Exiguobacterium alkaliphilum (DSM 21148, CCM 8459, 12/1)

Name: Exiguobacterium alkaliphilum (DSM 21148, CCM 8459, 12/1)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 24783

Type strain

Strain Designation 12/1

Culture col. no. DSM 21148 CCM 8459 12/1

NCBI tax ID(s) 1428684

Special Collections DSMZ Literature strains

History <- R. Kumar, Institute of Genomics and Integrative Biology, New Delhi, India; 12/1

Links

Exiguobacterium alkaliphilum 12/1 is a facultative anaerobe, mesophilic, Gram-positive prokaryote that was isolated from alkaline wastewater drainage sludge, beverage industry.

Gram-positive motile rod-shaped facultative anaerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 402287

DSM 21148

@ref 20215

Last LPSN update 2025-12-16 09:52:56

Domain Bacillati

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Bacillaceae

Genus Exiguobacterium

Species Exiguobacterium alkaliphilum

Full scientific name Exiguobacterium alkaliphilum Kulshreshtha et al. 2013

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Motility
30579	positive	2.5 µm	0.8 µm	rod-shaped

Pigmentation

30579

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
20560	TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)		Medium recipe at MediaDive	Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
20560	positive	growth	37	mesophilic
30579	positive	growth	05-40
30579	positive	optimum	35	mesophilic

Culture pH

@ref	Ability	Type	PH	PH range
30579	positive	optimum	9.5
30579	positive	growth	6.5-12	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
30579	facultative anaerobe
125439	aerobe	95.5

Spore formation

30579

Spore formationno

Halophily

@ref	Salt	Growth	Tested relation	Concentration
30579	NaCl	positive	growth	0-9.5 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
30579	28087 ChEBI	glycogen	+	carbon source
30579	506227 ChEBI	N-acetylglucosamine	+	carbon source
30579	30911 ChEBI	sorbitol	+	carbon source

Enzymes

@ref	Value	Activity	Ec
30579	catalase	+	1.11.1.6

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Food production	#Beverage
#Engineered	#Waste	#Industrial wastewater
#Environmental	#Terrestrial	#Mud (Sludge)
#Condition	#Alkaline	-

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
20560	alkaline wastewater drainage sludge, beverage industry	near New Delhi	India	IND	Asia

Taxonmaps

69479

Global distribution of 16S sequence EU379016 (>99% sequence identity) for Exiguobacterium from Microbeatlas

Aquatic Samples	2262
Soil Samples	574
Animal Samples	3194
Plant Samples	531
Total Samples	6561

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
20560	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	Exiguobacterium_alkaliphilum assembly for Exiguobacterium alkaliphilum 12/1	contig	GCA_000714435	506480.4	2585427936	506480	54.05
66792	ASM2523477v1 assembly for Exiguobacterium alkaliphilum 12_1	scaffold	GCA_025234775	1428684.7		1428684	50.61

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
20560	Exiguobacterium alkaliphilum 12/1 16S ribosomal RNA gene, partial sequence	EU379016	1477		506480
124043	Exiguobacterium alkaliphilum 12/1 strain CCM 8459 16S ribosomal RNA gene, partial sequence.	MT760204	1388		506480

GC content

@ref	GC-content (mol%)	Method
20560	56.6	high performance liquid chromatography (HPLC)
30579	56.6

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Exiguobacterium alkaliphilum 12_1
NCBI: GCA_025234775

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	83.60	no
125439	motility	BacteriaNetⓘ	yes	88.90	no
125439	gram_stain	BacteriaNetⓘ	variable	78.10	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	95.50	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Exiguobacterium alkaliphilum 12/1
PATRIC: 506480.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	76.24	yes
125438	anaerobic	anaerobicⓘ	no	96.19	yes
125438	spore-forming	spore-formingⓘ	no	51.51	no
125438	aerobic	aerobicⓘ	yes	60.84	no
125438	thermophilic	thermophileⓘ	no	97.19	yes
125438	flagellated	motile2+ⓘ	yes	77.02	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Exiguobacterium alkaliphilum sp. nov. isolated from alkaline wastewater drained sludge of a beverage factory.	Mohan Kulshreshtha N, Kumar R, Begum Z, Shivaji S, Kumar A	Int J Syst Evol Microbiol	10.1099/ijs.0.039123-0	2013

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 )
#20560	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 21148
#26910	IJSEM 4374 2013 ( DOI 10.1099/ijs.0.039123-0 , PubMed 23838447 )
#30579	Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #26910
#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) .
#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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Exiguobacterium alkaliphilum (DSM 21148, CCM 8459, 12/1)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Taxonmaps

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_000714435

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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