Staphylococcus edaphicus (DSM 104441, CCM 8730, CCUG 72269)

Name: Staphylococcus edaphicus (DSM 104441, CCM 8730, CCUG 72269)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 157258

Type strain

Strain Designation P5085

Culture col. no. DSM 104441 CCM 8730 CCUG 72269 P5085 CIP 111603

NCBI tax ID(s) 1955013

Special Collections DSMZ CCUG CIP

History DSMZ <- I. Sedlacek; Masaryk University, Brno, CZECH REPUBLIC; P5085<-I. Sedlácek; CCM, Masaryk University, Czech Republic CIP <- 2018, CCM <- 2016, I. Sedlacek, Mazaryk Univ., Brno, Czech Republic

Links

Staphylococcus edaphicus P5085 is an aerobe, Gram-negative, coccus-shaped bacterium that was isolated from Fragments of black porus stone.

Gram-negative coccus-shaped aerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 401196

DSM 104441,CCUG 72269T

@ref 20215

Last LPSN update 2026-05-29 08:43:41

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Caryophanales

Family Staphylococcaceae

Genus Staphylococcus

Species Staphylococcus edaphicus

Full scientific name Staphylococcus edaphicus Pantucek et al. 2018

Morphology

Cell morphology

@ref	Gram stain	Cell shape	Motility
118996	negative	coccus-shaped

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
64323	COLUMBIA BLOOD MEDIUM (DSMZ Medium 693)	Medium recipe at MediaDive	Name: COLUMBIA BLOOD MEDIUM (DSMZ Medium 693) Composition: Defibrinated sheep blood 50.0 g/l Columbia agar base
64323	TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92)	Medium recipe at MediaDive	Name: TRYPTICASE SOY YEAST EXTRACT MEDIUM (DSMZ Medium 92) Composition: Trypticase soy broth 30.0 g/l Agar 15.0 g/l Yeast extract 3.0 g/l Distilled water
118996	CIP Medium 72	Medium recipe at CIP

Culture temp

@ref	Growth	Type	Temperature (°C)
63798	positive	growth	37
64323	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
63798	aerobe
125439	obligate aerobe	92.468

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68375	22599 ChEBI	arabinose	-	fermentation	from API ID32STA
68375	29016 ChEBI	arginine	-	hydrolysis	from API ID32STA
68375	17057 ChEBI	cellobiose	-	fermentation	from API ID32STA
68375	15824 ChEBI	D-fructose	+	fermentation	from API ID32STA
68375	17634 ChEBI	D-glucose	+	fermentation	from API ID32STA
68375	16899 ChEBI	D-mannitol	+	fermentation	from API ID32STA
68375	16988 ChEBI	D-ribose	-	fermentation	from API ID32STA
68375	4853 ChEBI	esculin	-	hydrolysis	from API ID32STA
68375	17716 ChEBI	lactose	-	fermentation	from API ID32STA
68375	17306 ChEBI	maltose	+	fermentation	from API ID32STA
68375	59640 ChEBI	N-acetylglucosamine	+	fermentation	from API ID32STA
68375	17632 ChEBI	nitrate	+	reduction	from API ID32STA
68375	18257 ChEBI	ornithine	-	degradation	from API ID32STA
68375	16634 ChEBI	raffinose	-	fermentation	from API ID32STA
68375	17992 ChEBI	sucrose	+	fermentation	from API ID32STA
68375	27082 ChEBI	trehalose	-	fermentation	from API ID32STA
68375	32528 ChEBI	turanose	-	fermentation	from API ID32STA
68375	16199 ChEBI	urea	+	hydrolysis	from API ID32STA

Antibiotic resistance

@ref	ChEBI	Group ID	Metabolite	Is resistant	Resistance conc.
68375	28368	0	novobiocin		1.8 µg	from API ID32STA

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68375	15688 ChEBI	acetoin		from API ID32STA

Metabolite tests

@ref	Chebi-ID	Metabolite	Voges-proskauer-test
68375	15688 ChEBI	acetoin	-	from API ID32STA

Enzymes

@ref	Value	Activity	Ec
68375	alkaline phosphatase	-	3.1.3.1	from API ID32STA
68375	arginine dihydrolase	-	3.5.3.6	from API ID32STA
68375	beta-galactosidase	-	3.2.1.23	from API ID32STA
68375	beta-glucosidase	-	3.2.1.21	from API ID32STA
68375	beta-glucuronidase	+	3.2.1.31	from API ID32STA
68375	L-arginine arylamidase	-		from API ID32STA
68375	ornithine decarboxylase	-	4.1.1.17	from API ID32STA
68375	pyrrolidonyl arylamidase	-	3.4.19.3	from API ID32STA
68375	urease	+	3.5.1.5	from API ID32STA

API ID32STA

@ref	URE	ADH (Arg)	ODC	ESC	GLU	FRU	MNE	MAL	LAC	TRE	MAN	RAF	RIB	CEL	Reduction of nitrateNIT	Acetoin production (Voges Proskauer test)VP	beta GAL	L-arginine arylamidaseArgA	PAL	Pyrrolidonyl arylamidasePyrA	NOVO	SAC	NAG	TUR	ARA	beta GUR
64323	+	-	-	-	+	+	+/-	+	-	-	+	-	-	-	+	-	-	-	-	-	+	+	+	-	-	+

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Environmental	#Terrestrial	#Soil

Isolation

@ref	Sample type	Sampling date	Geographic location	Country	Country ISO 3 Code	Continent
63798	Fragments of black porus stone	2016	Ross Island,Lachman Cape	Antarctica	ATA	Australia and Oceania
64323	fragments of black porous stone (top of the hill)		James Ross Island (57° 47' 11" W, 63° 46' 58" S)	Antarctica	ATA	Australia and Oceania
118996	Environment, Fragments of black porus stone		Lachman Cap, J. Ross Island	Antarctica	ATA	Antarctica

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
118996	1	Risk group (French classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM261472v1 assembly for Staphylococcus edaphicus CCM 8730	contig	GCA_002614725	1955013.3	2802429263	1955013	68.78

16S sequences

@ref	Description	Accession	Length	NCBI tax ID
124043	Staphylococcus edaphicus strain CCM 8730 16S ribosomal RNA gene, complete sequence.	KY315825	1541	1955013
124043	Staphylococcus edaphicus strain CCM 8730 16S ribosomal RNA gene, partial sequence.	PP858928	726	1955013
124043	Staphylococcus edaphicus strain CCM 8730 16S ribosomal RNA gene, partial sequence.	PV760287	1492	1955013

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM261472v1 assembly for Staphylococcus edaphicus CCM 8730
NCBI: GCA_002614725

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	gram_stain	BacteriaNetⓘ	positive	54.66	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	92.47	no
125439	motility	BacteriaNetⓘ	no	62.85	no
125439	spore_formation	BacteriaNetⓘ	no	79.33	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Staphylococcus edaphicus strain CCM 8730 strain CCM 5085
PATRIC: 1955013.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	81.28	no
125438	anaerobic	anaerobicⓘ	no	99.43	yes
125438	spore-forming	spore-formingⓘ	no	69.84	no
125438	aerobic	aerobicⓘ	yes	60.93	no
125438	thermophilic	thermophileⓘ	no	96.52	yes
125438	flagellated	motile2+ⓘ	no	80.00	no

Literature

Topic	Title	Authors	Journal	DOI	Year
Genetics	Genomic Characterization of Marine Staphylococcus shinii Strain SC-M1C: Potential Genetic Adaptations and Ecological Role	El Samak M, Lotfy H, Sedeek A, Mohamed Y, Solyman S.	Microorganisms		2025
Phylogeny	Staphylococcus edaphicus sp. nov., Isolated in Antarctica, Harbors the mecC Gene and Genomic Islands with a Suspected Role in Adaptation to Extreme Environments.	Pantucek R, Sedlacek I, Indrakova A, Vrbovska V, Maslanova I, Kovarovic V, Svec P, Kralova S, Kristofova L, Keklakova J, Petras P, Doskar J	Appl Environ Microbiol	10.1128/AEM.01746-17	2018

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 )
#63798	Culture Collection University of Gothenburg (CCUG) ; Curators of the CCUG; CCUG 72269
#64323	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 104441
#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) .
#68375	Automatically annotated from API ID32STA .
#118996	Collection of Institut Pasteur ; Curators of the CIP; CIP 111603
#124043	Isabel Schober, Julia Koblitz: Data extracted from sequence databases, automatically matched based on designation and taxonomy .
#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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Staphylococcus edaphicus (DSM 104441, CCM 8730, CCUG 72269)

Name and taxonomic classification

Morphology

Cell morphology

Culture and growth conditions

Culture medium

Culture temp

Physiology and metabolism

Oxygen tolerance

Metabolite utilization

Antibiotic resistance

Metabolite production

Metabolite tests

Enzymes

API ID32STA

Isolation, sampling and environmental information

Isolation source categories

Isolation

Interaction and safety

Risk assessment

Sequence information

Genome sequences

Genome browser: GCA_002614725

16S sequences

Genome-based predictions

Predictions

Literature

Literature

References

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