Cite this strain

Clostridium sp. (JCM 10522)

Name: Clostridium sp. (JCM 10522)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 160976

Type strain

Culture col. no. JCM 10522

NCBI tax ID(s) 1095012

Special Collections JCM

History M. Ohkuma Hs50.

Links

JCM 10522 is a mesophilic prokaryote that was isolated from Termite gut.

mesophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 131351

JCM 10522

@ref 20215

Last LPSN update 2025-12-16 10:08:37

Domain Bacillati

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Clostridiaceae

Genus Clostridium

Full scientific name Clostridium Prazmowski 1880 (Approved Lists 1980)

Synonyms (8)

Thomasclavelia
"Erysipelatoclostridium"
"Pseudoclostridium"
"Andreesenella"
"Tyzzerella"
"Lachnoclostridium"
Anaerobacter
"Inflabilis"

Morphology

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	30	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	anaerobe	91.849
125439	anaerobe	97.6

Isolation, sampling and environmental information

Isolation

67770

Sample typeTermite gut

Taxonmaps

69479

Global distribution of 16S sequence AB673454 (>99% sequence identity) for Clostridium from Microbeatlas

Aquatic Samples	3962
Soil Samples	4923
Animal Samples	31978
Plant Samples	1109
Total Samples	41972

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID
66792	ASM131242v1 assembly for Clostridium sp. Hs50 JCM 10522	contig	GCA_001312425	1095012.4	2728369724	1095012

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Clostridium sp. Hs50 gene for 16S rRNA, partial sequence	AB673454	1474		1095012

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Clostridium sp. Hs50 JCM 10522
NCBI: GCA_001312425

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	97.60	no
125439	gram_stain	BacteriaNetⓘ	positive	85.30	no
125439	motility	BacteriaNetⓘ	yes	71.90	no
125439	spore_formation	BacteriaNetⓘ	yes	70.40	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Clostridium sp. Hs50 strain JCM 10522
PATRIC: 1095012.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	63.85	no
125438	anaerobic	anaerobicⓘ	yes	91.85	no
125438	spore-forming	spore-formingⓘ	yes	73.53	no
125438	aerobic	aerobicⓘ	no	97.55	no
125438	thermophilic	thermophileⓘ	no	90.43	yes
125438	flagellated	motile2+ⓘ	yes	78.59	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) .
#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 .
#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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