Cite this strain

"Defluviitalea phaphyphila" (CGMCC 1.5199, JCM 30481)

BacDive ID 163810

Type strain

Culture col. no. CGMCC 1.5199 JCM 30481

NCBI tax ID(s) 1473580

Special Collections JCM

History JCM <-- S. Ji; Qingdao Inst. of Bioenergy & Bioprocess Technol., CAS, China; Alg1.

Links

"Defluviitalea phaphyphila" JCM 30481 is a bacterium that was isolated from Coastal sediment of an amphioxus breeding zone in Qingdao.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 395631

JCM 30481

@ref 20215

Last LPSN update 2026-05-29 08:45:15

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Defluviitaleaceae

Genus Defluviitalea

Species "Defluviitalea phaphyphila"

Full scientific name Defluviitalea phaphyphila Ji et al. 2016

Morphology

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)
67770	positive	growth	55

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	anaerobe	97.865
125438	anaerobe	94.783

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Coastal sediment of an amphioxus breeding zone in Qingdao	China	CHN	Asia

Taxonmaps

69479

Global distribution of 16S sequence KJ411293 (>99% sequence identity) for Defluviitalea phaphyphila subclade from Microbeatlas

Aquatic Samples	22
Soil Samples	9
Animal Samples	33
Plant Samples	14
Total Samples	78

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM146630v1 assembly for Defluviitalea phaphyphila Alg1	scaffold	GCA_001466305	1473580.8	2791354880	1473580	57.17

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Defluviitalea phaphyphila strain Alg1 16S ribosomal RNA gene, partial sequence	KJ411293	1493		1473580

GC content

@ref	GC-content (mol%)	Method
67770	28	high performance liquid chromatography (HPLC)

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM146630v1 assembly for Defluviitalea phaphyphila Alg1
NCBI: GCA_001466305

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	97.87	no
125439	motility	BacteriaNetⓘ	yes	62.66	no
125439	gram_stain	BacteriaNetⓘ	positive	63.39	no
125439	spore_formation	BacteriaNetⓘ	yes	45.32	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Defluviitalea phaphyphila Alg1
NCBI: GCA_001466305.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	60.97	no
125438	anaerobic	anaerobicⓘ	yes	94.78	no
125438	aerobic	aerobicⓘ	no	97.74	no
125438	spore-forming	spore-formingⓘ	yes	59.97	no
125438	thermophilic	thermophileⓘ	yes	55.38	yes
125438	flagellated	motile2+ⓘ	yes	78.57	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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