Sphingomonas formosensis (DSM 24164, BCRC 80272, CC-Nfb-2)

Name: Sphingomonas formosensis (DSM 24164, BCRC 80272, CC-Nfb-2)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 14270

Type strain

Strain Designation CC-Nfb-2

Culture col. no. DSM 24164 BCRC 80272 CC-Nfb-2

NCBI tax ID(s) 861534

Special Collections DSMZ Literature strains

Links

Sphingomonas formosensis CC-Nfb-2 is a mesophilic, Gram-negative, rod-shaped prokaryote that was isolated from oil contaminated soil.

Gram-negative rod-shaped mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 398242

BCRC 80272,DSM 24164

@ref 20215

Last LPSN update 2025-12-16 09:50:18

Domain Pseudomonadati

Phylum Pseudomonadota

Class Alphaproteobacteria

Order Sphingomonadales

Family Sphingomonadaceae

Genus Sphingomonas

Species Sphingomonas formosensis

Full scientific name Sphingomonas formosensis Lin et al. 2012

Synonyms (1)

Flavisphingomonas formosensis

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell width	Cell shape	Confidence
30382	negative	1.4 µm	0.4 µm	rod-shaped
125439	negative				97
125438	negative				94.524

Pigmentation

30382

Productionyes

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
17502	TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535)		Medium recipe at MediaDive	Name: TRYPTICASE SOY BROTH AGAR (DSMZ Medium 535) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
17502	positive	growth	28	mesophilic
30382	positive	growth	25-37	mesophilic
30382	positive	optimum	30	mesophilic

Culture pH

@ref	Ability	Type	PH	PH range
30382	positive	optimum	7
30382	positive	growth	05-09	alkaliphile

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	aerobe	94.3

Spore formation

@ref	Spore formation	Confidence
125439		94.9

Halophily

@ref	Salt	Growth	Tested relation	Concentration
30382	NaCl	positive	growth	<3 %

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
30382	28260 ChEBI	galactose	+	carbon source
30382	17234 ChEBI	glucose	+	carbon source
30382	17992 ChEBI	sucrose	+	carbon source
30382	27082 ChEBI	trehalose	+	carbon source

Enzymes

@ref	Value	Activity	Ec
30382	alkaline phosphatase	+	3.1.3.1
30382	catalase	+	1.11.1.6
30382	cytochrome oxidase	+	1.9.3.1

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Engineered	#Contamination	#Oil (Fuel)
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
17502	oil contaminated soil	Kaohsiung County	Taiwan, Province of China	TWN	Asia

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
17502	1	Risk group (German classification) According to TRBA 466

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM975581v1 assembly for Flavisphingomonas formosensis CC-Nfb-2	contig	GCA_009755815	861534.3	2989658508	861534	67.85

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
17502	Sphingomonas formosensis strain CC-Nfb-2 16S ribosomal RNA gene, partial sequence	HM193517	1478		861534

GC content

@ref	GC-content (mol%)	Method
17502	62.8	high performance liquid chromatography (HPLC)
30382	62.8

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Sphingomonas formosensis CC-Nfb-2
NCBI: GCA_009755815

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	94.90	no
125439	motility	BacteriaNetⓘ	yes	61.20	no
125439	gram_stain	BacteriaNetⓘ	negative	97.00	no
125439	oxygen_tolerance	BacteriaNetⓘ	aerobe	94.30	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Sphingomonas formosensis CC-Nfb-2
NCBI: GCA_009755815.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	94.52	yes
125438	anaerobic	anaerobicⓘ	no	94.07	no
125438	aerobic	aerobicⓘ	yes	89.85	no
125438	spore-forming	spore-formingⓘ	no	84.58	no
125438	thermophilic	thermophileⓘ	no	97.88	no
125438	flagellated	motile2+ⓘ	yes	70.95	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Phylogeny	Sphingomonas profundi sp. nov., isolated from deep-sea sediment of the Mariana Trench.	Yang S, Li X, Xiao X, Zhuang G, Zhang Y	Int J Syst Evol Microbiol	10.1099/ijsem.0.004235	2020
Phylogeny	Sphingomonas crusticola sp. nov., isolated from biological soil crusts.	Zhang K, Tang K, Feng F, Yuan B, Zhang X, Meng J	Int J Syst Evol Microbiol	10.1099/ijsem.0.002074	2017
Phylogeny	Sphingomonas montana sp. nov., isolated from a soil sample from the Tanggula Mountain in the Qinghai Tibetan Plateau.	Manandhar P, Zhang G, Lama A, Liu F, Hu Y	Antonie Van Leeuwenhoek	10.1007/s10482-017-0915-6	2017
Phylogeny	Sphingomonas prati sp. nov., isolated from alpine meadow soil.	Manandhar P, Zhang G, Hu Y, Lama A, Gao F, Gu Z	Int J Syst Evol Microbiol	10.1099/ijsem.0.001346	2016
Phylogeny	Sphingomonas morindae sp. nov., isolated from Noni (Morinda citrifolia L.) branch.	Liu Y, Yao S, Lee YJ, Cao Y, Zhai L, Zhang X, Su J, Ge Y, Kim SG, Cheng C	Int J Syst Evol Microbiol	10.1099/ijs.0.000340	2015
Phylogeny	Sphingomonas formosensis sp. nov., a polycyclic aromatic hydrocarbon-degrading bacterium isolated from agricultural soil.	Lin SY, Shen FT, Lai WA, Zhu ZL, Chen WM, Chou JH, Lin ZY, Young CC	Int J Syst Evol Microbiol	10.1099/ijs.0.034728-0	2011

References

#17502	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 24164
#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 )
#30382	Barberan A, Caceres Velazquez H, Jones S, Fierer N.: Hiding in Plain Sight: Mining Bacterial Species Records for Phenotypic Trait Information. mSphere 2: 2017 ( DOI 10.1128/mSphere.00237-17 , PubMed 28776041 ) - originally annotated from #26721 (see below)
#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) .
#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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Sphingomonas formosensis (DSM 24164, BCRC 80272, CC-Nfb-2)

Name and taxonomic classification

Morphology

Cell morphology

Pigmentation

Culture and growth conditions

Culture medium

Culture temp

Culture pH

Physiology and metabolism

Oxygen tolerance

Spore formation

Halophily

Metabolite utilization

Enzymes

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_009755815

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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