Enterococcus hirae (DSM 100949, WCA-386-APC-3D)

Name: Enterococcus hirae (DSM 100949, WCA-386-APC-3D)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 158938

Type strain

Strain Designation WCA-386-APC-3D

Culture col. no. DSM 100949 WCA-386-APC-3D

NCBI tax ID(s) 1354

Special Collections DSMZ Pig DZIF

History DSMZ <- D. Wylensek, TU Munich, Freising-Weihenstephan, Germany; WCA-386-APC-3D

Links

Enterococcus hirae WCA-386-APC-3D is a human pathogen that was isolated from feces; pig, 4 month old, genotype: APC1311/+ referring to the adenomatous-polyposis-coli protein.

human pathogen genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 406830

DSM 100949

@ref 20215

Last LPSN update 2026-05-29 08:44:04

Domain Bacteria

Phylum Bacillota

Class Bacilli

Order Lactobacillales

Family Enterococcaceae

Genus Enterococcus

Species Enterococcus hirae

Full scientific name Enterococcus hirae Farrow and Collins 1985

BacDive ID	Other strains from **Enterococcus hirae** (24)	Type strain
5316	E. hirae DSM 20160, ATCC 8043, CCM 2423, CCUG 18659, ... (type strain)
5315	E. hirae M 19, CCUG 32258, NCIMB 8192, CCM 4533, DSM ...
130947	E. hirae SB, DSM 28619
24003	E. hirae Eh61, DSM 27815
135287	E. hirae AmMS 206, CIP 103564, ATCC 49135
143533	E. hirae CCUG 19908 B
145498	E. hirae CCUG 28689
145499	E. hirae CCUG 28690
147232	E. hirae CCUG 33114
149096	E. hirae CCUG 36850
149488	E. hirae CCUG 37829
150911	E. hirae CCUG 42698
152368	E. hirae CCUG 46536
152713	E. hirae CCUG 47453
153938	E. hirae CCUG 51711
154368	E. hirae CCUG 53265
154549	E. hirae CCUG 54371
155618	E. hirae CCUG 58425
160038	E. hirae Cla-CZ-137, DSM 109134
165943	E. hirae JCM 8717
165944	E. hirae JCM 8718
165945	E. hirae JCM 8719
165946	E. hirae JCM 8720
174436	E. hirae 114598, DSM 114598

Morphology

Cell morphology

@ref	Gram stain	Confidence
125438	positive	91.765

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
65761	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

Culture temp

@ref	Growth	Type	Temperature (°C)
65761	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	obligate aerobe	93.704

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68381	40585 ChEBI	alpha-cyclodextrin	+	builds acid from	from API rID32STR
68381	29016 ChEBI	arginine	+	hydrolysis	from API rID32STR
68381	18333 ChEBI	D-arabitol	-	builds acid from	from API rID32STR
68381	16899 ChEBI	D-mannitol	-	builds acid from	from API rID32STR
68381	16988 ChEBI	D-ribose	+	builds acid from	from API rID32STR
68381	16443 ChEBI	D-tagatose	-	builds acid from	from API rID32STR
68381	28087 ChEBI	glycogen	-	builds acid from	from API rID32STR
68381	606565 ChEBI	hippurate	-	hydrolysis	from API rID32STR
68381	30849 ChEBI	L-arabinose	-	builds acid from	from API rID32STR
68381	17716 ChEBI	lactose	+	builds acid from	from API rID32STR
68381	17306 ChEBI	maltose	+	builds acid from	from API rID32STR
68381	6731 ChEBI	melezitose	-	builds acid from	from API rID32STR
68381	28053 ChEBI	melibiose	+	builds acid from	from API rID32STR
68381	320055 ChEBI	methyl beta-D-glucopyranoside	+	builds acid from	from API rID32STR
68381	27941 ChEBI	pullulan	-	builds acid from	from API rID32STR
68381	16634 ChEBI	raffinose	+	builds acid from	from API rID32STR
68381	30911 ChEBI	sorbitol	-	builds acid from	from API rID32STR
68381	17992 ChEBI	sucrose	+	builds acid from	from API rID32STR
68381	27082 ChEBI	trehalose	+	builds acid from	from API rID32STR
68381	16199 ChEBI	urea	-	hydrolysis	from API rID32STR

Metabolite production

@ref	Chebi-ID	Metabolite	Production
68381	15688 ChEBI	acetoin		from API rID32STR

Metabolite tests

@ref	Chebi-ID	Metabolite	Voges-proskauer-test
68381	15688 ChEBI	acetoin	+	from API rID32STR

Enzymes

@ref	Value	Activity	Ec
68381	Alanyl-Phenylalanyl-Proline arylamidase	-		from API rID32STR
68381	alkaline phosphatase	-	3.1.3.1	from API rID32STR
68381	alpha-galactosidase	+	3.2.1.22	from API rID32STR
68381	arginine dihydrolase	+	3.5.3.6	from API rID32STR
68381	beta-galactosidase	+	3.2.1.23	from API rID32STR
68381	beta-glucosidase	+	3.2.1.21	from API rID32STR
68381	beta-glucuronidase	-	3.2.1.31	from API rID32STR
68381	beta-mannosidase	-	3.2.1.25	from API rID32STR
68381	glycyl tryptophan arylamidase	+		from API rID32STR
68381	N-acetyl-beta-glucosaminidase	+	3.2.1.52	from API rID32STR
68381	pyrrolidonyl arylamidase	+	3.4.19.3	from API rID32STR
68381	urease	-	3.5.1.5	from API rID32STR

API rID32STR

@ref	ADH (Arg)	beta GLU	beta GAR	beta GUR	alpha GAL	PAL	RIB	MAN	SOR	LAC	TRE	RAF	SAC	LARA	DARL	Acid from alpha-cyclodextrinCDEX	Acetoin production (Voges Proskauer test)VP	Alanyl-Phenylalanyl-Proline arylamidaseAPPA	beta GAL	Pyrrolidonyl arylamidasePyrA	N-Acetyl-glucosaminidasebeta NAG	Glycyl-tryptophan arylamidaseGTA	HIP	GLYG	PUL	MAL	MEL	MLZ	Acidification of methyl beta-D-glucopyranosideMbeta DG	TAG	beta MAN	URE
65761	+	+	+	-	+	-	+	-	-	+	+	+	+	-	-	+	+	-	+	+	+	+	-	-	-	+	+	-	+	-	-	-

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host Body Product	#Gastrointestinal tract	#Feces (Stool)
#Host	#Mammals	#Suidae (Pig,Swine)

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent
65761	feces; pig, 4 month old, genotype: APC1311/+ referring to the adenomatous-polyposis-coli (APC) protein	Kranzberg (Bavaria)	Germany	DEU	Europe

Taxonmaps

69479

Global distribution of 16S sequence MN537443 (>99% sequence identity) for Enterococcus from Microbeatlas

Aquatic Samples	2532
Soil Samples	1007
Animal Samples	51351
Plant Samples	654
Total Samples	55544

Interaction and safety

Risk assessment

@ref	Pathogenicity human	Pathogenicity animal	Biosafety level	Biosafety level comment
65761			2	Risk group (German classification)

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
66792	ASM1284377v1 assembly for Enterococcus hirae WCA-386-APC-3D	contig	GCA_012843775	1354.315	1354	71.52

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
65761	Enterococcus sp. strain DSM 100949 16S ribosomal RNA gene, partial sequence	MN537443	1513		35783

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM1284377v1 assembly for Enterococcus hirae WCA-386-APC-3D
NCBI: GCA_012843775

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate aerobe	93.70	no
125439	gram_stain	BacteriaNetⓘ	variable	56.49	no
125439	motility	BacteriaNetⓘ	yes	61.96	no
125439	spore_formation	BacteriaNetⓘ	yes	72.21	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Enterococcus hirae WCA-386-APC-3D
NCBI: GCA_012843775.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	91.77	no
125438	anaerobic	anaerobicⓘ	no	86.79	no
125438	aerobic	aerobicⓘ	no	96.17	no
125438	spore-forming	spore-formingⓘ	no	81.69	no
125438	thermophilic	thermophileⓘ	no	96.50	yes
125438	flagellated	motile2+ⓘ	no	88.50	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 )
#65761	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 100949
#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) .
#68381	Automatically annotated from API rID32STR .
#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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