Aliidiomarina maris (DSM 22154, CCTCC AB 208166, KACC 13974)

Name: Aliidiomarina maris (DSM 22154, CCTCC AB 208166, KACC 13974)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 6238

Type strain

Strain Designation CF12-14

Culture col. no. DSM 22154 CCTCC AB 208166 KACC 13974 CF12-14

NCBI tax ID(s) 531312

Special Collections DSMZ Literature strains

History DSMZ <- X. Zhang, State Key Lab. Microbial Technol., Marine Biotechnol. Res. Center, Shandong Univ., Jinan, China; CF12-14 <- M. Zhou and Y. Zhang

Links

Aliidiomarina maris CF12-14 is an aerobe, Gram-negative, motile bacterium that was isolated from deep-sea sediment at a water depth of 1153 m.

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

Name and taxonomic classification

SI-ID 398545

DSM 22154

@ref 20215

Last LPSN update 2026-05-29 08:26:21

Domain Bacteria

Phylum Pseudomonadota

Class Gammaproteobacteria

Order Alteromonadales

Family Idiomarinaceae

Genus Aliidiomarina

Species Aliidiomarina maris

Full scientific name Aliidiomarina maris (Zhang et al. 2012) Chiu et al. 2014

Synonyms (1)

Idiomarina maris

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Motility	Confidence
29985	negative	0.8-2.4 µm	0.3-0.6 µm	rod-shaped
125438	negative					99.994

Pigmentation

29985

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
16170	BACTO MARINE BROTH (DIFCO 2216) (DSMZ Medium 514)		Medium recipe at MediaDive	Name: BACTO MARINE BROTH (DIFCO 2216) (DSMZ Medium 514) Composition: NaCl 19.45 g/l MgCl2 5.9 g/l Bacto peptone 5.0 g/l Na2SO4 3.24 g/l CaCl2 1.8 g/l Yeast extract 1.0 g/l KCl 0.55 g/l NaHCO3 0.16 g/l Fe(III) citrate 0.1 g/l KBr 0.08 g/l SrCl2 0.034 g/l H3BO3 0.022 g/l Na2HPO4 0.008 g/l Na-silicate 0.004 g/l NaF 0.0024 g/l (NH4)NO3 0.0016 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
16170	positive	growth	28
29985	positive	growth	25-40
29985	positive	optimum	30-35

Culture pH

@ref	Ability	Type	PH	PH range
29985	positive	optimum	8.0-9.5
29985	positive	growth	6.0-11.5	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
29985	aerobe
125439	obligate aerobe	97.14

Spore formation

@ref	Spore formation	Confidence
29985
125439		93.516

Halophily

@ref	Salt	Growth	Tested relation	Concentration
29985	NaCl	positive	growth	0.1-15.0 %
29985	NaCl	positive	optimum	2-3 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
29985	25017 ChEBI	leucine	+	carbon source
29985	17632 ChEBI	nitrate	+	reduction
29985	53423 ChEBI	tween 40	+	carbon source

Enzymes

@ref	Value	Activity	Ec
29985	acid phosphatase	+	3.1.3.2
29985	alkaline phosphatase	+	3.1.3.1
29985	gelatinase	+

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Aquatic	#Marine
#Environmental	#Aquatic	#Sediment

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
16170	deep-sea sediment at a water depth of 1153 m	South China Sea (19° 44.94' N, 114° 44.95' E)	China	CHN	Asia	19.749	114.749 19.749/114.749

Taxonmaps

69479

Global distribution of 16S sequence EU723884 (>99% sequence identity) for Aliidiomarina maris from Microbeatlas

Aquatic Samples	156
Soil Samples	30
Animal Samples	223
Plant Samples	11
Total Samples	420

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
16170	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
66792	ASM398733v1 assembly for Aliidiomarina maris CF12-14	contig	GCA_003987335	531312.4	531312	67.27

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
16170	Idiomarina maris strain CF12-14 16S ribosomal RNA gene, partial sequence	EU723884	1502		531312

GC content

@ref	GC-content (mol%)	Method
16170	50.4	high performance liquid chromatography (HPLC)
29985	50.4

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM398733v1 assembly for Aliidiomarina maris CF12-14
NCBI: GCA_003987335

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	97.14	no
125439	gram_stain	BacteriaNetⓘ	negative	70.47	no
125439	motility	BacteriaNetⓘ	yes	60.44	no
125439	spore_formation	BacteriaNetⓘ	no	93.52	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Aliidiomarina maris CF12-14
NCBI: GCA_003987335.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	99.99	no
125438	anaerobic	anaerobicⓘ	no	93.60	no
125438	aerobic	aerobicⓘ	yes	77.95	yes
125438	spore-forming	spore-formingⓘ	no	89.86	yes
125438	thermophilic	thermophileⓘ	no	96.98	no
125438	flagellated	motile2+ⓘ	yes	79.83	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Aliidiomarina soli sp. nov., isolated from saline-alkaline soil.	Xu L, Sun JQ, Wang LJ, Liu XZ, Ji YY, Shao ZQ, Wu XL	Int J Syst Evol Microbiol	10.1099/ijsem.0.001709	2017
Phylogeny	Idiomarina maris sp. nov., a marine bacterium isolated from sediment.	Zhang YJ, Zhang XY, Zhao HL, Zhou MY, Li HJ, Gao ZM, Chen XL, Dang HY, Zhang YZ	Int J Syst Evol Microbiol	10.1099/ijs.0.027896-0	2011

References

#16170	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 22154
#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 )
#26352	IJSEM 370 2012 ( DOI 10.1099/ijs.0.027896-0 , PubMed 21441375 )
#29985	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 #26352
#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 .
#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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Aliidiomarina maris (DSM 22154, CCTCC AB 208166, KACC 13974)

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_003987335

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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