Inconstantimicrobium porci (DSM 108839, WCA-383-APC-5B, JCM 34424)

Name: Inconstantimicrobium porci (DSM 108839, WCA-383-APC-5B, JCM 34424)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 159202

Type strain

Strain Designation WCA-383-APC-5B

Culture col. no. DSM 108839 WCA-383-APC-5B JCM 34424

NCBI tax ID(s) 2652291

Special Collections DSMZ JCM Pig Literature strains DZIF

History DSMZ <- T. Clavel , TU Munich, Freising-Weihenstephan, Germany; JCM <-- B. Abt; DSMZ, Germany; DSM 108839 (=WCA-383-APC-5B) <-- T. Clavel; RWTH Aachen, Germany.

Links

Inconstantimicrobium porci WCA-383-APC-5B is an obligate anaerobe, Gram-positive, motile bacterium that was isolated from pig, APC, 25 weeks old, feces.

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

Name and taxonomic classification

SI-ID 408073

JCM 34424,DSM 108839

@ref 20215

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

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Clostridiaceae

Genus Inconstantimicrobium

Species Inconstantimicrobium porci

Full scientific name Inconstantimicrobium porci Wylensek et al. 2021

Morphology

Cell morphology

@ref	Gram stain	Cell length	Cell shape	Motility
69645	positive	2-10 µm	rod-shaped

Culture and growth conditions

Culture medium

@ref	Name	Medium link	Composition
66025	GAM Broth, modified (Gifu Anaerobic Medium Broth, modified) (DSMZ Medium 1715)	Medium recipe at MediaDive	Name: GAM Broth, mod. (Gifu Anaerobic Medium Broth, modified) (DSMZ Medium 1715) Composition: GAM Broth mod. powder 41.7 g/l Distilled water
69645	Wilkins-Chalgren Anaerobe broth		supplemented with L-cysteine and DTT (0.05% and 0.02% (w/v), respectively)
69645	Gifu Anaerobic Medium, modi?ed		supplemented with Propionate (20mM), Acetate (45mM) and Pyruvate (1 mM)

Culture temp

@ref	Growth	Type	Temperature (°C)
66025	positive	growth	37
67770	positive	growth	37
69645	positive	growth	37

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	facultative anaerobe	96.656
69645	obligate anaerobe

Observation

69645

ObservationCharacteristic swarming growth behaviour on solid media

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	Enrichment culture	Enrichment culture duration	Enrichment culture temperature	Isolation procedure
66025	pig, APC, 25 weeks old, feces	Kranzberg (Bavaria)	Germany	DEU	Europe
67770	Feces of an APC^1311/+ pig	Freising	Germany	DEU	Europe
69645	Pig feces	Thalhausen, Bavaria	Germany	DEU	Europe	Wilkins-Chalgren Anaerobe broth	2-4 days	37	anaerobic

Taxonmaps

69479

Global distribution of 16S sequence MN537551 (>99% sequence identity) for Clostridium from Microbeatlas

Aquatic Samples	1143
Soil Samples	2180
Animal Samples	8889
Plant Samples	385
Total Samples	12597

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM969646v1 assembly for Inconstantimicrobium porci WCA-383-APC-5B	contig	GCA_009696465	2606627.3	2964267936	2652291	60.3

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
66025	Inconstantimicrobium porci strain WCA-383-APC-5B 16S ribosomal RNA gene, partial sequence	MN537551	1463		2652291

GC content

@ref	GC-content (mol%)	Method
67770	31.4	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: ASM969646v1 assembly for Inconstantimicrobium porci WCA-383-APC-5B
BV-BRC: 2606627.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	gram_stain	BacteriaNetⓘ	positive	49.78	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	96.66	no
125439	motility	BacteriaNetⓘ	yes	69.14	no
125439	spore_formation	BacteriaNetⓘ	yes	67.66	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Clostridiaceae bacterium WCA-383-APC-5B
PATRIC: 2606627.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	65.88	no
125438	anaerobic	anaerobicⓘ	yes	89.39	yes
125438	spore-forming	spore-formingⓘ	yes	71.36	no
125438	aerobic	aerobicⓘ	no	98.56	yes
125438	thermophilic	thermophileⓘ	no	88.13	no
125438	flagellated	motile2+ⓘ	yes	79.35	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 )
#66025	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 108839
#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;
#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 .
#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 )

Rate our new design

Content

About us