly for Paenibacillus yonginensis DCY84	complete	GCA_001685395	1462996.4	2751185904	1462996	98.22

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Paenibacillus yonginensis strain DCY84 16S ribosomal RNA gene, partial sequence	KF915796	1474		1462996

GC content

@ref	GC-content (mol%)	Method
67770	62.6	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: Paenibacillus sp. DCY84
PATRIC: 1462996.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	96.70	no
125439	motility	BacteriaNetⓘ	yes	93.00	no
125439	gram_stain	BacteriaNetⓘ	variable	82.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	88.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Paenibacillus sp. DCY84
PATRIC: 1462996.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	69.13	no
125438	anaerobic	anaerobicⓘ	no	94.81	no
125438	spore-forming	spore-formingⓘ	yes	93.22	no
125438	aerobic	aerobicⓘ	no	59.30	no
125438	thermophilic	thermophileⓘ	no	91.33	yes
125438	flagellated	motile2+ⓘ	yes	81.74	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Metabolism	Improvement of Euglena gracilis Paramylon Production through a Cocultivation Strategy with the Indole-3-Acetic Acid-Producing Bacterium Vibrio natriegens.	Kim JY, Oh JJ, Jeon MS, Kim GH, Choi YE.	Appl Environ Microbiol	10.1128/aem.01548-19	2019
Genetics	Complete genome sequence of Paenibacillus yonginensis DCY84(T), a novel plant Symbiont that promotes growth via induced systemic resistance.	Kim YJ, Sukweenadhi J, Seok JW, Kang CH, Choi ES, Subramaniyam S, Yang DC	Stand Genomic Sci	10.1186/s40793-017-0277-8	2017
Phylogeny	Paenibacillus yonginensis sp. nov., a potential plant growth promoting bacterium isolated from humus soil of Yongin forest.	Sukweenadhi J, Kim YJ, Lee KJ, Koh SC, Hoang VA, Nguyen NL, Yang DC	Antonie Van Leeuwenhoek	10.1007/s10482-014-0263-8	2014
Phylogeny	Paenibacillus mobilis sp. nov., a Gram-stain-negative bacterium isolated from soil.	Yang D, Cha S, Choi J, Seo T	Int J Syst Evol Microbiol	10.1099/ijsem.0.002643	2018

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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Paenibacillus yonginensis (KCTC 33428, JCM 19885)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Spore formation

Observation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_001685395

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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