Belliella kenyensis (DSM 46651, CECT 8551, No.164)

Name: Belliella kenyensis (DSM 46651, CECT 8551, No.164)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 132193

Type strain

Strain Designation No.164

Culture col. no. DSM 46651 CECT 8551 No.164 UCCCB125

NCBI tax ID(s) 1472724

Special Collections DSMZ UCCCB

History <- J. K. Akhwale, Jomo Kenyatta Univ. of Agriculture and Technol., Nairobi, Kenya; No.164 J. K. Akhwale, Jomo Kenyatta Univ. of Agriculture and Technol., Nairobi, Kenya; No.164

Links

Belliella kenyensis No.164 is a bacterium that was isolated from soda lake sediment.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 397334

CECT 8551,DSM 46651

@ref 20215

Last LPSN update 2026-02-09 11:31:39

Domain Bacteria

Phylum Bacteroidota

Class Cytophagia

Order Cytophagales

Family Cyclobacteriaceae

Genus Belliella

Species Belliella kenyensis

Full scientific name Belliella kenyensis Akhwale et al. 2015

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	98.8
125438	negative	97.489

Multimedia

@ref:	23982
multimedia content:	DSM_46651.jpg
multimedia.multimedia content:	https://www.dsmz.de/microorganisms/photos/DSM_46651.jpg
caption:	Medium 830 28°C
intellectual property rights:	© Leibniz-Institut DSMZ
manual_annotation:	1

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
23982	R2A MEDIUM (DSMZ Medium 830)		Medium recipe at MediaDive	Name: R2A MEDIUM (DSMZ Medium 830) Composition: Agar 15.0 g/l Casamino acids 0.5 g/l Starch 0.5 g/l Glucose 0.5 g/l Proteose peptone 0.5 g/l Yeast extract 0.5 g/l K2HPO4 0.3 g/l Na-pyruvate 0.3 g/l MgSO4 x 7 H2O 0.05 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
23982	positive	growth	28
67772	positive	optimum	30-35

Culture pH

@ref	Ability	Type	PH	PH range
67772	positive	maximum	10.0	alkaliphile
67772	positive	minimum	8.0

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		98.8

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Lake (large)
#Environmental	#Aquatic	#Sediment
#Condition	#Alkaline	-

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude	Sampling date
23982	soda lake sediment	Kenyan Rift Valley, Lake Elmenteita (0° 27' S 36° 15' E at 1776 m above sea level)	Kenya	KEN	Africa	-0.45	36.25 -0.45/36.25
67772	Soda lake sediment		Kenya	KEN	Africa	-0.45	36.25 -0.45/36.25	2013

Taxonmaps

69479

Global distribution of 16S sequence KF976732 (>99% sequence identity) for Belliella from Microbeatlas

Aquatic Samples	7
Soil Samples	3
Animal Samples	2
Plant Samples	1
Total Samples	13

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
23982	1	Risk group (German classification)
67772	1

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
124043	ASM3040949v1 assembly for Belliella kenyensis CECT 8551	contig	GCA_030409495	1472724.5	8053375054	1472724	75.36
66792	ASM2254967v1 assembly for Belliella kenyensis DSM 46651	scaffold	GCA_022549675	1472724.3	8118435204	1472724	64.63
124043	ASM4265034v1 assembly for Belliella kenyensis CECT 8551	contig	GCA_042650345			1472724	59.37

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
23982	Belliella kenyensis strain No. 164 16S ribosomal RNA gene, partial sequence	KF976732	1451		1472724
124043	Belliella kenyensis strain CECT 8551 16S ribosomal RNA gene, partial sequence.	MT760302	1332		1472724

GC content

@ref	GC-content (mol%)	Method
23982	38.1	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: Belliella kenyensis DSM 46651
NCBI: GCA_022549675

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	98.80	no
125439	motility	BacteriaNetⓘ	no	75.10	no
125439	gram_stain	BacteriaNetⓘ	negative	98.80	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	78.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Belliella kenyensis DSM 46651
NCBI: GCA_022549675.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.49	no
125438	anaerobic	anaerobicⓘ	no	94.70	no
125438	aerobic	aerobicⓘ	yes	85.86	no
125438	spore-forming	spore-formingⓘ	no	89.94	no
125438	thermophilic	thermophileⓘ	no	95.51	yes
125438	flagellated	motile2+ⓘ	no	89.00	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Belliella aquatica sp. nov., isolated from a saline lake.	Zhong ZP, Liu Y, Hou TT, Zhou YG, Liu HC, Liu ZP	Int J Syst Evol Microbiol	10.1099/ijs.0.000148	2015
Phylogeny	Belliella kenyensis sp. nov., isolated from an alkaline lake.	Akhwale JK, Goker M, Rohde M, Schumann P, Klenk HP, Boga HI	Int J Syst Evol Microbiol	10.1099/ijs.0.066951-0	2014

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 )
#23982	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 46651
#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) .
#67772	The University of Coimbra Bacteria Culture Collection (UCCCB) ; Curators of the UCCCB;
#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 .
#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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Belliella kenyensis (DSM 46651, CECT 8551, No.164)

Name and taxonomic classification

Morphology

Cell morphology

Multimedia

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Spore formation

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_030409495

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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