Cite this strain

Butyrivibrio sp. (JCM 32525)

Name: Butyrivibrio sp. (JCM 32525)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164287

Type strain

Culture col. no. JCM 32525

NCBI tax ID(s) 28121

Special Collections JCM

Links

JCM 32525 is a mesophilic prokaryote that was isolated from Fecal sample of a healthy Japanese adult.

mesophilic genome sequence

Name and taxonomic classification

SI-ID 131774

JCM 32525

@ref 20215

Last LPSN update 2025-12-16 10:09:25

Domain Bacillati

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Lachnospiraceae

Genus Butyrivibrio

Full scientific name Butyrivibrio Bryant and Small 1956 (Approved Lists 1980)

Morphology

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	37	mesophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125439	anaerobe	99

Isolation, sampling and environmental information

Isolation

67770

Sample typeFecal sample of a healthy Japanese adult

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	IMG accession	NCBI tax ID	Score
67770	ASM358470v1 assembly for Lachnospiraceae bacterium GAM79	complete	GCA_003584705	2109691.3	3000245376	2109691	72.07

GC content

@ref	GC-content (mol%)	Method
67770	46.2	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Lachnospiraceae bacterium GAM79
PATRIC: 2109691.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	81.60	no
125439	motility	BacteriaNetⓘ	yes	85.10	no
125439	gram_stain	BacteriaNetⓘ	positive	72.00	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	99.00	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Lachnospiraceae bacterium GAM79
PATRIC: 2109691.3

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	71.84	no
125438	anaerobic	anaerobicⓘ	yes	81.42	no
125438	spore-forming	spore-formingⓘ	no	50.49	no
125438	aerobic	aerobicⓘ	no	96.57	no
125438	thermophilic	thermophileⓘ	no	93.97	yes
125438	flagellated	motile2+ⓘ	yes	71.95	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 )
#67770	Japan Collection of Microorganism (JCM) ; Curators of the JCM;
#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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