Qipengyuania sediminis (CGMCC 1.12928, JCM 30182)

Name: Qipengyuania sediminis (CGMCC 1.12928, JCM 30182)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 163731

Type strain

Culture col. no. CGMCC 1.12928 JCM 30182

NCBI tax ID(s) 1532023

Special Collections JCM

Links

Qipengyuania sediminis JCM 30182 is a mesophilic prokaryote that was isolated from Borehole sediment sample of Qiangtang Basin in Qinghai-Tibetan plateau.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 131881

JCM 30182

@ref 20215

Last LPSN update 2025-12-16 10:09:17

Domain Pseudomonadati

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Sphingomonadales

Family Erythrobacteraceae

Genus Qipengyuania

Species Qipengyuania sediminis

Full scientific name Qipengyuania sediminis Feng et al. 2015

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	negative	97.833
125439	negative	99.7

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	98

Spore formation

@ref	Spore formation	Confidence
125438		93.691
125439		96.7

Observation

67770

Observationquinones: Q-10

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Borehole sediment sample of Qiangtang Basin in Qinghai-Tibetan plateau	China	CHN	Asia

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM435842v1 assembly for Qipengyuania sediminis CGMCC 1.12928	complete	GCA_004358425	1532023.4	2887099864	1532023	94.82

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Qipengyuania sediminis strain M1 16S ribosomal RNA gene, partial sequence	KJ734993	1452		1532023

GC content

@ref	GC-content (mol%)	Method
67770	73.7	high performance liquid chromatography (HPLC)
67770	66.7	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Qipengyuania sediminis CGMCC 1.12928
NCBI: GCA_004358425

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	96.70	no
125439	motility	BacteriaNetⓘ	yes	53.00	no
125439	gram_stain	BacteriaNetⓘ	negative	99.70	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	98.00	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Qipengyuania sediminis CGMCC 1.12928
NCBI: GCA_004358425.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	97.83	no
125438	anaerobic	anaerobicⓘ	no	94.22	no
125438	aerobic	aerobicⓘ	yes	81.80	no
125438	spore-forming	spore-formingⓘ	no	93.69	no
125438	thermophilic	thermophileⓘ	no	91.13	yes
125438	flagellated	motile2+ⓘ	no	63.34	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Complete Genome Sequence of Qipengyuania sediminis CGMCC 1.12928(T), Shed Light on Its Role in Matter-Cycle and Cold Adaption Mechanism of the Genus Qipengyuania.	Gao Y, Wu YH, Xu L, Cheng H, Wang CS, Xu XW	Curr Microbiol	10.1007/s00284-019-01712-w	2019
Phylogeny	Qipengyuania thermophila sp. nov., isolated from a Chinese hot spring.	Zhao ZY, Xia TT, Jiao JY, Liu L, Su QY, Li MM, Lv AP, Ouyang YT, Li WJ, Ming H	Arch Microbiol	10.1007/s00203-022-02927-5	2022
Phylogeny	Qipengyuania sediminis gen. nov., sp. nov., a member of the family Erythrobacteraceae isolated from subterrestrial sediment.	Feng XM, Mo YX, Han L, Nogi Y, Zhu YH, Lv J	Int J Syst Evol Microbiol	10.1099/ijsem.0.000472	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;
#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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Qipengyuania sediminis (CGMCC 1.12928, JCM 30182)

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

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_004358425

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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