Elizabethkingia argenteiflava (YB22, JCM 32097, KCCM 43263)

Name: Elizabethkingia argenteiflava (YB22, JCM 32097, KCCM 43263)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 166656

Type strain

Strain Designation YB22

Culture col. no. YB22 JCM 32097 KCCM 43263

NCBI tax ID(s) 2681556

Special Collections JCM

Links

Elizabethkingia argenteiflava YB22 is a bacterium of the family Weeksellaceae.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 132496

JCM 32097

@ref 20215

Last LPSN update 2026-05-29 08:45:57

Domain Bacteria

Phylum Bacteroidota

Class Flavobacteriia

Order Flavobacteriales

Family Weeksellaceae

Genus Elizabethkingia

Species Elizabethkingia argenteiflava

Full scientific name Elizabethkingia argenteiflava Hwang et al. 2021

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	97.939
125438	negative	98.5
125438		94

Culture and growth conditions

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		99.783

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	BeanPod assembly for Elizabethkingia argenteiflava YB22	contig	GCA_009904105	2681556.3	2899542894	2681556	0

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20215	Elizabethkingia argenteiflava strain YB22 16S ribosomal RNA gene, partial sequence	KY510834	1439		2681556

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: BeanPod assembly for Elizabethkingia argenteiflava YB22
NCBI: GCA_009904105

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	motility	BacteriaNetⓘ	no	79.93	no
125439	gram_stain	BacteriaNetⓘ	negative	97.94	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	89.82	no
125439	spore_formation	BacteriaNetⓘ	no	99.78	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Elizabethkingia argenteiflava YB22
NCBI: GCA_009904105.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.50	no
125438	anaerobic	anaerobicⓘ	no	93.67	no
125438	aerobic	aerobicⓘ	yes	71.19	no
125438	spore-forming	spore-formingⓘ	no	88.99	no
125438	thermophilic	thermophileⓘ	no	97.50	no
125438	flagellated	motile2+ⓘ	no	94.00	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Elizabethkingia argenteiflava sp. nov., isolated from the pod of soybean, Glycine max.	Hwang JH, Kim J, Kim JH, Mo S	Int J Syst Evol Microbiol	10.1099/ijsem.0.004767	2021

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 )
#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 .
#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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Elizabethkingia argenteiflava (YB22, JCM 32097, KCCM 43263)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_009904105

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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