Alishewanella aestuarii (DSM 19476, KCTC 22051, B11)

Name: Alishewanella aestuarii (DSM 19476, KCTC 22051, B11)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 441

Type strain

Strain Designation B11

Culture col. no. DSM 19476 KCTC 22051 B11

NCBI tax ID(s) 453835

Special Collections DSMZ KCTC Literature strains

History <- S. W. Roh, Korea Res. Inst. Biosci. & Biotechnol. (KRIBB), Taejon, South Korea; B11 <- SW Roh, KRIBB

Links

Alishewanella aestuarii B11 is an aerobe, mesophilic, Gram-negative prokaryote that was isolated from tidal flat sediment.

Gram-negative motile rod-shaped aerobe mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 360704

DSM 19476,KCTC 22051,LMG 26132

@ref 20215

Last LPSN update 2026-02-09 11:17:52

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Chromatiales

Family Chromatiaceae

Genus Alishewanella

Species Alishewanella aestuarii

Full scientific name Alishewanella aestuarii Roh et al. 2009

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Confidence
32532	negative	rod-shaped
67771	negative
125438	negative		98.5
125439	negative		98.7

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
8108	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)	Range
8108	positive	growth	28	mesophilic
32532	positive	growth	18-44
32532	positive	optimum	37	mesophilic
67771	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
67771	aerobe
125439	aerobe	95.2

Spore formation

@ref	Spore formation	Confidence
125439		98.2

Halophily

@ref	Salt	Growth	Tested relation	Concentration
32532	NaCl	positive	growth	<5 %
32532	NaCl	positive	optimum	5 %

Observation

32532

Observationaggregates in clumps

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
32532	17306 ChEBI	maltose	+	carbon source
32532	17632 ChEBI	nitrate	+	reduction

Enzymes

@ref	Value	Activity	Ec
32532	acid phosphatase	+	3.1.3.2
32532	alkaline phosphatase	+	3.1.3.1
32532	catalase	+	1.11.1.6
32532	cytochrome oxidase	+	1.9.3.1
32532	gelatinase	+

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Tidal flat
#Environmental	#Terrestrial	#Sediment

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
8108	tidal flat sediment	Yeosu	Republic of Korea	KOR	Asia
67771	From flat tidal		Republic of Korea	KOR	Asia

Taxonmaps

69479

Global distribution of 16S sequence EF660759 (>99% sequence identity) for Alishewanella from Microbeatlas

Aquatic Samples	585
Soil Samples	58
Animal Samples	351
Plant Samples	31
Total Samples	1025

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
8108	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM28005v1 assembly for Alishewanella aestuarii B11	contig	GCA_000280055	1197174.4	2531839095	1197174	70.44

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
8108	Alishewanella aestuarii B11 16S ribosomal RNA gene, partial sequence	EF660759	1358		1197174

GC content

32532

GC-content (mol%)49.5

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Alishewanella aestuarii B11
NCBI: GCA_000280055

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	95.20	no
125439	gram_stain	BacteriaNetⓘ	negative	98.70	no
125439	motility	BacteriaNetⓘ	yes	84.10	no
125439	spore_formation	BacteriaNetⓘ	no	98.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Alishewanella aestuarii B11
PATRIC: 1197174.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	98.50	yes
125438	anaerobic	anaerobicⓘ	no	92.61	no
125438	spore-forming	spore-formingⓘ	no	89.83	no
125438	aerobic	aerobicⓘ	yes	73.41	no
125438	thermophilic	thermophileⓘ	no	97.47	no
125438	flagellated	motile2+ⓘ	yes	88.30	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Genome sequence of pectin-degrading Alishewanella aestuarii strain B11(T), isolated from tidal flat sediment.	Jung J, Choi S, Chun J, Park W	J Bacteriol	10.1128/JB.01255-12	2012
Phylogeny	Alishewanella aestuarii sp. nov., isolated from tidal flat sediment, and emended description of the genus Alishewanella.	Roh SW, Nam YD, Chang HW, Kim KH, Kim MS, Oh HM, Bae JW	Int J Syst Evol Microbiol	10.1099/ijs.0.65643-0	2009

References

#8108	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 19476
#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 )
#28750	IJSEM 421 2009 ( DOI 10.1099/ijs.0.65643-0 , PubMed 19196789 )
#32532	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 #28750
#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) .
#67771	Korean Collection for Type Cultures (KCTC) ; Curators of the KCTC;
#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 )

Rate our new design

Content

About us

Alishewanella aestuarii (DSM 19476, KCTC 22051, B11)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Observation

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_000280055

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

BacDive

Help

Social Media