Pseudarcobacter ellisii (DSM 25472, LMG 26155, CECT 7837)

Name: Pseudarcobacter ellisii (DSM 25472, LMG 26155, CECT 7837)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 160690

Type strain

Strain Designation F79-6T

Culture col. no. DSM 25472 LMG 26155 CECT 7837 F79-6T

NCBI tax ID(s) 913109

Special Collections DSMZ

Links

Pseudarcobacter ellisii F79-6T is a mesophilic prokaryote that was isolated from mussels .

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 371536

LMG 26155,CECT 7837,DSM 25472

@ref 20215

Last LPSN update 2025-12-16 10:08:33

Domain Pseudomonadati

Phylum Pseudomonadota

Class Epsilonproteobacteria

Order Campylobacterales

Family Arcobacteraceae

Genus Pseudarcobacter

Species Pseudarcobacter ellisii

Full scientific name Pseudarcobacter ellisii corrig. (Figueras et al. 2011) Pérez-Cataluña et al. 2019

Synonyms (2)

Pseudoarcobacter ellisii
Arcobacter ellisii

Morphology

Cell morphology

@ref	Gram stain	Confidence
125439	negative	99.6
125438	negative	96.894

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
67600	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

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67600	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	96.5

Spore formation

@ref	Spore formation	Confidence
125439		92.6
125438		90.397

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68373	30089 ChEBI	acetate	+	assimilation	from API CAM
68373	16947 ChEBI	citrate	-	assimilation	from API CAM
68373	17634 ChEBI	D-glucose	-	assimilation	from API CAM
68373	606565 ChEBI	hippurate	-	hydrolysis	from API CAM
68373	25115 ChEBI	malate	-	assimilation	from API CAM
68373	17632 ChEBI	nitrate	+	reduction	from API CAM
68373	17272 ChEBI	propionate	+	assimilation	from API CAM
68373	30031 ChEBI	succinate	-	assimilation	from API CAM
68373	78019 ChEBI	triphenyltetrazolium chloride	-	reduction	from API CAM
68373	16199 ChEBI	urea	-	hydrolysis	from API CAM

Antibiotic resistance

@ref	ChEBI	Metabolite	Sensitivity conc.
68373	474053	cefazolin	224 µg	from API CAM
68373	48923	erythromycin	14 µg	from API CAM
68373	100147	nalidixic acid	84 µg	from API CAM

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68373	16136 ChEBI	hydrogen sulfide		from API CAM

Enzymes

@ref	Value	Activity	Ec
68373	alkaline phosphatase	+	3.1.3.1	from API CAM
68373	catalase	+	1.11.1.6	from API CAM
68373	esterase	+		from API CAM
68373	gamma-glutamyltransferase	-	2.3.2.2	from API CAM
68373	L-arginine arylamidase	-		from API CAM
68373	L-aspartate arylamidase	-	3.4.11.21	from API CAM
68373	pyrrolidonyl arylamidase	-	3.4.19.3	from API CAM
68373	urease	-	3.5.1.5	from API CAM

API CAM

@ref	URE	Reduction of nitrateNIT	EsteraseEST	HIP	GGT	TTC	PYRA	L-arginine arylamidaseArgA	L-aspartic acid arylamidaseAspA	PAL	H2S productionH2S	GLU	SUT	NAL	CFZ	ACE	PROP	MLT	CIT	Erythromycin resistance (+) sensitivity (-)ERO	CAT
67600	-	+	+	-	-	-	-	-	-	+	-	-	-	-	-	+	+	-	-	-	+

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
67600	mussels ( Mytilus edulis)	Reus	Spain	ESP	Europe	41.1472	1.1669 41.1472/1.1669

Taxonmaps

69479

Global distribution of 16S sequence FR717550 (>99% sequence identity) for Arcobacter from Microbeatlas

Aquatic Samples	9375
Soil Samples	408
Animal Samples	847
Plant Samples	137
Total Samples	10767

Interaction and safety

Risk assessment

@ref	Biosafety level	Biosafety level comment
67600	1	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM354491v1 assembly for Arcobacter ellisii LMG 26155	complete	GCA_003544915	913109.7	2850489734	913109	95.8
66792	ASM411581v1 assembly for Arcobacter ellisii CECT 7837	contig	GCA_004115815	913109.8	2868779703	913109	47.76

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67600	Arcobacter sp. F79-6 partial 16S rRNA gene, type strain F79-6T	FR717550	1402		913109
124043	Arcobacter ellisii strain LMG 26155 16S ribosomal RNA gene, partial sequence.	OP536157	675		913109

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Arcobacter ellisii LMG 26155
NCBI: GCA_003544915

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	no	92.60	no
125439	motility	BacteriaNetⓘ	yes	55.30	no
125439	gram_stain	BacteriaNetⓘ	negative	99.60	no
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	96.50	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Arcobacter ellisii LMG 26155
NCBI: GCA_003544915.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	no	96.89	no
125438	anaerobic	anaerobicⓘ	no	50.77	no
125438	aerobic	aerobicⓘ	no	62.25	no
125438	spore-forming	spore-formingⓘ	no	90.40	no
125438	thermophilic	thermophileⓘ	no	86.93	yes
125438	flagellated	motile2+ⓘ	yes	77.11	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 )
#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) .
#67600	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 25472
#68373	Automatically annotated from API CAM .
#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 .
#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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