Clostridium gelidum (DSM 112608, NBRC 114689, C5S11)

Name: Clostridium gelidum (DSM 112608, NBRC 114689, C5S11)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 169423

Type strain

Strain Designation C5S11

Culture col. no. DSM 112608 NBRC 114689 C5S11

NCBI tax ID(s) 704125

Special Collections DSMZ

History <- A. Ueki, Yamagata Univ., Tsuruoka, Japan; C5S11 <- S Homma; {2009}

Links

Clostridium gelidum C5S11 is a bacterium that was isolated from rice paddy field soil.

genome sequence 16S sequence Bacteria

Name and taxonomic classification

SI-ID 401828

NBRC 114689,DSM 112608

@ref 20215

Last LPSN update 2026-02-09 11:41:02

Domain Bacteria

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Clostridiaceae

Genus Clostridium

Species Clostridium gelidum

Full scientific name Clostridium gelidum Honma et al. 2022

Morphology

Culture and growth conditions

Culture medium

@ref	Name	Growth	Medium link	Composition
68704	PY + X MEDIUM (N2/CO2) (DSMZ Medium 104c)		Medium recipe at MediaDive	Name: PY + X MEDIUM (N2/CO2) (DSMZ Medium 104c) Composition: Yeast extract 10.0 g/l D-Glucose 5.0 g/l Trypticase peptone 5.0 g/l Meat peptone 5.0 g/l Na2CO3 1.0 g/l L-Cysteine HCl x H2O 0.5 g/l NaHCO3 0.4 g/l NaCl 0.08 g/l K2HPO4 0.04 g/l KH2PO4 0.04 g/l MgSO4 x 7 H2O 0.02 g/l CaCl2 x 2 H2O 0.01 g/l Sodium resazurin 0.0005 g/l Distilled water

Culture temp

@ref	Growth	Type	Temperature (°C)
68704	positive	growth	10

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	facultative anaerobe	98.9

Spore formation

@ref	Spore formation	Confidence
125439		94.4

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Geographic location	Country	Country ISO 3 Code	Continent	Latitude	Longitude
68704	rice paddy field soil	Yamagata, Tsuruoka-shi	Japan	JPN	Asia	38.7533	139.91 38.7533/139.91

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
66792	ASM1997765v1 assembly for Clostridium gelidum C5S11	complete	GCA_019977655	704125.3	8072560873	704125	98.61

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
68704	Clostridium gelidum gene for 16S ribosomal RNA, partial sequence	AB539905	1419		704125

GC content

@ref	GC-content (mol%)	Method
68704	29.0	sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Clostridium gelidum C5S11
NCBI: GCA_019977655

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	94.40	no
125439	motility	BacteriaNetⓘ	yes	89.70	no
125439	gram_stain	BacteriaNetⓘ	positive	82.40	no
125439	oxygen_tolerance	BacteriaNetⓘ	facultative anaerobe	98.90	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Clostridium gelidum C5S11
NCBI: GCA_019977655.1

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	58.93	no
125438	anaerobic	anaerobicⓘ	yes	81.86	no
125438	aerobic	aerobicⓘ	no	92.98	no
125438	spore-forming	spore-formingⓘ	yes	73.27	no
125438	thermophilic	thermophileⓘ	no	92.95	yes
125438	flagellated	motile2+ⓘ	yes	75.41	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) .
#68704	Leibniz Institut DSMZ-Deutsche Sammlung von Mikroorganismen und Zellkulturen GmbH ; Curators of the DSMZ; DSM 112608
#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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