Suipraeoptans intestinalis (DSM 104945, 68-1-5, JCM 34387)

Name: Suipraeoptans intestinalis (DSM 104945, 68-1-5, JCM 34387)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 159628

Type strain

Strain Designation 68-1-5

Culture col. no. DSM 104945 68-1-5 JCM 34387

NCBI tax ID(s) 2606628

Special Collections DSMZ JCM Pig Literature strains DZIF

History DSMZ <- T. Looft, USDA-ARS-NADC; 68-1-5 JCM <-- B. Abt; DSMZ, Germany; DSM 104945 (=68-1-5) <-- T. Looft; ARS, USDA, USA.

Links

Suipraeoptans intestinalis 68-1-5 is an anaerobe, Gram-positive, rod-shaped bacterium that was isolated from intestinal tract of a three month-old healthy pig.

Gram-positive rod-shaped anaerobe genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 399464

JCM 34387,DSM 104945

@ref 20215

Last LPSN update 2026-05-29 08:44:14

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Lachnospiraceae

Genus Suipraeoptans

Species Suipraeoptans intestinalis

Full scientific name Suipraeoptans intestinalis corrig. Wylensek et al. 2021

Synonyms (1)

Suipraoptans intestinalis

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell shape	Motility	Confidence
125438					90.9
69645	positive	0.5 µm	rod-shaped

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
66464	BHI MEDIUM (DSMZ Medium 215)	Medium recipe at MediaDive	Name: BHI MEDIUM (DSMZ Medium 215) Composition: Brain heart infusion 37.0 g/l Distilled water
66464	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
69645	Hog gastric mucin medium
69645	Brain Heart Infusion (Oxoid, ref. CM1135)
69645	Wilkins-Chalgren Anaerobe broth		supplemented with L-cysteine and DTT (0.05% and 0.02% (w/v), respectively)

Culture temp

@ref	Growth	Type	Temperature (°C)
66464	positive	growth	37
67770	positive	growth	37
69645	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	anaerobe	95.414
125439	obligate anaerobe	99.844
69645	anaerobe

Observation

69645

ObservationCells grow as single cells or in pairs

Metabolite utilization

@ref	Chebi-ID	Metabolite	Utilization activity	Kind of utilization tested
68380	29016 ChEBI	arginine	-	hydrolysis	from API rID32A
68380	16024 ChEBI	D-mannose	-	fermentation	from API rID32A
69645	17234 ChEBI	glucose	+	assimilation
68380	29985 ChEBI	L-glutamate	-	degradation	from API rID32A
68380	17632 ChEBI	nitrate	-	reduction	from API rID32A
68380	16634 ChEBI	raffinose	-	fermentation	from API rID32A
68380	27897 ChEBI	tryptophan	-	energy source	from API rID32A
68380	16199 ChEBI	urea	-	hydrolysis	from API rID32A

Metabolite production

@ref	Chebi-ID	Metabolite
69645	30089 ChEBI	acetate
69645	15740 ChEBI	formate
68380	35581 ChEBI	indole	from API rID32A

Metabolite tests

@ref	Chebi-ID	Metabolite	Indole test
68380	35581 ChEBI	indole	-	from API rID32A

Enzymes

@ref	Value	Activity	Ec
68380	alanine arylamidase	-	3.4.11.2	from API rID32A
68380	alpha-arabinosidase	-	3.2.1.55	from API rID32A
68380	alpha-fucosidase	-	3.2.1.51	from API rID32A
68380	alpha-galactosidase	-	3.2.1.22	from API rID32A
68380	alpha-glucosidase	-	3.2.1.20	from API rID32A
68380	arginine dihydrolase	-	3.5.3.6	from API rID32A
68380	beta-galactosidase	-	3.2.1.23	from API rID32A
68380	beta-Galactosidase 6-phosphate	-		from API rID32A
68380	beta-glucosidase	-	3.2.1.21	from API rID32A
68380	beta-glucuronidase	-	3.2.1.31	from API rID32A
68380	glutamate decarboxylase	-	4.1.1.15	from API rID32A
68380	glutamyl-glutamate arylamidase	-		from API rID32A
68380	glycin arylamidase	-		from API rID32A
68380	histidine arylamidase	-		from API rID32A
68380	L-arginine arylamidase	-		from API rID32A
68380	leucine arylamidase	-	3.4.11.1	from API rID32A
68380	leucyl glycin arylamidase	-	3.4.11.1	from API rID32A
68380	N-acetyl-beta-glucosaminidase	-	3.2.1.52	from API rID32A
68380	phenylalanine arylamidase	-		from API rID32A
68380	proline-arylamidase	+	3.4.11.5	from API rID32A
68380	pyrrolidonyl arylamidase	-	3.4.19.3	from API rID32A
68380	serine arylamidase	-		from API rID32A
68380	tryptophan deaminase	-	4.1.99.1	from API rID32A
68380	tyrosine arylamidase	-		from API rID32A
68380	urease	-	3.5.1.5	from API rID32A

API rID32A

@ref	URE	ADH (Arg)	alpha GAL	beta GAL	beta-Galactosidase 6-phosphatebeta GP	alpha GLU	beta GLU	alpha ARA	beta GUR	beta-N-Acetyl-beta-glucosaminidasebeta NAG	MNE	RAF	GDC	alpha FUC	Reduction of nitrateNIT	IND	PAL	L-arginine arylamidaseArgA	ProA	LGA	Phenylalanine arylamidasePheA	Leucine arylamidaseLeuA	PyrA	Tyrosine arylamidaseTyrA	Alanine arylamidaseAlaA	Glycin arylamidaseGlyA	Histidine arylamidaseHisA	Glutamyl-glutamate arylamidaseGGA	Serine arylamidaseSerA
66464	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	+/-	-	+	-	-	-	-	-	-	-	-	-	-
66464	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	+/-	-	+	-	-	-	-	-	-	-	-	-	-

Isolation, sampling and environmental information

Isolation source categories

Cat1	Cat2	Cat3
#Host	#Mammals	#Suidae (Pig,Swine)
#Host Body-Site	#Gastrointestinal tract	-

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Enrichment culture	Enrichment culture duration	Enrichment culture temperature	Isolation procedure	Latitude	Longitude
66464	intestinal tract (ileal contents) of a three month-old healthy pig		USA	USA	North America					42.0308	-93.6319 42.0308/-93.6319
67770	Ileal content of a pig in Ames	Iowa	USA	USA	North America
69645	Ileal content of a pig	Ames, Iowa	USA	USA	North America	Hog gastric mucin medium	3-5 days	37	anaerobic

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM969648v1 assembly for Suipraeoptans intestinalis 68-1-5	contig	GCA_009696485	2606628.3	2936237273	2606628	64.02

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
66464	Suipraeoptans intestinalis strain 68-1-5 16S ribosomal RNA gene, partial sequence	MN537470	1380		2652301

GC content

@ref	GC-content (mol%)	Method
67770	47.7	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM969648v1 assembly for Suipraeoptans intestinalis 68-1-5
BV-BRC: 2606628.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	obligate anaerobe	99.84	no
125439	motility	BacteriaNetⓘ	yes	68.77	no
125439	gram_stain	BacteriaNetⓘ	positive	48.61	no
125439	spore_formation	BacteriaNetⓘ	yes	54.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Clostridiaceae bacterium 68-1-5
PATRIC: 2606628.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	82.56	no
125438	anaerobic	anaerobicⓘ	yes	95.41	no
125438	spore-forming	spore-formingⓘ	no	68.17	no
125438	aerobic	aerobicⓘ	no	98.06	yes
125438	thermophilic	thermophileⓘ	no	94.63	yes
125438	flagellated	motile2+ⓘ	no	90.90	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 )
#66464	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 104945
#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;
#68380	Automatically annotated from API rID32A .
#69645	David Wylensek, Thomas C. A. Hitch, Thomas Riedel, Afrizal Afrizal, Neeraj Kumar, Esther Wortmann, Tianzhe Liu, Saravanan Devendran, Till R. Lesker, Sara B. Hernández, Viktoria Heine, Eva M. Buhl, Paul M. D'Agostino, Fabio Cumbo, Thomas Fischöder, Marzena Wyschkon, Torey Looft, Valeria R. Parreira, Birte Abt, Heidi L. Doden, Lindsey Ly, João M. P. Alves, Markus Reichlin, Krzysztof Flisikowski, Laura Navarro Suarez, Anthony P. Neumann, Garret Suen, Tomas de Wouters, Sascha Rohn, Ilias Lagkouvardos, Emma Allen-Vercoe, Cathrin Spröer, Boyke Bunk, Anja J. Taverne-Thiele, Marcel Giesbers, Jerry M. Wells, Klaus Neuhaus, Angelika Schnieke, Felipe Cava, Nicola Segata, Lothar Elling, Till Strowig, Jason M. Ridlon, Tobias A. M. Gulder, Jörg Overmann, Thomas Clavel: A collection of bacterial isolates from the pig intestine reveals functional and taxonomic diversity. Nat. Commun. 11: 2020 ( DOI 10.1038/s41467-020-19929-w )
#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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