Paradevosia tibetensis (CGMCC 1.12719, JCM 19854)

Name: Paradevosia tibetensis (CGMCC 1.12719, JCM 19854)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 162634

Type strain

Culture col. no. CGMCC 1.12719 JCM 19854

NCBI tax ID(s) 1447062

Special Collections JCM

History JCM <-- J. Lv F4.

Links

Paradevosia tibetensis JCM 19854 is a bacterium that was isolated from Subsurface sediment core of Qiangtang Basin permafrost.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 27970

JCM 19854

@ref 20215

Last LPSN update 2026-05-29 08:44:59

Domain Bacteria

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Hyphomicrobiales

Family Devosiaceae

Genus Paradevosia

Species Paradevosia tibetensis

Full scientific name Paradevosia tibetensis (Wang et al. 2015) Li 2025

Synonyms (1)

Youhaiella tibetensis

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	96

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		96.778

Observation

67770

Observationquinones: Q-10

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Subsurface sediment core of Qiangtang Basin permafrost	China	CHN	Asia

Taxonmaps

69479

Global distribution of 16S sequence KF740588 (>99% sequence identity) for Hyphomicrobiaceae from Microbeatlas

Aquatic Samples	1574
Soil Samples	2214
Animal Samples	620
Plant Samples	659
Total Samples	5067

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM800075v1 assembly for Paradevosia tibetensis fig4	complete	GCA_008000755	1447062.3	2883300558	1447062	97.78
66792	ASM1463856v1 assembly for Paradevosia tibetensis CGMCC 1.12719	contig	GCA_014638565	1447062.4	8062289101	1447062	77.83

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Youhaiella tibetensis strain fig4 16S ribosomal RNA gene, partial sequence	KF740588	1447		1447062

GC content

@ref	GC-content (mol%)	Method
67770	60.7	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: ASM800075v1 assembly for Paradevosia tibetensis fig4
BV-BRC: 1447062.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	86.09	no
125439	gram_stain	BacteriaNetⓘ	negative	74.14	no
125439	motility	BacteriaNetⓘ	yes	50.09	no
125439	spore_formation	BacteriaNetⓘ	no	96.78	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Youhaiella tibetensis strain fig4
PATRIC: 1447062.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	96.00	no
125438	anaerobic	anaerobicⓘ	no	96.44	no
125438	spore-forming	spore-formingⓘ	no	86.19	no
125438	aerobic	aerobicⓘ	yes	86.21	no
125438	thermophilic	thermophileⓘ	no	97.08	yes
125438	flagellated	motile2+ⓘ	yes	62.85	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Complete Genome Sequence of Potential Deoxynivalenol-Degrading Bacterium Youhaiella tibetensis Type Strain F4.	Wang Y, Wang S.	Microbiol Resour Announc	10.1128/mra.00984-19	2019
Phylogeny	Youhaiella tibetensis gen. nov., sp. nov., isolated from subsurface sediment.	Wang YX, Huang FQ, Nogi Y, Pang SJ, Wang PK, Lv J	Int J Syst Evol Microbiol	10.1099/ijs.0.000219	2015

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 )
#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) .
#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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Paradevosia tibetensis (CGMCC 1.12719, JCM 19854)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Spore formation

Observation

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_008000755

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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