Celeribacter ethanolicus (CGMCC 1.15406, JCM 31095)

Name: Celeribacter ethanolicus (CGMCC 1.15406, JCM 31095)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 163946

Type strain

Culture col. no. CGMCC 1.15406 JCM 31095

NCBI tax ID(s) 1758178

Special Collections JCM

History Y. Wu; Second Inst. of Oceanogr., State Oceanic Admin., China; NH195.

Links

Celeribacter ethanolicus JCM 31095 is a bacterium that was isolated from Seawater of the South China Sea.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 132994

JCM 31095

@ref 20215

Last LPSN update 2026-02-09 11:39:44

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Rhodobacterales

Family Roseobacteraceae

Genus Celeribacter

Species Celeribacter ethanolicus

Full scientific name Celeribacter ethanolicus Jian et al. 2016

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	96.1
125438	negative	97.8

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	37

Physiology and metabolism

Spore formation

@ref	Spore formation	Confidence
125439		94.5
125438		90.641

Observation

67770

Observationquinones: Q-10

Isolation, sampling and environmental information

Isolation

67770

Sample typeSeawater of the South China Sea

Taxonmaps

69479

Global distribution of 16S sequence KT852989 (>99% sequence identity) for Celeribacter ethanolicus from Microbeatlas

Aquatic Samples	198
Soil Samples	3
Animal Samples	8
Plant Samples
Total Samples	209

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM155009v1 assembly for Celeribacter ethanolicus NH195	scaffold	GCA_001550095	1758178.3	2728369167	1758178	64.48

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Celeribacter ethanolicus strain NH195 16S ribosomal RNA gene, partial sequence	KT852989	1455		1758178

GC content

@ref	GC-content (mol%)	Method
67770	61.3	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Celeribacter ethanolicus NH195
NCBI: GCA_001550095

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	94.50	no
125439	motility	BacteriaNetⓘ	yes	66.50	no
125439	gram_stain	BacteriaNetⓘ	negative	96.10	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	83.20	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Celeribacter ethanolicus NH195
NCBI: GCA_001550095.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.80	no
125438	anaerobic	anaerobicⓘ	no	93.50	no
125438	aerobic	aerobicⓘ	yes	82.28	no
125438	spore-forming	spore-formingⓘ	no	90.64	no
125438	thermophilic	thermophileⓘ	no	95.96	no
125438	flagellated	motile2+ⓘ	no	55.12	no

Literature

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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