Acetivibrio saccincola (DSM 104321, JCM 31827)

Name: Acetivibrio saccincola (DSM 104321, JCM 31827)
Creator: BacDive
License: http://creativecommons.org/licenses/by/4.0/

BacDive ID 164132

Type strain

Culture col. no. DSM 104321 JCM 31827

NCBI tax ID(s) 1677857

Special Collections DSMZ JCM

Links

Acetivibrio saccincola JCM 31827 is a thermophilic prokaryote that was isolated from Cellulose-degrading bacterial community inhabiting bovine manure compost on Ishigaki Island.

thermophilic genome sequence 16S sequence

Name and taxonomic classification

SI-ID 131959

JCM 31827

@ref 20215

Last LPSN update 2025-12-16 10:09:23

Domain Bacillati

Phylum Bacillota

Class Clostridia

Order Eubacteriales

Family Oscillospiraceae

Genus Acetivibrio

Species Acetivibrio saccincola

Full scientific name Acetivibrio saccincola (Koeck et al. 2016) Tindall 2019

Synonyms (2)

Herbivorax saccincola
Hungateiclostridium saccincola

BacDive ID	Other strains from **Acetivibrio saccincola** (1)	Type strain
132679	A. saccincola GGR1, DSM 101079, CECT 9155 (type strain)

Morphology

Culture and growth conditions

Culture temp

@ref	Growth	Type	Temperature (°C)	Range
67770	positive	growth	55	thermophilic

Physiology and metabolism

Oxygen tolerance

@ref	Oxygen tolerance	Confidence
125438	anaerobe	95.37
125439	anaerobe	99.7

Isolation, sampling and environmental information

Isolation

@ref	Sample type	Country	Country ISO 3 Code	Continent
67770	Cellulose-degrading bacterial community inhabiting bovine manure compost on Ishigaki Island	Japan	JPN	Asia

Taxonmaps

69479

Global distribution of 16S sequence KX714804 (>99% sequence identity) for Acetivibrio saccincola subclade from Microbeatlas

Aquatic Samples	988
Soil Samples	4138
Animal Samples	1026
Plant Samples	1183
Total Samples	7335

Interaction and safety

Sequence information

Genome sequences

@ref	Description	Assembly level	INSDC accession	BV-BRC accession	NCBI tax ID	Score
67770	ASM296921v1 assembly for Acetivibrio saccincola A7	contig	GCA_002969215	1677857.4	1677857	72.16

16S sequences

@ref	Description	Accession	Length	Database	NCBI tax ID
67770	Clostridium sp. strain A7 16S ribosomal RNA gene, partial sequence	KX714804	1485		1506

GC content

@ref	GC-content (mol%)	Method
67770	34.9	genome sequence analysis

Genome-based predictions

Predictions

Predictions from Deep Learning for Genome Sequence Data. R package version 0.3.1 based on: Acetivibrio saccincola A7
NCBI: GCA_002969215

@ref	Trait	Model	Prediction	Confidence in %	In training data
125439	spore_formation	BacteriaNetⓘ	yes	83.00	no
125439	motility	BacteriaNetⓘ	yes	78.40	no
125439	gram_stain	BacteriaNetⓘ	variable	66.20	no
125439	oxygen_tolerance	BacteriaNetⓘ	anaerobe	99.70	no

Predictions from bacterial phenotypic traits through improved machine learning using high-quality, curated datasets based on: Herbivorax saccincola strain A7
PATRIC: 1677857.4

@ref	Trait	Model	Prediction	Confidence in %	In training data
125438	gram-positive	gram-positiveⓘ	yes	62.12	no
125438	anaerobic	anaerobicⓘ	yes	95.37	no
125438	spore-forming	spore-formingⓘ	yes	76.53	no
125438	aerobic	aerobicⓘ	no	98.14	no
125438	thermophilic	thermophileⓘ	yes	53.18	yes
125438	flagellated	motile2+ⓘ	yes	81.12	no

Literature

Topic	Title	Authors	Journal	DOI	Year
	Extracytoplasmic polysaccharides control cellulosomal and non-cellulosomal systems in Herbivorax saccincola A7.	Baramee S, Thianheng P, Uke A, Cheawchanlertfa P, Tachaapaikoon C, Waeonukul R, Pason P, Ratanakhanokchai K, Liu YJ, Kosugi A.	Appl Microbiol Biotechnol	10.1007/s00253-024-13310-3	2024
Genetics	Characterization and high-quality draft genome sequence of Herbivorax saccincola A7, an anaerobic, alkaliphilic, thermophilic, cellulolytic, and xylanolytic bacterium.	Aikawa S, Baramee S, Sermsathanaswadi J, Thianheng P, Tachaapaikoon C, Shikata A, Waeonukul R, Pason P, Ratanakhanokchai K, Kosugi A	Syst Appl Microbiol	10.1016/j.syapm.2018.01.010	2018

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;
#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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Acetivibrio saccincola (DSM 104321, JCM 31827)

Name and taxonomic classification

Morphology

Culture and growth conditions

Culture temp

Physiology and metabolism

Oxygen tolerance

Isolation, sampling and environmental information

Isolation

Taxonmaps

Interaction and safety

Sequence information

Genome sequences

Genome browser: GCA_002969215

16S sequences

GC content

Genome-based predictions

Predictions

Literature

Literature

References

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