Novosphingobium aquimarinum (KCTC 72894, JCM 33983)

Name: Novosphingobium aquimarinum (KCTC 72894, JCM 33983)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164702

Type strain

Culture col. no. KCTC 72894 JCM 33983

NCBI tax ID(s) 2682494

Special Collections JCM KCTC

History S.-R. Ko; KRIBB, South Korea; M24A2M.

Links

Novosphingobium aquimarinum JCM 33983 is a bacterium that was isolated from Seawater .

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 129324

JCM 33983,KCTC 72894

@ref 20215

Last LPSN update 2026-02-09 11:39:55

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Sphingomonadales

Family Erythrobacteraceae

Genus Novosphingobium

Species Novosphingobium aquimarinum

Full scientific name Novosphingobium aquimarinum Le et al. 2020

Synonyms (1)

Pseudonovosphingobium aquimarinum

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	99.4
125438	negative	94.262

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	25

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	99

Spore formation

@ref	Spore formation	Confidence
125439		97.9

Observation

67770

Observationquinones: Q-10

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Latitude	Longitude
67770	Seawater (34° 40' 44" N, 128° 23' 30" E)	34.6789	128.392 34.6789/128.392

Taxonmaps

69479

Global distribution of 16S sequence MN826708 (>99% sequence identity) for Novosphingobium from Microbeatlas

Aquatic Samples	22
Soil Samples	18
Animal Samples	3
Plant Samples
Total Samples	43

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM974658v1 assembly for Novosphingobium aquimarinum M24A2M	contig	GCA_009746585	2682494.3	2900148625	2682494	63.23

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Novosphingobium aquimarinum strain M24A2M 16S ribosomal RNA gene, partial sequence	MN826708	1353		1874826

GC content

@ref	GC-content (mol%)	Method
67770	63.9	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Novosphingobium aquimarinum M24A2M
NCBI: GCA_009746585

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	97.90	no
125439	motility	BacteriaNetⓘ	yes	58.50	no
125439	gram_stain	BacteriaNetⓘ	negative	99.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	99.00	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Novosphingobium aquimarinum M24A2M
NCBI: GCA_009746585.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.26	no
125438	anaerobic	anaerobicⓘ	no	93.27	no
125438	aerobic	aerobicⓘ	yes	88.64	no
125438	spore-forming	spore-formingⓘ	no	89.53	no
125438	thermophilic	thermophileⓘ	no	96.62	yes
125438	flagellated	motile2+ⓘ	yes	61.46	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Novosphingobium aquimarinum sp. nov., isolated from seawater.	Le VV, Ko SR, Lee SA, Jin L, Ahn CY, Oh HM	Int J Syst Evol Microbiol	10.1099/ijsem.0.004493	2020

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 )
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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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Novosphingobium aquimarinum (KCTC 72894, JCM 33983)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Oxygen tolerance

Spore formation

Observation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_009746585

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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